VOLUME 10, ISSUE 7, JULY 2021

Abstract: The development of energy systems to the paradigm of the intelligent protection system strongly depends on the wireless response for the feedback system. To achieve this goal, new infrastructures, technologies, and applications need to bearer increasingly needed. This paper introduces an intelligent switching infrastructure that includes a large, range of possible services for the automation and management of distribution networks. The proposed architecture is based on a wireless monitoring and feedback control platform that enables communication with the intelligent platform. On the one hand, and provides the necessary interfaces for the services of the distribution network in the other. While a large number of applications can be created typical of intention, in this document the focus will be in real-time, the role will present the key function of the monitoring solution for scalability, interoperability, and flexibility, and to enable the integration of different services for the automation of the distribution system. Focus on how to design a smart protection layer based on a wireless system with a smart control platform an example of the coordinated operation of various services of the distribution network via the platform.

Keywords: Smart Protection, platform, Android, Mechanism switch

Abstract: The rapid growth of the mobile devices and its services being experienced in a recent years brought both challenges and opportunities in the wireless network systems. The scarcity of the resources, high capital and operational costs are among the challenges facing the provision of the growing mobile services. The development of wireless network virtualization brought hope for the future networks to fulfil the users’ demands. It allows different service providers to share the same physical infrastructure which in return, reduces both capital expenses (CAPEX) and operational expenses (OPEX). In this paper, the framework for wireless network virtualization is proposed. Also, the detailed description of the model based on the software define network (SDN) architecture is presented. On top of that we have proposed a load based resources sharing approach among the virtual networks (VNs). Our proposed approach has shown that, through sharing the excess resources, the VNs can significantly minimize unnecessary cost and utilize the available resources effectively.

Keywords: Virtual networks, Resource Block, Resource allocation and sharing, Cost minimization, Effective resource utilization

Abstract: The Internet of Things technology played a vital role in our daily lives. It allows billions of devices and people to communicate, share data, and personalize services to enhance the living style. This wireless communication devices are distributed everywhere at smart homes, smart cities, smart transportations, as well as in military, business, and healthcare fields. Due to the rapid increase of IoT devices all around the world, it became a target for many hackers to trespass the privacy of people by collecting sensitive information and use it in suspicious tasks. Moreover, many of intruders have harmful intentions to destroy systems and infrastructures of some organizations. The deployment of efficient security and privacy protocols in IoT networks is extremely needed to ensure confidentiality, authentication, access control, and integrity, among others [5]. In this paper, the Internet of Things topic is introduced, its architectures and characteristics are clarified, the security threats and challenges are highlighted, and some essential solutions are explained.

Keywords: Internet of Things (IoT), Security, Privacy, Authentication, Access Control, Cyberattack, Fog Computing, Cloud Computing, Blockchain.

Abstract: The huge amount of streaming data available nowadays are due to massive use of new technologies. Such tremendous amounts of data add a great deal of challenges to the traditional relational database paradigm. The challenges are: performance in reading data and scalability (that is the ability of a database to handle changing demands by adding/removing resources). However, the use of NoSQL database in new enterprises is not a major issue because the new application design will be based on NoSQL database. But the problem appears when the existing systems that relay on relational database are restructuring their systems to implement NoSQL database. They need to reanalyze the system requirements to build up the new database schema. This study aims at developing a mechanism for mapping relational database schema to NoSQL schema and query rewriting of SQL to NoSQL queries. Conceptual mapping has been used which involved the concepts of a relational structure (Table, Simple Attribute, Primary Key (PK), Foreign Key (FK)), and NoSQL concept (Document Collection, Document, Field, Embedded Field, Field List, ObjectId, DBRef). Relationships were realized by defining object references between objects belonging to documents. Mapping algorithm used the metadata stored in the MySQL system tables. The system was implemented in PHP. Experiments were conducted on MySQL and MongoDB based on migration speed and query speed. The read speed of each database was tested, four queries were conducted to pull the number of rows from the product table. The average of these five queries were taken for each implementation. MongoDB proved the faster database management system with a time of 1.78 seconds as compared to 3.35 seconds for MySQL

Abstract: Service providers (SP) are constantly attempting to match their network to cater to rapidly evolving offerings from content providers and digital application providers. Layered and siloed architecture in tradition Service Provider Network, requires higher management and operational costs and pose challenges in rapidly scaling. In order to solve these problems, alternative approaches are being tried out. Naturally, the approach from equipment manufacturer (OEM) could be different from that of Operator consortium or open-source community. Hence it’s prudent to visualize these three alternative architectures side-by-side and analyse them simultaneously. This paper focuses on analysing these three alternative architecture approaches with respect to each other. This analysis brings out the common features as well as key differences in these three approaches. Additionally, the analysis presented in this paper enables a practical insight into offered choices, provides a new tool to check fitment of the solution and provides a ready list of key design considerations. At present, no other article covers these useful guiding points and is a unique contribution.

Keywords: Routed Optical Network (RON), Open Disaggregated Transport Network (ODTN), Virtual Online Termination Hardware Abstraction (VOLTHA), Open Network Foundation (ONF), Software Defined Network (SDN)

Abstract: The existence of counterfeit drugs or pharma products in walks of health care services and in the pharmaceutical supply chain has recently become very evident with the increase in serious illness and death from the use of such drugs. Such pharma products can probably contain the wrong dose of the ingredient or be mixed with the wrong composition. Not only are these products useless for treating people, but they can also lead to serious health conditions. With regard to supply chain systems in our country, most of the transfers that take place in the chain are not recorded correctly and transparency is at stake, every stakeholder within the chain has to trust the other person in the chain and proceed with the handovers. Tracking the origin of the falsified drug or any other discrepancy is a difficult task. The main focus of this paper is to discuss the various practices, challenges and existing approaches in digitizing transfers in a supply chain and proposing a solution to ensure security and transparency is achieved by utilizing the technology of blockchain.

Keywords: Blockchain Technology, Supply Chain, Secure, Transparency, Decentralized.

Abstract: Health care system is more affluent and more complex nowadays. One of the main resources in healthcare is health records of patients. Most of the hospital altered to Electronic Health Record (EHR) which enhanced the health care system. EHR consists of most subtle data and this has to be managed properly. There are a lot of issues faced in management of EHR like security, privacy, interoperability. The proposed system describes the solutions for the issues discussed here. This paper proposes a secure EHR system which will preserve the privacy and maintain interoperability using Blockchain. The Blockchain is a data structure that display the way the data are stored and sensibly joined together in a peer-to-peer network. Hyperledger Fabric is used to manage EHR. Sharing health records between the several hospitals is a vital and life-saving during emergency. This will significantly reduce the time needed for the physicians to prescribe and take precautionary actions required as swiftly as possible. This helps to attend the patient’s on-time and save their lives during the emergency circumstances.

Keywords: - Blockchain, Hyperledger Fabric.

Abstract: The latest advances in electronics and microelectronics gadgets permit the improvement of newly low-price tracking gear utilized by peoples for fitness preventive purposes. Sensors utilized in scientific equipment convert diverse kinds of human frame crucial symptoms and symptoms into electric signals. Therefore, the healthcare tracking structures thinking about non-invasive and wearable sensors with incorporated verbal exchange mediums permit an green option to stay a snug domestic life.

Keywords: Sensor-MLX90614 sensor, Digital sign processing, OpenCV, Face Detection.

Abstract: Inventory the executives framework is extremely fundamental for undertakings. The dealer should track buys and deals. The stock administration framework can follow data about deals and accessible stock. The program comprises of two sections: An interface has been created. Use progressed Web innovation and SQL Server information base backend. To address the issues of clients, the organization's distribution center should have adequate stock. This record presents the examination of stock administration framework. The framework is intended to incorporate an information base that permits you to store and recover all exchanges.

Keywords: ware the board framework, information base, public and programming.

Abstract: In today’s industrialized countries, women’s participation in the workforce has dramatically increased. This participation is one of the main reasons that affect baby care in many families from the birth of the baby to a certain age. The most important factors that should be followed in infants are values, body temperature and sleep patterns, which we can sometimes call vital functions. An abnormal increase in the temperature of the baby during sleep is one of the most critical factors causing sudden infant death syndrome, a febrile complication. In this article, an internet of things (IoT) based baby monitoring mechanism, namely a smart cradle structure, which tracks the real-time temperature, heart rate, wetness and sound of the baby is proposed, and the data received from the sensors will be transferred to a web platform via Wi-Fi and checked in real-time. In the case of crying, the cradle will swing autonomously. The alarm will be activated if the crying does not stop or if an abnormal increase in the measured body temperature, heart rate and humidity level is observed. Thanks to the alarm, it will be ensured that the person responsible for the care of the parent or baby will respond to the care that the baby needs in a timely manner. In addition, the LED will be placed in the cradle, and it will be monitored whether or not an alarm is given over the cradle. KEY WORDS: Smart baby cradle system, internet of things (IOT).

Abstract: Use of Cloud computing technology in agricultural areas has larger probability within the overall development of Asian nation. Encouraging in agriculture sector is an effective implementation of cloud computing. Cloud Computing is emerging these days as a billboard infrastructure that eliminates the necessity for maintaining costly computing hardware, software, info technology, staff, infrastructure, recourses and their maintenance. Cloud computing could be a network-based surroundings that focuses on sharing computations, Cloud computing networks access to a shared pool of configurable networks, servers, storage, service, applications & alternative vital computing resources. In era of cloud computing technology terribly useful for centralized the allagricultural connected knowledge bank (Soil-related, weather, Research, Crop, Farmers, Agriculture promoting, fertilizers and chemical information) within the cloud. during this paper, conjointly discuss Computing model, characteristics, deployment model, cloud service model, cloud edges and challenge of cloud computing in agriculture field.

Keywords: : Cloud computing, Community model, Hybrid model, Public model, personal model, Agriculture, IaaS.

Abstract: Kannada handwritten reports were the only way of documentation available in government offices and healthcare departments in Karnataka state. Reproducing the contents of these old documents through typewriting is a tedious task, as the documents are difficult to read and understand. Hence there is a need for a computer-based system to overcome the gap between machines and humans. This project proposes an efficient method for Kannada handwritten character recognition system which uses image preprocessing techniques to enhance the quality of an image and exploring deep learning technique for feature extraction. . The proposed work is concentrated on developing an offline handwriting recognition system to recognize the Kannada statements to a suitable degree of recognition.

Keywords: Kannada character recognition, deep neural networks, OpenCV.

Abstract: This demand bill discusses the protection over information within cloud computing. It is a education about data into the planet or elements associated in conformity with that concerning security. The paper pleasure suffice between in conformity with important points concerning records safety techniques and methods aged in the course of the world in conformity with insure most statistics protection with the aid of decreasing dangers yet threats. Availability about facts into the planet is auspicious for much services however it poses gambles via exposing data after purposes as may in the meanwhile hold safety loopholes in them. Similarly, use of virtualization for bird computing would possibly gamble statistics now a visitor OS is move upon a hypervisor barring knowing the reliability regarding the guest OS as would possibly hold a security recipe into it. The bill of exchange will additionally supply an insight about statistics safety components because of Data-in-Transit or Data-at-Rest. The learning is primarily based regarding entire the ranges on SaaS (Software so a Service), PaaS (Platform namely a Service) and IaaS (Infrastructure as a Service).

Keywords: Data Security, Cloud Computing, Data Protection, Privacy, Risks and threat.

Abstract: Machine Learning (ML) is a field of artificial intelligence that uses statistical techniques to give computer systems the ability to "learn from data”, without being explicitly programmed. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data – such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs.

Keywords: Machine Learning (ML), Personal Identification Numbers (PINs), Real Time Eye Pupil Tracking, Virtual Assistants.

Abstract: The basic security demands of a home, whether in a metropolis or a metropolitan zone, continue to be a serious issue. In today's context, establishing a full-featured and reliable model that will accurately send alerts to the destined mode of reference in the event of an intrusion or attempted threat is essential. In this research, we offer a full simulation of an experimental prototype of a wireless sensor network based on infrared sensor technology, with individual nodes strategically and sequentially deployed. The Internet of Things underpins the operation of this system, which includes an ESP32-CAM as a functioning microcontroller. The system shall transmit the recognition to the user through the Blynk application and sound and light alert emission in the specific place where the intrusion is identified, when the suspected intrusion occurs. Because it uses solar energy as a power source, this system is cost effective and reliable, has minimal power consumption, and is environmentally friendly. The system detects human trespass using a PIR-based sensor and sends out warnings as needed.

Keywords: Solar Energy, ESP-32 CAM, PIR sensor, Blynk, Wi-Fi Module, Zigbee, Alert, Simulation.

Abstract: The integration of PV with the electric vehicle (EV) charging system has been on the rise due to several factors, namely continuous reduction in the price of PV modules, rapid growth in EV and concern over the effects of greenhouse gases. Over the years, numerous papers have been published on EV charging using the standard utility (grid) electrical supply; however, there seems to be an absence of a comprehensive overview using PV as one of the components for the charger. With the growing interest in this topic, it is timely to review, summarize and update all the related works on PV charging, and to present it as a single reference. For the benefit of a wider audience, the paper also includes the bries description on EV charging stations, background of EV, as well as a brief description of PV systems. Some of the main features of battery management system (BMS) for EV battery are also presented. It is envisaged that the information gathered in this paper will be a valuable one-stop source of information for researchers working in this topic. of vehicle-to grid (V2G) connection impacts.

Keywords: Integration, Comprehensive, Greenhouse, Charging, Growing, Photovoltaic, Vehicle.

Abstract: Supermeals is an order management software for food delivery companies. It is a delivery-oriented system that allows clients to order from multiple household messes at the same time and provides the possibility to order individually or in a group. Orders can be placed by users through the web interface. The data related to Messes, foods and orders is managed by administrators. A mobile application is used by the delivery personnel as well as messes. Both client applications are served with data by a central server. The article presents an architecture and the implementation of the software system. The technologies, tools used during the development are as follows.

Keywords: Mess Searching, Mess Subscription, Job Opportunity, Tiffin Delivery.

Abstract: Cryptography based on ciphertext policy attributes (CPABE) is a promising cryptographic method that can be used to fine-tune access to outsourced knowledge in the cloud. However, flaws in key management make your application difficult to detect. A central theme in the written agreement. Please note that buyers’ front-end devices (such as smartphones) often have limited data protection. Therefore, if it is completely controlled by a non-public key, consumers may leak a key that is almost unrecognizable, but initially in the previous version. explore. Use ABE wisely. In the course of this work, we proposed the collaborative key management protocol in CPABE (CKMCPABE). Our design performs the distributed generation, release and storage of private keys without adding additional infrastructure. When the key is updated, immediate and detailed attribute revocation is provided. The cooperation mechanism not only effectively solves the core problem of the written agreement, but also effectively solves the problem of key leakage. At the same time, it helps to significantly reduce the workload of consumer decryption. A comparison with various representative CPABE themes shows that our model performs slightly better in terms of external knowledge sharing in the mobile device cloud. Finally, we provide proof of security for the proposed protocol. Index terms: cloud data exchange, CPABE, key management, security, efficiency.

Abstract: The cloud data storage service plays a major role in a day to day life. Many scientists have noticed about secure search over encrypted information. The main target of this service is to promise the secrecy of the information stored in the cloud server. However, the huge data stored in a cloud are protected using various privacy and security algorithm. In this regard, to handle the security concerns, it is desirable to deploy sensitive information in encrypted structure. Encrypted information storage protects the information against illegal access. It includes much basic and fundamental functionality such as the search on the information. The searching Handled by keywords is made by two to more keywords to be added. In this proposed project, we have used one of the privacy and preserving encrypted multi-sharing mechanism to achieve the searching. The merit of re-encryption with unnamed method in which an encrypted can be shared multiple times without revealing both the knowledge of elementary message & the uniformity data of cipher text senders/receivers.

Keywords: privacy, security, re-encryption, cloud computing.

Abstract: The farmers are struggling to obtain higher rate of yield due to lack of poor knowledge about the soil and water nutrients of the crop for the soil. Internet of Things (IoT) technology has brought revolution to each and every field of common man’s life by making everything smart and intelligent. IoT refers to a network of things which make a self-configuring network. The development of Intelligent Smart Agriculture IoT based devices is day by day turning the face of agriculture production by not only enhancing it but also making it cost-effective and reducing wastage. The aim of this project work is to propose a Novel Smart IoT based Agriculture this assisting farmers in getting Live Data (Temperature, Soil Moisture, humidity and Rain status) for efficient environment monitoring which will enable them to do smart farming and increase their overall yield and quality of products. The Smart Agriculture being proposed via this project is integrated with Adriano Technology, Breadboard mixed with various sensors and live data feed can be obtained online from using android application and by SMS and also by e-mail. The project being proposed is tested on Live Agriculture Fields giving high accuracy over 98% in data feeds.

Keywords: Adriano, soil moisture sensor, PIR sensor, temperature and humidity sensor, Think speak cloud, Submersible pump.

Keywords: Brain-machine interface, neuroprosthetics, neuronal amplification, artificial intelligence, neuroengineering, neuralink,tangible,engine work.

Abstract: Decentralizing multi-authority attribute-based encryption (ABE) has been adopted for solving problems arising from sharing confidential corporate data in cloud computing. For decentralizing multi authority ABE systems that do not rely on a central authority, collusion resistance can be achieved using a global identifier. Therefore, identity needs to be managed globally, which results in the crucial problems of privacy and security. A scheme is developed that does not use a central authority to manage users and keys, and only simple trust relations need to be formed by sharing the public key between each attribute authority (AA). User identities are unique by combining a user's identity with the identity of the AA where the user is located. Once a key request needs to be made to an authority outside the domain, the request needs to be performed by the authority in the current domain rather than by the users, so, user identities remain private to the AA outside the domain, which will enhance privacy and security. In addition, the key issuing protocol between AA is simple as the result of the trust relationship of AA

Abstract: Obstacle avoidance is one of the most important aspects of mobile robotics. Now day’s many industries are using robots due to their high level of performance and reliability and which is a great help for human beings. This project proposes robotic vehicle that has an intelligence built in it such that it directs itself whenever an obstacle comes in its path. so, to protect the robot from physical damages. This can be design to build an obstacle avoidance robotic vehicle using ultrasonic sensors for its movement. A micro - controller (AT mega 328P) is used to achieve the desired operation. An ultrasonic sensor is used to detect any obstacle ahead of it and sends a command to the micro- controller. Depending on the input signal received, the micro-controller red erects the robot to move in an alternate direction by actuating the motors which are interfaced to it through a motor driver. The GSM module we here going to use is Sim900 which is capable of connecting to GPRS and through which we can send and receive commands. Key Words : Obstacle , Arduino ,LCD Display , Smart phone, Ultrasonic sensor, GSM.

Abstract: - Nowadays digital media service is highly increasing as the number of wireless subscription is growing heavily. To meet this growing need, mobile wireless networks have been advanced at a huge pace over recent days. However, the architecture of live mobile networks, with limited volume and range of bandwidth of the radio access network and small bandwidth of the radio access network and small bandwidth back-haul network, can not handle the heavily increasing mobile traffic. Newly, we have seen the growth of new mechanisms of data caching and transfer methods through the transitional caching server.MEC is recognized as a key to 5G networks. This paper is aimed to present a survey on Recent advance in mobile edge computing and text caching, in MEC(Mobile Edge Computing) deploy an edge server and content caching within the mobile networks, we have identified and discussed some important open challenges in mobile edge computing with text caching

Abstract: In recent times, Heart Disease prediction is one of the most complicated tasks in medical field. In the modern era, approximately one person dies per minute due to heart disease. Data science plays a crucial role in processing huge amount of data in the field of healthcare. As heart disease prediction is a complex task, there is a need to automate the prediction process to avoid risks associated with it and alert the patient well in advance. This paper makes use of heart disease dataset available in UCI machine learning repository. The proposed work predicts the chances of Heart Disease and classifies patient's risk level by implementing different data mining techniques such as Decision Tree, Knn, Logistic Regression and Random Forest. Thus, this paper presents a comparative study by analyzing the performance of different machine learning algorithms. The trial results verify that Random Forest algorithm has achieved the highest accuracy of 90.16% compared to other ML algorithms implemented.

Keywords: Decision Tree, KNN, Logistic Regression, Random Forest, Heart Disease Prediction

Abstract: In manufacturing industries, there arises a need to sort parcel. The parcels may be of similar or different types. The system should be able to detect the parcel and then differentiate the parcel from each other based on their sections. Thus, different parcels and different conditions require different type of processing. Our aim is to scan the QR code attached to parcels using QR code scanner. The input QR code will be processed for detecting the given sections. This automated system does not requires any special human intervention and thus reduces the probability of human made errors. The result of the system are completely reliable which can be further used with huge working systems.

Keywords: Raspberry Pi 3b, web camera, SD card, Arduino Uno, Servo motor.

Abstract: In recent years, huge amounts of structured, unstructured, and semi-structured data have been generated by various institutions around the world and, collectively, this heterogeneous data is referred to as big data. The health industry sector has been confronted by the need to manage the big data being produced by various sources, which are well known for producing high volumes of heterogeneous data. Various big-data analytics tools and techniques have been developed for handling these massive amounts of data, in the healthcare sector. In this paper, we discuss the impact of big data in healthcare, and various tools available in the Hadoop ecosystem for handling it. We also explore the conceptual architecture of big data analytics for healthcare which involves the data gathering history of different branches, the genome database, electronic health records, text/imagery, and clinical decisions support system. Key words: big data; healthcare; Hadoop; MapReduce

Abstract: Everybody loves speed and speedy internet, so it's no surprise that every major telecom in the world is working to make it even faster. Smartphones, watches, homes, and cars are increasingly requiring stable internet connections. To survive in a world wherein every second the speed changes and where we urge for more and more technology, here comes the fifth generation technology: 5G. In the future, i.e., a world beyond 4G, some of the prime objectives that need to be fulfilled are increased capacity, improved data rate, decreased latency, and quality service. To meet these demands, large-scale improvement in the cellular architecture of 5G is required. This paper emphasizes the 5th generation i.e. 5G cellular network architecture and some of the essential emerging technologies that can prove fruitful in humanizing the architecture and summiting the demands of users. This paper is contented with the details related to 5g with the prime focus on the massive multiple inputs multiple output technology and device-to- device communication (D2D). A general credible 5G cellular network architecture is being proposed with the guideline taken from the internet books and by the detailed study of the topic.

Abstract: The cloud is interconnected and huge network of powerful servers that performs services for business and people. The IOT is a system of interrelated computing devices, mechanical and digital machines, objects or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human to human or human to computer interaction. Internet of things Cloud service creates excessive communication between inexpensive sensors in the IOT which means even greater connectivity. IOT generates lots of data while on the other hand, cloud computing provides way for this data to travel. In this survey paper we try to focus on cloud providers who take advantage of this to provide a pay-as-you-use model where customers pay for the specific resources used.

Keywords: Cloud Computing, IOT, Future Computing, Security

Abstract: Mobile cloud computing has gained popularity because of its potential to minimize power consumption and enhance user experience by outsourcing resource/computation intensive applications/operations from mobile devices to clouds. Mobile Cloud Computing: Architectures, Algorithms, and Applications is the first complete reference book on mobile cloud computing. Mobile devices suffer from poor battery life and limited resource and storage capacity. To overcome these constraints, mobile cloud computing has introduced offloading, where data storage and computations are performed inside the remote cloud instead of the mobile device. With this emergence, mobile cloud computing has become a vital issue that requires an energy-efficient mobile network and green cloud environment. Resource allocation and security are also important issues discussed in detail in this book. Mobile cloud computing–based health monitoring, gaming, learning, and commerce are feasible due to high-speed 4G/5G mobile networks. The issues of mobile cloud computing are discussed in the 14 chapters with future open research problems

Keywords: Mobile cloud computing, cloud computing, mobile cloud services, mobile cloud applications, and mobile computing

Abstract: The numerous activities related to e-commerce are carried out in social networks, in which trust plays an important role in decision making of customers. Suggestion by a friend is a common service that has been provided by almost all of the social networks, and evaluation of trust between users improves the quality of suggestions. Social networks have become the main infrastructure of today’s daily activities of people during the last decade. In these networks, users interact with each other, share their interests on resources and present their opinions about these resources or spread their information. Since each user has a limited knowledge of other users and most of them are anonymous, the trust factor plays an important role on recognizing a suitable product or specific user. The inference mechanism of trust in social media refers to utilizing available information of a specific user who intends to contact an unknown user. Next, fuzzy logic is incorporated to rank the membership of trust to a specific class, according to two-, three- and five-classes classification. Finally, to classify the trust values of users, three machine learning techniques, namely Linear Regression, Decision Tree (DT), and Random forest, are used instead of traditional weighted sum methods, to express the trust between any two users in the presence of a special pattern.

Keywords: Data mining, Pre processing, Transformation, Data Mining.

Abstract: Phishing is a form of fraud in which the attacker tries to learn sensitive information such as login credentials or account information by sending as a reputable entity or person in email or other communication channels. Typically, a victim receives a message that appears to have been sent by a known contact or organization. The message contains malicious software targeting the user’s computer or has links to direct victims to malicious websites in order to trick them into divulging personal and financial information, such as passwords, account IDs or credit card details. The aim of this research is to develop these methods of defense utilizing various approaches to categorize websites. Specifically, we have developed a system that uses machine learning techniques to classify websites based on their URL. We have used two classifiers: The Decision Tree classifier and Naive Bayesian classifier. These classifiers were trained and tested using a dataset that has values of features of 88647 websites. The accuracy of the proposed system is 95.4 % which is higher than most of the other proposed systems.

Keywords: Phishing sites; Machine learning; Classification; Malicious sites; Detection; Cybersecurity;

Abstract: In Content-Based Image Retrieval (CBIR) the indexing of the image and the representation is done using visual contents of an image like color, shape, texture and spatial layout. Cloud storage is a popular choice to handle a large size data because its cost is much lower than hardware upgrade and infrastructure reorganization. Nowadays, image-based data is getting important in many applications such as face identification, disease detection and object recognition and it usually needs more storage than text-based data. However, the images usually contain personal and confidential information and hence directly outsourcing the image dataset to the cloud will arouse the privacy issue. To protect the sensitive information in images, it is necessary to encrypt images before being uploaded to the cloud. After storing the encrypted image data in the cloud, the users will ask the cloud server for the search of the target image data. However, current content-based image retrieval technologies are usually useless for searching encrypted image data, and hence this system tries to solve the problem of searching encrypted images in a large database.

Keywords: k-Nearest Neighbour( kNN ) , Homomorphic Encryption( HE ) , Asymmetric Scalar Product Preserving Encryption( ASPE ) , Content Based Image Retrieval( CBIR ) , Text Based Image Retrieval( TBIR )

Abstract: Phishing website is one of the internet security problems that target the human vulnerabilities rather than software vulnerabilities. It can be described as the process of attracting online users to obtain their sensitive information such as usernames and passwords and bank account details. Cyber security persons are now looking for trustworthy and steady detection techniques for phishing websites detection. Deals with machine learning technology for detection of phishing URLs by extracting and analysing various features of legitimate and phishing URLs. Random forest and Support vector machine algorithms are used to detect phishing websites. The propose a learning-based approach to classifying Web sites into 3 classes: Benign, Spam and Malicious. Benign are the safe websites with normal services. Spam is the Website performs the act of attempting to flood the user with advertising or sites such as fake surveys and online dating etc. Malware are the Website created by attackers to disrupt computer operation, gather sensitive information, or gain access to private computer systems. Thus, it eliminates the run-time latency and the possibility of exposing users to the browser-based vulnerabilities.

Keywords: phishing, website, security, vulnerabilities. cyber security, information

Abstract: The sense of vision is an important aspect of human being life. But, unfortunately some people lack the ability of visualizing things. Visually impaired people find difficulties and has to face many challenges in their daily lives . The normal stick used , do not provide any ways to detect obstacles in ahead of them and also it is not efficient for those kinds of people. The smart stick comes as a proposed solution to enable them to identify the world around them probably in better ways. In this project we propose a solution for visually disabled people for improved navigation . This system helps in providing the artificial vision and detecting the obstacles or objects in prior. The main aim of the proposed system is to provide low cost and efficient navigation tool for the visually impaired persons who can feel or sense and gain information about the environmental scenario of stable and unstable objects around them. The Ultrasonic sensors, which calculates the distance of the obstacles around the blind person to guide them to available path in form of sequence of beep sound which the blind person can hear . The use GSM and GPS sensors helps in case of emergency and track down the location information the blind person through the smart phones. The smart stick is of low cost and highly efficient.

Keywords: ATM, security, authentication, style implications, field study, lessons learned.

Abstract: Haptic technology provides a form of human-computer interaction. Haptic technology is an important part of today's world. Haptic technology allows humans to feel vibrations, movements and movements. Haptic is a sense of touch that controls interaction with computer applications. People can feel real through touch devices and virtual environments. It Describe the working principle of user touch by allowing the creation of a touch-controlled virtual environment. It refers to the technology that connects humans and the virtual environment through touch by applying action or movement, force, and vibration to the user. Haptic refers to manipulation and perception through actions, movements, and touch. This article includes the meaning of haptic technology and its principles of operation, haptic devices and technologies, their applications, and their advantages and disadvantages.

Keywords: To fasten response, Sense of Touch, Virtual Environment creation, Haptic rendering.

Keywords: Node MCU, Gas Sensors, Arduino IDE, Thinger.io

Abstract: Privacy-Preserving Content-based image retrieval (CBIR) applications have been rapidly developed along with the increase in the quantity, availability and importance of images in our daily life. However, the wide deployment of the CBIR scheme has been limited by its severe computation and storage requirements. In a privacy- preserving content-based image retrieval scheme, it allows the data owner to outsource the image database and CBIR service to the cloud, without revealing the actual content of the database to the cloud server. Local features are utilized to represent the images, and earth mover’s distance (EMD) is employed to evaluate the similarity of images. The EMD computation is essentially a linear programming (LP) problem. The proposed scheme transforms the END problem in such a way that the cloud server can solve it without learning the sensitive information. In Addition, local sensitive hash (LSH) is utilized to improve the search efficiency. The Security analysis and experiments show the security and efficiency of the proposed scheme. In that the encrypted database, secure searchable index and encrypted query will not reveal extra information to the cloud.

Keywords: AES, Advanced Encryption Standard, CBIR, Content-Based Image Retrieval

Abstract: Parkinson Disease (PD) is a kind of neural disorder that affects a range of people. This disease has continuously growing stages to halt entire neural activities of any people. There are many techniques proposed to detect and predict PD using medical symptoms and measurements. The medical measurements provided by different experiments must be effectively handled to produce concrete results on the detection of PD. This saves many people from PD at earlier stage itself. Recent technologies focus on Machine Learning (ML) and Deep Learning (DL) techniques for effective PD data analysis for making efficient prediction system. They are concentrating to build complex artificial neural systems using effective learning functions. However, the existing systems are lacking to attain multi-attribute and multi-variant data analysis to predict PD. To attain multi-variant Parkinson symptom analysis, the artificial neural systems must be equipped with more characteristics. In this regard, the Proposed system is developed using Multi-Variant Stacked Auto Encoder (MVSAE). The MVSAE based PD Prediction System (MSAEPD) helps to analyze more PD symptoms than existing systems. This article provides four different variants of SAE construction procedures to predict PD symptoms. The MSAEPD is implemented and compared with existing works such as MANN, GAE and UMLBD. This comparison shows the MSAEPD system gives 5% to 10% better results than existing works.

Keywords: Parkinson Disease, Multi-Variant, Multi-Attribute, Machine Learning.

Abstract: Cryptocurrencies are new economic and financial tools with special and innovative features. Investment in cryptocurrency has been in trend from last many years. Bitcoin is one of the most popular and valuable cryptocurrency. Many studies have been done on bitcoin price prediction using various parameters which includes bitcoin factors, social media etc. The most important thing is that they are not related assets, not issued by any government or central authority. In recent years, cryptocurrency (Bitcoin) is rising and become an attractive investment for traders. Unlike stocks or foreign exchange, Bitcoin price is fluctuated, mainly because of its 24- hours a day trading time without close time. To minimize the risk involved and maximize capital gain, traders and investors need a way to predict the Bitcoin price trend accurately. However, many previous works on cryptocurrency price prediction forecast short-term Bitcoin price, have low accuracy and have not been cross-validated. A comparative study of the various parameters affecting bitcoin price prediction is done based on Root Mean Square Error using various deep learning models like Multilayer Perceptron , Long Short Term Memory.

Keywords: LSTM Long Short Term Memory MLP Multilayer Percepton RSME Root Mean Square Error MSE Mean Squared Error RNN Recurrrent Neural Network

Abstract: Village management system is the project which deals with the day-today activities of the villagers. The villagers find it difficult to adapt themselves to “Digital India” so, the project helps the villagers survive in the developing world. The web application is a time constraint application which saves the time of the villagers in doing day-to-day activities. Village management system is the management of activities done by the village panchayat board such as payment system of domestic taxes like water tax, residence tax, Mahatma Gandhi 100-days work scheme management(100 naal velai thittam) and Women’s Self-Help Groups(Magalir Suya Udhavi Kuzhu) i.e SHG’s. A successful implementation of the Village Management System helps the villagers as well as the Panchayat staffs in maintaining and easy access of their information.

Keywords: Self Help Group (SHG), Unified Payment Interface (UPI)

Abstract: The Internet of things (IOT) is the network of devices, vehicles, and smart home containing electronics, software, actuators and connectivity which allows these things to connect, interact and exchange data. Embedded with technology, these devices can communicate and interact over the Internet and they can be remotely monitored and controlled. The existing system tell us about detect the obstacles in their path through touching poking. The proposed system using RF-433mhz transmitter/receiver module to transfer the data and alert blind person using buzzer to cross a roads. A cost effective solution to the issue is the key contribution of the paper using a simple framework based on Arduino Nano. Moreover, in India this program is more important and essential. The smart crossing systems detect people as well as reduce road accidents.

Keywords: obstacles, ultrasonic sensor, radio frequency transmitter and receiver, controller, vibration.

Abstract: This project prioritizes a convolutional neural network model that has been trained to differentiate and detect pneumonia from X-ray image samples. Unlike other procedures that relay on learning methods of transmission or traditional hand-crafted procedures for obtaining different isolation functions, the convolutional neural network model from scratch to extract features from a given X-ray chest image and isolate to determine whether a person has pneumonia or not. This model can help reduce the reliability and accountability challenges they face when dealing with medical imaging.

Keywords: Convolutional Neural Network (CNN), World Health Organization (WHO), artificial neural network (ANN), Artificial neural network, CheXNet algorithm.

Abstract: Melanoma is considered to be a fatal form of skin cancer. However, due to their similar visual look and symptoms, it is often difficult to differentiate it from the nevus. The number of cases among children is growing but if it is detected at its earlier stage then the risk of survival is very high. The cost and time needed for the physicians to treat all melanoma patients is very high. In this research work we propose a method that uses state-of-the-art image processing techniques to detect and differentiate melanoma from nevus. Pre processing is initially used to eliminate noise from the skin lesion of the images obtained, followed by the use of enhanced HSV colour space conversion clump to section out the lesion. The extraction of textural and colour choices from the lesion Shape a distinctive hybrid super-feature vector. Support Vector Machine (SVM) is used to classify skin cancer into melanoma and nevus. Our goal is to check the efficacy of the projected segmentation strategy, select the most suitable options and compare the results of the classification Within the literature the opposite strategies are present. Our proposed methodology archives encouraging result

Keywords: Support Vector Machine (SVM), Image processing techniques, distinctive hybrid super-feature vector.

Abstract: The most common cause of heart disease is narrowing or blockage of the coronary arteries, the blood vessels that supply blood to the heart itself. Early sign of heart disease will help you to choose the best treatment based on doctor recommendations to you. In an echocardiogram of heart, these echoes are turned into moving picture of your heart. Echocardiogram is a common test using sound wave map out shape and size of heart. This paper has focused on echocardiography where the decision is to detect the defect in the four chambers of heart quick. This work proposes to study Convolutional Neural Networks in medical science. It focuses on echocardiography. The term echocardiography means that the internal structure of a patient’s heart is studied through the images. The ultrasound waves create these images. The abnormalities in these images are found through echo. This work proposes to study Convolutional Neural Networks in medical science. It focuses on echocardiography. 2D echocardiogram is the test in which pictures of heart and various parts of heart are taken with the help of probe. The motive of this work is to decrease the overhead of the cardiologist. This approach will result in pointing the abnormality in the heart. Since, cardiologist and less experienced surgeons may take a while to figure out the defect or may miss the defect in the heart, this is a powerful approach which can detect even a little defect in heart which human eye tends to ignore.

Keywords: Convolutional neural network, Deep learning, Quality assessment, Echocardiography, Apical four-chamber, Machine Learning, Artificial Intelligence and Image Processing, etc.

Abstract: OSI model is a reference model for communication in a computer network. Network layer is the third layer in the OSI model [1]. The network layer provides connectivity and path selection between two host systems. It is responsible for routing data packets and selecting the best path to deliver data. The network layer prioritizes data known as Quality of Service (QOS) [2]. Routers [3] and Layer 3 switches operate at the network layer. A Router can also act as a Layer 2 and Layer 1 device. A routing protocol [4] specifies how routers communicate with each other. A routing protocol is a set of rules used by routers to determine the most appropriate path into which they should forward packets towards their intended destination. In this paper we give you a brief introduction on redistribution. Using a routing protocol to advertise routes that are learned by some other means, such as by another routing protocol, static routes or directly connected routes, is called redistribution. This situation never arises in the case of single protocol routing environment but multi-protocol routing is common for a number of reasons like company mergers, multiple departments managed by multiple network administrators, and multi-vendor environments. Route redistribution allows different routing protocols to exchange routing information. In this paper we have considered one such situation of route redistribution. Redistribution is done at the boundary routers at the boundary of two merged companies- company A and company B, adapting OSPF and EIGRP routing protocols respectively in their respective AS.

Keywords: Route-redistribution, Network layer, OSI model, Quality of Service (QOS), Routers and Layer 3 switches, multi-protocol routing, redistribution, Open Shortest Path First (OSPF) and EIGRP, Autonomous System (AS).

Abstract: The cloud security is one of the important roles in cloud, here we can preserve our data into cloud storage. More and more clients would like to store their data to PCS (public cloud servers) along with the rapid development of cloud computing. Cloud storage services allow users to outsource their data to cloud servers to save local data storage costs. It makes the clients check whether their outsourced data is kept intact without downloading the whole data. In our system we are using checksum Algorithm for our own auditing based on the token generation. Using this key generation technique, we compare the key values from original keys and we can find out the changes in the file. The content will be stored and also encrypted in the cloud server. Here we are using block chain double hashing algorithm for splitting the original file into three different files and to store that files in three different locations in cloud. The Encryption and Decryption Technique are done by using Cryptographic Hashing techniques. Anyone can download the files from the server with file owner permission. At the time of download key will be generated (code based key generation) and it will send to the file owner. We can download that file by using verification key.

Keywords: Data security and privacy, Advance Encryption Standard Technique (AES), Blockchain Technology.

Abstract: Computer networks has become the most substantial problem in our day-to-day life. The subsequent research paper presents an outline regarding the evolving technology of Dynamic Multipoint VPN. The main purpose of this research paper is to understanding the working principle of Dynamic Multipoint VPN in GNS3 tool using RIP protocol by building tunnel and providing security features(encryption) so that spokes can access hub resources.

Keywords: VPN, GNS3, RIP, tunnel, encryption

Abstract: Computer network is an important thing to connect to various device to get desired information. Networks can be wired or wireless, but most networks will use both. The subsequent paper provides an outline regarding Wi-Fi model technologies using tool like packet tracer. This simulation tool is very easy to build network that can be used to accomplish, analyse numerous networking activities Also, it gives an idea of using WLC and LWAP component to connect to various department and to access the ISP it uses NAT process. WLC is commonly used in the company location to give an individual wireless network in a huge geographical region.

Keywords: Wi-Fi, WLC, LWAPP, ISP, NAT.

Abstract: Parkinson’s disease is a progressive and chronic neurodegenerative disorder.That affects about 1 million people in the united states, with approximately 60,000 new clinical diagnoses made each year. Due to motor symptoms, it affects the normal life of a person. There is a severe need to identify PD in its early stage to avoid it getting worse and to control its symptoms easily. As the dopamine generating neurons in parts of the brain become damaged or die, people begin to experience difficulty in speaking, writing, walking, or completing other simple tasks. Therefore it is difficult for doctors it in initial stage. A new methodology is proposed in this project for the prediction of Parkinson’s disease severity using Long Short-Term Memory (LSTM) architecture for Parkinson’s disease diagnosis. ‘keras and TensorFlow’ library is used for the implementation of our neural network to predict the severity.The accuracy values obtained by our method are better as compared to the accuracy obtained in previous research work.

Keywords: Parkinson”s disease, Deep Neural Network, LSTM, Keras and Tensor Flow, Chronic Neuro Disorder

Abstract: Fake Web application is software that mimic functionality of valid, reliable and genuine applications. once this applications are installed they perform malicious actions like aggressively display advertisements to get revenue from that, intercept sensitive data from your system, infect devices and so on. Most of the times the user cannot differentiate between the fake and legitimate applications hence before downloading any app people always enquire about the opinion of the app by the users. In this paper we are introducing a platform where people can enquire about the application before downloading it. The results are based on previous reviews and ratings given by the user which provides a chance to recognize user experience with a particular mobile app. Basically we will analyze the reviews using sentiment analysis which is a text classification technique which analysis text and tells whether the sentiment is positive, neutral or negative

Keywords: Sentiment analysis, text classification

Abstract: A product recommendation is basically a filtering system that seeks to predict and show the items that a user would like to purchase. It may not be entirely accurate, but if it shows you what you like then it is doing its job right. With the vast amount of data that the world has nowadays, Companies like Amazon use their huge amounts of data to give recommendations for users. Based on similarities among items, systems can give predictions for new items rating. Recommender systems use the user, item, and ratings information to predict how other users will like a particular item. The motivation for this project comes from the eagerness to get a deep understanding of recommender systems. In this project, a website has been developed that uses different techniques for recommendations namely Frequent Itemset and Association Mining using Apriori algorithm.

Keywords: Product Recommendation, Similar Data items, Machine Learning.

Abstract: Color image encryption is important to ensure its confidentiality during its transmission on insecure networks or its storage. A compression-encryption model to solve these problems. This model consists of three processes. The first process is the dynamic symmetric key generation. The second one is the compression process, which is followed by encryption using key streams and S-Boxes that are generated using a chaotic logistic map. The last process is the symmetric key distribution. The asymmetric key is encrypted twice using Rivest-Shamir-Adleman (RSA) to provide both authentication and confidentiality. Then, it is inserted into the cipher image using the End of File (EoF) method. The evaluation shows that the symmetric key generator model can produce a random and dynamic symmetric key. Hence, the image data is safe from ciphertext-only attacks. This model is fast and able to withstand entropy attacks, statistical attacks, differential attacks, and brute-force attacks.

Keywords: Encryption,Decryption,Symmeteric Key,Dynamic key

Abstract: The project entitled “Cloud based E-Ticketing for MTC buses” is aimed at developing bus e-ticket account to register and purchase e-ticket to avoid direct contact with people. The people who are in need of bus e-ticket can apply through online system. They must provide the basic information necessary for creating an account to get register in the site. The admin approves the application of the person. When they required to purchase an e-ticket they need to select the bus using unique ID(TN 14 XXXX). The public is also allowed to block or deactivate their account if necessary. Thus the project saves time for the public need not wait to get the bus ticket. Steps involved in maintaining the user /client information in the database. After registering, the user can login by entering the username and password. If the password doesn’t match with the password in the database an error message is displayed. If the user wants to change their password they have to provide the current password and new password to confirm his/her password. The password is in the encrypted form in. After login, user has to apply for the form by providing necessary details to get the e-ticket. The admin can check the received applications, verify and then issue the pass. Depending upon the criteria specified, the fixed amount will be deducted from users account when the submit button is clicked. There is a need of reformation of the existing bus ticketing system in this pandemic period we need a contactless e-ticket system with more advantages and flexibility. The main objective of this project is making the entire bus e-ticket process in cloud based system.. The core objective is to integrate the process in the cloud. Keywords—E-Ticket

Abstract: Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. Some of the major fields in which image processing is widely used are Image Sharping and restoration, Medical field, video processing. Image processing is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Fault Detection and Isolation (FDI) is essential in industry to detect and isolate objects with manufacturing defect. Manual inspection is time consuming and all the features of the components cannot be verified accurately. Hence, there is a need for an image processing based system to detect the anomalies in the components. Components are detected by using camera and the captured image are pre-processed to remove background noise, then image is enhanced to get the appropriate features by KNN algorithm. The KNN algorithm is more efficiency than the existing SVM algorithm and Region of Interest is extracted to measure the diameter.

Keywords: Fault Detection and Isolation, Image processing, KNN algorithm.

Abstract: Virtualization has attained mainstream status in enterprise IT industry. Despite its widespread adoption, it is known that virtualization also introduces non-trivial overhead when tasks are executed on a virtual machine (VM). In particular, a combined effect from device virtualization overhead and CPU scheduling latency can cause performance degradation when computation intensive tasks and I/O intensive tasks are co-located on a VM. Such an interference also causes extra energy consumption. In this paper, we present Hylics ,a novel solution that enables efficient data traverse paths for both I/O and computation intensive workloads. This is achieved with the provision of in-memory file system and network service at the hypervisor level. Several important design issues are pinpointed and addressed during our prototype implementation, including efficient intermediate data sharing, network service offloading, and QoS-aware memory usage management. Based on our real-world deployment on KVM, we show that Hylics can significantly improve computation and I/O performance for hybrid workloads. Moreover, this design also alleviates the existing virtualization overhead and naturally optimizes the overall energy efficiency Keywords VRM Virtual reality Machine IDE Integrated Development Environment KVM Kernel based Virtual Machine

Abstract: In smart cities, water problem may arise in the summer season and wastewater can be reused to solve this problem. Wastewater is the water once used and it requires cleaning before reuse. It can be reused for various purposes such as for planting, washing, and other purposes. The home and industry are the major sources for releasing a large amount of wastewater. This water should be treated before reuse. In this paper, a new cloud assisted wastewater management system (CWMS) is introduced to clean the wastewater; reuse based on its purity and shares it globally. The proposed CWMS contains three different steps such as primary, secondary, and tertiary treatment and various sensors have been incorporated for checking the quality (pH, turbidity, salinity, etc.) of treated water. For testing, the wastewater is taken from two places of the study area, Bangalore city, India, and various parameters have been studied. An experimental setup has been developed using Arduino UNO and the performance of CWMS is tested for two different wastewater types. All the details about the treated water have been updated in the cloud for global access and proper utilization.

Keywords: Waste water management.

Keywords: Face Recognition, Image Processing, Eigen face, Principle Component Analysis

Abstract: Secure password storage is a vital aspect in systems based on password authentication, which is still the most widely used authentication technique, despite its some security flaws. In the password authentication framework that is designed for secure password storage and could be easily integrated into existing authentication systems. In our framework, first, the received plain password from a client is hashed through a cryptographic hash function (e.g., SHA-256). Then, the serialized code is converted into a negative password. Finally, the negative password is encrypted into an Encrypted Negative Password (abbreviated as ENP) using a Hashing algorithm (e.g., SHA 152), and multi iteration encryption could be employed to further improve security. The cryptographic hash function and symmetric encryption make it difficult to crack passwords from ENPs. Moreover, there are lots of corresponding ENPs for a given plain password, which makes pre computation attacks (e.g., lookup table attack and rainbow table attack) infeasible. The algorithm complexity analyses and comparisons show that the ENP could resist lookup table attack and provide stronger password protection under dictionary attack. It is worth mentioning that the ENP does not introduce extra elements.

Abstract: Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms. However, traditional diagnostic approaches may suffer from subjectivity as they rely on the evaluation of movements that are sometimes subtle to human eyes and therefore difficult to classify, leading to possible misclassification. In the meantime, early non_motor symptoms of PD may be mild and can be caused by many other conditions. Therefore, these symptoms are often overlooked, making diagnosis of PD at an early stage challenging. To address these difficulties and to refine the diagnosis and assessment procedures of PD, machine learning methods have been implemented for the classification of PD and healthy controls or patients with similar clinical presentations (e.g., movement disorders or other Parkinsonian syndromes). To provide a comprehensive overview of data modalities and machine learning methods that have been used in the diagnosis and differential diagnosis of PD. These studies demonstrate a high potential for adaptation of machine learning methods and novel biomarkers in clinical decision making, leading to increasingly systematic,informed diagonosis of PD.

Abstract: Android is an open source and Linux-based Operating System for mobile devices such as smart phones and tablet computers. Android was developed by the Open Handset Alliance, led by Google, and other companies. Android offers a unified approach to application development for mobile devices which means developers need only develop for Android, and their applications should be able to run on different devices powered by Android. The first beta version of the Android Software Development Kit (SDK) was released by Google in 2007 where as the first commercial version, Android 1.0, was released in September 2008.Android powers hundreds of millions of mobile devices in more than 190 countries around the world. It's the largest installed base of any mobile platform and growing fast. Every day more than 1 million new Android devices are activated worldwide. .

Keywords: Alert Message System, APK (Android Package Kit)

Abstract: Mobile technology have rapidly advanced over the years, successful researches of Virtual Reality on mobile phones under the different mobile platforms have made it possible to implement augmented reality technology on mobiles. Now the possibility of combining real time visual with VIRTUAL reality seems to be a success. Virtual Reality (VR) has become one of the leading trends in recent years. There is no doubt this technology will dominate in 2020 and the years that follow. Real estate agents, designers and people who plan to remodel their houses, apartments or offices can all find an ideal solution in AR.The model house is a package of commercial houses, and is also a reference example of the decoration effect of the buyers. The model house is the face of a real estate, and its quality directly affects the sales of the house. While VR allows users to see things in a three-dimensional space in a timely and unrestricted manner, as if they were there. Therefore, combining VR with a model house can bring a better experience to users.

Abstract: The increasing use of media in communications, the content security of digital images attracts much attention in both the academia and the industry. Meanwhile, for the symmetric cryptosystem, the key transmission and management is burden on users. Here propose an asymmetric image encryption algorithm based on an elliptic curve cryptosystem (ECC). The sender and the recipient agree on an elliptic curve point based on the public key sharing technique. First, to reduce the encryption times, the sender groups pixel values together and converts them into big integers. Second, the sender encrypts big integers with ECC and the chaotic system. Finally, the encrypted image is obtained from encrypted big integers. The algorithm makes the key transmission and management relatively simple and secure. Simulation data show that the proposed algorithm exhibits both the strong security and the high efficiency.

Abstract: The motivation for every location based information system is: “To assist with the exact information, at right place in real time with personalized setup and location sensitiveness”.Now a days we live in an era of technology, smart phone become a part of our daily life. It is no longer a communication device only but also an essential part of our working life.. In our project we have developed an android based application named “Android Location Alarm” at this application we tried to provide various location based services in one place. The app provides nearby service and it also has an alarm system that will work when user set the alarm to specific place and come near the place. The user may set, reset, disable, edit and set duration of the alarm as their wishes. User may view the destined locations on a map to check how far he/she is from the destined location

Keywords: Android Location Alarm, Location Based Services

Abstract: In order to effectively prevent the spread of COVID19 virus, almost everyone wears a mask during corona virus epidemic. This almost makes conventional face recognition technology ineffective in many cases, like community access control, face access control, facial attendance, facial security checks at train stations, etc. Therefore, it's very urgent to enhance the popularity performance of the prevailing face recognition technology on the masked faces. Most current advanced face recognition approaches are designed supported deep learning, which depend upon an outsized number of face samples. Deep Learning has proven its effectiveness in recognition and classification through image processing. However, at the present, there are not any publicly available masked face recognition datasets. To this end, this work proposes three kinds of masked face datasets, including Masked Face Detection Dataset (MFDD), Real- world Masked Face Recognition Dataset (RMFRD) and Simulated Masked Face Recognition Dataset (SMFRD). Among them, to the only of our knowledge, RMFRD is currently the world’s largest real-world masked face dataset. These datasets are freely available to industry and academia, supported which various applications on masked faces are often developed. The multigranularity masked face recognition model we developed achieves 92% accuracy, exceeding the results reported by the industry.

Keywords: Deep Learning, Face Recognition Dataset,COVID19.

Abstract: The market data of web based business agrarian products has the attributes of intricacy and delay. It is hard for makers to acquire and precisely handle the constant market data on schedule, bringing about monetary misfortunes under the data imbalance. From the viewpoint of item makers, joined with the application layer of new blockchain innovation and the fundamental stage and administration foundation of internet business data stage, an internet business farming product choice emotionally supportive network, which depends on blockchain innovation and fixated on blockchain information base, is developed. The framework comprises of three sub-frameworks: online business horticultural product data administration stage, inventory data input stage and coordinations data criticism stage, and it finishes the assortment, arranging and yield of these three sorts of data under the help of blockchain framework, in order to help rural makers settle on correct choices and accomplish the motivation behind advancing agrarian product deals and expanding ranchers' pay.

Keywords: - decision support system; blockchain; e-commerce; information service

Abstract: Cloud computing is a rapidly emerging technology. This technology offers access of services, software, applications, database storage and required resources for infrastructure computing to any user from anywhere. Virtualization is also a key feature in cloud computing. Many organizations uses virtualization for cost savings, to reduce power consumption, Server Consolidation, Testing and Development, Dynamic Load Balancing and Disaster Recovery, Virtual Desktops and Improved System Reliability and Security. This paper will be focused on emerging virtualization technology, classification of virtualization, applications, advantages and disadvantages of virtualization.

Keywords: Virtualization, Cloud Computing, Classification of Virtualization.

Abstract: Trust assessment is one in all the foremost difficult problems that arise in a cloud computing environment. Consumers feedback is a good source to assess the overall trustworthiness of cloud services. To make these difficult problems be simpler by getting feedbacks from users. Generally a cloud refers to a public semi-public space on transmission lines that exists between the end points of a transmission. Cloud providers can be chosen based on advertisements. Based on the usage of particular provider service users can be considered as real users. Reviews can be collected from all users. By the use of Trust Management Service (TMS) algorithm an original user reviews can be identified accurately because it provides an interface between users and cloud services for effectiveness in trust management. Attackers can disadvantage a cloud service by giving several multiple misleading feedbacks (i.e.,collusion attacks) or by creating a multiple accounts (i.e., Sybil attacks). Filtering of fake reviews done based on the attacks of Sybil and collusion. Consumer privacy is achieved through feedbacks. In order to protect cloud services from malicious users reviews can be filtered.

Keywords: Trust Assessment (TS), Trust Management Service (TMS)

Abstract: Enterprise culture is the soul of an enterprise, which is the key to obtain sustainable competitive advantage. For enterprise survival and development, enterprise culture is not the direct factor, but the most lasting decisive factor. In this paper, given the important role of enterprise culture in the process of human resource management practice, combining cultural construction with recruiting ,training, utilizing, and retaining talent to improving the level of human resource management to achieve benign interaction between culture construction (of the company) and human resource management. An effort is made in realizing a long-term sustainable competitive goal to obtain an invincible position in the present competitive market. Human Resource Management can be defined as planning, organizing, directing and compensating human resources resulting in the creation and development of human relation with a view to contribute proportionately to the organizational and individual goals. The examination of raw or crude data and drawing conclusions out of it is called data analytics. In this paper we will be analysing the employee turnover pattern and the factors contributing to it. Efforts will be made to create a model that can predict if a certain employee will leave the company or not. The goal is to create or improve different retention strategies on targeted employees. The first step in data analytics- data pre-processing is presented in the paper. Data pre-processing techniques convert crude data into useful format. Real world data are generally incomplete- noisy, inconsistent and contains many errors. Removing these factors improves the quality of analysis and prediction. The focus of data analytics lies in inference, the process of deriving conclusions. In this paper 2 out of top 3 strategies affecting employee turnover are being analysed and graphs plotted. The 3 top features include evaluation v/s exit, average monthly income v/s exit and satisfaction v/s exit. In this paper we have taken up the challenge of predicting the exit vs. evaluation trends of the company, first using Logistic Regression method, and later using Random forest or Random decision forest method. We also implement SVM (Support Vector Machine) and KNN (K Nearest Neighbour) classification algorithm on the dataset and compare the accuracies of the model. Best model is selected on the basis of ROC graph and Accuracy Percentage.

Keywords: Logistic Regression, Random decision forest, Human Resource Management, examination of raw or crude data and drawing conclusions- data analytics, employee turnover pattern, data pre-processing, evaluation v/s exit, average monthly income v/s exit, satisfaction v/s exit, planning, organizing, directing and compensating, competitive advantage, SVM (Support Vector Machine), KNN (K Nearest Neighbour) classification algorithm, ROC graph.

Abstract: From these last two decades nearly 1lac students were gone missed while going to the collage or school so its require the collage and school authorities should take the responsibility. It is important to build the system which is automatic and secure. Conventional method of attendance taking is very time consuming task, every time students have sign the attendance sheets of lecture has to call their name it is not easy to maintains attendance. There many digital systems are evolved but they have their own flows. So this face detection attendance management system will solve all existing problems. The attendance is marked by detecting the face which is captured by the CCTV camera; it will compare the extracted face data with the database. Once the faces are detected then it will update the attendance report with time and date. It will mark the present for recognized students and it will mark absent for other students who data is present in data base but not recognized.

Keywords: - Artificial Intelligent, Machine learning.

Abstract: Robotics has become a rapidly growing science that will enter the life of all classes of people. A project that uses robotics and detection method to help people and rescuers at the time of disasters by detecting alive human beings is proposed. Natural calamities like Earthquakes, Tsunami and man-made disasters bomb explosion, building collapse often occur and they cannot be stopped. They produce a devastating effect and find no difference among human and material. Therefore at that time humans are buried among the detritus and it becomes impossible to detect them. Only a timely rescue can only save people, who are buried and wounded. Detection by rescue workers like policeman, fire fighters and medical services is time consuming because of the vast area that gets affected. Human rescuers must make quick decisions under stress and try to get victims to safety at their own risk. They need to find the location, status of victims and the stability of the structures as fast and early as possible so that medics and fire fighters can enter the disaster area and save the victims. This project proposes a mobile robotic vehicle that moves in the disaster prone area for detecting humans in such devastating environments and helps to identify the victims during the rescue operations

Abstract: Our proposed research work is based on the online data base authentication system, using this we can make our country as smart country. Not only smart country but also, we can make our country secure and crime free where any person would think before performing any illegal activity. This system is controlled and authenticated by online database. The special feature of this system is that it can be installed anywhere easily. For example, if we implement this system into a vehicle than any other person cannot drive the vehicle without driving license and without any permission of the owner of the vehicle. Apart from this, if any person tries to drive the vehicle without following the rules in a proper way and caught then the Challan will be applicable on the driver of the vehicle instead on the vehicle. If that driver does not pay the Challan within a certain time limit, his driving ID will be suspended and after that he will not have the right to ride any vehicle. Not only this, if we implement this system in mall, taxies, buses, banks, parks, shops, and other social places then only a person can go to these places who have Indian citizenship or who is validate by Indian government. As a result, with the help of this project, illegal activities like terrorism and stealing can be stopped as well as persons come from other countries can also evaluated. Apart from this, if any person performs any illegal activity or crime, his ID can be blocked so that he cannot go to those places where this system is installed. If he tries to run after doing any crime, then he can be easily caught by the system which is installed in buses and taxis. Or if he goes to the social places where our system is installed then also, he can be easily caught. In such a way we can enhance the security of any place by installing this system even that place can be our home, or any social place. System consist of a smart card (RFID CARD) and fingerprint (optional). RFID cards contain the information of driving ID number (like A4BCN356) and it is verified by our created online data base where the data base contained the information of an driving ID numbers of vehicle driver there from it will verified by online stored data base after passing this authentication, an acknowledgment signal will send by microcontroller which is shown on display to verify the RFID detail of driver after this whole process vehicle will start or ignited.

Keywords: Security System, RFID, Vehicle Security, Authentication.

Abstract: Machine learning involves artificial intelligence, and it is used in solving many problems in data science. One common application of machine learning is the prediction of an outcome based upon existing data. The machine learns patterns from the existing dataset, and then applies them to an unknown dataset in order to predict the outcome. Classification is a powerful machine learning technique that is commonly used for prediction. Some classification algorithms predict with satisfactory accuracy, whereas others exhibit a limited accuracy. This paper investigates ensemble classification, which is used for improving the accuracy of weak algorithms by combining multiple classifiers. Experiments with this tool were performed using a heart disease dataset. A comparative analytical approach was done to determine how the ensemble technique can be applied for improving prediction accuracy in heart disease.

Keywords: Bagging, Boosting, Stacking, Voting Classifier, Heart Disease Prediction Model.

Abstract: In today’s world, Diabetes may be a quite common disease which affects tons of people’s health. As the number of diabetic patients is increasing significantly in India, there is a rise in numerous associated diseases that have disturbed the society. Diabetic Retinopathy (DR) is taken into account to be one among such silent diseases which occur as results of either Type 1 or Type 2 diabetes. Late diagnosis of this disease may cause permanent eye blindness. Thus, for early diagnosis of Diabetic Retinopathy, a software-based algorithm is meant here. This technique are often promising for the pre-detection of DR with none involvement of an expert doctor and hence will save both time and money. Here, CNN based image processing is used which exploits the knowledge of Computer Science and Biomedical Engineering to identify whitish lesions, cotton wool spots and hard exudates associated with DR. Based on the worth of pixel counts, the image of the patient’s eye under examination is assessed as a Diabetic Retinopathy eye or a Non-Diabetic Retinopathy eye.

Keywords: Amazon Web Server, Digital Ocean Server, Puttygen.exe, Putty.exe, Winscp

Abstract: Many metric-based classification models have been developed and applied to software fault-proneness prediction. This paper presents a novel prediction model using Random Forest classifier. Random Forest (RF) can be a promising candidate for software quality prediction because it is one of the most accurate classification algorithms available and has strengths in noise handling and efficient running on large data sets. The RF model is constructed and the attribute selection process of the input data is performed before the model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I and Type II error rates, and compared with well-known prediction models, MultiLayer Perceptron (MLP) neural network model and Support Vector Machine (SVM) model. The results show that the RF model significantly outperforms the SVM model and slightly outperforms the MLP model.

Keywords: fault-proneness, prediction model, random forest

Abstract: The objective of the study is to compared the Physical well-being of Student Athletes and Regular Yogic Practitioners. Total 100 students athletes Who had participated in inter collegiate tournaments and 100 Regular Yogic Practitioners was randomly selected as subject for the present study. The findings of the study reveal that Students Athlete was better Nutritional dimension of physical well being Universal Supreme Health compared to Yogic Practitioners . The findings of the study reveal that Students Athlete was better Exercise dimension of physical well being Universal Supreme Health compared to Yogic Practitioners. This study will help to know about to improve Universal supreme Health for all well being among all people

Abstract: COVID-19 is the greatest humanitarian challenge facing the world ever since World War II. World has been fighting the pandemic with great spirit, with the unlocking phases being in motion. Wearing mask properly has become an effective method to cut down the spread of virus transmission. In this work, we are targeting to build a system where we can detect fine-grained state of wearing mask. This work involves three major challenges: 1) different face orientations, 2) various mask types and patterns and 3) facial occlusions. To resolve these challenges we created a new practical dataset, which contains 4000 images. The proposed approach here uses OpenCV and Machine Learning with MobileNetV2 architecture as image classifier to perform mask detection in real time. This model achieves an accuracy of 97%. The new practical dataset created can be used for further advanced models for thermal screening and facial recognition.

Keywords: COVID-19, new practical dataset, OpenCV, Machine Learning, MobileNetV2.

Abstract: The immensely improving the advancement of upcoming generations, the fifth-generation wireless technology continuously developed and extent to more progressive. The field of mobile technology offers improved network capacity, small latency, excessive availability, additional reliability with dynamic speed. This paper presents an outline of fifth-generation wireless technology. In recent times, energy cost and its involvement to global carbon dioxide emissions are evolving as key concerns, which is a severe problem for cellular networks. Moreover, Energy Efficiency (EE) is an enormous approach that massively declines the circuit power consumption in fifth-generation cellular networks. This significance is enhanced due to the expanding number of antennas in massive multiple-input multiple-output (MIMO) systems. Energy efficiency has now become a major aspect in context of communication networks. With the advent of the fifth generation of wireless networks, with millions of additional base stations and billions of connected devices, the demand for energy-efficient system design and operation will be even more fascinating. Further, this paper emphases in simulating an area enclosed by random implementation of small cells to serve hundreds of users i.e., Massive MIMO in the simulation area. The outcomes illustrates that the energy efficiency exploiting operation point might be very spectrally inefficient, and the efficient energy can be significantly enhanced by increasing the base station density. Thus, Massive MIMO is a promising solution for maximal energy efficiency implementation.

Keywords: Fifth generation, Massive MIMO, small cells, base station, Energy Efficiency (EE).

Abstract: Bigdata is a potential instrument to transform traditional governance into smart governance. There are a long debate and discussion on the application of big data for the transformation of traditional public administration to modern and smart public administration in the academician, researchers, and policymakers. This study aims to explore the suitability and applicability of big data for smart governance of public agencies. A systematic review of literature and meta-analysis method is employed with various levels of scales and indicators. Literature survey shows that a number of models have been developed to explain smart governance but systematic research on the suitability and applicability of big data for smart governance of public agencies is still lacking. This article argues that the application of big data for smart governance in the public sector can increase the efficiency of the public agencies fastest public service delivery, enhancing transparency, reducing public hassle and helping to the become a smart agency.This paper further argues that implementation of big data for smart governance has a significant role in timely, error-free, appropriate and cost-effective service delivery to citizens which leads to the sustainable economic development of a country. The findings suggest that every public-sector agency should be brought under smart governance which should be a fully promoted under big data technologies for easy access, transparent and accountable, and hassle-free public agencies

Keywords: Governance; public administration; Big Data; Digital; Smart Governance

Abstract: Cloud computing field is a rising technology and despite much research has been carried out but still challenges exist in work related to load balancing in cloud related applications. Load balancing algorithms are viewed from cloud environments such as Static and Dynamic Environment. An efficient task scheduling is an important action in cloud computing and understanding Load balancing from this perspective is essential for designing an algorithm which should be efficient from already existing algorithms . Task Scheduling is an important factor in load balancing and scheduling tasks. The main goal of this paper is to study and understand load Balancing and the parameters that affect the performance of an algorithm, analyze it on the basis of environment and performance in the view of task scheduling by considering task parameters such as execution time, Makespan, resource allocation.This paper also highlights the need of performance metrics from the view of Task scheduling and how it can increase the overall performance of the load balancing algorithm and also be economical at the same time.

Keywords: Cloud computing,resource utilization, load balancing,task scheduling,Virtual machines(VMs),makespan.

Abstract: The idea of Cloud gaming involves allowing users to play games from anywhere while being connected to a network without worrying about the hardware and software requirements of the game. This is achieved by running the game on high end devices located far away and streaming the video to the user while accepting his commands. The system faces issues like latency which degrades the Quality of Experience. However, with advancements in 5G technology and Edge Computing the problem of delay, bandwidth utilization can be solved to achieve a smooth user experience. The coming days will only attract more users to the already popular Cloud gaming area so, the existing system must keep improving to provide service indistinguishable from conventional gaming. This paper presents a survey on utilizing Edge Computing for improving Cloud Gaming systems. The study of the edge based system is done using two Cloud Gaming systems namely EdgeGame and GamingAnywhere. The paper highlights some of the prospects of Edge Computing that can be used to improve Cloud Gaming. The Edge Computing technologies can be used to reduce latency, bandwidth usage and congestion to improve overall user experience in Cloud Gaming. The paper also presents the opportunities and potential challenges faced in the area of cloud gaming.

Keywords: Cloud Gaming, Edge Computing, Edge nodes, Cloud Data Center, Quality of Experience, Latency, Bandwidth.

Abstract: Nowadays testing has become most important to ensure better reliability, security and high performance. The subsequent research paper presents an outline regarding Selenium. The main purpose of this research paper is to understand automating of applications in Eclipse tool using Selenium Web driver by writing code to the every fields in an application.

Keywords: Testing, Selenium, Eclipse, Web driver.

Abstract: The rise of e-commerce in each B2C and B2B sectors have provided a superfluity of opportunities for businesses to expand their reach, generate omnichannel revenue, and target new customers. It does, however, bring tremendous competition, as new firms, giant and tiny, frequently enter the market and contend for a bit of the action.The Indian retail trade has become one in all the foremost dynamic and fast industries as results of the entry of the many new enterprises. Total consumption expenditure is predicted to succeed in virtually US$ three, 600 billion by 2020, up from US$ one, 824 billion in 2017. In fact, the retail sector accounts for quite simple fraction of the country's gross domestic product and employs over 8 May 1945 of the force. India is that the worlds fifth-largest retail destination. India is placed 73rd within the 2019 Business-to-Consumer (B2C) E-commerce Index discharged by the United Nations Conference on Trade and Development. In keeping with the planet Bank's Doing Business 2020 report, India is that the world’s fifth-largest retail destination, stratified 63rd. In terms of retail, India is that the world's fifth largest destination. India is placed sixteenth within the FDI Confidence Index (after the USA, Canada, Germany, UK, China, Japan, France, Australia, European nation, and Italy). (Indian complete Equity Foundation) Businesses should make sure that their offer chain management activities square measure well joined so as to flourish in ecommerce. The Supply chain must be equivalently capable of supply ecommerce sales channels because it is in offline marketplaces. This paper tries to answer the subsequent queries by relating the prevailing literature why offer chain is thus necessary to e-commerce success, what square measure the vital areas to be targeted whereas adopting offer chain management and {to provide tooffer to produce} appropriate suggestions so as to boost supply chain potency. Key Words: Logistics, supply chain management, e-commerce, e-supply chain management, Internet, competitive advantage, information systems and technologies.

Abstract: This paper describes the various benefits offered by drone for commercial as well as home purpose. Traditionally people uses remote to control the drone however it is very difficult to control and stabilize the drone and it may results into an accident. Sometimes drone undergoes into an unstable conditions which makes our drone uncontrollable. In this paper we have used GSM module to make our drone more stable and to set to co-ordinates. These upgrades to the basic drone will make more cost efficient in terms of maintenance. These upgrades probably make our experience more reliable and beneficial. Keywords Drone, Raspberry Pi, GSM, Ultrasonic sensor and UAV.

Abstract: This is a unique system that functions as a voice assistant for visually impaired persons. This system is used to assist the visually impaired in accessing the phone's most vital capabilities while also improving the system's quality through the use of bespoke layouts and text-to-speech. The object detection system employs tensor flow object detection techniques, in which an android application detects obstacles and guides the end-user via voice alert, providing information such as the distance between the object and the person, as well as the object's direction [left, right, or middle]. All in all, the System is a voice assistant for whatever action the user has taken with a custom app while using data from the default app.

Keywords: Visually challenged, object detection, distance of the object, direction of the object, voice output.

Abstract: Emotional stability enables the person to develop an integrated and balanced way of perceiving the problems of life. The objective of the study is to determine the Emotional Stability characteristics of College going Sportsperson and students. Total 100 players of different sports discipline and 100 students were randomly selected as subject for the present study. Their age ranged from 18-25 years. Self design Questionnaires were distributed to the respondents. Descriptive statistics for all studied variables, T-test analysis, was considered statistically technique throughout the study and the level of significant was set-up at.05 level. The result reveals that the significant difference was found out in (t=2.88, P < 0.05) players of different sports discipline and students

Abstract: Technology is ameliorating in it’s characteristics day by day so we could find solutions to the quandaries that people face. There are many of the people who couldn’t walk due to visual impairment, for those people travelling is one of the major quandary. If they require to utilize public convey they must depend on the good will of the people around them to avail. Thus an Perspicacious electric conveyance can solve their quandary. This conveyance is composed of many technologies such as Digital image processing for obstruction detection, road detection, traffic signals and sonar, infrared LiDar predicated obstruction avoidance. GPS and map predicated location guidance for conveyance. We design a thoroughly perspicacious electric conveyance for blind which can be implemented prosperously. The conveyance is designed in such a way that it complies with all the traffic signals so that the design is apt for genuine world. Keywords—Ultrasonic sensor, Image processing, Traffic Management , Auduino

Abstract: Time table age is monotonous occupation for educationalist concerning time and labor. Giving a programmed time table generator will assist with creating time table consequently. Proposed arrangement of our undertaking will assist with producing it consequently likewise assists with saving time. It keeps away from the intricacy of setting and overseeing Timetable physically. In our venture we will utilize calculations like hereditary, heuristic, asset planning to diminish these troubles of producing schedule. These calculations join a numeral of methodology, expected to work on the operativeness of the inquiry activity. The framework will take different information sources like number of subjects, instructors, responsibility of an educator, semester, need of subject. By depending on these information sources, it will create conceivable time tables for working days of the week for educating workforce. This will incorporate by utilizing all assets such that will best suit the limitations.

Abstract: Cloud computing is a subscription-based service to obtain network storage space and computer resources. Cloud provide users to store large volume of data and to perform application over cloud also provides greater flexibility of storing and computation of data but, Such applications can be processed, huge volume processing data sets are to be generated. For Storing some valuable intermediate datasets has been considered in order to avoid the high recomposing them. In this paper, the concepts involved in data anonymization will be addressed, some of the techniques used for this anonymization will be studied, which are the risks of re-identification associated and the analysys of some software tools that allows to perform these techniques.

Keywords: Cloud, Anonymiization, ARX.

Abstract: A non-invasive diagnosis technique place an important role for early detection of melanoma malignant for dermoscopic image. Even for experienced dermatologist, diagnosis by human vision can be non-reproducible, inaccurate and subjective. The image characteristics include fuzzy lesion boundaries, varying lesion shapes and their sizes, presence of hair and color types of different skin. To assist in the interpretation of the image, the automatic classification of dermatoscopy images has proven to be a valuable aid in clinical decision making. However, existing methods have problems in representing and differentiating skin lesions due to the high degree of similarity between melanoma and non-melanoma images and large except from the images a variety of skin lesion. To overcome these limitations, this study proposes a new method for automatic multi-scale public of melanoma in dermoscopy images of the lesion is biased representation (1000) and vice versa general classification (JRC). For the diseases of the skin by means of the representation of the 1000 round, so that is set before us represent a number of scales, to use the traditional methods from a variety of Histograms of one of the scale is very near and the skin is able to represent the histogram of the lesion. 1000 or representation was used by the JRC melanoma detection. JRC The proposed model allows us to use additional data to derive a set of approximately Histograms of melanoma is going, where existing histogram like most trust in him. General Calendar method in public in our dataset of dermoscopy images, and demonstrates superior performance compared to the current state of the art method.

Keywords: JRC, Lesion Segmentation, MATLAB, Image Acquisition system.

Abstract: This project is to design and implement the smart train Black box system for train accident and security system. The rapid rise of technology and infrastructure has made our lives easier. The high demand of automobiles has also increased the traffic hazards and road accidents. Life of the people is under high risk. The delay in reaching of the ambulance to the accident location and the traffic congestion in between accident location and hospital increases the chances of death of the victim. This proposed IOT based accident detection system helps to reduce the loss of life due to accidents and also reduces the time taken by the ambulance to reach the hospital. To detect the accident there is accelerometer sensor present in this rescue system and the IOT module included sends messages about the location to the respective guardian and rescue team. This automatic ambulance rescue system project is useful in detecting the accident. The sensor will work as a providing security to the owner who is inside the train.

Keywords: IDE, LDO, RST, DIP Black box system.

Abstract: In today’s cyber attacks and cyber crimes world Botnet is the severe threat which occurs usually. Botnet are intended to perform predefined functions in an automated fashion, where these malicious actions ranges from online searching of data, accessing lists, moving files sharing channel information to DDoS attacks not in favor of critical targets, phishing. Various types of techniques and approaches have been projected for detection, mitigation and preventation to Botnet attack. This paper discusses in detail about Botnet and related research including Botnet evolution, life-cycle, command and control models, communication protocols, Botnet detection etc. Also an general idea of research on Botnets which describe the possible attacks performed by various types of Botnet communication technologies in future.

Keywords: Bot; Botnet; C&C mechanism; communication protocols; honeynet; passive traffic; attacks; defense; preventaation