Ahmed Y. Qasim, G.A. Quadir Salih Hameed, Waleed A. Obaid, Adel Abdalrahman Ziyed
Performance analysis of a newly designed three frame VAWT having cavity vanes
Ahmed Y. Qasim, G.A. Quadir Salih Hameed, Waleed A. Obaid, Adel Abdalrahman Ziyed
A vertical axis wind turbine model having three frames with cavity vanes has been designed, fabricated and tested in a low speed wind tunnel. This type of model has a high drag coefficient when the vanes close the frame on one side while rotating with wind direction and capturing the wind efficiently. On the other side, the frame rotates in the opposite direction of the wind which opens the frame causing the wind to pass through the frame with low resistance. The model is tested in a wind tunnel with the wind speeds varying between 3 m/s and 17 m/s. The present model gives the maximum power coefficient of 0.32 at a wind speed of 8.2 m/s and tip speed ratio of 0.31 which is higher than those of the vertical axis wind turbines in the literature for the purpose of comparison. The performance of a similar prototype VAWT having a scale ratio of 10:1 is also predicted using the dimensional analysis.
Comparison of Control Algorithms for Shunt Active Filter for Harmonic Mitigation
Shaik Mohammad Bhasha , B. Lalitha
Shunt Active Filter generates the reference current, that must be provided by the power filter to compensate harmonic currents demanded by the load. This paper presents different types of SRF methods for real time regeneration of compensating current for harmonic mitigation. The three techniques analyzed are the Synchronous Reference Frame Theory (SRF), SRF theory without synchronizing circuit like phase lock loop (PLL) also called instantaneous current component theory and finally modified SRF theory. The performance of Shunt Active Power Filter in terms of THD (Total Harmonic distortion) of voltage and current is achieved with in the IEEE 519 Standard. The comparison of all methods is based on the theoretical analysis and simulation results obtained with MATLAB/SIMULINK
A Study on Wireless Sensor Network, Protocol, Application, Challenges
P.S.Sathish, E.Annal Sheeba Rani
Wireless Sensor Network is a network in which sensor are deployed in a targeted environment to sense the status of area. The data are collected from sensor, processed, computed and perform the communication process to know about the target environment. The study focuses on the application, protocols, challenges of sensor network which helps for learning process about wireless sensor network and special issue on wireless sensor networks for agriculture. The future work of study is measuring the underground growth and water level monitoring in the plant tapioca (manihot esculenta) using wireless sensor network
Enhanced Cluster Based Distributer Fault Tolerance Algorithm for Mobile Node in WSN
Avrinderpal Kaur , Er. Upasna Garg
A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices using sensors to monitor physical or environmental conditions. A WSN system incorporates a gateway that provides wireless connectivity back to the wired world and distributed nodes.
Connecting two or more computers together in such a way that they behave like a single computer that is called clustering. Clustering is used for parallel processing, load balancing and fault tolerance. The clustering technique is used where network organizes around a small set of cluster heads which then gather data from their local cluster aggregate this data and transmit it to the base station. Fault tolerance techniques attempt to prevent lower-level errors from propagating into system failures. By using various types of structural and informational redundancy, such techniques either mask a fault or detect a fault and then effect a recovery process which, if successful, prevents a system failure .In this paper we are reviewing comparison of existing clustering technique by using various performance factors like time complexity, node mobility, cluster count etc.
Image fusion can be defined as the process of extracting the appropriate information from a set of images and then combining them intelligently to form a single composite image with extended information content in order to overcome the limitation of the type and resolution of the hardware sensors capturing images . Image fusion technology can be applied to many areas dealing with images such as medical image analysis, remote sensing, military surveillance, etc. This paper discusses about the problems in color image fusion and PCA(principal Component Analysis SWT(stationary wavelet transform ,DWT(Discrete Wavelet transform) based image fusion techniques along with the process flow diagram and .
Modified AODV for Detection and Recovery of Worm Hole Attack
Aarushi, Mr. Harish Bedi
This paper studies the wormhole attack in the mobile adhoc network. This paper modifies the AODV routing protocol to detect and recover from the wormhole routing attack. The result analysis of modified AODV is done by varying the number of wormhole nodes. The result analysis is done by using the PDR and the end 2 end delay. The simulation results confirm the better performance of the modified AODV.
Decision Support System for Information Security in the Semantics of Bio- Medical Documents
Tadi Bhanu , Venkata Pradeep
Technology and it’s requirement comes in various ways, considering one of the aspect as the building tool to next level journey of security as Information Security with the Theme behind to make the Bio-Medical efficiently in the context of Technology , i.e. how it plays the role in making and controlling the decision system. Making a prejudice statement on the support system is lead to nest level of insecurity. But In this paper we try to give a best perdition based on information where we consider as security to the information system. Time and Technology may play the complementary aspect in the decision support based on information security, at now we can give the best to mingle of various technology where security and its related decision are most important to these days software revolution, which we call it as most important and high risky to main component if IT market for Bio- Medical. The purpose of the security plan is to provide an overview of the security requirements of the system and describe the controls that are in place or those controls that are planned for meeting the security requirements. The system security plan also delineates responsibilities and expected behavior of all the individuals who access the system. The security plan should be viewed as documentation of the structured process of planning adequate, cost-effective security protection for the system. It should reflect input from the various managers who are responsible for the system. This includes the information owners, the system operators, the system security manager, and the system administrators.
Design and Implementation of Livestock Data Marts for a Web and Mobile-Based Decision Support System for Smallholder Livestock Keepers: Case Study of Tanzania
Bernard Mussa, Zaipuna Yonah, Charles Tarimo
Design of data marts is a fundamental task when preparing data destined for implementation of a Decision Support System (DSS). To answer questions on the underlying users information needs, a data-mart designer is challenged to distill the relevant information from various data sources, enable in-depth data analysis and provide ease of access of information to targeted DSS users. This paper presents the design of data marts for analysis of livestock datasets using dimensional modelling techniques. The designed data marts are then implemented for supporting information and knowledge extraction, leveraging large quantities of livestock data from livestock data source that was identified in the case study environment. Appropriate data mart dimensions and facts were modeled in order to ease data analysis and queries in a role-based information decision support model that was adopted in studied context. Data models based on dimensional modelling (star schema model) are provided and discussed. A comprehensive example showing how a piece of data is loaded from livestock data repository to ‘fact’ and ‘dimension’ tables using an open source CloverETL Designer tool is also given. The paper concludes with an overview of the overall detailed schema for the livestock data mart that will serve as a backend engine for On-Line Analytical Processing (OLAP) analysis, reporting, data visualization and information querying via mobile and web access. It is anticipated that the overall DSS once implemented, can be used for improving information delivery, sharing and decision making process to smallholder livestock keepers and livestock experts in Tanzania.
Ms. Kanchan P.Kamdi , Mr. Rahul Dhuture, Mr. G. Rajesh Babu
Improved Routing Performance in MANET Using Anonymity Algorithm
Ms. Kanchan P.Kamdi , Mr. Rahul Dhuture, Mr. G. Rajesh Babu
MANET is a type of wireless ad-hoc network that usually has a routable networking environment. Mobile Ad Hoc Networks use unidentified routing protocols that hide node identities and routes from outside observers to provide anonymity protection. Our existing anonymous routing protocols depending on either hop-by-hop encryption, redundant traffic either produce high cost or it cannot provide privacy protection to data sources, destinations, and routes. We propose a new location based routing protocol which offers high privacy protection at low cost to sources, destinations, and routes. It also has approaches to effectively counter intersection and timing attacks. The proposed plan ensures the privacy of both route and nodes which westudy and simulate the result. This existing protocol achieves better route privacy protection and its lower cost compared to other unidentified routing protocols, and also improving the routing efficiency compared to other geographical routing protocol.
A novel algorithm for sensing the digital signal in cognitive radio: Maximizing the spectrum utilization using the Bayesian approach
Saritha.N., sri T.Sarath Babu (PhD)
The proposed literature presents the novel framework to maximize the utilization of spectrum in cognitive radio networks. In order to achieve the higher spectrum utilization we propose an optical Bayesian detector for spectrum sensing to achieve higher spectrum utilization in cognitive radio networks. We derive the optimal detector structure for MPSK modulated primary signals with known order over AWGN channels and give its corresponding suboptimal detectors in both low and high SNR (Signal-to-Noise Ratio) regimes. Through approximations, it is found that, in low SNR regime, for MPSK (M>2) signals, the suboptimal detector is the energy detector, while for BPSK signals the suboptimal detector is the energy detection on the real part. The performance analysis of proposed framework is expressed in terms of probabilities of detection and false alarm, and selection of detection threshold and number of samples. The simulations have shown that Bayesian detector has a performance similar to the energy detector in low SNR regime, but has better performance in high SNR regime in terms of spectrum utilization and secondary users’ throughput.
A Novel Framework for Nanoscale Wireless Communications Using Minimum Energy Channel Codes
B.Swetha, M. Devendra M.S, (Phd)
In the world of nanoscale wireless communications, usage of energy plays a vital role in the communications. In our proposed algorithm, a novel minimum energy coding scheme (MEC) and a novel modulation scheme is proposed for wireless nano sensor networks (WSNS). Unlike conventional algorithms, MEC maintains the reliability in the process of minimizing the energy. It is analytically shown that, with MEC, code words can be decoded perfectly for large code distances, if the source set cardinality is less than the inverse of the symbol error probability. The state of-the-art nanoscale power and energy limits are used to obtain high end achievable rates of nano nodes and high performance, which are expected to be on the order of Mbps, neglecting the processing power. Our proposed evaluation results outperform the popular Hamming, golay and Reed-Solomon in the average codeword energy sense.
Image processing is one of most growing analysis space today and currently it is much integrated with the medical and biotechnology field. Image processing will be used to analyze completely different medical and MRI images to get the abnormality within the image. Using mutual information as a criterion for medical image registration, which requires no prior segmentation or preprocessing, has been both theoretically and practically proved to be an effective method in these years. However, this technique is confined in registering two images and hard to apply to multiple ones. The reason is that unlike mutual information between two variables, high dimensional mutual information is ill defined. This paper proposes associate degree economical K-Means clustering algorithmic rule beneath Morphological Image Processing (MIP). Medical Image segmentation deals with segmentation of growth in CT and MR images for improved quality in diagnosis. It is a very important method and a difficult drawback because of noise presence in input images throughout image analysis. It’s required for applications involving estimation of the boundary of associate degree object, classification of tissue abnormalities, form analysis, contour detection. Segmentation determines because the method of dividing a image into disjoint invaried regions of a medical image. The quantity of resources needed to explain large set of knowledge is simplified and is chosen for tissue segmentation. In our paper, this segmentation is disbursed using K-means agglomeration algorithmic rule for higher performance. This enhances the growth boundaries more and is extremely quick compared to several alternative clustering algorithms. This paper produces the reliable results that are less sensitive to error.
Application and Architecture Survey on Internet of Things
Bidyapati Thiyam, Swathi B S
Due to many advance technology Internet of things is now used in many application including low-cost sensors, low-power processors, commerce, industry, and education applications. Interconnection can be done with other object around us with the other world through Internet of thing (IoT) which are virtual connection, even wireless connectivity are available. In this paper, we take you to the introduction of Internet of things (IOT), different applications and architectures of Internet of things.
The information on the web search engine is escalating alarmingly and the efficiency of the information generated depends on the way of retrieving the information. There are several models which help to retrieve the pertinent information.
In Information Retrieval system, the generated outputs are ranked according to their relevance. Thus information retrieval process commences as soon as the user inputs a query to hunt sufficient information. The aim of information retrieval system is to retrieve the documents attaining the user query. This paper expounds the architecture of the search engine and several different information retrieval models such as Boolean model, Vector space model, Latent semantic Indexing (LSI) model and Latent Dirichlet allocation (LDA) model. It also covers the comparative analysis of these models.
Android is now the most used mobile operating system in the world. Android now has more users, more phones and more tablets worldwide than any other mobile operating system. One of the most difficult challenges facing testing teams is their ever changing and evolving configurations. The number of mobile device variations in the marketplace is quite staggering. Dozens of new mobile devices, such as Smart Phones, are being released monthly by device manufacturers, many with incremental operating system features and enhancements, which are further adding to the variation of configurations of these devices. Also application development life cycle for android is very short and hence testing time is squeezed. Testing of application across different version of android is a challenge. In this paper we present an approach for automating the testing process for Android applications, with a focus on GUI and functional bugs.
A Novel QR Code Watermarking In Digital Media Using DWT
Bhanuprakash V (S.E) , Muni Sekhar V (Sr.Grade)
Due to the extensive use of digital media applications, multimedia security and copyright protection has gained tremendous importance. Digital Watermarking is a technology used for the copyright protection of digital applications. In this project, a comprehensive approach for watermarking digital QR code image is introduced. We propose a hybrid digital media watermarking scheme based on Discrete Wavelet Transform (DWT) for a digital invisible watermarking is to embed binary image in the QR code image. In our method we embed a binary image considered as watermark embedded into one of selected wavelet subband. The proposed algorithm is also implemented on videos which is a novel approach compared to previous works based on the images. The experimental results show that our method has more robustness to attacks in different considerations and it can achieve a viable copyright protection and authentication.
Content Based Image Retrieval using User Interaction
Shubhangi Shirsath, Nilesh Bhosle
Due to the enormous increase in image database size as well as its vast deployment in various applications the need of Content Based Image retrieval (CBIR)systems becomes an crucial part of today’s cutting edge technology. In this paper we have proposed a CBIR system using color and texture feature. To reduce the semantic gap between the low level feature and high level semantics, relevance feedback mechanisms have been applied to the system. In most existing CBIR systems the current RF techniques still lack satisfactory user interaction to improve the search accuracy and interaction as well. In this paper, we proposed a user interaction model using Support Vector Machine. Experimental results show that our system gives improved results as compared to other systems available in the literature.
A Survey on Data Mining Techniques In Business Intelligence
B.Sangameshwari, P. Uma
There are assortment of procedures, methodologies and distinctive zones of the exploration which are useful and stamped as the vital field of data mining Technologies. Numerous MNC's and vast associations are worked in better places of the distinctive nations. Each one spot of operation may produce expansive volumes of data. Corporate chiefs oblige access from all such sources and take vital choices .The data distribution center is utilized within the critical business esteem by enhancing the adequacy of managerial choice making. In a dubious and very aggressive nature's turf, the estimation of vital data frameworks, for example, these are effortlessly perceived however in today the earth, effectiveness or velocity is by all account not the only key for aggressiveness. This sort of gigantic measure of data's are accessible as tera- to peta-bytes which has definitely changed in the ranges of science and building. To examine, oversee and settle on a choice of such sort of tremendous measure of data we require systems called the data mining which will changing in numerous fields. This paper confers more number of uses of the data mining furthermore centres extent of the data mining which will accommodating in the further research.
Detection of Red Lesions and Hard Exudates in Color Fundus Images
Jyothis Jose, Jinsa Kuruvilla
Diabetic Retinopathy is the damage caused to the blood vessels in retina due to diabetes. The severe case of diabetic retinopathy leads to vision loss. It is important to diagnose diabetic retinopathy in earlier stage. In this work automatic methods for detection of various lesions of diabetic retinopathy from color fundus images are explained. The retinal structures which include blood vessels, optic disc and fovea are also detected. The prominent lesions present in an abnormal color fundus image include the brighter lesion such as hard exudates and darker lesions such as microaneurysms and haemorrhages. The severity of the disease based on location of the hard exudates in the retina is also explained. Hard exudates are detected by a supervised learning technique on normal color fundus images. The global features of normal color fundus image are captured using a feature extraction technique. Based on this feature the images are classified to be normal or abnormal. The classification of abnormal image as moderate or severe is done by considering the rough rotational symmetry of the macula of a normal color fundus image. The presence of red lesions is detected based on its appearance on the color fundus image. A moat operator is used for the red lesion detection. The algorithms were tested on a small dataset. Hard exudates are detected with an accuracy of 95% and classified with an accuracy of 96%. Red lesions are detected with an accuracy of 90%.
A new diskless checkpointing approach for handling multiple processor failures
Dipali B. Parase, Dr. Mrs. S. S. Apte
In a distributed computing environment, it is necessary to handle the multiple processor failures. In this paper we present a new diskless checkpointing approach which combines neighbor based diskless checkpointing and parity-based diskless checkpointing. As we are storing checkpoint in the peer processors memory, the problem of stable storage is overcome by using neighbor-based diskless checkpointing method. Also for reducing memory consumption problem we use parity-based diskless checkpointing technique. There is no need of dedicated checkpoint processors. It can handle multiple processor failures simultaneously in the system.
Channel imperfections deteriorates the quality of the transmitted signal. This results in high bit error rate on receiver side and hence makes it difficult for the receiver to recover the original signal. Channel response is dynamic in nature and in order to decrease the bit error rate adaptive equalizers are generally used at the receiver side. This paper presents the FPGA implementation of adaptive equalizer.
Bhuvaneswari, E. George Dharma Prakash Raj, J. Sangeetha
A Framework for Handoff Decision and Signal Selection Algorithms for Heterogeneous Network
Bhuvaneswari, E. George Dharma Prakash Raj, J. Sangeetha
The mobile and wireless communication technologies are launching much advancement every day to the mobile user. To make use of this advancement the user has to receive the signal properly. But because of the mobility nature of the mobile users the receiving signal strength is diminishing while the user moves away from coverage region of antenna. This problem has been reduced using handoff techniques. But the handoff decision and the efficient target signal selection should be done within short span of time. This paper proposes a framework which meets the above mentioned requirements for handoff.
Design and development of shunt hybrid power filter for harmonic mitigation
Reena Meghwal
This paper presents design, simulation and development of Shunt Hybrid Power Filter (SHPF) for mitigation of the power quality problem at ac mains in ac-dc power supply feeding to a nonlinear load. The power filter is consisting of a shunt passive filter connected with a shunt active power filter. At first passive filter has been designed to compensate harmonics, and then similarly active filter is designed. The drawback associated with the passive filter like fixed compensation characteristics and resonance problem is tried to solve by SHPF.Simulations has been carried out to verify the proposed filter system. Harmonic contents of the source current has been calculated to demonstrate the influence of harmonic extraction circuit on the harmonic compensation characteristic of the shunt hybrid power filter.
Enhanced Modified model for safe driving using Embedded Automotive control systems
C.Divya, Amarendra Jadda
The population of our country has been increasing rapidly, which indirectly has increased the vehicle density and lead to many road accidents. The main causes of accidents include drowsiness of driver, health conditions, drunk and drive, collision of vehicles etc. The main aim of this project is to minimize the road accidents occurring due to driving fatigue which cause the loss of invaluable human life and other valuable things, till now we saw many ways to reduce causes for accidents,[1] we now implement a new concept of monitoring the driver’s health condition, by that we can avoid the accidents up to some extent, if the person met with any health issues the vehicle will get slow down/stopped and then the message will be sent to doctor for medical services using GSM, then by using GPS receiver the vehicle will be tracked to serve emergency medical services to the victim present inside the vehicle.
FPGA Based Low Area Motion Estimation with BISCD Architecture
R.Pragathi, Dr. K.Babulu
The Motion Estimation Computing Array (MECA) is used in Video Encoding applications to calculate the best motion between the current frame and reference frames. The MECA is in decoding application occupies large amount of area and timing penalty. By introducing the concept of Built-in Self test technique the area overhead is increased in less amount of area. In this Paper the Built-in Self test Technique (BIST) is included in the MECA and in each of Processing Element in MECA is tested using residue codes .the quotient and remainder was cross checked across the processing element and test code generator. Further the residue and quotient code complex operation is replaced with the simple Boolean logic division operation in order to reduce the area of the circuit. Thus by introducing the BIST Concept the testing is done internally without Connecting outside testing Requirements. So the area required is also reduces. And in this Paper the Errors in MECA are Calculated and the Concept of Diagnoses i.e. Self Detect and Self Repair Concepts are introduced.
Improving Power Line Utilization and Performance With Facts Devices In Disturbed Power Systems
M. Siva Sankar
This Paper describes the theory and simulation by mat lab of flexible Alternative Current Transmission Systems (FACTS) devices used in the disturbed power systems. One of these devices, Unified Power Flow Controller (UPFC) will be chosen for a specific application, detailed in this Project. Simulation investigate the effect of UPFC on the voltage of the related bus, it also considers the effect on the amount of active and reactive power flowing through the transmission system.
Finally simulation results have been presented to indicate the improvement in the performance of the UPFC to control voltage in disturbed power systems.
An Efficient certificate Revocation Method For Mobile Ad Hoc Network
Yogini R.Joshi, Dr.Mrs.Sulabha Apte
Mobile adhoc networks (MANETs) have attracted much attention due to their mobility and ease of deployment. However the wireless and dynamic natures render them more vulnerable to various types of security attacks than the wired networks. Certificate Revocation is an important integral component to secure network communications. The main challenge for certificate revocation is to revoke the certificates of malicious nodes promptly and accurately. When the certificate of malicious node is revoked,it is denied from all activities and isolated from network. In this paper we build upon previously proposed scheme,a clustering based certificate revocation scheme.This scheme is used for quick revocation of attackers certificates and recovery of falsely accused certificates .
To overcome the limitation of the Clustering based certificate revocation scheme we use node release method .To identify the malicious nodes the zkp (zero knowledge protocol ) is used.Extensive simulation show that the new method can effectively improve the performance of Certificate Revocation.
The MANETs is to extend mobility into the realm of autonomous, mobile and wireless domains, where a set of nodes form the network routing infrastructure in an ad-hoc fashion. The majority of applications of MANETs are in areas where rapid deployment and dynamic reconfiguration are necessary and wired network is not available.
In ad-hoc networks, nodes are not familiar with the topology of their networks. Instead, they have to discover it. The basic idea is that a new node may announce its presence and should listen for announcements broadcast by its neighbors. Each node learns about nodes nearby and how to reach them, and may announce that it, too, can reach them.
The Multicast protocol can generally be categories into two: proactive and Reactive i.e On-Demand, DVMRP and PIM-DM . ODMRP is a mesh-based, rather than a conventional tree based, multicast scheme and uses a forwarding group concept. Three prominent multicast routing protocols are selected for performance protocols. The simulation environment Qualnet 5.0.2. The main aim is to calculate the relative feature and quality of each protocol.
A Novel Method of Early prediction of Packet Delay for Mobile Nodes with modified constraint violation Detection Algorithm
K. Nithiya
Network delay is an important performance characteristic of a computer network or telecommunications network. The delay of a network specifies how long it takes for a bit of data to travel across the network from one node or endpoint to another. It is typically measured in multiples or fractions of seconds.The work presented here belongs to domain of wireless network , the real Time Early Prediction of network delay is done using the proposed constraint prediction Algorithm.Anew application is presented concerning the delivery delays of packets in GPRS network.The distributed monitoring of events from GPS device is considered for delay prediction in TCP/IP network.Whenever the GPS device crosses the access point , the event dispatchfrom the device is monitored regularly for correct prediction.
Improved Emotion Detection by Regression Algorithm with SURF Feature and SVM
Navdeep Kaur, Er. Varinderjit Kaur
One of the major concerns in the field of computer vision and pattern recognition is emotion detection. One difficulty in face recognition is how to handle the variations in the expression, pose and illumination when only a limited number of training samples are available. In this paper KNN Regression algorithm with SURF feature is proposed for facial expression detection. Initially the eigenspace was created with eigenvalues and eigenvectors.. From this space, the eigenfaces are constructed, and the most relevant eigenfaces have been selected using Principal Component Analysis (PCA). The proposed method was carried out by taking the picture database. The database was obtained with 50 photographs of a person at different expressions. Another database was also prepared for testing phase by taking 10 photographs of that person in different expressions but in similar conditions ( such as lighting, background, distance from camera etc.) and these database images were stored in test folder.
A Survey on Object Based Image Retrieval using Local and Global Features
Ami M Patel
An image is an artifact that depicts or records visual perception. Object Based Image Retrieval (OBIR) is a technique to find specific object from image database. Similar images can be retrieved from image database by comparing image features. A feature is a piece of information which is relevant for solving the computational task related to a certain application. Visual content of the entire image refer to the global features. Locally rich information like interesting point detection can be addressed in local features. This paper include color features and edge detection feature as global feature and corner detection feature as local feature. Some techniques for finding each features and comparison of those techniques are mentioned here.
Hetertogenous Database Migration using ODTDM Supported with SAX and SDM algorithms
Priyanka Talole, Mayur Talole
This paper proposes to describe an approach used for migration of historical database from one database to required database, and setting up a daily feed from the product into the system data to have previous day reports available for current day trading. Here are different type of database we used like Ms Access, MSSQL, Oracle in source and destination. At present day there are only one language to other migration code conversion techniques. This paper attempts to give pros and cons of developed approach over existing ways in order to achieve enhanced database migration system.
A Novel Approach To Enhance The Lifetime And Throughput Of Wireless Sensor Network Using Actor Nodes.
Diksha Garg, Geetanjali Babbar
Wireless sensor networks is a self-configured network means any node can join it or leave it at any time. it is a self-healing and self-organizing. Self-healing networks allow nodes to reconfigure their link associations and find other pathways around powered-down nodes or failed nodes. Self-organizing allows a network automatically join new node without the need for manual interference. In this paper, we are using actor nodes to solve energy hole problem so that we can reduce energy consumption and can enhance throughput of network.
Energy saving Mechanism in cloud computing by using multi core architecture
Shiva Chaudhry
Energy efficiency is more and more essential for upcoming information and communication technologies (ICT), for the reason that the enlarged usage of ICT, jointly with growing energy expenses and require to decrease green house gas emissions call for energy-efficient technologies that reduce the overall energy utilization of computation, storage and communications. Cloud computing is becoming an opportunity for industry to permit a high level of communication expertise, scalability, and usability of computing resources. The optimization of Cloud computing has grows in the industry of huge-scale data centres over the globe have various nodes. We can keep energy by CPU Utilization and using DVFS, live migration of VM and virtualization by using multi –core architecture. This paper presents analysis of cloud computing features, issues and software for dynamic resource saving mechanism with Virtual Machines (VMs) and multi-core architecture is used to hold multi-virtual machines in Cloud data centres.
Urban Area Classification Using High Resolution Remote Sensing Data: A Hybrid Classification Approach
Kiran Bagade, Amol Vibhute, K.V. Kale
Increasing urbanization has resulted in reduction of agricultural land. There is immense requirement of keeping track urban development’s to avoid depletion of agricultural land. This paper explains urban area classification using remote sensing and GIS Mapping of classification is done with help of top sheet E43D/5, with scale 1:50, 0000 and IRS-P6 LISS-IV image of Feb. 2014 having resolution of 5.8 m and GPS receiver My GPS coordinates is used. Classification methods like supervised and unsupervised both are used and detailed results analysis is done. For doing this the acquired image went through the series of process namely Preprocessing, Classification and Result analysis. Some image enhancement techniques were also performed to improve the satellite imagery for better visual interpretation. ENVI 4.4 image analysis tool were used for data processing and analysis. Maximum Likelihood, Mahalanobis distance, and Isodata classifiers were performed for urban classification in this study. Seven urban classes have been identified from the satellite image classification processes. It is observed that area is covered by barren land, agricultural area (with crops and without crops), hilly area, buildings and water bodies and play ground etc. The experimental results were compared with different supervised and unsupervised classifiers, such as Mahalanobis distance, and Maximum Likelihood and Isodata classifiers respectively. The performances of the classifiers were evaluated in terms of the classification accuracy with respect to the ground truth. The result of the classifications suggests that, each used and covered type were best classified by the Hybrid classification technique. Hybrid classification is done by first applying unsupervised classification like ISODATA classification, followed by various supervised classification techniques like Maximum likelihood, Mahalanobis classification. Hybrid classifier is best classifier of all. Combination of Supervised and Unsupervised classifier results in better accuracy as compared to supervised classification alone.
Wormhole attack is a severe threat against ubiquitous sensor networks. Due to variety of proactive protocols used in the network DSDV does not exploit the large network. AODV is an effective routing protocol for networks that doesn’t maintain any routing tables at nodes which results in less overhead and more bandwidth. The connection setup delay is lower. MRT will work efficiently only when wormhole node will come in the path from source to destination. In this paper detection and isolation of the wormhole has been proposed. This approach is implemented using NS-2. The results and conclusions are shown in the paper.
Software failures usually can be defined as a delivery service mechanism failure when a system usually does not agree for expected service or function as desired. According to Laprie it can be said as failures to systems usually occur when delivered service no longer compiles with the specifications, the definition is applicable to both hardware & software system failures
Detecting Client Based HTTP Attacks on Web Proxy by Temporal and Spatial Locality Behavior and Protocol Modification
Jabin A
Distributed Denial-of-Service (DDoS) attack is a major threat for Internet applications. DDoS attacks relay on interrupting the services of a host connected to the Internet. In computer networks, a proxy server act as an intermediate server for bypassing the HTTP requests from clients to web servers. Client can access web server through different proxies. A novel attack detection scheme is proposed to prevent http attacks in web proxy based network. Here the attack detection is carried out at server. Accurate attack detection at server is difficult if proxy hide the information of clients. In the proposed scheme the detection is client based rather than proxy based. Here the client information is also passed along with the request so the server can easily identify the client and the attack detection become more accurate. This scheme utilizes locality behaviours such as Temporal and Spatial Localities(TSL) of proxy to server traffic.
A Survey of Requirement Engineering Practices in Software Development
Swathine.K, Dr. J.KomalaLakshmi
Requirement Engineering is process of formulating, maintaining, and documenting software requirements. Requirements are given by the User of the system, according to that engineers will develop the system. Requirement Engineering deals on Functional and Non Functional requirements. Functional and Non Functional requirements are the work as bricks to support software edifice. Finally, design, implementation and testing add stories to construct entire software tower on top of this foundation. For this purpose, requirement engineers come across with numerous challenges to develop successful software. Requirements engineering is an iterative process.
Predict the Future Path based on Frequent Path Detection using Particle Swarm and Binary Bat Optimization Technique
M.Selvi Mohana, Dr.B.Rosiline Jeetha
Swarm is a technique to identify the collective behavior of an object. In this modern world web usage gets increases day by day. Difficult task to identify the user’s interest in a web and provide a related data to the user in a quick mode. Based on their attention a developer has to upgrade their websites and improve the performance of the web pages and provide related information to the user with these data identify the user need in future. This paper present a comparative analysis of PSO and BBA algorithm which improves the predictable form by detecting the frequent path based on this find the future path.
In the era of internet the probability of system or application being vulnerable to malwares such as viruses, Trojans, botnets etc. has provoked data corruption, data manipulation, security breaching and so on. Different techniques like antivirus and firewalls have emerged to combat against malware attacks. However existing signature based detections are unable to counteract anomalous behaviour of specific applications. There exist various behaviour based techniques which detects malicious content by observing applications at run-time. The focal point of this paper is on immunising an application against specific threats.
FPGA Implementation of Canny Edge Detection Algorithm
Ms. P.H. Pawar, Prof. R. P. Patil
Edge detection is the first step in many computer vision applications. Edge detection of image significantly reduces the amount of data and filters out unwanted or insignificant information and gives the significant information in an image. This information is used in image processing to detect objects in which there are some problems like false edge detection, missing of low contrast boundaries, problems due to noise etc. In this paper Canny Edge Detection algorithm is implemented. Canny Edge Detection algorithm for stored image is implemented on Virtex 5 Field Programmable Gate Array (FPGA) board. Using Xilinx platform studio and Xilinx ISE output image displayed on Video Graphics Array (VGA) monitor which is interfaced with board by using DVI connector.
Cloud based ERP system architecture provides solutions to all the difficulties encountered by conventional ERP system. It provides flexibility to the existing ERP systems and improves overall efficiency. This paper aimed at comparing the performance traditional ERP systems with cloud base ERP architectures. The challenges before the conventional ERP implementations are analyzed. All the main aspects of an ERP systems are compared with cloud based approach. The distinct advantages of cloud ERP are explained. The difficulties in cloud architecture are also mentioned.
A new Data Embedding approach in digital images Using Adaptive Pixel Pair Matching
Dabbukottu Ajayulu , P. Ravi Kiran
This paper presents a novel data embedding method using adaptive pixel pair matching (PPM).it is a new Data hiding method which use the value of pixel pair as reference coordinate, and search a coordinate in the neighborhood set of this pixel pair as per the a given message digit. Then the pixel is replaced by the new coordinate to conceal the digit. Exploiting modification direction (EMD) and diamond encoding (DE) are two hiding methods based on PPM. The maximum capacity of EMD is 1.161 bpp. The proposed method offers much lower distortion than DE provides. It allows embedded digits in any notational system by providing compact neighborhood. Comparing with the optimal pixel adjustment process (OPAP) and DE method, the proposed method not only provides better performance but it also has low distortion for various payloads. It also secure the detection of some well-known steganalysis technique
A Novel Approach for Channel Estimation In MIMO-OFDM System Using The Efficient Pilot Patterns
K. Siva Nagamma , Smt. K. Udaya Kiran
A novel approach is presented in this work to efficient pilot patterns estimation as well as channel estimation in multiple input-multiple output orthogonal frequency division multiplexing system. In our proposed work, we exploit the basic orthogonal property of unitary matrix based on scattered pilot, continuous pilot and edge pilot in order to estimate the pilot patterns in accurate manner. Efficient channel frequency response and channel impulse response estimation is done in our proposed work by orthogonal property analysis. Finally, the proposed work simulation results evaluation yields high end performance when compare to the conventional works such as multi input-single output OFDM system.
PAPR Reduction for High-Data-Rate Through-Metal Control Network Applications Using Bit-Loaded
U.Divya Jyothi , L.Lakshmi Prasanna Kumar
Data transmission through metallic structures is commonly needed in industrial control applications. in an exceedingly range of those applications, mechanically penetrating the structure to pass cables and establish a wired communication link is either impossible or undesirable. Examples of such structures include metal bulkheads, pressure vessels, or pipelines. Ultrasonic communication has been projected as an answer for through-metal information transfer without penetrating the structure. The reverberating nature of the through-metal channel, however, will cause significant inter-symbol interference, limiting the info rate possible by conventional single-carrier communication techniques. During this paper, we tend to describe a through-metal communication technique that exploits the slow-varying nature of the ultrasonic channel to implement AN orthogonal-frequency-division multiplexing-based rate-adaptive peak-to-average power quantitative relation (PAPR) reduction algorithm. Measurements of the projected adaptive algorithm have demonstrated transmitted output rates. This improvement provides the desired output and error rate to support high-rate network applications in otherwise data-limited environments.
Comparison of Communication Algorithms on OTIS-HHC and OTIS-Ring Parallel Architectures
Abdul Hannan Akhtar, Keny Thomas Lucas
The OTIS (Optical Transpose Interconnection System) has recently attracted the attention of researchers and it has become very popular for solving real life computation and communication intensive applications. In this paper, we have presented a comparison of communication algorithms on OTIS-HHC and OTIS-Ring architectures. Gossiping is a common process for solving some of the problems like polynomial interpolation, matrix multiplication, prefix computation and enumeration sorting. The proposed algorithm is based on some predefined data routing functions. To analyze the time complexity of the proposed communication algorithms, we have considered the data movements on electronic link and optical link. The time complexity of both the proposed algorithms is O(n) OTIS moves and O(n2) electronic moves.
Performance Evaluation of Low Power Dynamic Circuit Using Footed Diode Domino Logic
Monika Jain, Dr. Subodh Wairya
Power saving is more important than any other thing now a days because high speed and low power design continues to get more attention. In this paper, low power dynamic circuit [1] has been implemented at 180nm, 90nm, 45nm and 32nm technology, using HSPICE. The simulations are performed on CosmosScope. The power saved is up to 46%, 50%, 51% and 73% for 180nm, 90nm, 45nm and 32nm technology respectively using the proposed footed diode circuit [1]. Domino buffer and a two input AND gate have been used as a test circuit to show the simulation results.
Task Scheduling of Special Types of Distributed Software in the Presence of Communication and Computation Faults
Kamal Sheel Mishra, Anil Kumar Tripathi
This work is an extension of our previous work on task scheduling of a Distributed Computing Software in the presence of faults [2] in which an attempt was made to identify the task scheduling algorithms used for distributed environments that perform well in the presence of faults due to network failure or processor failure in the distributed system. In this paper we give some extensive results for identifying the task scheduling algorithms that perform well in the presence of communication and computation faults present in some special task graphs like systolic array task graphs, Gaussian elimination task graphs, Fast Fourier transform task graphs, and divide-and-conquer task graphs which can represent the distributed software. For our study we have selected six task scheduling algorithms. We have compared these algorithms using three comparison parameters like normalized schedule length, number of processors used and average running time, and evaluated them on the above mentioned task graphs in the presence of communication and computation faults. It is further evaluated under random and constant fault delays.
Temporal Segmentation of Facial Behavior in Static Images Using HOG & Piecewise Linear SVM
Preeti Saraswat , Srikanth G
Temporal segmentation of facial gestures in spontaneous facial behavior recorded in real-world settings is an important, unsolved, and relatively unexplored problem in facial image analysis. Several issues contribute to the challenge of this task. These include non-frontal pose, moderate to large out-of-plane head motion, large variability in the temporal scale of facial gestures, and the exponential nature of possible facial action combinations. To address these challenges, we propose a two-step approach to temporally segment facial behavior. The first step uses spectral graph techniques to cluster shape and appearance features invariant to some geometric transformations. The second step groups the clusters into temporally coherent facial gestures. We evaluated this method in facial behavior recorded during face-to-face interactions. The video data were originally collected to answer substantive questions in psychology without concern for algorithm development. The method achieved moderate convergent validity with manual FACS (Facial Action Coding System) annotation. Further, when used to preprocess video for manual FACS annotation, the method significantly improves productivity, thus addressing the need for ground-truth data for facial image analysis. Moreover, we were also able to detect unusual facial behavior. This paper consists of efficient facial detection in static images using Histogram of Oriented Gradients (HOG) for local feature extraction and linear piecewise support vector machine (PL-SVM) classifiers. Histogram of oriented gradient (HOG) gives an accurate description of the contour of image. HOG features are calculated by taking orientation of histogram of edge intensity in a local region. PL-SVM is nonlinear classifier that can discriminate multi-view and multi-posture from the images in high dimensional feature space. Each PL-SVM model forms the subspace, corresponding to the cluster of special view. This paper consists of comparison of PL-SVM and several recent SVM methods in terms of cross validation accuracy.
Adaptive Rate Limiting Strategy To Defend Against Distributed Denial Of Service Attacks
Mrs.C. krishnaveni
Distributed Denial of Service (DDoS) attacks is one of the more serious threats currently faced by Internet based companies. In this study, we deal with DDoS attacks by proposing a dynamic reactive defense system to detect and prioritize the malicious traffic flow towards a target system. Approach: The proposed scheme identifies the most critical flaw in the attack traffic based on the strength of malicious flow and the duration of attack persistence and applies an adaptive rate limiting on each individual flow instead of a fixed rate limit on the collective attack flow. The results: The scheme reacts very quickly to any changes in the network state. The results observed on the dataset shows that the proposed scheme detects the onset of the attacks very early and reacts to the threat by rate limiting the malicious flow. Conclusion: The proposed system can be successfully implemented as an autonomous defense system to limit damage to the victim by limiting the malicious flows towards the target system with a higher degree of accuracy.
Data Routing though being the most basic service provided by the Wireless Sensor Network (WSN) Nodes, it is also the one which consumes the highest amount of energy. Sensor Nodes are usually fitted with power sources that are non-rechargeable and due to the vast application of WSNs they are also usually practically irreplaceable. This makes the longevity of Nodes a critical factor for consideration while designing the routing protocols. In this paper we survey the protocols that are being used and show their efficiency.
Purpose of our application is to be used by banks for web-clients. Banks are always looking for more powerful and user-friendly applications to upgrade their existing websites. So, our hypothesis is that AI would perform on all platforms using artificial algorithms to analyze and understand user’s queries relating to the bank’s loan, account, policy etc. This shows that AI would perform as per design and expectation. No specific format would be required for the client to ask questions. For instance, the question “what is the interest on home loan?” can be framed as “Let me know about interest on home loan”. It has integrated text-to-speech concept & graphical representation of a person speaking out answers. It also consists of ATM finder and Branch locator systems for other bank related help.
Combining Support Vector Machine Learning with the Discrete Wavelet Trannsform and Contourlet Transform in Image Compression
Neena Hulkoti
In this paper, the results of combining support vector machine (SVM) learning with discrete wavelet transform and contourlet transform in image compression are compared. The algorithm combines SVM learning with the discrete wavelet transform (DWT) and contourlet transform (CCT) of the image. An SVM selects the minimum number of training points, called support vectors which ensure modeling of the data within the specified level of accuracy. It is this property that is exploited as the basis for an image compression algorithm. Now, the SVMs learning algorithm performs the compression in a spectral domain of DWT and CCT coefficients.
Peak signal to noise ratio (PSNR) is computed for the images compressed using wavelet and contourlet transforms. Results show that contourlet transform based image compression is more effective in capturing smooth contours (due to anisotropy property) than wavelet transform based compression.
Prof. R.S. Suryavanshi,Kunal Khivensara, Gulam Hussain, Nitish Bansal, Vikash Kumar
Home Automation System Using Android and WiFi
Prof. R.S. Suryavanshi,Kunal Khivensara, Gulam Hussain, Nitish Bansal, Vikash Kumar
Today’s world has seen rapid and lucent spread of Android Devices. Any system, thus, developed which has support of the ubiquitous Android –enabled devices will be much appreciated. Our project is based on this idea along with the much-needed Automation System interfaced with the Android Systems. We have harnessed the easy-to-understand Android GUI to a constructive work whereby we see to it that the home is automated and energy is saved. This makes our home intelligent enough to save electricity, which is the need of the hour. We have elucidated this idea into realization with the help of Wi-Fi technology, which really offers easy and really much awaited Home Automation Systems (HASs). This system has an upper hand from other similar developments made with the technologies such as Bluetooth since it works on Wi-Fi. Thus we have offered a scalable and cost-effective Home Automation Systems (HASs).
Manish Bhutada, Meenakshi Raut, Mohammed Esoofally, Sanjyot Agureddy
Controlling a Car Buggy Using a NIR Camera with Hand Gestures
Manish Bhutada, Meenakshi Raut, Mohammed Esoofally, Sanjyot Agureddy
We live in the digital era where the use of digital components is increasing in automotive engines, direction systems & other devices. Hence giving rise to new user interfaces due increase in Human-Vehicle Interaction (HVI). HVI devices having many key characteristics such as stability, reliability and robustness of the system. HVI devices help to track the gesture, recognize it and perform the desired operations in real time. This can be implemented using hand gesture control mechanism as one of its components. The gestures control technique has become a new trend for many human based electronic products. In this paper we will be using a near infrared Camera (NIR) camera which will track the images which will then be forwarded to the gesture recognition architecture. This architectures makes use of series of different recognition algorithms to recognize the gesture and perform the desired action.
A Novel Image Retrieval Approach for Digital Images Based On Pseudo-Zernike Moment Invariants
P.Ramjee, S Srividya
In this paper we propose a new and effective image retrieval scheme using color, texture and shape features based on pseudo-Zernike moment. Image is predefined by using fast color quantization algorithm with cluster merging. A small number of dominant colors and their percentage can be obtained. The spatial features are extracted using steerable filter decomposition. This offers an efficient and flexible approximation of early processing in the human visual system (HVS). Sharp descriptor of an image uses pseudo-Zernike moment. It provides better feature representation and more robust to noise then other representations. Finally, the combination of the color, shape and texture feature provides a robust feature set for image retrieval. Experimental result shows that the proposed method provides a better color image retrieval. It provides accurate and effective in retrieving the user-interested images.
Compressing Land Images using Fractal Lossy Compression
Amandeep Kaur, Vikas Wasson
This paper presents a multistep approach for segmenting and compressing satellite based land images acquired from Google Maps in accordance to reduce the storage space and transmission time requirements. Land images are often noisy thus first step involves removing noise by using Adaptive Filter for better enhancement of the image. Then Region Based Segmentation is performed to achieve the uniform regions of an image that helps in mapping areas. Finally compression is performed. This work proposed Fractal Lossy Compression algorithm for compressing Land images as it has tendency to produce efficient and optimal results in different applications. The performance of proposed algorithm is compared with other lossy compression technique i.e Cartesian Perceptual Compression based on some parameters. Experimental results proved that the proposed technique is more efficient, effective and accurate as compared to Cartesian Perceptual Compression
UNPRIVILIGED BLACK BOX DETECTION OF USER-SPACE KEYLOGGERS
R.Suguna, R.Ramya
Software keyloggers are a fast growing class of invasive software often used to harvest confidential information. One of the main reasons for this rapid growth is the possibility for unprivileged programs running in user space to eavesdrop and record all the keystrokes typed by the users of a system. The ability to run in unprivileged mode facilitates their implementation and distribution, but, at the same time, allows one to understand and model their behavior in detail. Leveraging this characteristic, we propose a new detection technique that simulates carefully crafted keystroke sequences in input and observes the behavior of the keylogger in output to unambiguously identify it among all the running processes. We have prototyped our technique as an unprivileged application, hence matching the same ease of deployment of a keylogger executing in unprivileged mode. We have successfully evaluated the underlying technique against the most common free keyloggers. This confirms the viability of our approach in practical scenarios. We have also devised potential evasion techniques that may be adopted to circumvent our approach and proposed a heuristic to strengthen the effectiveness of our solution against more elaborated attacks. Extensive experimental results confirm that our technique is robust to both false positives and false negatives in realistic settings.
Explore Multidocument Text Clustering With Supervised And Unsupervised Constraints
V.Shanmugapriya, S.Krishnaveni
Clustering techniques are used for automatically organizing or summarizing a large collection of text; there have been many approaches to clustering. As described below, for the purpose of the work, we are particularly interested in two of them: coclustering and constrained clustering. This thesis proposes a novel constrained coclustering method to achieve two goals. First, it combines information-theoretic coclustering and constrained clustering to improve clustering performance. Second, it adopts both supervised and unsupervised constraints to demonstrate the effectiveness of the algorithm.
The unsupervised constraints are automatically derived from existing knowledge sources, thus saving the effort and cost of using manually labeled constraints. To achieve our first goal, we develop a two-sided hidden Markov random field (HMRF) model to represent both document and word constraints. It then used an alternating expectation maximization (EM) algorithm to optimize the model. It also proposes two novel methods to automatically construct and incorporate document and word constraints to support unsupervised constrained clustering. 1) Automatically construct document constraints 2) Automatically construct word constraints The results of the evaluation demonstrates the superiority of our approaches against a number of existing approaches.Unlike existing approaches, this thesis applies stop word removal, stemming and synonym word replacement to apply semantic similarity between words in the documents. In addition, content can be retrieved from text files, HTML pages as well as XML pages. Tags are eliminated from HTML files. Attribute name and values are taken as normal paragraph words in XML files and then preprocessing (stop word removal, stemming and synonym word replacement) is applied
The number plate recognition system is one kind of an Intelligent Transport System. The proposed work is used to extract numbers from the number plate. This technology is used in various security purposes for finding stolen cars, traffic management system, in electronic toll collection, smuggling of cars, usage of cars in terrorist attacks and illegal activities. This work is based on edge detection and efficient morphological operations. Character segmentation is the process of extracting the characters and numbers from the license plate. Noises in the image are removed using filtering techniques. Optical Character Recognition (OCR) technique is used for the character recognition. In OCR the filtering character is matched with template using template matching algorithm and finally the character is extracted.
Face Recognition using Local Derivative Pattern Face Descriptor
Pranita R. Chavan, Dr. Dnyandeo J. Pete
Face detection and recognition is becoming increasingly important in context of surveillance, credit card fraud detection, assistive devices for visual impaired, etc. There are multiple cues available and can be used as features. It has been observed that local features perform better than global cues. Local binary pattern and local derivative pattern try to encode directional pattern of a face image. Hence it becomes important to critically evaluate the performance of LBP and LDP for rotated and scaled faces. Facial features are extracted and compared using support vector machine classification algorithm. We have considered standard databases containing the rotated faces. Also, we have created a database of annotated rotation angle to find out the permissible degree of rotation for LBP and LDP.
Component-Based Development Technologies and Limitations
Mrs. Jyotsna
The primary role of component-based software engineering is to address the development of systems as an assembly of parts (components), the development of parts as reusable entities, the maintenance and upgrading of systems by customising and replacing such parts. This paper defines current component-based software technologies used and their advantages and disadvantages
Performance Evaluation of Different Types of CMOS Operational Transconductance
Vijeta, Dr. Subodh Wairya
The Operational Transconductance Amplifier is a basic building blocks found in many analog circuits such as data converter’s (ADC& DAC) and Gm-c filters. The OTA is an amplifier whose differential input voltage produces an output current .Thus ,it is a voltage controlled current source(VCCS) whereas the Op-amp are voltage controlled voltage source(VCVS). There is usually an additional input for a current to control the amplifier’s transconductance. The paper represents the different topology of CMOS OTA is described and at last comparison between different configuration is given.
Today’s Online Social Networks (OSNs) do not provide an ability to control the contents of the message posted on user’s private wall. Any unwanted contents can be easily posted on the walls. Security in posting of unwanted message is an important issue in OSN. Up to now OSN have provided little control regarding who can post on user’s private wall. Here we have proposed a system that will prevent unwanted messages from being posted on user’s wall. To achieve this, the messages are scanned using text categorization techniques. We have also proposed a Blacklisting mechanism which will block such frequent message creators and prevent them from further posting any messages on the user’s wall.
Benjamin Ghansah , Benuwa Ben-Bright, Frank Kataka Banaseka
Cloud Computing And Virtualization: Trends And Technologies
Benjamin Ghansah , Benuwa Ben-Bright, Frank Kataka Banaseka
In our world today, the inculcation of ICT in government and business has become an indispensable tool in the implementation of government’s policies and also for businesses to tap into the realms of competiveness. Previous studies have proved the ubiquitous of ICT to be one of the efficient and effective way in realizing this phenomenon. A contemporary technology in recent times is cloud computing; whose aim is to deliver the utility of ICT in a cost efficient and effective manner. It adopts the technique of elasticity that rides on the principle of “pay as you need”, which prevents redundancies and allows for scalability and much more diversity in the use of resources. This paper aims at reviewing the provision of the cloud computing capabilities and the constraints that comes with it.
G. S. L. Alekhya, M. S. S. Bhargav, A. Narayana Kiran
Efficient Data Transmission by Introducing Stuffing Bits in HUFFMAN Coding Technique
G. S. L. Alekhya, M. S. S. Bhargav, A. Narayana Kiran
In recent years, image and video encoding has become more popular in network access. The rapid development in wired and wireless digital communication has made the extensive use of the text data. However, there are few researches focusing on encoding data and memory usage. The basic characteristics of text data like transmission rate, bandwidth, redundancy, bulk capacity and co-relation among text data makes basic compression algorithms mandatory. Therefore this paper considers the problem of memory usage and encoding scheme to provide low bit rate transmission based on HUFFMAN coding. As for n bit being transmitted it requires 2n memory stack for further increase in the data bits it requires 2n+1 memory stack which is wide waste of memory if there presents redundancy bits. Image transmission has large repeated sequences at some places which can be considered as redundant. The proposed method uses stuffing bits in order to provide high speed and low cost transmission
As fire is the test of gold, being patient is the test of men, so is the testing is the test of assessing the quality of the product!!!” With the development of Fourth generation languages (4GL), the proportion of time devoted to testing has been increased and is truly effective means. Testing technique research leads to the destination of practical testing methods and tools. Progress toward this destination requires fundamental research, and the creation, refinement, extension, and popularization of better methods. The methodology for the paper is case study of our college (Sophia Girls’ College) Office Automation Software. Our study focuses on the state of the art in testing techniques, as well as the latest techniques which representing the future direction of this area.
Implementation on Secure Routing Method for Detecting False Reports and Gray-hole Attacks along with Elliptic Curve Cryptography in Wireless Sensor Network
Ms. Sneha M. Sakharkar , Prof. R. S. Mangrulkar
Wireless Sensor Networks (WSNs) are used in many applications in military, environmental, and health-related areas. These applications often include the monitoring of sensitive information such as enemy movement on the battlefield or the location of personnel in a building. Security is important in WSNs. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the use of insecure wireless communication channels. These constraints make security in WSNs a challenge. In this paper, we explore security issue in WSN. First, the constraints, security requirements and attacks with their corresponding countermeasures in WSNs are implemented. Individual sensor nodes are subject to compromised security. An adversary can inject false reports into the networks via compromised nodes. Furthermore, an adversary can create a Gray hole by compromised nodes. If these two kinds of attacks occur simultaneously in a network, some of the existing methods fail to defend against those attacks. The Ad-hoc On Demand Distance (AODV) Vector scheme for detecting Gray-Hole attack and Statistical En-Route Filtering is used for detecting false report. For increasing security level, the Elliptic Curve Cryptography (ECC) algorithm is used. Simulations results obtain so far reduces energy consumption and also provide greater network security to some extent.
Mehebub Alam, SK Mohammad Yasin, Mandela Gain, Saifuddin Mondal
Renewable Energy Sources (RES): An Overview with Indian Context
Mehebub Alam, SK Mohammad Yasin, Mandela Gain, Saifuddin Mondal
Nowadays Renewable Energy Sources (RES) play an important role in electricity market as the changing climate is placing our planet in peril .So, there is an urgent need for transition from existing fossil fuel based energy system to one based on Renewable Energy Sources(RES) to decrease dependence on depleting reserves of fossil fuels with an objective to assess how Sustainable Development is possible. This paper presents an overview of various renewable energy sources such as solar power, wind power, small hydro power(SHP), Biomass Power(BP), Geothermal Power(GP), Tidal Power(TP), Ocean Thermal Energy Conversion(OTEC), hydrogen fuel cell etc .This paper comprehensively elucidates why we are going towards RES ,their economic, social and environmental impact, challenges associated with RES and also suggests some recommendations in order to promote RES to ensure Sustainable Development.
Parallel Prefix Algorithm for OTIS-HHC Architecture
Abdul Hannan Akhtar , Keny Thomas Lucas
The OTIS (Optical Transpose Interconnection System) has become one of the popular models for developing parallel algorithms solving various computation and communication intensive problems. Various real life problems including job scheduling, knapsack, loop optimization, evaluation of polynomials, solutions of linear equations, and polynomial interpolation depend on the time complexity of prefix computation for the efficiency for their respective solutions. In this paper, we have proposed an algorithm for parallel prefix computation on OTIS-Hyper Hexa-cell. In this architecture, the time complexity of the algorithm for n2 data elements is O(n) electronic moves and O(n) OTIS moves.
Investigation of Water Balance at Catchment Scale using MIKE-SHE
Asadusjjaman Suman , Farnaz Akther
The paper presents water balance of Karup catchment, Denmark using integrated catchment modelling tool MIKE SHE. In the present study, water balance in saturated and un-saturated zone was investigated. Beside this, by changing land use water balance is simulated for Karup catchment. Unsaturated zone water balance is characterized by returning 48% water to the atmosphere as evapotranspiration, 49% as percolation and remaining 3% as un-saturated zone storage change. On the other hand, saturated zone water balance is characterized by flowing 28% water to the river as base flow, 50% as drain to river, 20% as saturated zone storage change and rest of are capillary rise and model error. Model simulation shows subsurface storage change was higher during November to February of each year. Beside this, model shows 1982 was quite dry year with low saturated zone storage.
Water balance in Karup catchment will be changed substantially if land use changed from forest and wetland to agricultural use. Model shows, the infiltration will be increased from 49% to 51% which can partly justified by loose soil due to agricultural practice. The storage in the saturated zone will be increased from 20% to 25% and drain to the river will be increased from 50% to 63% consequence of more infiltration. However, subsequently base flow to river will be decreased from 28% to 11%. For proper planning and better management of crops in catchment scale it is worth to have the knowledge about catchment scale water balance. Similar approach can be applied in other catchment to investigate water balance in catchment scale.
Comparison of Selective Harmonic Elimination And Space Vector PWM for Common-Mode Voltage Reduction in Three-Level Neutral-Point-Clamped Inverters for Variable Speed Induction Drives
Gangadhara Swamy, Nomula Ganesh..
This paper proposes a hybrid selective harmonic elimination pulsewidth modulation (SHEPWM) scheme for common mode voltage reduction in three-level neutral-point-clamped inverter-based induction motor drives. The scheme uses the conventional SHEPWM (C-SHEPWM) to control the inverter at high frequency (≥ 0.9 motor rated frequency) and uses the modified SHEPWM (M-SHEPWM) to control the inverter at low frequency. It also uses a scheme to ensure the smooth transition between the two SHEPWM schemes. As a result, at high frequency, the C-SHEPWM provides the required high modulation index for the motor, while at low frequency, when a passive filter is less effective for common-mode voltage reduction, the M-SHEPWM is used to suppress the common-mode voltage. Experimental results show that the proposed hybrid SHEPWM scheme could meet the modulation index need of the motor and reduce the common-mode voltage in the drive, and the two SHEPWM schemes could transition smoothly
Controlled Single Switch Step down AC/DC Converter without Transformer
Arukonda Sathish , T.Sarala.
This paper presents a transformer less ac/dc converter which can be used in voltages between 90- 230 Vrms. Instead of a transformer, this topology consists of a buck dc/dc converter and a buck boost dc/dc converter. By the absence of transformer, reduce the complexity of converter and it is cost effective. Buck dc/dc converter keeps o/p voltage below the line voltage; limit the leakage current. By controlling the circuit with feedback, we can increasing the efficiency and reduce total harmonic distortion. Output voltage is 40 V with THD 12.36%. And output current is near 4 A. For further modification a feedback PI controller is used. After using PI controller THD is reduced to 6.231%.Thus using controlled circuit harmonic content is reduced and efficiency is improved. Working of the proposed circuit and verification by simulation results are discussed in this paper. MATLAB Simulation is done.
A Review Paper on Data Embedding in Scrambled Digital Video for Data Security & Authentication
Jamna Kaur, Rachna Rajput
In the recent years with the development of internet technologies, video technologies have been broadly used in TV, communication and multimedia, So security is required on video data. A technique for embedding data in scrambled AVI video is described. The embedding technique is applied to the video sequence jointly with the video scrambling algorithm. The scrambling operation together with the data embedding process are performed prior to AVI encoding, and the scrambled and data-embedded video is AVI encoded with a minimal increase in the AVI bit rate. In this study a data embedding in scrambled video for the security and authentication of data.
Resource Allocation in Cloud Computing with General Classification Time and Exponential Service (G/M/s)
R.Murugesan, C.Elango, S.Kannan
In this article we considered a Cloud Computing Network (CCN) with four nodes, classifier, SaaS, PaaS and IaaS. The classifier node serve as agent for the Service Level Agreement (SLA). It is a routing server which takes a random time which is independent identically and distributed. The other service stations took an exponentially distributed service time. Thus the CCN became a Network of G/M/s queues. The G/M/s type queue is justified because the arrival of service request to CCNs are in general not follow Poisson Process System perform measures are obtained to compute the total expected cost for the CCN.
Dhanalakshmi.D, IEEE Member, Dr.J.KomalaLakshmi IEEE Member
A Survey on Data Mining Research Trends
Dhanalakshmi.D, IEEE Member, Dr.J.KomalaLakshmi IEEE Member
Presently, a very large amount of data stored in databases is increasing at a tremendous speed. This growing need gives a view for a new research field called Knowledge Discovery in Databases (KDD) or Data Mining, which attract attention from researchers in from various fields which includes Database Design, Statistics, Pattern Recognition, Machine Learning, and Data Visualization et,. In this survey approximately 40 research papers were collected concerning various fields in data mining and discussed each and categorized them under the few areas and the trends was interpreted based on the area of research and applications.
Design Recovery of Student Information Legacy System
Bello AlhajiBuhari, Abba Almu
Reverse engineering for software is the process of analyzing a program in an effort to create a representation of the program at a higher level of abstraction than source code. Reverse engineering is a process of design recovery. Reverse engineering tools extract data, architectural, and procedural design information from an existing program. This paper explores the application of reverse engineering in recovering the design of a legacy student information system developed using Dbase V atUsmanuDanfodiyo University Sokoto using UML based approach. Use case model is used in recovering the design specifications (i.e., functionalities)of the student information system. In addition,object oriented design model for the system is proposed using class diagramso that the system can be implemented using object oriented programming.
An Efficient Design of Parallel Pipelined FFT Architecture
Serin Sera Paul, Simy M Baby
This paper presents a new parallel pipelined architecture to compute Discrete Fourier Transform (DFT) using FFT architecture. This particular architecture uses folding transformation technique as well as register minimization technique for the design of FFT architecture. Novel FFT architectures for the computation of complex and real valued signals are derived. Pipelining is used to reduce the power consumption. Parallel processing and pipelining exploits concurrency. Parallel processing also aids to the reduction of power consumption by reducing the supply voltage. The power consumption is reduced very effectively using the parallel architecture. This paper also includes various techniques to reduce the computation time and power using different types of multipliers.
Performance Analysis of Image Compression Using DWT And WPT
V.Priya, Dr.B.Ananthi
With the increasing growth of technology and the entrance into the digital age, one has to handle a vast amount of information every time which often presents difficulties. So, the digital information must be stored and retrieved in an efficient and effective manner, in order for it to be put to practical use. Wavelets provide a mathematical way of encoding information in such a way that it is layered according to level of detail. This layering facilitates approximations at various intermediate stages. These approximations can be stored using a lot less space than the original data. This paper aims at the analysis on image compression technique using Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT) with Set Partitioning in Hierarchical Tree (SPIHT). Finally a performance comparison is made between the techniques based on different parameters like Peak Signal to Noise Ratio (PSNR), Compression Ratio (CR), Mean Square Error (MSE) and Root Mean Square Error (RMSE).
Semantic Search Based Feature Subset Selection for Multi Dimensional Data
M. Srinu, K. Aruna Bhaskar
Cluster analysis is one of the prominent unsupervised learning techniques widely used to categorize the data items based on their similarity. Mainly off-line and online analysis through clusters is more attractive area of research. But, high dimensional big data analysis is always introducing a new dimension in the area of data mining. We have different variable selection methods for clustering of data like density based, model based and criterion based variable selection methods. Because high dimensional cluster analysis is giving less accurate results and high processing time when considering maximum dimensions. To overcome these issues dimensionality reduction techniques have been introduced. Here, a million dollar questions are, which dimensions are to be considered? , what type of measures have to be introduced? And how to evaluate the cluster quality based on those dimensions and measures? Proposed approach effectively answers these questions by introducing Ensemble feature subset selection measure along with Extend leader follower algorithm to justify the proposal with experimental evaluations.
A Novel Approach for Quality Evaluation of Digital Images By Auto Regressive Approach Based On Internal Generative Mechanism
D. Rihana Bhanu , Trupthi gadhale (Ph.D)
The main aim of Objective image quality assessment (IQA) is to evaluate image quality consistently with human perception. We have different types of perceptual IQA metrics but they cannot accurately represents the degradations from different types of distortions, e.g., existing structural similarity metrics perform well on content dependent distortions and gives the better peak signal-to-noise ratio (PSNR) but it is not well on content-independent distortions. In this paper, we integrate the merits of the existing IQA metrics with the guide of the recently revealed internal generative mechanism (IGM). The IGM indicates that the human visual system actively predicts sensory information and tries to avoid residual uncertainty for image perception and understanding. Motivated by the IGM theory, here we assume an autoregressive prediction algorithm to decompose an input scene into two portions, the predicted portion with the predicted visual content and the disorderly portion with the residual content. Distortions on the predicted portion causes to degrade the primary visual information, and structural similarity procedures are employed to measure its degradation; distortions on the disorderly portion mainly change the uncertain information and the PNSR is employed for it. Based on the noise energy deployment on the two portions, finally we mix the two evaluation results to acquire the overall quality score. Simulation results show better performance comparable with the state-of-the-art quality metrics.
A Survey: Gene Selection Methods VIA Spectral Biclustering
Dr.V.Anuradha , P.Ramya
Gene selection is an important issue in microarray data processing. Microarray gene expression data usually consists of a large amount of genes. Spectral Bi-clustering is used for the selection of publically available datasets. The existing work semi unsupervised gene selection method finds much smaller and informative gene subsets without class information a priori. It uses gene ranking and gene combination selection methods of semi unsupervised gene selection where the gene combinations are selected based on the similarity between genes. The time efficiency in this method is very high. Compared to the previous work, our method can make accurate predictions with smaller gene subsets and able to identify the cancer in a single or two gene combinations. In this paper, we study a new and efficient semi-unsupervised gene selection method which results in much smaller gene subsets without prior subtype knowledge. Also it reduces the number of genes combinations.
Multipliers play a significant part in the DSP architecture. Truncation helps in the reduction of power consumption by disabling a portion of the partial product. In this paper different multipliers are made to truncate the partial products variably using a control bit and then compared for power and delay. The comparison results show that the Dadda multiplier shows a small improvement in power and Baugh Wooley is better in terms of delay.
Comparative Study of Hydrogen Adsorption on Alkali Metal Assisted Carbon-Nano Structured Materials
Darshan Habale , Rita A. Gharde
Using first-principles density functional theory, we have studied the hydrogen storage capacity of alkali metal decorated graphene and carbon nanotubes. Due to curve nature of nanotubes, it shows higher capacity of storing hydrogen than the graphene. We also found that the sodium decorated nano-structure adsorbs more hydrogen molecules than the lithium and potassium decorated systems. The charge transfer from metal to the nanotubes is responsible for the higher hydrogen uptake. The gravimetric density of hydrogen for the alkali metal assisted carbon nanotubes is calculated to be 9.2 wt% to 11.2 wt %.
Internet traffic classification using Hybrid Aggregated classifier and Neural Network
Ms. G. Rubadevi, Mrs. R. Amsaveni
Internet traffic classification is a fundamental technology for modern network security such as quality of service (QoS) control. It is useful to tackle a number of network security problems including lawful interception and intrusion detection. There is an increasing demand on the development of modern traffic classification techniques due to the development of different application. In this work, Internet traffic is carried out by using the supervised classification techniques namely the Neural Network such as Multilayer perceptron (MLP) and Radial base function (RBF) and Hybrid Aggregated Classifier. The task involved in this work is IP packet capturing, Preprocessing, Flow container construction (If the flows observed in a certain period of time share the same destination IP, port, and transport layer protocol, they are determined as correlated flows and modeled as “Flow Container”), separating low density and high density flow, feature extraction and classification. The accuracy of the classifier Hybrid aggregated classification is better than Neural Network.
Efficient and Secure Node Recovery in Wireless Sensor and Actor Network Using Minimal Topology Changes
Kokilapriya , G.Sophia Reena
In wireless sensor-actor networks, sensors probe their surroundings and send their data to actor nodes. Actors collaboratively react to achieve predefined application mi. Since actors have to synchronize their operation, it is necessary to hold a highly connected network topology all the time. Moreover, the length of the inter-actor connection paths may be constrained to meet latency requirements. Failure of an actor may cause the network to separate into disjoint blocks and break such connectivity. One of the effective restoration methodologies is to autonomously reposition a subset of the actor nodes to restore connectivity. Contemporary restoration schemes either impose high node relocation over-head or extend some of the inter-actor data paths. This paper overcomes these drawbacks and presents a Least-Disruptive topology Repair (LeDiR) algorithm. LeDiR relies upon the local view of a node about the network to devise a recovery plan that relocates minimum number of nodes and ensures that no path between any pair of nodes is expanded. The performance of LeDiR is examined mathematically and validated through extensive simulation experiments.
Co-Channel Speech Separation by Cochlear Filtering And Binary Masking.
Ligin George, Lekshmi M.S
Human speech undergoes much interference in a medium. These distortions in the speech signal may leads many disadvantageous in the hearing aid application, speech separation and synthesis. So an effective application can make right turn in field of speech separation. The development of CASA (Computational Auditory Scene Analysis) is trying to reduce these defects and improve the speech applications. The possibility of separating the dominant speech from a mixture and amplifying that may be used in the hearing aid applications. In this paper, we are introducing cochlear design of filters as the channels. Segregation and the grouping are the main methods implemented in this paper. Pitch determination is done based on the response of the cochlea model and combining them using the periodicity detection. Frequency domain analysis done based on the STFT (Short Time Fourier Transform) method. Separation of the dominant speech is done by masking. This method is computationally less complex and we can obtain the better SNR (Signal to Noise Ratio) compare to other related methods available in this literature.
The process of Single channel speech separation is done to efficiently separate the required speech signals from a mixture. In this research paper we used WPST (Wavelet Packet Based Sub-band Transform) to offer a multi resolution property of wavelet transform to increase the efficiency by reducing the number of coefficients required in each sub-band vector to replace the previously used SPWT (Sub-band perceptually weighted transformation).The new approach improves the separation quality and it results lowest error bound in terms of objective measurements such as Perceptual Evaluation of Speech Quality (PESQ)),segmented SNR in comparison with SPWT based features.
Recommendation algorithms are best known for their use on e-commerce web sites, where they are used to create additional business opportunities by suggesting additional products and services. Generally, the recommendation are created by collating feedback from various users who have purchased the same or different products, as well as comparing the features of the products themselves. While recommendations have been most successful in domains like retail, due the availability of large volume of feedback, it is challenging to implement in domains where there is no such prior information or the information available is very small in volume. This paper presents how a hybrid recommender system was leveraged in insurance domain, by integrating an attribute based recommendation system with preference-based recommendation system.
Cloud computing has become part day today life. There are large numbers of vendors providing different cloud offerings. With the evolution of mobile devices, mobile cloud computing has drawn attention. Even though cloud security is a well thought aspect, there is need to look at cloud security from a mobile device perspective. In this paper we have analyzed different research happenings in this area and presented future research needs.
Anvesh Nalluri, K Shashank Goud, Anirudh S, Davuluri Sai Teja. GUIDE: Chandu DS
Performance Analysis of A 3*2 MIMO System For Fading Channel
Anvesh Nalluri, K Shashank Goud, Anirudh S, Davuluri Sai Teja. GUIDE: Chandu DS
This paper studies a multiple-input multiple-output (MIMO) wireless broadcast system along with its advantages and performance. Graphical representation and technical comparison between different input and output systems and other simulation results are presented.
Survey on User Behavioral Search using the Auxiliary Information Mining
Pooja Awandkar, Amit Pimpalkar
Many text mining applications contains side-information along with the text documents. Many web documents consist of meta-data with them which correspond to various different kinds of attributes such as the origin or other information related to the origin of the document. Data such as location, possession or even temporal information may prove to be informative for mining purposes in other cases. Such side-information may contain a huge amount of information. This huge amount of information may be used for performing clustering.
However, it may be difficult to compute the importance of this side-information, especially when some of the information from it is noisy. When the information is noisy it can be a risky approach for performing mining process along with the side information, because it can actually worsen the quality of mining process. This is why we need a principled way for performing the mining process, so that the advantages from using this side information can be maximized. We will do mining and clustering using the side information and iterative clustering and clusters will be formed. From these clusters we will search the desired keyword using user behavior, localization, personalization.
CBIR Approach Based On Combined HSV, Auto Correlogram, Color Moments and Gabor Wavelet
Amit Singla, Meenakshi Garg
Content based image Retrieval is an active research field in past decades. Against the traditional system where the images are retrieved based on the keyword search, CBIR system retrieve the images based on the visual content. The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods, three were based on analysis of color feature and other one based on analysis texture feature using gabor wavelet coefficients of an image.
In the last few decades, many researchers have been devoted to develop new techniques for image compression Digitized images have replaced analog images as digital photographs in many different fields. In their unrefined form, digital images have need of a remarkable memory capacity for storage and large amount of bandwidth for transmission.. More recently, wavelets have become a cutting edge technology for compressing the images by extracting only the visible elements. Our work presents implements the decomposition based Wavelet technique with it types such as Coiflets filter, Symlet filters and Daubechies filter and also neural network based Gradient technique been implemented. Also, a non-uniform threshold technique based on average intensity values of pixels in each sub band has been proposed to remove the insignificant wavelet coefficients in the transformed image. Experimental results are obtained to compare the Neural network based Gradient approach better to compress the image.
Implementation of a Zero-Voltage-Switching and Zero-Current-Switching Interleaved Boost and Buck Converter
Banoth Govind Nayak , Harinath saggu
A novel interleaved boost and buck converter with zero-voltage switching (ZVS) and zero-current switching (ZCS) characteristic is proposed in this paper. By using the interleaved approach, this topology not only decreases the current stress of the main circuit device but also reduces the ripple of the input current and output voltage. Moreover, by establishing the common soft-switching module, the soft-switching interleaved converter can greatly reduce the size and cost. The main switches can achieve the characteristics of ZVS and ZCS simultaneously to reduce the switching loss and improve the efficiency with a wide range of load. This topology has two operational conditions depending on the situation of the duty cycle. The operational principle, theoretical analysis, and design method of the proposed converter are presented. Finally, simulations results are used to verify the feasibility and exactness of the proposed converter.
Dr. Yogesh Bhomia, Dr. S.V.A.V. Prasad, Pradeep Kumar
Designing of Combinational Fractal Microstrip Patch Antenna using Iteration Methods
Dr. Yogesh Bhomia, Dr. S.V.A.V. Prasad, Pradeep Kumar
This paper presents a design of microstrip patch antenna combining Crown and Sierpienksi fractal slots by cutting different slots on rectangular microstrip antenna and experimentally studied on IE3D software. This design is achieved by cutting multi shapes in square pattern combining with Crown & Sierpienksi fractal slots & placing a microstrip line feed. This design has been studied in 3 iterations. The radiation pattern of the proposed fractal shaped antennas maintained because of the self similarity and centro-symmetry of the fractal shapes. With fractal shapes patch antenna is designed on a FR4 substrate of thickness 1.524mm and relative permittivity of 4.4 and mounted above the ground plane at a height of 6 mm. Details of the measured and simulated results of the individual iterations are presented & discussed.
Data mining is the process of extracting patterns from data. Data mining is becoming an increasingly important tool to transform this data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. Aim is to make such an application which has lots of inbuilt features and functions, so that many tasks can be performed on same platform, so as to save time, and also enable in curbing cost with the use of technology. At the end our goal is to come up with a good system, well-computerized and embedded with the latest technology in order to give a better service to customers, give a competitive edge to the business.
Contentious News Article Categorization by Identifying Opponents
Pradip Patil, Prof. Srikant Lade
With the use of mining in the field of the text researchers get new era for working, which discover knowledge from the text documents. One of the application of text mining is to categorize the opponent from the contentious news article is focus in this paper. Here as per the different opponent present in the article are identify which is base on the dictionary and frequency of the opponent in the article then all the opponent are also classify into two main party where each opponenet relation is find with the other is based on the words they use in the sentence.
To evaluate this work articles from different debate category has been passed and got results that is very highly acceptable.
