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ijmcs  IJMCS

National Conference on (Advances in Modern Computing and Application Trends) Organised By Acharya Institute of Technology Bangalore, India

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    Volume-3 Issue-3(October 2015)
    Title: Analysis of Network Performance in Heterogeneous Network over Different AQMS
    Authors: Shallu Bedi and Mr. Gagangeet S. Aujla
    Abstract: A MANET is a single network including Internet, may be connected to a larger network. All nodes free of every other node can communicate with each other and in this type of network nodes are independent. An example of a P2P network and multi - hop network are connected. The heterogeneous nature of the networks can sometimes create problem in the traffic management on the backbone links. The multimedia traffic and graphics mostly flows on UDP and traffic like HTTPS and link management’s flows on TCP. In order to analyze the traffic management, we must understand the behavior of various Active Queue Management Techniques on different traffic classes via TCP and UDP. In this thesis, a multi class network is analyzed for both TCP and UDP traffic classes for various network performance parameters like Throughput, Packet loss ratio and Average end to end delay for various networks Active Queue Management Techniques. In the thesis four Active Management Techniques are tested for both TCP and UDP traffic classes. Most of the fast multimedia and graphics traffic is based on UDP. Therefore analysis of this type of traffic class of supremely important. In this paper, a concise result analysis of detail findings is represented of Drop Tail, SFQ, RED, and REM under varying network conditions. The throughput of the network in calculated by varying the network conditions like bandwidth, delay, channel error rate. In case of TCP it has been observed SFQ was intended to perform best in as it employs Fair Queuing Algorithms for the handling of flow of packets on link with simultaneous sessions. On the other hand in UDP Drop tail, RED and REM performed best in different scenarios as their Queue management involves only the link state and the congestion and not on the traffic flow.
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    Title: Mitigation of High Rate Shrew DDOS Attack
    Authors: Kanika Minhas, Er.Amanpreet Kaur and Dr. Dheerendera Singh
    Abstract: Denial of Service attacks is frequently presenting an increasing threat to the global inter-networking infrastructure in networking area and scenario. The algorithm for TCP congestion control is highly efficient for the various networking areas and operations as well its internal assumption of end-system cooperation results are well prone to attack by high-rate flows. A Shrew attack uses the concept of a low-rate burst which is carefully designed to use the TCP’s retransmission timeout mechanism in an unfair way and can affect the bandwidth of a TCP flow in a smooth manner without coming into appearance as an intruder. A Shrew attack has further classifications such as a low rate shrew attack or an high rate shrew attack. A high rated shrew attack uses the concept of timely sending high rate packet stream in low frequency. Such attack can affect the performance of a network to a large extent.
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    Title: Recognition of the image by using plant diseases ontology in image processing
    Authors: Er. Nikita Rishi and Er. Jagbir Singh Gill
    Abstract: Plant disease is condition caused by infectious organisms or environmental factor. Plant plays a very decisive role in the ecological balance and is a prerequisite to life. There are various environmental factors that have cause various plant diseases beside the diseases caused due to infection causing micro-organisms. Hence there is an urgency to determine the disease for the betterment of agriculture. In this paper, image segmentation, feature extraction, PCA (Principal Component Analysis) and adaptive K-means clustering have been examined for the identification of heterogeneous plant diseases.
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    Title: A Survey on Anomaly Detection Behaviour with Kernel Mapping and Inclusion
    Authors: Dr R.Umagandhi and K.Gomathi
    Abstract: Anomaly detection is a significant problem that has been researched within various research areas and application domains. Many anomaly detection methods have been particularly examined for certain application domains, as others are more standard. This survey papers is describes an anomaly detection technique for unsupervised data sets accurately reduce the data from a kernel Eigen space lacking performing a batch re-computation. For each anomaly behavior activities is to identify the key factors, which are used by the methods to differentiate between normal and abnormal actions. This survey paper provides a best and brief understanding of the techniques belonging to each anomaly and kernel mapping category. Further, for each grouping, to identify the improvements and drawbacks of the techniques in that category. It also provides a discussion on the computational complexity of the techniques since it is an important issue in real application domains hope that this survey will provide a good understanding of the many directions in which research has been done on this topic.
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    Title: Improved Routing Protocol Using Hybrid Ant Colony Optimization and Particle Swarm Optimization
    Authors: Neelam Kumari and Arpinder Singh Sandhu
    Abstract: The principle problem of QoS routing would be to setup a new multicast hierarchy that may meet specific QoS concern. In order to lessen the constraints of the earlier work a whole new improved approach is proposed with this exertion. Inside of proposed technique the challenge of multi-cast sapling is removed using clustering primarily based technique. For starters multi-radio along with multichannel primarily based clustering will be deployed along with these bunch head have the effect of the multicasting. It's going to diminish the general energy consumption of nodes along with complexity of intelligent algorithms. The way will end up being evaluated based upon the ish colony marketing. Thus they have produced better results in comparison with other strategies.
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    Title: A Comprehensive Study on MCC (Mobile Cloud Computing) Architecture, Challenges and Benefits
    Authors: Dr. Mukesh Chandra Negi
    Abstract: Cloud computing is a technique where based on cloud delivery model , your complete or partial IT infrastructure and applications are managed by some third party cloud service provider or you just have to subscribe for the services you wanted to use if it’s completely managed and own by the provider. It’s helpful especially where you have a requirement of high efficient resources like memory, processor, CPU, storage etc with costing constraints. Seeing the growth of smart mobile devices in last few years, it has been realized to identified and develop a rich application platform for mobile devices to gain the benefits of cloud computing in mobile devices. Mobile Cloud Computing (MCC) concept has been developed realizing the same and it’s a great concept and platform to leverage the benefits of cloud computing with mobile devices [1] [2]. It’s a concept where some thin mobile client applications developed for the mobile devices and all backend processing workload offloaded to the clod environment, which execute the user requirements and send back results to the user mobile device thin application. In this paper I am going to explain basic and high level architecture, challenges and benefits of mobile cloud computing concept and technology.
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    Title: A Study of Code Smells in Software Versioning System Using Datamining Techniques
    Authors: Dr.R.Beena and Dithy MD
    Abstract: Code Smell is System used to identify the poor design and implementation choices which lead to deeper problem in the code repositories. Code smell symptom may hinders code comprehensions, many approaches has proposed to perform this action but they still might not be adequate for detecting many of the smells based on Principle constraints and quality Measure . The present study is discussed with the Detection System and prevention system models to detect the code smells based on Structural and historical information in the instance of the code smell techniques like divergent changes, shotgun surgery, parallel inheritance, blob and feature envy. Prevention technique has considered mandatory for improving code behaviour as agile development become popular among developer, hence prevention of the code smells has to be developed using refactoring technique. Experimental results has conducted and evaluated against competitive approaches by using data mining metrics like precision and recall.
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    Title: Review Paper on Facebook Drones Technique
    Authors: Ankita Jiyani
    Abstract: Today, human being can’t think of surviving without internet as it becomes the inevitable part of their life where each and everything in this world is connected together with the help of internet. Connectivity is one of the fundamental challenges to achieve this, and for the same continuous efforts have been made and nowadays efforts have been made in the direction of sky or (towards the sky). As number of the users accessing internet keeps on increasing day by day, and for the same facebook makes an initiative in form of DRONES. This paper focuses on the mechanism which is a level ahead of the previous ones for providing internet services and the initiative taken by project handled by facebook and Internet.org in the form of “FACEBOOK DRONES”. Aiming to provide internet service to the areas of the world where humans have no or little internet access. It is a technique of providing internet services through huge drones which has a wingspan of a Boeing 737 weighing less than a car will operate at the height of 60,000 to 90,000 feet , in the air ,and can stay airborne for three months while offering the internet speeds of 10 gigabits per second.
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    Title: TSM: TWU and Suffix-based High Utility Itemset Mining Algorithm
    Authors: Sonam Panwar and Ajay Jangra
    Abstract: Utility mining considers individual items different according to their respective utilities and mines items with high utilities. This mining task is commonly known as High Utility Itemset (HUI) mining.To do so, most available algorithms first generate large number of candidates among which many are eventually found to be low utility itemsets. Moreover, a large amount of time is consumed in join operations needed to generate larger itemsets from smaller ones. In this paper, we present a fast Hash-Map based algorithm named TSM that efficiently prunes low-utility itemsets using co-occurrence information. The overall impact is a considerable reduction in join operations and hence faster execution.
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    Title:A Review of Novel Hybrid Image Forgery Detection Model
    Authors:Samiksha Singla and Harpreet Tiwana
    Abstract: The image forgery is the term given to the copying of the image content after editing the digital image data in order to remove the similarity with the original image. The image forgery cause monetary losses to the graphic designer professionals or the digital media companies. Latter organizations run their business from the graphic designing etc, which is severely hurt by the image forgery. The image forgery detection is the branch of digital image processing to detect the image forgery in the image content for the purpose of copyright protection. In this paper, we are proposing the image forgery detection model for the images using the hybrid algorithm, which uses the combination of the SURF, FREAK, SVM and GREEDY algorithms. The proposed model is designed to work in the double layered model for the forgery detection and relies upon the greedy algorithm for the final result generation. The proposed model is expected to outperform the existing image forgery detection models. The proposed model results would be employed in the form of accuracy, precision and recall. The statistical analysis would be performed over the obtained results in order to analyze the performance of the proposed model..
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    Title: Greedy Routing Transmission Control Protocol (GRTCP) In Wireless Sensor Networks (WSNS)
    Authors: S.Sangeetha and S.Rajesh Singh
    Abstract: In this paper the solution to the void problem is taken up as the issue. This situation which exists in the currently existing greedy routing algorithms has been studied for the wireless sensor networks. The GAR protocol is a new protocol proposed here to guarantee the delivery of packets and excessive consumption of control overheads is resolved. This protocol is a combination of the GF algorithm and the RUT scheme. To enhance this protocol’s functionality we go in for three mechanisms that can also be implemented in this project. The hop count reduction (HCR) scheme is utilized as a short-cutting technique to reduce the routing hops by listening to the neighbour’s traffic, the intersection navigation (IN) mechanism is proposed to obtain the best rolling direction for boundary traversal with the adoption of shortest path criterion. These three schemes are incorporated within the GAR protocol to further enhance the routing performance with reduced communication overhead. The proofs of correctness for the GAR scheme are also given in this paper.
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    Title: Comparative analysis of different image restoration techniques using different image formats
    Authors: Kanupriya and Silky Narang
    Abstract:Image Restoration is the process of restoring the image from some degradation and improve its quality. Images are produced to collect the useful information. But the images get degraded or blurred while capturing because of the presence of some noise or other reasons. These images can be restored by using different restoration techniques. This study aims to restore the image which is degraded by some known and unknown degraded function. The restoration techniques like Deconvolution using Lucy Richardson Algorithm (DLR), Deconvolution using Wiener Filter (DWF), Deconvolution using Regularized Filter (DRF) and Blind Image Deconvolution Algorithm (BID) are implemented over two different images formats i.e. .jpg and .tif. Their results are compared on the basis of three metrics like PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), RMSE (Root Mean Square Error).
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    Title: Appraisal of Robust Face-Name Graph Matching for Different Movie Frames
    Authors: M.Nandhini and C.Sathiyakumar
    Abstract: Image Processing is a technique to improve the RAW-receive images from cameras/sensors on satellites, probes and aircraft or images in normal day-to-day life for different applications. Character identification of the film is a challenge, the problem of the large differences in appearance. The existing system includes clustering surfaces with K-where the number of clusters as the number of different speakers. Co-occurrence names in the script and face-clusters in Video provides you with the appropriate surface graph and graph name it changes the traditional global matching framework with ordinal diagrams for robust representation and the introduction of a ECGM-based graph Matching Method. The affinity Graph matching is used in the traditional global interval measures the co-occurrence relationship between characters. In this study proposes an integrative face-name Graph matching based framework for robust film character detection. In this proposed scheme two schemes are taken into account. There are many connections, as well as the differences between them. About the ports, the two proposed rules both fit into the general mapping based category, in which the external script resources are used. Explore this study to improve the robustness, the ordinal graph is turned on for the face and the name Graphic illustration and a novel graph matching algorithm called Error Correcting Graph Matching (ECGM) is introduced.
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    Title: Implementation of a Crossover Operator in Solving Travelling Salesman Problem Using Genetic Algorithm
    Authors:Rishu Gupta
    Abstract: The travelling salesman problem (TSP) is an NP-hard problem in combinatorial optimization, important in operations research. It asks the following question: Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city? It is a special case of Traveling Purchaser Problem. The TSP has several applications such as planning and logistics. In these applications, the concept city represents customers and the concept of distance represents travelling times or cost. In this paper a crossover operator is used in genetic algorithm to solve travelling salesman problem. The crossover operator be Common Sub Path (CSP). The performance of new crossover operator is compared with the traditional crossover operator. The new crossover operator is practically implemented and the result has been taken into due consideration. The results of the experiment justifies that the new operator is better than the traditional crossover operator in Genetic Algorithm.
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    Title: A Survey on Multilingual Ontologies
    Authors: Ravi Lourdusamy and Merlin Florrence Joseph
    Abstract: Ontologies are used in artificial intelligence, biomedical informatics, library science, chemistry and many other subjects. Most of the ontologies are developed in English language which is quite difficult to understand by the different language users. To overcome this defect multilingual ontologies are developed. Most of the multilingual ontologies are developed in English language and translated into desired languages. This article analyzes the features of multilingual ontologies, methods and techniques that are used to create multilingual ontologies. The existing multilingual ontology applications are evaluated by using the proposed set of criteria.
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    Title: A Survey on Privacy Preserving and Malicious Detection of Packet Dropping Attacks in Wireless Ad Hoc Networks
    Authors: Dr S.Mythili and T.Ramjan begam
    Abstract: Privacy-Preserving wireless sensor networks Concepts and Techniques presents state-of-the-art information sharing and data integration methods that take into account privacy and security requirements. Much of the existing work on wireless sensor networks (WSNs) has focused on addressing the packet losses in multi-hop wireless ad hoc network of WSNs. Recently, there have been heightened privacy concerns over the data gathering by and transmitted through WSNs. In a multi-hop wireless ad hoc network, packet drops are attributed to insensitive channel constraints and intentional packet discard by malicious nodes. WSNs provides techniques for a state-of-the art survey of privacy-preserving on packet drops attacks. In particular, two main sources for packet drops are reviewed and the drops are caused by link errors only, or by the combined effect of link errors and malicious drop are to be identified then observing a sequence of packet losses in the network.
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    Title: Security Mechanisms for Mitigating Multiple Blackholes Attack in MANETS
    Authors: Shikha Sharma and Manish Mahajan
    Abstract: Wireless Adhoc networks are decentralized, self-organizing networks capable of forming a communication network without relying on any fixed infrastructure. This type of wireless network requires rapid and automatic establishment of services in the absence of a fixed. Mobile Ad hoc Networks (MANETs) do not have a centralized piece of machinery, which could lead to a single point of failure and the consequent absence of authorization facilities, thus, make the network that much more vulnerable. Security have recently become very important and actively researched topics because of a growing demand to support live streaming audio and video in civilian as well as military applications. Security is the combination of processes, procedures, and systems used to ensure confidentiality, authentication, integrity, availability, access control, and non-repudiation. In this paper, the behavior of multiple black hole attacks and the performance impact of this attack on AODV protocol and its counter measures using IDS AODV and Watchdog AODV scheme is studied. The NS2 network simulator is used for evaluation.
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    Title: Block Based Mean Variation in Total Video for Estimating and Removing Mixed Noise Data Using ANN
    Authors:Mandeep Kaur and Amandeep Kaur
    Abstract: Video denoising is conventional problem in video processing. The purpose of denoising process is to improve the quality of degraded video. The aim of this paper is to remove the mixed Gaussian and Impulse noise from the video as well as preserving the quality and structure of the video signal. For video denoising number of techniques are used. In this paper a new algorithm Block Based Mean Variation using Artificial Neural Network (ANN) has proposed. In which we calculate the mean variation of the blocks and then find a Gaussian patch filter to denoise the video signal. We use the Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index Measurement (SSIM) to measure the performance of this algorithm.
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    Title: A Modified Mean based Particle Algorithm for Object Tracking using Artificial Neural Network
    Authors: Neha Singla and Amandeep Kaur
    Abstract: A considerable amount of research is now a day’s undergoing in the field of Video Surveillance, which is currently one of the most active and promising research topic in the computer vision community. During motion, the surveillance system can detect and track the various moving objects in a video scene using tracking algorithms and also identify them as living and non-living things like humans, animals, vehicles, birds, floating clouds, swaying tree etc. In this paper, a new algorithm named Modified Mean based Particle Algorithm has proposed using Artificial Neural Network (ANN) for Non-blind object tracking in video scenes that requires lesser computational resources, as compared to its needs. Experimental results show that the Object motion in current applied system has correctly classified than the previous approach.
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    Title: Allocation of MR jobs using Genetic Algorithm
    Authors: Anu B Paul and Aswathy R
    Abstract: In today’s Internet era, a report says in each day lots and lots of data is created. This data is obtained from many sources and is known as Bigdata. Hadoop plays an important role in processing and handling big data. It includes MapReduce and HDFS – Hadoop Distributed file system. This framework provides solution for large data nodes by providing distributed environment. To move all input data to a single datacenter before processing the data is expensive. Hence to find an optimized execution path for sequential executions of map reduce jobs on geo-distributed data, we are enhancing our proposed work the G-MR Framework. We analyze possible ways of executing jobs, and propose Genetic algorithm to perform the job efficiently by determining the data centers. The job sequences which are optimized either with respect to execution time or communication cost. Our evaluations show that G-MR is more efficient for improving time and cost for the geo-distributed data sets.
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    Title: Amelioration of Gait Recognition System Using Dimension Diminution Framework
    Authors: Riant Kaur and Heena
    Abstract: In real time, there is an evident threat to security in different organisations. Therefore, there is a need for an efficient identification and recognition system which can help stop unfortunate events from occurring. One such system which can be functional in solving this problem is Gait Recognition system which can identify unique humans by their unique biological instinct that is their fashion of walking; the term coined as GAIT. In this disquisition, work is executed on a database containing home videos captured from a normal mobile video camera in MATLAB software. This treatise has conducted an inclusive perusal with a notable emphasis on using modified hanavan’s model for emulation of four distinctive features which have not been extracted before acting as a basis for identification. The matching and non-matching pixels are disparate as a result of Support Vector Machine acting as a hyperplane between these pixels. The matching and recognition procedure is augmented using K-means algorithm performing efficient cluster analysis and MDA (multi-linear discriminant analysis) dimension diminution framework generating CCR (Correct Classification Rate) and computational time of matching. The proposed algorithm gives ameliorated results as compared to solely using SVM.
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    Title: Hybrid Approach for Multiple Object Tracking: KPM
    Authors: Er Navneet Pal kaur, Dr. Shashi Bhushan and Er. Manish Mahajan
    Abstract: Video object tracking deals with tracking of objects in the video sequence. Tracking can be done by using semi blind or blind technique. This paper discuss the proposed technique for multiple object tracking using semi blind technique .The proposed hybrid technique is the combination of three filters kalman filter, mean shift filter and the particle filter. Performance of system is analyzed in various environments such as normal, noisy, blur and motion. Proposed technique is tested over various parameters time, mean square error, peak signal to noise ratio, frame correlation vs time maximum error per frame, error estimation. The hybrid approach works efficiently under these parameters.
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    Title: Performance Improvement of Particle Swarm Optimization to Solve Large Scale Optimization Problems
    Authors: Shailendra S. Aote, Dr.M.M.Raghuwanshi and Dr.L.G.Malik
    Abstract: With the increasing demands in solving larger dimensional problems, it is necessary to have the algorithm which converges faster as well as more efficient. Though the lot of efforts have been put towards increasing the efficiency of the algorithms, it is difficult to achieve better solutions for large scale optimization problems. This paper presents a new approach of particle swarm optimization with cooperative coevolution. The proposed technique [PSO-LSO] is built on the success of an early CCPSO2 that employs an effective variable grouping technique random grouping. Instead of using simple velocity update equation, the new velocity update equation is used from where the contribution of worst particle is subtracted. A new technique is proposed to deal with stagnation which generates new swarm around the global best particle. Experimental results show that our algorithm performs better as compared to other promising techniques on most of the functions.
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    Title: Identification of Pattern and Feature Unsheathing for Image Retrieval
    Authors: Hemjot and Amitabh Sharma
    Abstract: The dynamic web and automated headways have constrained unending augmentation in the measure of visual information available to clients. This pattern incited the headway of investigation range where recovery of pictures is done through the content of data which got comfortable as CBIR (Content based Image Retrieval). CBIR structures are, all things considered, used as a piece of restorative picture annotation, face acknowledgment frameworks, security systems etc. In this paper we will talk about around an effective framework for recovering pictures speedier since pace and accuracy are imperative and in addition systems to acquire better order of pictures. To vanquish the issue of broad number of components removed which obliges immeasurable measure of memory and handling power we have to construct a mix of effective strategies which best depict the data with satisfactory exactness. Henceforth, we are utilizing dimensionality diminishment calculation LDA for the characterization reason and SURF which is speedy and powerful intrigue point finder.
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    Title: Review of Software Bug Prediction Metrics
    Authors: Anu Singla and Vijay Kumar
    Abstract: Software Testing Consumes major percentage of project cost, so researchers focuses of the “How to minimizes cost of testing in order to minimize the cost of the project”. The Software bug prediction is a method which predicts bugs from historical database. Data mining Techniques are used to predict Software bugs from historical databases. There are number of bug prediction metrics. Bug prediction metrics play the most important role to build a statistical prediction model. Most bug prediction metrics can be categorized into two kinds: code metrics and process metrics.
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    Title: Comparative Study of Color Combination as Design Issue in Various Websites
    Authors: Mubashir Hussain and Jatinder Manhas
    Abstract: Websites are very important means of communication in this current era of information technology. Website can give a competitive edge to any organization only when it meets the needs of the intended users [1]. Different institutions / organizations put lots of efforts to portray complete information on beautifully designed websites. Lot of efforts are given to provide users with all the facilities of the concerned institutions / organizations online through websites, which act as an online agent through which a user can get his work done without physically visiting the organizations. With this the responsibility of the designer and the concerned institutions / organizations increases manifold so that the websites behavior should remain similar when accessed by different sections of users. Authors in this paper developed an online tool using .NET Framework using C# to study color combination as Design issue in various categories of the websites like Government, Commercial, Educational, Social networking and Job portals. The automated tool developed by author function on the basis of the different standards prescribed in W3C guidelines document WCAG 2.0 in guideline 1.4(Distinguishable) [4] and act like a parser and renders the complete code of the website and produces result on the basis of the various types of color combinations used by the web designers in developing various parts of the website and their effects on the different sections of the users that suffer from various color blindness problems. Various groups of user are sensitive to different combinations of colors. While certain users are able to recognize any combination of colors that may cause hindrances to other group of users. The results produced shows that out of the five different categories of websites employed for analysis the Job portal sites follow the minimum of standards as far as color combination parameter is concerned whereas govt. sites show least divergence from the standards. Click Here to Download Pdf
    Title: A Novel Approach of Data Security Using Hybrid Method of k-MM and Crossover in Steganography
    Authors: Amanjot Kaur and Dr. Bikrampal Kaur
    Abstract: Steganography can be defined as the art of invisible communication. Steganography usually occur with the method of concealing any information content to be communicated so that it can remain confidential. The main purpose of the steganography is to provide confidentiality in communication. In image steganography, the security is achieved by embedding data into image and generating a stego image. There are different types of steganography techniques such as LSB (Least Significant Bit), DCT (Discrete Cosine Transform), DWT(Discrete Wavelet Transform) and k- Modulus Method. In this paper, secret information is secured in an image after applying a hybrid technique of k-Modulus Method and a Crossover technique which achieves high security and capacity.
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