VOLUME 6, ISSUE 9, SEPTEMBER 2017

Abstract: Usually, professor in institutes take students attendance by roll call or through attendance record sheet where students mark their signature. These approach of taking attendance is tedious and time consuming. These Bluetooth attendance Android App will help Professor to take students attendance through student mobile phone Media Access Control (MAC) addresses, since MAC is unique for each device proxies can be eliminated. Within the fraction of seconds student�s attendance can be taken. Moreover, detailed record of a student's attendance can also be generated for printing and filing, in an Excel sheet format in the professor�s mobile phone or mail the attendance record to the professor�s email.

Keywords: Android, attendance, meeting record, professor�s personal digital assistant, attendance tracker, dynamic timetable.

Abstract: Because of the progressive changes in the innovation and creation of cellular networks, the versatile clients are using ubiquitous internet access. As the mobile internet access becomes heavy in densely populated cellular base stations, there are several challenges for cellular operators in providing constant speed to all users without throttling speed connection. We have provided load balancing in selected base stations called drop zones where the cellular infrastructure is upgraded and internet access is provided at low cost. There is more chance for drop zone to be overloaded beyond its capacity due to low cost and good speed and as it is located in populated areas. Drop Zone approach with load balanced dynamic source routing protocol forms ad-hoc network with incoming mobile hosts if it needs to download prefetched content by other mobile hosts. If the incoming mobile host need to upload content and if the capacity of the drop zone is overloaded then the mobile host is routed to the nearby normally loaded drop zone by knowing the user�s route.

Keywords: Load balancing drop zone, DSR, Cellular Networks.

Abstract: This paper addresses the development of a hand gesture recognition system for Indian Sign Language. In this a Sensor Glove is developed which is used by speech impaired people to communicate with others. The Glove converts the hand gestures into corresponding text as well as speech. The Hand glove is composed of 5 flex sensors, a MPU 6050 which combination of both accelerometer and gyroscope, a Microcontroller which is Arduino Pro Micro and Bluetooth transceiver HC-05. The readings from the sensors send by the microcontroller to the Mobile Application using Bluetooth connectivity via Bluetooth transceiver. Mobile applications directly send these readings to the server using UDP (User Datagram Packet) Connection. On the Server side hand gesture is recognized using Artificial Neural Networks (ANNs). A Machine Learning algorithm using Multilevel Perceptron is implemented on Server, to which a input of 78 features extracted from readings are given a and output is obtained as recognition of words or letters corresponding to the gesture. This output is send back to the App where it is displayed as text as well as can be heard as a speech. Thus in this way system helps to give the voice to the speech impaired people.

Keywords: Sign Language, Flex Sensors, 3-axis Accelerometer, Microcontroller, Bluetooth Transceiver, Multilayer Perceptron.

Abstract: Due to limited battery capacity of each sensor nodes, minimization of energy consumption is a potential research area in Underwater Wireless Sensor Networks (UWSNs). However, energy hole and coverage hole creation leads performance degradation of UWSNs in terms of network lifetime and throughput. It address the hole creation issue due to lack of energy in depth based routing techniques, and devise a technique to overcome the deficiencies in existing techniques. Besides addressing the energy hole issue, proposition of coverage hole repair technique is also part of this research work. In areas of dense deployment, sensing ranges of nodes redundantly overlap. Coverage-aware sensor automation (CASA) protocol is proposed to realize an automated smart monitoring network. Two centralized algorithms are included in the CASA protocol suite: enhanced virtual forces algorithm with boundary forces (EVFA-B) and sensor self-organizing algorithm (SSOA). Unlike most previous works that tackle the deployment problem only partially, we intend to address the problem from both global deployment (EVFA-B) and local repairing (SSOA) perspectives.

Keywords: Sensor, automated, routing, protocol.

Abstract: The issues on public health care and how to make right decisions on public health care. This helps in effective use of data and how to utilize the data in a proper way including improvements. The purpose of this study is to examine the use of data usage considering issues related to that. The study is analysed to over-come with the issues at public health care system by using certain methodology. The major prospect of this methodology is to make out the organizations between usage of data and data mining to help with decision making at various levels of public health care in India. The designed model also shows the improvements on decision making using analytical skills. Despite skills are not only required or not only sufficient in public health. Thus by combining the decision making with models would generate strong platform for data mining. To apply the constructed models are possibly the high effective involvement that enriches usability of data. In order to support the analysing of data and non-stop assessment of models on approved set of indicators of success on which their presentation are assessed of India.

Keywords: Public Healthcare; DSS; Data Mining; CRISP-DM; Decision Making.

Abstract: The design and implementation of the energy load management is proposed in this paper. The proposed system executes the load prioritization and encourages the real time monitoring of the associated loads in view of the predefined maximum load. This paper proposes the arrangement of a self-decision control framework using Artificial Neural Network (ANN).The ANN is used to generate effective energy load designs. The condition of load is controlled by microcontroller which depends on upon real time monitoring data through PC with the utilization of RF transreceiver module for communication .The server can control each one of the load depend on upon the continuous data from the sensors which are associated with the controller .The real time data of the process is sent to the customer through IOT. To avoid shortage of power on the required load the ANN Algorithm is executed in this system.

Keywords: Electricity, Energy management, Real time monitoring, ANN, IOT.

Abstract: Code Clones are the entities in software ecosystems which can be unavoidable. Demand of software based clone detection has risen in industries day by day. Due to code duplication means the copy and paste activities, such pattern is recurrent thereby developers can reduce effort and time of rewriting similar code fragment by editing already written code. Code duplication may affect on quality, consistency, maintainability and comprehensibility. The trial is variety of syntax, compiler dependent language, and various coding patterns to resolve a single problem. There is lots of software tools, code clone detection algorithms exist, but they have some restrictions to detect perfect cloning. Earlier research and tools developed till now can find only Type-1, Type-2 and some part of Type-3 clones. Some tools are very slow and time consuming for comparing codes and with low in precision. Type-4 clone detection represents a challenge in current scenario. Type-4 is the Code with similar functionality that may be syntactically different but logically similar referred as semantic clones. Proposed system presents an algorithm for clone detection based on comparing parts of abstract syntax tree (AST) of programs and finding semantic coding styles.

Keywords: Type-1, Type-2, Type-3, Type-4, AST.

Abstract: QDMiner aims to offer the opportunity of finding the main points of multiple documents and thus save users� time on reading whole documents. The difference is that most existing summarization systems dedicate themselves to generating summaries using sentences extracted from documents. In addition, return multiple groups of semantically related items, while they return a flat list of sentences. However, the relative importance of this side-information may be difficult to estimate, especially when some of the information is noisy. In such cases, it can be risky to integrate side-information into the mining process, because it can either improve the quality of the representation for the mining process, or can add noise to the process. Therefore, a principled way is required to perform the mining process, so as to maximize the advantages from using this side information. This project designs an algorithm which combines classical partitioning algorithms with probabilistic models in order to create an effective clustering approach.

Keywords: DQMiner, partitioning algorithms, summarization.

Abstract: Cloud computing, individuals can store their data on remote servers and allow data access to public users through the cloud servers. As the outsourced data are likely to contain sensitive privacy information, they are typically encrypted before uploaded to the cloud. This, however, significantly limits the usability of outsourced data due to the difficult of searching over the encrypted data. An efficient search technique for document retrieval from encrypted cloud data is developed. Original contributions are three-fold. First, relevance scores and preference factors are introduced upon keywords which enable the precise keyword search and personalized user experience. Second, a practical and very efficient multi-keyword search scheme is developed . The proposed scheme can support complicated logic search the mixed and �AND�, �OR�, and �NO� operations of keywords. Third, classified sub dictionaries technique is employed to achieve better efficiency on index building, trapdoor generating and query. Lastly, the security of the proposed schemes is analyzed in terms of confidentiality of documents, privacy protection of index and trapdoor, and unlinks ability of trapdoor.

Keywords: Cloud computing, encrypted, confidentiality, trapdoor.

Abstract: Development of web applications or other applications such as windows applications, android/iOS applications are generally carried out in two stages �Back-end development [1] and Front-end development. In this paper, we illustrate the back-end design of a web-based application using MySQL [2] as the back-end tool. In a web application, different categories of login exist like user login, client login, and the administrator login or the admin login. The administrator of a website enjoys added privileges as compared to the user or the client. In this paper, we illustrate the added privileges that the admin savours and his role in managing and amending the website when needed or on a periodic basis. An admin is responsible for adding, deleting and editing employees and employee information; protecting the website against intrusions by proper security settings and encryption; manually adding, deleting or editing items for sale and manually checking the sales report in case of report corrigenda.

Keywords: Back-end development and Front-end development, user login, client login and the administrator login, ER diagram, Referential Integrity, Relational Database Management System, MySQL, database, PHP, HTML and JavaScript.

Abstract: Crime prevention and detection become an important trend in crime and a very challenging to solve crimes. The crime data previously stored from various sources have a tendency to increase steadily. As a consequence, the supervision and analysis with huge data are very tricky and complex. To solve the problems, data mining techniques employ many learning algorithms to extort hidden knowledge from huge volume of data. Data mining is data analyzing techniques to find patterns and trends in crimes. It can help solve the crimes more speedily and also can help alert the criminal detection automatically. Clustering is a data analyzing technique in unsupervised type. This technique is used to divide the same data into the same group and the different data into the other group. For the simple and effective clustering techniques, there are several algorithms such as K-means clustering. This approach is supervised learning scheme that used to dispense objects to one of many pre-determined categories. The algorithms of categorization have been widely applied to the numerous problems that include many various applications. Crime are characterized which change over time and increase continuously. The changing and increasing of crime direct to the issues of understanding the crime behavior, crime predicting, precise detection and managing large volumes of data obtained from various sources.

Keywords: Data Mining, Clustering, K-means clustering, Association Rule Mining.

Abstract: Social recommendation is popular and successful between various urban sustainable applications like products recommendation, online sharing and shopping services. Users make use of these applications to form several implicit social networks through their daily social interactions. The users in such social networks can rate several interesting items and give comments. The majority of the existing studies investigate the rating prediction and recommendation of items based on user-item bipartite graph and user-user social graph, so called social recommendation. However, the spatial factor was not consider in their recommendation mechanisms. With the rapid development of the service of location-based social networks, the spatial information gradually affects the quality and correlation of rating and recommendation of items. This paper proposes Index Base Spatial Social union (IB-SSU), an approach of similarity measurement between two users that integrates the interconnection among users, items and locations. The IB-SSU-aware location-sensitive recommendation algorithm is then devised. This paper evaluates and compares the proposed approach with the existing rating prediction and item recommendation algorithms. The results show that the proposed IB-SSU-aware recommendation algorithm is more effective in recommending items with the better consideration of user�s preference and location.

Keywords: Rating prediction, recommendation, IB-SSU.

Abstract: Autism is a potential threat to the present world as a great number of individuals in the world have been suffering from autism. Some studies indicate that one in every 300 newborn babies is autistic, and others estimate that one in 166 has autistic behavior. Autism is characterized by i) impairment verbal and non-verbal communication, ii) impairment social interaction, iii) lack of imagination, and by restricted and repetitive behavior. Newly emerging theories of neurological functioning in autism are highlighting inter-regional functional and anatomical connectivity of the brain. In the present work, a computational model of the neuron is constructed using electrophysiological and morphological data to analyze autism. The data are considered for the rat sub-thalamic neurons as various researchers indicate that rat sub-thalamic neurons are tantamount to human neurons. In pursuing the study, simulation software NEURON is used to create neurons and connected them. From the response of the simulation experiment some characteristics of autism are explored.

Keywords: Computational, Brain, Modeling, Neuron, Autism, sub-thalamic.

Abstract: Land surface temperature (LST) is a key variable in climatic and ecological studies. However, accurate measurements of LST over continents are not yet available for the whole globe. This thesis first reviews the state of the science of land surface temperature (LST) estimates from remote sensing platforms, models, and in situ approaches. Considering the suspicions, we review the current Land Surface Temperature confirmation and estimation method. Then the requirements for LST products are specified, from the different user communities. In this paper analysis a physics-based method to retrieve LST from the MODIS daytime MIR data in channels 22 (centered at 3.97 �m) and 23 (centered at 4.06 �m). In this method to separate the reflected solar direct irradiance and the radiances emitted by the surface and atmosphere. The MIR spectral region (3�5 �m) has many advantages with respect to the TIR spectral region. MIR using the multispectral thermal imager and found that LST retrieved from MIR is only half as sensitive to errors in LSE as those retrieved from TIR. Consequently, it seems to be more appropriate to retrieve LST from MIR rather than TIR data. However, measurements in the MIR region at satellite altitudes during the daytime consist of a combination of both reflected radiance due to solar irradiance and emitted radiance from both the surface and the atmosphere. In this paper proposed clustering method is implemented to process subsequences of time series data and detects land cover change temperature measured as a function of time. Land cover change temperature measured is declared when consecutive subsequences that are extracted from one MODIS time series transitions from one cluster to another cluster and remains in the newly assigned cluster for the rest of the time series. The temporal sliding window designed to operate on a subsequence of the time series to extract information from two spectral bands from the MODIS product.

Keywords: Land Surface Temperature (LST), Mid-Infrared (MIR), Modis, Image Segmentation, Fuzzy c-means clustering.

Abstract: Data gathering is one of most important functions provided by WSNs, where sensor readings have to be collected from sensor nodes to one or few data collection sinks node. Due to the fact that there may exist high correlations among these sensor readings, it is inefficient to directly deliver raw data to the destination(s). In this paper the application of CS with random walks for data gathering in WSNs. The proposed system adopts the standard random walk algorithm to collect random measurements along multiple random paths. However, such an approach will lead to the non-uniform selection of measurements and it is still unknown whether such an approach can be used to recover sparse signals in a WSN scenario. However, previous works focus on finding the movement patterns of each single object or all objects. This survey of efficient distributed mining algorithm to identify a discover their movement patterns and group of moving objects in wireless sensor networks. The compression algorithm includes a sequence of merge and entropy reduction phases. In the sequence merge phase, a Merge algorithm is to merge and compress the location data of a group of moving objects. The survey results show that the proposed compression algorithm leverages the group movement patterns to reduce the amount of delivered data effectively and efficiently.

Keywords: Compressive Sensing, Data Gathering, Random Walk, Wireless Sensor Network.

Abstract: In this paper keep the information of social graphs (SGs) available to their related business services. Some users also hide or limit the information of their connections from the public in social media platforms due to privacy concerns. Accessing these SGs is getting more difficult and costly in today�s online social networks, and novel applications using SGs become almost impossible to be offered independently by third-party practitioners and individuals. However, billions of user shared images are generated by the folks in many social networks daily, and this particular form of user data is indeed very accessible to others due to the nature of online image sharing. In addition, the paper show that privacy recommends models can be further enhanced by utilizing user enhanced privacy sentiment for mass customization. In this thesis detecting user improved privacy approach and privacy managing models can be automatically tailored specific to the privacy sentiment and needs of the user.

Keywords: Big data, Connection Discovery, Social network Service, User-shared images.

Abstract: Mobile cloud computing applications. To ensure a correctness of users� data in the mobile cloud, our study an effective and secure distributed model including a Self-Proxy Server (SPS) with self-created algorithm. The model resolves a communication Mobile cloud computing provides a novel ecommerce mode for organizations without any upfront investment. Since cloud computing uses distributed resources in open environment, it is important to provide secure keys to share the data for developing bottleneck due to re-encryption of a shared data in the cloud whenever users are revoked. It offers to reduce security risks and protect their resources because a distributed SPS dynamically interacts with Key Manager (KM) when the mobile users take on cloud services. This paper describe a survey of comprehensive mobile cloud design which provides an effective and secure mobile cloud computing services on mobile devices.

Keywords: Mobile Cloud Database, SPS, Key Management, Multi key Distribution, Self Proxy Server.

Abstract: In this paper survey LBS systems employ a pull model or user-initiated model, where a user issues a query to a server which responds with location aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in next-generation location-based services. In the push model, subscribers register spatio-textual subscription to capture their interests, and publishers post spatio textual messages. These calls for a high-performance location-aware publish/subscribe system to deliver messages to relevant subscribers. This computing model bring new user experiences to mobile users, and can help users recover information without explicitly issue a query. The publish/subscribe system should support tens of millions of subscribers and deliver messages to relevant subscribers in milliseconds. while messages and subscriptions contain both location information and textual description, it is rather costly to deliver messages to relevant subscribers. These calls for an efficient filtering technique to support location-aware publish/subscribe services. Moreover, a prediction strategy is proposed to predict the subsequent mobile behaviors. Mean while, a time segmentation approach is presented to find segmenting time intervals where similar mobile characteristics exist. To the best knowledge, this is the first work on mining and prediction of mobile behaviors with considerations of user relations and temporal property simultaneously. Through survey under various the proposed methods are shown to deliver excellent performance.

Keywords: LBS, MBR Filter, Pull Model, Push Model.

Abstract: Mobile social sensing network is one kind of emerging networks in which sensing tasks are performed by mobile users and sensing data are shared and collected by leveraging the intermittent inter-contacts among mobile users. In this paper, propose a simple Energy Efficient framework for Social-based Routing (EE-SR) in mobile social sensing networks to balance the load of nodes while maintaining the delivery ratio within an acceptable range by limiting the chances of forwarding in traditional social-based routing. Furthermore, propose an improved version of EE-SR to dynamically adjust the controlling parameter. Simulation results on real-life mobile traces demonstrate the efficiency of proposed framework. In this paper, the problem of routing in intermittently connected wireless networks comprising multiple classes of nodes is addressed. We show that proposed solutions, which perform well in homogeneous scenarios, are not as competent in this setting. To this end, we suggest a class of routing schemes that can recognize the nodes of �maximum utility� for routing, civilizing the wait and release ratio by 4-5�.Additionally, projected an analytical framework based on fluid models that can be used to consider the presentation of various opportunistic routing strategies, in heterogeneous settings.

Keywords: Social Routing, Social Metrics, MANET, Topology Routing, EE-SR.

Abstract: Data mining is the process of sorting through large datasets to identify patterns and establish relationships to solve problems through data analysis. Data mining is a technique which is used to separate the accurate value from the dataset. Support vector machine is a supervised machine learning algorithm used for classification and regression, SVM mainly used to classifies the datasets to improve classification accuracy, several SVM algorithm are there such as LIB-SVM,DC-SVM,CA-SVM and Dip-SVM these algorithms are used to find the accuracy and performance while performing classification in data mining. Dip-SVM also reducing the communication overhead between clusters.

Keywords: Classification, SVM, Dip-SVM, CA-SVM, DC-SVM.

Abstract: Search engine aims to produce relevant and correct results to a user for their query that they have requested. In this paper, we propose to represent a flexible tag management scheme with automated textual descriptors in user�s profile. We develop a recommendation based personalized system that operates on clustering tags based on the category. In this scheme we implement weighted k means clustering approach to effectively cluster the history of user interests which provides flexibility among multiple user environments. We use a synthetic dataset to show our system performance .The main objective of this system is to develop interest based recommendation system using user�s past rendition. This methodology is developed to produce relevant query results which are based on the user�s previous historical data and to generate personalized user profile with that generated data. Here we implement effective word embedding model to extract the similar words from the extracted corpus. We use LDA scheme with incremental learning algorithm for effective data processing. Incremental algorithm is used for accurate query retrieval even the data changes occurred in user behavior. Then we calculate rank for each repeated words. This calculation mainly focuses on users profile information and historical data of the user�s profile.

Keywords: Clustering, recommendation, query, LDA, Incremental Algorithm.

Abstract: Educational data mining (EDM) is an emerging discipline that focuses on applying data mining tools and techniques to educationally related data. Applying data mining (DM) in education is an emerging interdisciplinary research field also known as educational data mining. It is concerned with developing methods for exploring the unique types of data that come from educational environments. The discipline focuses on analyzing educational data to develop models for improving learning experiences and improving institutional effectiveness. A literature review on educational data mining topics such as student retention and attrition, personal recommender systems within education, and how data mining can be used to analyze course management system data.

Keywords: data mining, educational data mining, academic analytics, learning analytics.

Abstract: Face recognition is the detection and identification of humans by the unique characteristics of their Faces. Face recognition technology is the least intrusive and fastest bio-metric technology. It works with the most obvious individual identifier the human face. This research aims at providing a system to automatically record the students� attendance during lecture hours or exam in a hall or room using facial recognition technology instead of the traditional manual methods. The objective of this research is to thoroughly study the field of pattern recognition (facial recognition), which is very important and is used in various applications like identification and detection. And finally, apply this technology to support the student's attendance system. These will help the attendance system to record more efficiently. The proposed system will update the attendance once the students face is match with the template database.

Keywords: Biometrics, Face detection, Face recognition, Student Attendance System, database.

Abstract: In computer vision the extraction of text in an image is a classical problem . Extraction process includes detection, localization, tracking, extraction, enhancement and recognition of the text from the given image. The problem of automatic text extraction extremely challenging because of variation of text due to difference in size, style, orientation, alignment, low image contrast and complex background make. Text extraction needs binarization which leads to loss of important information contained in gray scale images. Extraction becomes more difficult because the images may contain noise and have complex structure. This paper involves an algorithm which is insensitive to noise, skew and text orientation. It does not contain artifacts that are generally introduced by thresholding using morphological operators. There are many examples that presents the performance of proposed method.

Keywords: Mathematical Morphology, Localization, Morphological Operators, Connected Component, Edge Detection

Abstract: The development of an improved and intelligent model for the evaluation of instructors� performance in higher institutions uses the efficient data mining techniques considering the drawbacks of the prior traditional techniques. This proposed system analyses the factors related with the evaluation of instructors teaching performance using predictive data mining techniques known as regression statistical model. Regression is a data mining predictive technique that is used to make statistical prediction of the variables, given a set of data. Consequently, the evaluation of instructors� performance is useful for the academic institutions as it helps to make effective managerial decisions, improve the quality, reliability and efficiency of the instructors, provides a basis for the performance improvement that will optimize students� academic outcomes and improve standard of education and contribute to successful accomplishment of the organizational goals.

Keywords: Prediction algorithms, Statistical Regression Model, Linear Regression algorithm, Performance Evaluation, Educational Data Mining (EDM).

Abstract: This paper investigates the significance of Supra-Segmental features in continuous speech of Tamil. The Supra-Segmental parameters like fundamental frequency, pitch, intensity, time duration, rhythm and etc., can help to signal the syntactic structure of utterances into larger discourse segments and provide additional information for human speech processing. It also provides information about the linguistic structure of speaker�s message and the emotional state. In human speech processing, linguistic context and phonological rules help the brain to separate syntactic units into phonemes, syllables, words, sentences and phrases. In the case of agglutinative languages, searching space reduction is very important during automatic speech processing. The entitled study focused on Tamil language, which belongs to the family of languages called Dravidian and noted for its highly agglutinative nature. Here the aim is to examine and prove that prosodic information carried out acoustically by the speech signal can be used to improve the performance of speech processing and to add syntactic, semantic level functionality to it. Therefore, the study introduces a rule-based model which shows the relationship between the Supra-Segmental parameters of phoneme to sentence level and their statistics. Finally, the results were compared to analyse the accuracy and efficiency of the model. The methods introduced here are easily adoptable to other agglutinative languages. Instead of using the prosodic level boundaries the study make use of statistical properties, which are more advanced.

Keywords: Tamil, Supra-Segmental, Fundamental frequency, Duration, Intensity, PRAAT.

Abstract: Smartphones have become a part of our daily life. Smartphone users expect PC like functionalities over their phones. Making such vision is possible by offloading computationally intensive tasks from resource constrained smartphone to powerful cloud infrastructure. Much architecture like Cloudlet, Virtual Smartphone over IP (VSIP), CloneCloud, etc. are present in the literature, which uses the cloud based Virtual Machines (VMs) for computation offloading. However, such approaches require more time during startup and have high virtualization overhead, which results in increase in execution time of application. Also, VM based deployment requires more amount of disk space at cloud side. Container is latest, OS-level virtualization technique used in cloud environments for application deployments. Containers give better performance in terms of startup speed and size as compared to VMs. In the proposed system, we have used container based lightweight Docker technology for computation offloading over cloud. Our evaluation shows that, Docker based solution takes less amount of time during startup which in turn reduces response time to user. Also Docker based solution requires less amount of disk space for application deployment as compared to VM based approach, which in turn saves storage resources over cloud.

Keywords: Cloud computing, Container, Computation offloading, Virtualization, Smartphones, Docker.

Abstract: Data mining is the process of extracting the useful data, patterns and trends from a large amount of data by using techniques like clustering, classification, association and regression. Data mining techniques are used for information retrieval, statistical modelling and Machine learning. These techniques employ data pre-processing, data analysis and data interpretation. There are a wide variety of applications in real life. Data mining is becoming increasingly common in both the private and public sectors. Industries such as banking, insurance, medicine, and retailing commonly use data mining to reduce costs, enhance research, and increase sales. Various tools are available which supports different algorithms. A summary about data mining tools available and the supporting algorithms is the objective of this paper. Comparison between various tools has also been done to enable the users use various tools according to their requirements and applications.

Keywords: Data mining, Clustering, Classification, Association and Regression.

Abstract: Cloud Computing is a fast-growing area and its security issues block the prevalence widely in various areas; wherein the data protection is one of the critical/important among these. Guaranteed data protection is required to have data transfer from organizations to cloud for ensuring security in various aspects. Security is the primary concern in all areas of applications wherein still many challenges are there, even after proposing/recommending many techniques. Biometric is a most prevalent technique, which can be used in addressing these security issues. This paper enlightens about various biometric authentication methods available for cloud security, in which our research would be focusing on, by using any of the cryptographic methodologies.

Keywords: Cloud Security, Authentication, Biometrics, Identification, Verification.

Abstract: Cloud computing as a popular solution to provide for storage of data. Today some applications like database, media etc deals with the large amounts of data having higher I/O data demands. In order to improve performance and reduce loss of data of these applications can use parallel file systems. PVFS2 is a free parallel file system developed by a multi-institution team of parallel I/O, networking and storage experts. In this paper we present the design of an implementation for cloud environment to reduce loss of data through using remote servers that can be accessed through the Internet. The implementation aims to increase the availability of data and reduce in loss of information.

Keywords: PVFS2, Parallel file system, Loss of data.

Abstract: This paper presents a state-of-the-art implementation of lossless image compression algorithm LOCO-R, which is based on the LOCO-I (low complexity lossless compression for images) algorithm developed by weinberger, Seroussi and Sapiro, with modifications and betterment, the algorithm reduces obviously the implementation complexity. Experiments illustrate that this algorithm is better than Rice Compression typically by around 15 percent.

Keywords: Image Compression, Video Compression, EZW, Compression Ratio.

Abstract: Cloud computing is most Prominent Solution for large data storage and data sharing, which has lot of benefits for industry and individuals. However, there exists a natural problem for directly outsource and share the data in the cloud server since the they contain valuable information so it requires the high-level security. It is necessary to provide the highly cryptographically access control Mechanism for data sharing. Therefore, in this project we use Identity-based encryption, which is a promising cryptography technique for building a practical data sharing system. Since access, control is not a static mechanism. When some user�s authorization is expired, there should be a mechanism that can remove him/her from the system. In addition, we need to check the revoked user cannot access both the previously and subsequently shared data. So has to make this system to be implement we propose revocable-storage identity-based encryption, which can provide the forward/backward security of cipher text by introducing the functionalities of user revocation and cipher text update simultaneously. The proposed RS-IBE scheme has advantages in terms of functionality and efficiency, and thus is feasible for a practical and cost-effective data-sharing system. Finally, we provide implementation results of the proposed scheme to demonstrate its practicability.

Keywords: Revocation, Encryption, Key Exchange, Private key generator, cipher text.

Abstract: This article describes various plotting algorithm and hence concludes the efficient algorithm which can be used to speed up the plotting process. Various graphical algorithms will be analysed and the best algorithm will speed up the plotting process adopted by various plotter. We will also have a look on the advantages and disadvantages of all the algorithms.

Keywords: Computer Graphics, Plotting, Digital Differential Analyzer, Bresenham.

Abstract: Current antivirus software�s are effective against known viruses, if a malware with new signature is introduced then it will be difficult to detect that it is malicious. Signature-based detection is not that effective during zero-day attacks. Till the signature is created for new (unseen) malware, distributed to the systems and added to the anti-malware database, the systems can be exploited by that malware. But Machine learning methods can be used to create more effective antimalware software which is capable of detecting previously unknown malware, zero-day attack etc. We propose an approach that learns from the header data of PE32 files. We examine various features of the PE32 header and check those which are suitable for machine learning classifier. We hypothesize that machine learning classifiers can tell apart the difference between malware and benign software. Various machine learning methods such as Support Vector Machine (SVM), Decision tree, Logistic Regression and Naive Bayes will be used

Keywords: Malware, detection, Feature extraction, machine learning, Classifier, SVM, Decision Tree, Na�ve Bayes, Header Data.

Abstract: This paper presents an overview and an approach of automatic irrigation system using android mobile. In this paper. After a brief introduction, the focus is on literature review wherein we have studied 15 papers related to the topic and have successfully analysed and them. On the basis of the literature review, we have proposed a GSM based automatic irrigation system having promising scope. Proposed work attempts to save the natural resources available for human kind by continuously monitoring the status of the soil, the flow of water can be controlled and thereby reduce the wastage. Also, by knowing the moisture and temperature content through GSM, water flow can be controlled thereby conserving both water and labour.

Keywords: Automatic irrigation control system, android based irrigation, moisture and temperature sensors

Abstract: This paper deals with the online voting system that will make the voting system smart, more secure and easy to vote. This paper illustrates a system which can be is linked with Aadhaar card. In the whole country Aadhaar card Number is Unique for every person and it contains biometric information of each citizens. So it will be helpful in eliminating fake Voting. The proposed model has a greater security in the sense that voter high security password is confirmed before the vote is accepted in the main database of Election Commission of India. After voting user want to cross check their vote then they can confirm with reference of unique id, which was generated by ECI. In this model a person can also vote from outside of his/her allotted Constituency or from his/her preferred location. Our system also facilitate the live streaming of vote counts thus saving a huge time by providing on time result.

Keywords: AADHAAR ID based online election, Reference ID, Candidate ID, Online voting system, Election commission of India, Unique identification authority of India.

Abstract: Cluster analysis enclosed a number of different algorithms and methods for grouping objects into a respective cluster using the similarity among objects. The attractiveness of cluster analysis is its ability to find groups or clusters directly from the given data. Many clustering approaches and algorithms have been developed and successfully applied to many applications. Spectral clustering groups the objects with high similarity measure and eigenvalues. This paper gives an overview of the various types of clustering and the research conclusion from the recent techniques. The analysis of the various application involved with the spectral clustering is studied with its problem analysis.

Keywords: Consensus Clustering, Ensemble Clustering, Spectral Clustering, Co-association Matrix, Weighted K-means.

Abstract: As water supply is becoming scarce in today�s world there is an urgency of adopting smart ways of irrigation. The project describes how irrigation can be handled smartly using IOT. This project aims at saving time and avoiding problems like constant vigilance. It also helps in conserving water by automatically providing water to the plants/field depending on the water requirements. This system can also prove to be helpful in agriculture, parks and lawns. The objective of this system is to detect the moisture content of the soil and depending on it sprinkle water .This entire information will be sent to the user�s mobile phone.

Keywords: Soil moisture sensors, IOT, Arduino, Android, Microcontroller.

Abstract: The aim of the paper is to focus on Important Aspect of the Diseases which is Effecting a Huge Amount of Population today i.e Alzheimers and building an Android application that could ease the everyday life of a person affected by Alzheimer�s disease. This app provides various functionalities such as tracking movements of the patient through GPS, providing medicine and food timing notifications, daily routine tracker and quiz/Games to increase cognitive functioning of the patient and Timely Alarm for to Provide a Reminder of the App. The main objective of this project is to make people suffering from Alzheimer�s as independent as possible. So this project is not only about creating an application but also address the problem of increased dependency of Alzheimer patients on caregivers and Helping them in a Techie Way as Each Person on Earth Owns a Mobile Phone Specially if you Consider India as India is Ranking Among Top Countries wherein its Population is Suffering from This Diseases.

Keywords: Android, Alzheimer�s, Location tracking GPS, Alarm Notifier, Popups.

Abstract: MPEG-21 is an open standards-based framework for multimedia delivery and consumption. It aims to enable the use of multimedia resources across a wide range of networks and devices. Multimedia standards are MPEG-1 (1993), MPEG-2 (1996), MPEG-4 (1999), and MPEG-7 (2001). In this paper MPEG-21's parts, achievements, ongoing activities, and opportunities for new technologies and an overview of the video compression standards related to the MPEG family are discussed. MPEG-21 is mainly used for DRM. (Digital Rights Managements).

Keywords: Multimedia Framework, MPEG-1, MPEG-2, MPEG-4, MPEG-7, MPEG-21.

Abstract: Web development is the process of creating advanced and complex websites for the internet or an intranet. It is usually made up of many/ multiple programming and mark-up languages like HTML, CSS, JavaScript, and PHP. HTML is the base line for the entire project. Cascading Style Sheets (CSS) is used to style or beautify the webpages. It is inserted or scripted into HTML and external style sheets can also be used. PHP also called Personal Home Page hypertext pre-processor and formerly abbreviated as Personal Home Page is a server-side scripting language and used to create dynamic websites. In this paper, we are developing a website called �shutter speed photography� which can be used by amateur or professional photographers. Customers can book their appointment with a photographer who has registered with shutter speed for his/her occasion. There are many applications of this web application and the users are just one click away from their desire.

Keywords: Web development, HTML, CSS, JavaScript, and PHP, Cascading Style Sheets (CSS).

Abstract: A data or a computer network can be classified based on the range up to which it can operate. It can be classified into Local Area Network (LAN), Personal Area Network (PAN), Wide Area Network (WAN) and global network. Body Area Network (BAN) is a special class of Personal Area Networks in which the signals are restricted to the circumference of the body of human beings. Wireless Body Area Networks (WBAN) includes the use of wireless technologies to interconnect the devices, sensors or other network components within the body. This can also be called wireless intra-body communication [1]. WBAN development includes the amalgamation of embedded system technology and resound networking. Embedded system lifecycle is followed in the development of WBAN. In this paper, we report the ongoing research and the developments in the project based on rapid prototyping technology. In this module, two sensors- Heartbeat sensor and body temperature sensor values are fed to the cloud via Wi-Fi. OSPF routing protocol is used for routing and sharing the data along the best available path.

Keywords: Local Area Network (LAN), Personal Area Network (PAN), Wide Area Network (WAN) and global network, wireless intra-body communication, Heartbeat sensor and body temperature sensor, OSPF routing protocol.

Abstract: The project aims to develop a device that allows file transfers between two USB memory devices without the need for a Personal Computer. Now a day�s portability is most important. So to achieve this, we are designing such a system which can be carried out anywhere. Generally, we used to transfer data between two pen drives by using laptops or desktops. But it is not always possible to carry such a large size device to the particular location. So to solve this problem, we are designing a hardware which is more compact to carry anywhere. With the help of this project we can not only transfer the data but also we can see the transfer of the particular file which we want to send by using Touch display Interface. In our implementation, we are transferring the data between two pen drives without using any computers or laptops. We have designed a project which is known as pen drive to pen drive data transfer, in which we will be transferring the data between two pen drives using ARM processor [4]. In the block diagram we can observe, Whenever we insert the pen drive into the USB port then a signal will be sent to the ARM processor indicating that sender�s pen drive is inserted so now ARM processor will start fetching the data from the sender�s pen drive into the buffer and ARM processor waits for the signal from destination receiver�s pen drive. When ARM processor gets the signal from the destination pen drive now ARM processor is ready to transfer the data between those. Thereafter the ARM processor should get the input from external hard key from the user, once the user press the hard key the ARM processor gets the information to transfer the data between two pen drives [2][4].

Keywords: USB, FAT, Flash disk, Touch Screen, ARM.

Abstract: Landslide monitoring is based on geotechnical instrumentations using, for examples ultrasonic sensors, water level sensors, vibration sensors, accelerometer, inclinometer, rainfall sensor, or. However, cable based monitoring systems are costly, require continuous maintenance, and are limited in their communication flexibility. To overcome these limitations, wireless sensor networks and Internet of things are a viable alternative technology. State-of the-art wireless landslide monitoring systems collect environmental data from the slope and transfer it to connected computer systems for persistent storage. It monitors and detects the landslide and alert people from landslide hazards through android app.

Keywords: Landslide, Arduino, IOT, Rainfall, Sensors.

Abstract: The estimation of unseen noise is the major challenge in speech enhancement algorithm in adverse environments. It is difficult to understand the speech signal under presence of noise from background areas. The human speech and hearing system is inherently sensitive to interfering noise. The use of speech enhancement algorithm removes or reduces the presence of noise. The aim of the noise reduction algorithms is to estimate the clean speech signal from the noisy recordings in order to improve the quality and intelligibility of the enhanced signal. Due to this, it presents a review on method for speech enhancement using mask estimation iteratively. In this work, it will provide the concept of optimization of cost function by iterative method. This will help for reducing the noise from signal. All simulations will be implemented in MATLAB.

Keywords: Speech Enhancement, Speech Processing, Noise Filtering, Sparse Representation etc.

Abstract: Blood pressure (BP) monitoring is not yet practically available for daily use. Challenges include making the system easily wearable, reducing noise level and improving accuracy. Variations in each person�s physical characteristics, as well as the possibility of different postures, increase the complexity of continuous BP monitoring, especially outside the hospital. This work attempts to provide an easily wearable solution and proposes training to specific posture and individual for further improving accuracy. The wrist watch based system we developed can measure electrocardiogram (ECG). From these two signals we measure pulse transit time (PTT) through which we can obtain systolic and diastolic blood pressure through regression techniques. We proposed Automatic Blood Pressure Monitoring and Triggering System for Hospital, which is focused on the development of a convenient device for continuous blood pressure (BP) monitoring with wireless communication interface. The reliability of long-term automatically monitoring is the main focus for current paper. 18 healthy subjects were tested with the continuous BP monitor against a brand of community-based BP monitor. Accuracy assessment of the monitor has been accomplished.

Keywords: Blood Pressure, Electrocardiogram, Photoplethysmogram, Pulse transit time.

Abstract: Today digital communications is at an advanced level. Performance of digital communication system is also play critical Performance optimization of digital communications systems can be done by fine-tuning of parameters of modern digital communications systems. The accurate knowledge of the parameters characterizing the quality of a communication channel is extremely important for efficient data transmission. The application of the Particle Swarm Optimization (PSO) algorithm successfully applied to wide range of engineering problems. In very recent this algorithm becomes very popular due to its simplicity and effectiveness. Researchers have explored PSO algorithm for communication engineering applications. This algorithm can be successfully applied to various digital communication systems for improving performance. The purpose of this paper to explore the different applications of PSO in digital communication system.

Keywords: Digital communication system; Particle swarm optimization.

Abstract: Wireless sensor network is a distributed sensor network and it consists of a large number of tiny, portable devices called sensor nodes. Wireless sensor network has attracted many researchers because of its infrastructure less nature. It has emerged as promising technology in wireless communication field. Network sensor nodes are having limited energy and resources in wireless sensor network. Sensor node performs the function of collecting, processing and forwarding data to destination. Localization techniques are used to detect location or geographical placement of sensor nodes. Localization is a one of the problem in wireless sensor network. Without localization data collected in many applications is not accurate and even not useful also. In both networking and application domain of wireless sensor network localization play very significant role. In this paper various localization techniques are discussed with their requirements, area of applications and limitations

Keywords: Wireless sensor network, Practicle swarm optimization (PSO) and Binary practicle swarm optimization (BPSO), Localization.

Abstract: High speed and low power consumption is one of the most important design objectives in integrated circuits. Digital multipliers are most critical functional units. The overall performance of this system depends on the throughput of multiplier design. Aging problem of transistors has a significant effect on performance of these systems and in long term, the system may fail due to timing violations. Aging effect can be reduced by using over-design approaches, but these leads to area, power inefficiency. Hence to reduce the maximum power consumption and delay, variable latency multiplier with adaptive hold logic is used. The multiplier is able to provide higher throughput through the variable latency and can adjust the AHL circuit to mitigate performance degradation that is due to the aging effect. The proposed architecture can be applied to image multiplication. Based on the idea of razor flip flop and adaptive hold logic the timing violations are reduced. In the fixed latency usage of clock cycles is increased. The re-execution of clock cycles is reduced by using variable latency.

Keywords: Adaptive Hold Logic (AHL), Negative Bias Temperature Instability (NBTI), Positive Bias Temperature Instability (PBTI), reliable multiplier, variable latency.

Abstract: In this section we make an endeavor to diminish the quantity of info choice parameters so the handling is computationally quicker without influencing the final products. That is, rather than utilizing an entire arrangement of parameters, we utilize just a subset of these parameters to get similar outcomes. At long last, we likewise endeavor to foresee cutting edge estimations of some significant parameters to construe the site suitability and additionally ranking, futuristically (next five years).

Keywords: Dimension lessened, swarm, semantic, industrial plant, parameters, optimization.