VOLUME 6, ISSUE 12, DECEMBER 2017

Abstract: FEAF2.0 framework is a complete architecture which by integrating with leading cloud computing technology leads to improvement of components and essential processes. Also an analytical review will be done on choosing of improvement field for locating the federal enterprise architecture in management layer of cloud computing technology and ways to improve it, how to measure the quantitative and qualitative improvement by comparing the proposed method with other approaches and ultimately the success or failure of data recovery method. in this paper, a new architecture is provided based on the needs of organizations. This architecture brings together processes of standard frameworks related to information technology, organizational architecture components of FEAF 2.0 and the benefits of a cloud environment. for achieve this goal, the presented study considers appropriate processes in cloud environment from proposed frameworks as well as components of an organizational architecture of FEAF 2.0 for selected cloud environment and management layer of cloud computing.

Keywords: Architecture FEAF2.0, layer of cloud management, cloud computing, Localize Utilize Organizational.

Abstract: Support vector machine (SVM) based intrusion detection system (IDS) presently working as the machine learning approach for classification. It helps to detect new attacks from the datasets which are used in the machine learning. At IDS, the task of the machine learning method is to construct a projectile model which can be distinguished between normal and illegitimate activity. Any IDS can be developed to get high accuracy, high detection rate and low false positive rate, which show the efficiency of that intrusion detection system. In this paper, we use a direct kernel method with SVM classifier to get the high accuracy and detection rate, also low false positive rate. For the performance evaluation of the projected system we use KDDCup99 dataset, NSL-KDD dataset and Kyoto 2006+ datasets.

Keywords: Machine learning, SVM, datasets, kernel methods, IDS.

Abstract: The face is one of the important remote biometrics and it is used in facial analysis systems, like human-computer interaction, face detection and recognition and so on. Giving poor quality images and low resolution from inexpensive videos sequences they may give error nous and unstable results so we need a proper mechanism to deal with this problem on low resolution front face images. The approach which I have mentioned in this paper exactly deals with .To deal with this approach we need to apply the reconstruction based techniques. This algorithm has mainly two problem one is that it requires a similar images and another its improvement factor limited only two. To resolve the first problem we introduce an approach of three-step, which produces a sequence of faces which consists of similar front faces having maximum possible quality. To resolve the problem of improvement factor limitation we applied super-resolution which is based on learning based algorithm to the result of the reconstruction-based technique to enhance the quality of images. Because of this technique the improvement factor gets improved by four for whole system. Face recognition is a biometric system used to identify or verify a person from a digital image. Face Recognition system is used in security. Face recognition system should be able to automatically detect a face in an image. This involves extracts its features and then recognize it, regardless of lighting, expression, illumination, ageing, transformations (translate, rotate and scale image) and pose, which is a difficult task.

Keywords: Face-log generation, Face quality assessment, Super-resolution, surveillance video.

Abstract: In this paper, we focus on implementation of research, and the efficient management of resulting Indian ocean data. Data management and integration consider the careful collection, management and dissemination of research data is taken to provide vast ocean information integration. In order to develop robust ocean information system, the data from in-situ ocean observing systems such as Argo floats, drifting buoys, moored buoys, XBT surveys, tide gauges, coastal radars, current meter mooring array, bottom pressure recorders has been considered to design by implementing data acquisition, processing, quality control, and database generation. The diverse data sets has been acquired from in-situ platforms needs to be quality controlled, organized and disseminated in real time to data users. This paper on ODIS provides ocean data management and web-based ocean information system and its visualization functions for oceanographic data. An integrated observing system will also require improved combination of data from in-situ platforms which observations depends on their parameters and data types.

Keywords: Heterogeneous data, Oceanography, Visualization, Data Management, Integration, Argo Data products.

Abstract: Diabetic Foot Ulcer (DFU) is a serious health issue for a patient with diabetes. The death risk is greater for a patient suffering from Diabetic Foot ulcer when compared with a patient without the history of Diabetic Foot ulcer. Normally the healing status of the wound is determined based on the visual examination done by the clinicians. The conclusions made about the wound and its healing status by this procedure is not accurate. A simple methodology for the assessment of the wound and its healing status is proposed. Here the foot images of the patients are taken on regular basis and these images are analyzed using various image processing tools. The foot image is filtered, preprocessed and then the wound and foot regions are determined. After this the color tracing of the wound is performed. Finally, the healing score is determined by comparing the two foot images taken on regular time intervals.

Keywords: Diabetic Foot Ulcer, Wound Tracing, Color Tracing, Healing Score.

Abstract: Augmented Reality (AR) is a technology that augments the real physical world with computer-generated 3D virtual objects such that the users can interact with them using the screen of their mobile devices. In current traditional childhood teaching there are difficulties in inspiring children�s learning interest, lack of teaching situations and low study efficiency. We are going to develop an AR mobile application prototype to teach kindergarten students in an interactive and attractive way. It allows kindergarten students to learn using a mobile device. This project uses natural feature detection algorithm with some improvements. OpenCV also include some feature detection algorithms. This algorithm is good for capturing and detecting images with greater accuracy and speed. With that, some parents were complaining about over usage of the mobiles will affect children�s health. For the solution monitoring function is added which monitors the individual activities and usage time. With help of this ability, we can control usage, monitor and analyse students learning. This project will help students learn in effective way and with greater efficiency.

Keywords: Augmented Reality, OpenCV, Kindergarten Education, Human Computer Interaction, Natural feature detection algorithms.

Abstract: Fault Tree Analysis is a graphical and analytical model for identifying and accessing the relevant causes of a system risk or fault or undesired event. it is used in process system for identifying basic events or causes of an event, identifying common-cause(Minimal cut sets) failures, displaying causes and consequence of undesired event, evaluating design and investigating process accidents/incidents. The main aim of any fault-tree algorithm is to compute the minimal cut sets as quickly as possible. A cut set is a collection of component failure modes that could lead to a system failure. Cut Set Analysis (CSA) is applied to critical systems to identify and rank system vulnerabilities at design time. This paper presents a critical review of the various quantitative fault tree analysis techniques and also provide a formal procedure of each of the techniques.

Keywords: Fault Trees, Cut sets, Algorithm, Fault Tree Analysis, Minimal Cut set.

Abstract: Data science has attracted a lot of attention, promising to turn vast amounts of data into useful predictions and insights. Data scientists see data science from three perspectives namely, statistical, computational and human. The effective combination of all three components is the essence of what data science is about. Now a day�s Data science is a buzzword used in business, academia and government. Data Science has occupied a prominent role in e-business and has started fetching fruits in online shopping like Amazon, Flipkart etc. In future Data Science will have a prominent role in every walk of human life right from domestic life to official life.

Keywords: Data Science, Big Data, Analytics , e-Business, Online Marketing.

Abstract: Substantial growth in the use of wireless communication services over the last few years has led to an increase in the number of base stations. Consequently, exposed Electromagnetic Radiation (EMR) levels has risen. Therefore, monitoring of exposed EMR levels emitted by base stations have become more crucial than before for human health. For this reason, in this study EMR measurements were conducted in the years of 2015, 2016 and 2017 in Unye which is one of the most populated districts of Ordu/Turkey. The total electric field strength (E) in the band between 100 kHz � 3 GHz was measured using PMM-8053 EMR meter, and the maximum E (Emax) and the average E (Eavg) were recorded at 47 different locations. According the total 141 measurement results, the maximum Emax is 6.05 V/m, while the maximum Eavg is 2.40 V/m that both recorded in 2017. Furthermore, only 2% of all measurement results are above 2 V/m of each years� measurement. Based on the measurement results annual percentage change in Eavg levels are 15.2% and 21.5% from 2015 to 2016, and from 2016 to 2017 respectively. Since E levels in the environment have continuous tendency to increase, accurate monitoring and evaluation of E levels is very crucial to keep exposed EMR levels below the limits.

Keywords: Electromagnetic radiation, Electric field strength (E), Base station, ICNIRP, PMM-8053.

Abstract: Today's anyone cannot buy some expensive devices for gaming. Virtual reality gaming is where a person can experience being in a three-dimensional (3D) environment and interact with that environment during a game. Creating fake 3D effect is an important part of the game. Anyone cannot buy expensive hardware but we already have the hardware in your pocket. This application uses the display and sensors of your existing android phone to transform it into a portal to your PC games, so that we can play our PC games in virtual reality on android mobile. This VR system is basically about mirroring your Windows display to your Android Smartphone in the split-screen VR mode. It also makes sure to create a fake 3D effect on games. VR (Virtual Reality), Three-Dimensional Environment, Remote Procedure Call (RPC).Joystick Events, Screen mirroring.

Keywords: VR (Virtual Reality), Three-Dimensional Environment, Remote Procedure Call (RPC).Joystick Events, Screen mirroring.

Abstract: This paper presents the advanced IoT based concept wherein electricity bills are switched to prepaid facility. This work is used to monitor power consumption and automatically alerts the user to recharge the account through the Internet and SMS. An Arduino processor is used to monitor and control entire system model and the GSM Technology is used to update the user about the account through the SMS service. This is for people in the rural areas where internet has still not managed to create its hold on a daily basis. The IoT based system is used to update the data whereas the APIs are used to notify tech savvy people via emails and notifications. This process is periodic in nature and hence power reduction takes place at a greater rate. This technology finds application in electricity distribution companies, corporates, household and rural areas where power theft is still an issue. The implementation of this project will result in better energy management, conservation of energy and eradicate unnecessary hassle over incorrect billing. The automated billing system keeps track of time and energy consumption simultaneously leaving little scope for disagreement on consumption and billing. This project provides major benefits of data collection that allow substantial saving through reduction of meter re-read, greater data accuracy, frequent reading and improved customer service

Keywords: Prepaid electricity, Power security, Arduino controller, GSM/GPRS, IoT, APIs.

Abstract: Modern technology and networking generates huge volume of data. Privacy of data is a crucial issue and a topic for significant research. Data Publishing undergoes the major problem of deciding how to publish the useful data while preserving privacy-sensitive information according to the associated privacy requirements of data holders. According to the concept of the privacy protection, it is defined as such the accessing of published data must not allow the unwanted users to identify anything about the targeted individuals. This paper represents an analysis and classification of various anonymous techniques for privacy preservation like t-closeness, k-anonymity, l-diversity, slicing and differential privacy.

Keywords: Privacy-Sensitive Information, Preservation, t-closeness, k-anonymity, l-diversity slicing and Differential Privacy.

Abstract: This paper presents the design of microstrip rectangular patch antenna with center frequency at 3.8 & 5GHz for WiMAX & WLAN application. The antenna with microstrip line feeding technique was designed and simulated using Computer Simulation Tool (CST) Microwave Environment software. The antenna designed on Roger4004substrate with overall size of 30x40 x 1.59 mm3 and dielectric substrate with e_r = 4.4. This antenna structure isdesigned by using CST Software based on the characteristic impedance for the transmission line model. The performances of designed antenna are compared in terms of parameters like substrate dimension, feed size and ground plane. The antenna performance in terms of its frequency domain and time domain characteristics are investigated.

Keywords: CST Microwave Studio, UWB, WiFi, WiMax, Simulation, Microstrip Line Feed, microstrip Antenna, Omni-directional patterns.

Abstract: The forced termination probability with respect to handoff call is very critical as it�s less desirable to subscribers than the blocking probability of new call. This paper proposes analytic and simulation models to optimize the performance of hand-off calls using Neyman-Pearson criterion (NP). It is observed that using the NP criterion gives high priority to hand-off attempts over initial access attempts without degrading the initial access seeks.

Keywords: Nayman-Pearson Criterion, Force Termination, Blocking Probability.

Abstract: Autonomous Transport Vehicle (ATV) is a driverless transport vehicle. It is basically used to transport people to pre-determined locations. As an autonomous vehicle, it is capable of sensing its environment and navigating without human input. To make the ATV cost effective and less complex than presently available, driverless cars, which uses DIP technology, GPS, Cartesian coordinating etc., here we use RF-ID tagging for pre-determining the location. This ATV uses IR sensors to determine the path. ATV determines the shortest path to be taken between two predetermined locations using Dijkstra�s Algorithm. It uses an obstacle sensor which is the ultrasonic sensor for detection of pedestrians on the path. An on-board LCD display is in-cooperated within ATV to display information regarding its functioning. Such type of small scale ATVs can be used in institutional areas like within the campus and in tourist areas like parks for recreational purpose. Here we use our ATV inside the campus for transportation purpose within the campus.

Keywords: Cartesian Coordinating, Dijkstra�s Algorithm Arduino Mega.

Abstract: People looking to buy a new home tend to be more conservative with their budgets and market strategies. The existing system involves calculation of house prices without the necessary prediction about future market trends and price increase. Aim of this project was to develop a real estate web application using Microsoft ASP .NET and SQL 2008.The real estate system Give the functionality for buyers, allowing them to search for houses by features or address. It provides functionality for the seller, authorize them to log into the system and add new advertisements or delete existing ones. For this each user is provided a login account with login ID and password. Along with this, when the user will search for the property, original property value and predicted property value will be displayed. By analysing previous market trends and price ranges, and also upcoming developments future prices will be predicted. For the price prediction we will be using classification algorithm .The functioning of this project involves a website which accepts customer�s specifications and then uses the application of data mining. This application will help customers to invest in an estate without approaching an agent. It also decreases the risk involved in the transaction. The property, original property value and predicted property value will be displayed. By analysing previous market trends and price ranges, and also upcoming developments future prices will be predicted. For the price prediction we will be using classification algorithm. The functioning of this project involves a website which accepts customer�s specifications and then uses the application of data mining. This application will help customers to invest in an estate without approaching an agent. It also decreases the risk involved in the transaction.

Keywords: House prices; real estate price; classification algorithm; price prediction; data mining; market trends

Abstract: This work deals with estimating the education level of social media users. There may be different reasons for inferring new information from social media data. Security and economical ones are the top ones. Data mining � especially Idea Mining � on social networks have become more widespread in the international literature. Even though the number of studies done domestically have been increasing, it is not enough. This work aims to take a small step towards finding out the education level of Twitter users. The last part of this work shares the experience we had out of this research for future studies.

Keywords: Social Networks, Data Mining, Twitter.

Abstract: Network intrusion poses a serious threat to the security of financial and all other systems. The main objective of any online security system is to provide protection against malicious intentions of a user. The techniques used by intruders are bound to change and every day new methods of attacks on the network are being faced by all the systems on the net. One method to gain reliable security against unknown intrusions is to use Anomaly Detection Systems. Many existing intrusion detection systems are Rules Based, which have limitations when new intrusions appear. The proposed work intends to provide a system which detects network anomalies using machine learning (ML). The proposed system intends to improve the accuracy of anomaly detection as compared to the existing systems.

Keywords: Machine Learning, Intrusion Detection, Anomaly Detection.

Abstract: This paper involves identifying how the people management is done in software companies in India in the recent years by analysing the key process areas of People Capability Maturity Model. From our survey along with study of the principles of Total Quality Management, an approach to people management is put forwarded to rectify people capability management. People capability management is a hugely important part of putting together and managing high performance software engineering people. People Capability Management has known to make IT people more responsive, more productive, leaner and more efficient. People capability management has brought revolution to the IT sector after its introduction by which companies are now able to maintain a healthy relationship with all its employees, thereby encouraging them to work efficiently with less stress and achieve desired goal within stipulated time.

Keywords: People, Management, Survey, P-CMM, TQM, IT sector.

Abstract: Frequent Itemset mining is important part of data mining techniques, which focuses on looking at sequences of actions or event. In real world, a lot of exists on large datasets that are stored on cloud servers in recent years. By using data mining techniques on these large dataset increases the accuracy of in terms of data result and also the efficiency. But it also brings the possibility of data leakage of confidential private datasets. Therefore, in this proposed work we focus on the privacy and efficiency of frequent Itemset. Proposed system uses the FP growth algorithm, which is best performing algorithm for frequent pattern mining. Also to maintain the privacy of frequent item set patterns, encryption algorithm has been implemented.

Keywords: Data Mining, Cloud computing, frequent pattern mining

Abstract: As networks become borderless in modular times, the accessibility of networks are also increasing in proportionate to its growth. Enterprises have employees and partners who often needed to access their corporate resources from their respective remote location keeping in mind about the confidentiality, integrity and availability of the data throughout the whole access phrases. Borderless networks encourage and promote the growth of secured remote access to corporate resources to their remote employees and partners. In modeler times out of several remotes access methods, VPN is one of the most used methods that provide C.I.A (confidentiality, integrity, availability) factors. Traditional VPNs supports the C.I.A factor with the help of only predefined authentications, possibly in certain cases linked with third party authorized authentication servers. In this work it has been proposed to use VPN in traditional way but added with an extra Layer of authentication name called 2 step authentications which involves the use of dynamically generated OTP/OTAC with Bcrypt Algorithm. The remote user/partner needs to pan the traditional authentication along with the 2nd step verification before the private access is granted to him/her.

Keywords: C.I.A - Confidentiality, Integrity, and Availability, , VPN, OTP/OTAC

Abstract: The rapid expansion of the Internet in the past years has immediately increased the availability of digital data such as audio, images and videos to the general public. Whilst the computers are more and more incorporated via the system, the supply of digital press has gotten faster, easier, and also requiring less attempt to make accurate copies. One of the key impediments will be the dearth of strong intellectual property security of digital networking to discourage unauthorized copying and supply. In this paper, a powerful technique to protect text and video is suggested which makes use of text hiding technique and watermarking algorithm based on Discrete Wavelet Transform (DWT), Singular value decomposition and Hamming error code to procuring video and text. Initially measure the writing will be hidden in the image using LSB algorithm then in second measure frames will be pulled and watermarking is used on singular worth subsequent to the SVD is completed. Before renewing added parity bits are inserted to create the watermarking method more secure and powerful. Preliminary results reveal that this suggested technique is robust to the previous signal processing techniques and geometric distortions.

Keywords: Steganography, LSB Algorithm, Digital watermark, Discrete Wavelet Transform, Singular Value Decomposition (SVD), Video Watermarking, Hamming Code.

Abstract: Recently, enormous information investigation has gotten critical consideration in an assortment of utilization areas including business, fund, space science, medicinal services, media transmission and Internet of Things (IOT). Among these zones, IOT is considered as an imperative stage in bringing individuals, procedures, information and things/protests together keeping in mind the end goal to improve the nature of our regular day to day existences. Nonetheless, the key difficulties are the way to successfully remove valuable highlights from the huge measure of heterogeneous information created by asset obliged IOT gadgets so as to give continuous data and criticism to the end-clients, and how to use this information mindful insight in improving the execution of remote IOT systems. In spite of the fact that there are parallel advances in distributed computing and edge figuring for tending to a few issues in information investigation, they have their own particular advantages and constraints. The meeting of these two figuring ideal models, i.e., gigantic for all intents and purposes shared pool of registering and capacity assets from the cloud and constant information handling by edge processing, could viably empower live information examination in remote IOT systems. In such manner, we propose a novel system for facilitated handling amongst edge and distributed computing/preparing by incorporating points of interest from both the stages. The proposed system can misuse the system wide learning and chronicled data accessible at the cloud focus to control edge figuring units towards fulfilling different execution prerequisites of heterogeneous remote IOT systems. All the more significantly, we recognize and portray the potential key empowering agents for the proposed edge-cloud community oriented system, the related key difficulties and some intriguing future research bearings.

Keywords: Data Analytics, Internet of Things (IOT), Edge computing/Fog computing

Abstract: The power quality affects form injection of wind power into an electric grid. Wind turbine performance and power quality are determined on the basis of measurements. According to the guideline specified in International Electro-technical commission standard, IEC-61400. Wind turbine with grid system concerning the power quality measurements. The active power, reactive power, a variation of voltage, flicker, harmonics and electrical behavior of switching operation are the measurement of power quality. The power described a power quality problem. The power quality problem presented to the installation of wind turbines with the grid. In this proposed scheme is Static Compensator(STATCOM). Battery energy storage system(BESS) with a point of common coupling is connected to the Static Compensator to mitigate power quality issues. The integration of the real power source under fluctuating wind power is BESS. Using MATLAB/SIMULING to simulated the STATCOM control scheme for grid-connected wind system in power system block. From reactive power demand of the load and induction generator, the proposed scheme relies on the main supply. The co-ordination rule of the grid development and the scheme for the improvement in power quality as per the IEC-standard on the grid has been presented.

Keywords: STATCOM, Induction generator, Grid-connected system, flicker harmonics, wind turbine.

Abstract: The new technologies characterizing the internet of Things permit realizing real sensible environments ready to offer advanced services to the users. Recently, these sensible environments also are being exploited to renovate the users� interest on the cultural heritage, by guaranteeing real interactive cultural experiences. During this paper, we have a tendency to style and validate an inside location-aware design ready to enhance the user expertise during adiposity. Above all, the projected system depends on a wearable device that mixes place recognition and Localization capabilities to mechanically offer the users with cultural contents associated with the determined artworks. The localization data is obtained by a Bluetooth infrastructure put in within the College. Moreover, the system interacts with the Cloud to store multimedia system contents created by the user and to share environment-generated events on his/her social networks.

Keywords: Bluetooth, Place recognition, IoT, Tracking system, Location-awareness, SoA, Smart College.

Abstract: Quality Management is very important in Software Projects. Quality is achieved to the extent that a project end product meets the client's needs and expectations; it also means that a product should meet its specification. Paper discusses about Life Cycle approach to Software Quality Management process and its principles, activities, factors, methods, benefits, and also Principles of Quality Risk Management.

Keywords: Clients needs and expectations, project management, quality control, quality factors.

Abstract: Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. Due to social web portals and social networks, web users are motivated to share their pictures over the internet and that permit other users to tag and comment on the pictures. Many people share their posts, images on social portals, many are been labeled with appropriate names but many are not labeled, which becomes hard to understand the names for an unknown individual person. In this task, we propose two new systems to tackle this issue by taking in two discriminative proclivity grids from the marked pictures. Firstly we propose system called regularized low-rank representation by using regulated data to take in a low-rank recreation coefficient framework, while find out about different subspace structures of the information. With this technique, we compare recreation coefficients identification with the circumstances where a face is reproduced, so as to utilize face pictures from different subjects. In a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face from different subjects or itself. With description of reproduction coefficient lattice, a discriminative proclivity network can be obtained. In addition, we add another separation metric learning strategy called equivocally regulated auxiliary metric so as to learn administered data to look for a discriminative separation metric. Hence, another discriminative proclivity framework can be obtained utilizing the likeness lattice in view of the separations of the information. Exhaustive analyses show the viability of our methodology.

Keywords: Low Rank Representation;automatic image annotation; Automatic face annotation; feature extraction; Speeded Up Robust Features; Scale Invariant Feature Transform; Convolutional Neural Network; Gabor Wavelet Transform; Eigenfaces; Local Binary Pattern.

Abstract: Cardiovascular Disease (CVD) is the single foremost cause of mortality around the globe and is projected to stay so for a while. Cardiac Arrhythmia is a very common type of CVD and may contribute to an increased risk of stroke or sudden cardiac death. But, this can be averted now, due to the swift growth in technology. The proposed system utilizes a unique and efficient architecture for improving the existing healthcare systems by reducing the delay in medical attention with the help of Android-based mobile devices and a smart wearable with Bluetooth interface. This system focuses on building a real-time heart monitoring system considering the ease of application, cost, and accuracy. The system on the user (or patient) side mainly consists of various sensors for data acquisition, a microcontroller (e.g., Arduino), and software along with a smart device. The hospital side system will contain a Windows application which will be used to access the patient's data. The patient�s temperature, heart rate, blood pressure, blood glucose level and ECG data are continuously monitored, displayed, and stored by the system.The records of the patient will be synchronized to the central server to reflect the current status of the patient. The wearable device on detecting any abnormal readings will immediately report it to the smart device (mobile phone or tablet) which can further contact the nearest hospital, the listed Emergency contact, and the family doctor. Communication from a smart device (via the application) to hospital or family doctor will be using GSM Network.

Keywords: Internet of Things (IoT), Cardiovascular disease (CVD).

Abstract: The Internet of Things (IoT) is the network of physical objects, devices, vehicles, buildings and other items which are embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange data. IoT has many potential applications and can be implemented in fields like home automation, offering several features like economical use of energy to protection and safety. This section illustrates detailed working of IoT based security systems and Energy efficient devices. This topic aims at controlling home appliances via Smartphone using Wi-Fi as communication protocol. It provides information regarding various hardware and software components required for implementing the same. It shows us how the IoT will touch our life in near future.

Keywords: Internet of Things (IOT).

Abstract: This paper study of clustering algorithm for trajectories elements which is based on dense of the grouping element. Our experiments give new method for partitioning the TRACLUS algorithm and provide the Euclidean distance of moving element. We provide a new approach of moving elements. This approach develops a cluster of trajectory object and calculates the actual distance of moving object. This algorithm works on the CLSTR algorithm and calculates the actual cell value. This paper assumes the entropy of moving object and heuristic parameter.

Keywords: Trajectory algorithm, Partition and group work, Data mining, Cluster, Trajectory clustering.

Abstract: Metastability occurs when signals are transferred between asynchronous clock domains. In today�s modern world where everything is digitized and miniaturized we need small and stable digital system for years. The circuit failure largely depends upon metastable state in digital circuits. This can be avoided by using synchronizer. The goal of the proposed work is to design a synchronizer with both CNTFET and MOSFET technology and simulate in HSPICE with 32nm scale. This paper presents how the metastability response in terms of MTBF, Noise margin, power, Delay and Power Delay Product (PDP) parameters are better in CNTFET based synchronizer as compare to MOSFET. The simulation results show that circuits designed using CNTFETs have a high robustness to voltage and temperature variations as compared to MOSFET based circuits. Also due to variation in voltage and temperature in CNTFET give no or very less variation in PDP. This paper will confirm that CNTFET technology is a viable solution to replace conventional MOSFET technology and it turns out to be an effective choice of future technology if manufacturability issues such as controllability of metallic/semiconducting property and metallic contacts are taken care of.

Keywords: CNTFET, MTBF, Sequential Circuits, MOSFET, PDP, Noise Margin

Abstract: In this paper, an attempt has been made to summarize segmentation techniques which are useful for separation of tumor region from brain tumor MRI images. By selecting a proper segmentation technique, it is possible to segment tumor region accurately, which helps in measuring the area of tumor region from brain tumor MRI image. This is possible by using digital image processing tool. Digital image processing is useful for CT scan, MRI, and Ultrasound type of medical images. Digital image processing improves the quality of these medical images using various enhancement techniques. From this enhanced image the radiologist can easily identify infected region and its location. Digital image processing also able to separate out infected region from MRI or CT scan images easily which helps radiologist for diagnoses of the disease at earlier stage. It has several advantages overother imaging techniques, providing high contrast between soft tissues. However, the amount of data isfar too much for manual analysis, which has been one of the biggest obstacles in the effective use of MRI.The detection of tumour requires several processes on MRI images which includes image preprocessing,feature extraction, image enhancement and classification. The final classification process concludes that aperson is diseased or not. Although numerous efforts and promising results are obtained in medicalimaging area, reproducible segmentation and classification of abnormalities are still a challenging taskbecause of the different shapes, locations and image intensities of different types of tumours. In thispaper, various approaches of MRI brain image segmentation algorithms are reviewed and theiradvantages, disadvantages are discussed.

Keywords: MRI, segmentation, morphology, MATLAB.

Abstract: Data gathering is a common but critical operation in many applications of wireless sensor networks. Modern techniques enhances the energy efficiency to protract the network lifetime which were required extremely. Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. The framework employs distributed load balanced Clustering and dual data uploading, which is referred to as LBC.A distributed load balanced clustering algorithm is proposed for sensors to self-organize themselves into clusters. This work used mobile divider for split the data about cluster and cluster head calculation. In contrast to existing clustering methods, our scheme generates multiple cluster heads in each cluster to balance the work load and facilitate dual data uploading. The trajectory planning for Mobile collector is optimized to fully utilize dual data uploading capability by properly selecting polling points in each cluster. By visiting each selected polling point, Mobile collector can efficiently gather data from cluster heads and transport the data to the static data sink. Extensive simulations are conducted to evaluate the effectiveness of the proposed LBC schemes.

Keywords: Wireless Sensor networks, load balanced clustering algorithm, Data uploading, Efficient Data Gathering.

Abstract: Participation has been widely used as a method to track students' academic behavior. But conventional approaches tend to be slow and imprecise. In this paper, we have proposed an automatic attendance detection system, where students can use smart phones to present their presences in parallel. The identity of a student is verified in collaboration with a fingerprint and position in real time. There are various forms of presence systems, such as the ERP system, RFID cards, and the biometric assistance system where fingerprints are considered the best and fastest method. In this system, we are monitoring the presence by matching the fingerprints and the position to improve the old method of recording presences. Replacing the tedious traditional form of assistance will save time, minimize administration workload and change paper and pen with digital devices.

Keywords: Geo-fence, Fingerprint matching, GPS location, attendance management system.

Abstract: Internet has transformed E-Commerce and customer now have access to wide range of products offered through E-Commerce websites. In order to remain competitive and defend market share, E-Commerce firms formulates online marketing strategies based on real time data. This has steered to a paradigm shift in the E-Commerce, where data is seen as a biggest asset to the firm in understanding specific needs of customers, predicting behavior, tailoring specific needs and offering performance metrics to assess effectiveness. E-Commerce firms are finding ways to extract meaningful information from larger datasets where data gets generated at greater velocity, different variety and at high volumes that are often referred to Big Data. E-Commerce firms are investing huge on Big Data Analytics to empower them to take accurate and timely decisions. This paper investigates how the use of big data analytics is perceived as value creator that can guide E-Commerce companies attain competitive advantage.

Keywords: Analytics for E-Commerce, Big Data Analytics, E-Commerce, E-tailing, Value Creation, Personalization, Dynamic Pricing.

Abstract: Tweet sentiment analysis is an effective and valuable technique in the sentiment analysis domain. It is the most extensively used approach for tweet sentiment analysis. Machine learning algorithms and Sentiment analysis of tweets are an application of mining Twitter and it is growing in popularity as a means of determining public opinion. Machine learning algorithms are used to perform sentiment analysis; however, data quality issues such as high dimensionality, class imbalance or noise may negatively impact on classifier performance. Machine learning techniques are for targeting these problems but it has not been applied to this domain or studied in detail.

Keywords: Machine learning, sentiment,optimization,tweets

Abstract: Now a days the scientific databases and web databases maintain huge and different type of data. Due to the enhancement of web databases and scientific databases user is not able to get required results with the predefined static query forms. To avoid such a problem in this paper proposed the Dynamic Query Forms (DQF). In this newly defined Dynamic Query Form user can execute the query by selecting the desired form component and then he/she should submit the query for execution. At the time when user searching for the required result the system is able to catch the user interest by using the users feedback and according to that system recommend a ranked list of query form component to user. So user will be able to find the desired result as early as possible. A user can perform the form component selection and query submission operation iteratively until he/she is satisfies with the query results.

Keywords: Query Form, Query Execution, Users feedback, Dynamic Query Forms (DQF).