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ijmcs  IJMCS

Volume-5 & Issue-5 Published (Acceptance Ratio=27.27%)http://www.ijmcs.info/current_issue

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Volume-5 & Issue-2 Published (Acceptance Ratio=25%)http://www.ijmcs.info/current_issue

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Submit your Paper Last date 20th June 2017 http://www.ijmcs.info/submit_your_paper

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Volume-5 & Issue-1 Published (Acceptance Ratio=28.94%)http://www.ijmcs.info/current_issue

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Volume-4 & Issue-4 Published (Acceptance Ratio=54.02%)http://www.ijmcs.info/current_issue

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Volume-4 & Issue-1 Published (Acceptance Ratio=50%)http://www.ijmcs.info/current_issue

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Volume-3 & Issue-2 Published (Acceptance Ratio=34%)http://www.ijmcs.info/current_issue

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Submit your Paper Last date 10th October 2015 http://www.ijmcs.info/submit_your_paper

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Volume-2 & Issue-6 Published (Acceptance Ratio=69.56%) http://www.ijmcs.info/current_issue

ijmcs  IJMCS October

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ijmcs  IJMCS

Volume-2 & Issue-4 Published (Acceptance Ratio=25%) http://www.ijmcs.info/current_issue

ijmcs  IJMCS

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

  • For More Detail Click Here
  • http://www.acharya.ac.in/Techman_2014.pdf

    Volume-4 Issue-1(February 2016)
    Title: Android Mobile Application Build on Android studio
    Authors: R.Thamizharasi
    Abstract: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. The Google Play app store has been growing at breakneck speed and with almost as many apps as the Apple app store. This, for entrepreneurs and developers, is the chance of a lifetime to make even more money and reach an even broader audience base. This paper gives a complete knowledge of how to develop an application in Android studio.
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    Title: To Examine the Performance of Digital Image Watermarking by Applying DWT, Neural Network and RSA
    Authors: Sujata Nagpal, Shashi Bhushan and Manish Mahajan
    Abstract: Security in multimedia is exceedingly major concern for the internet as a consequence of the easiness of the distribution, duplication and manipulation of the multimedia data. The digital image watermarking is an area of information hiding that hides the essential information in the original data file for fortification from illegal replication as well as distribution of multimedia data which is increasing exponentially day by day. The image watermarking methods will help us to attain artificial intelligence. In current years, numerous digital watermarking methods are presented which are based on Discrete Cosine Transform, Discrete Fourier Transform and Discrete Wavelet Transform. In this paper, we have proposed a novel technique by utilizing Neural Network, Discrete Wavelet Transform and Rivest, Shamir and Adleman encryption for enhancing security in watermarking that is improved in the proposed work. The whole simulation has been taken place in MATLAB environment.
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    Title: A Survey on the Adaptable e-Learning Systems and their Characteristics
    Authors: P. Sivaranjani, J. Agalya, B. Kowsalya, J. Sivasankari and Dr. M. Maria Dominic
    Abstract: Learning is a process of gaining knowledge. Learning is a two stage activity that involves reception of information and processing it. Every learner has his own favoured way of obtaining and dispensing of the information which is known as learning style. E-learning is the use of information and computer technology to make learning involvements in a more automated way. Since each learner is unique and the need of the hour is an adaptable e-learning systems in order to provide a personalization to the learning process. At present the e-learning market is crowded with bountiful adaptable e-learning architectures providing personalization to the learning process. Different architecture employs different methods to provide adaptability and uses different learning style models to serve the learners. So there is a need to identify and consolidate the characteristics exhibited in the popular adaptive e-learning systems that are available in the market. This paper consolidates the characteristics of 19 popular adaptive e-learning systems.
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    Title: A Comparative Study on Natural Inspired Routing Algorithms Based On Optimization Techniques
    Authors: H.Fathima
    Abstract:A new agent-based routing algorithm using optimization techniques is discussed in this paper. The different optimization techniques are Bat, artificial immune systems, PSO, Bacterial Colony Optimization, Gravitational Search Algorithm are the combinations used in the packet delivery between the networks. The routing is a process of carrying the data from source to destination in the network. The outputs of these algorithms are determined by the simulation time and throughput. The experiments are implemented with the NS2 software platform, which is based on the basics of C, C++, and TCL Scripting Language. The results of the algorithm showed that the Gravitational Search Algorithm is much better than the other algorithms in the packet delivery between the networks.
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    Title: Childhood Obesity epidemic analysis using classification algorithms
    Authors: Suguna. M
    Abstract: Obesity is the one of the most serious public health challenges of 21st century globally there are more than one billion overweight adults and it is increasing three fold. In Today’s world people get affected by many diseases where such disease leads to many other diseases. Obesity is such a condition that leads to many diseases. In this paper several data mining classification algorithms are used to detect the obesity and overweight conditions in children and detect the cause further.
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    Title: Combining Language Independent and Language Dependent Features for Punjabi Named Entity Recognition
    Authors:Amandeep Kaur and Gurpreet Singh Josan
    Abstract:Named Entity Recognition has become a preprocessing module in various Natural Language Processing tasks like Information Extraction, Machine Translation, and Question Answering etc. This paper reports about the development of a Punjabi NER system using a Conditional Random Fields approach. In this work, the evaluation of Language Independent and Dependent features for Punjabi Named Entity Recognition system has been presented. As per evaluation results, the best feature set has been found to be consisting of Context word window 7, POS information of word window 7, length of word, Digits information, Prefixes and Suffixes of length 4, all gazetteer lists which has reported an F-score value of 92.50%. This feature set was also evaluated on 14 individual tags and reported more than 90% F-score values Person (NEP), Date (NEDA), Number (NEN), Title-Person (NETP), Relationship (NREL), Time (NETI), Measure (NEM) tags. The F-score values for Time (NETI), Designation (NED), Organization (NEO), Location (NEL), Relationship (NREL), Facility (NFAC) and Abbreviation (NEA) tags have been found to be above 84%.
    Click Here to Download Pdf
    Title: Review Paper on Various Aspect Level Opinion Mining Probabilistic Approaches for Drug Reviews
    Authors: Tushar N Tekade and Emmanuel M
    Abstract: Now-a-days with the increasing use of web technology for various purposes, online healthcare forums, blogs, healthcare websites have gained importance. These online sources have become a great source of information for people suffering from various health issues. Mining information from this large web bodies is a challenging task. Various evaluation techniques exist for working analytically on these web bodies. Opinion mining, a sentiment analysis approach works for interpreting sentiments about a product from large quantity of data. To interpret and analyze more closely, aspect based mining, a more refined opinion mining is a good approach. Various frequency based and relation based approaches for aspect mining are available which use probabilistic algorithms for their interpretations.
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    Title: Contrast enhancement based forensics in digital images against security attack
    Authors: N.Suruthi, M.Sowmiya and M.Sathiyapriya
    Abstract: Contrast enhancement is the technique used to adjust global brightness and contrast of digital images. Malicious users sometimes perform contrast enhancement provincially for creating a realistic composite image. It is important to detect contrast enhancement authenticating for the originality of the digital images .In this paper, we proposed an algorithm to overcome the malware practice. First step is to detect the image using RSA algorithm. Neural network classification is used to detect the forgery involved in digital images. The main strategy based on the blind identification of zero-height gap bins. In gray level histograms the zero-height gap bins are exploited as identifying features. The probability of detecting and false alarm determined by thresholds which are estimated as the percentage of the enhanced images correctly classified and that of the unenhanced images inaccurately classified, respectively. For evaluation, the receiver operating characteristic (ROC) curves are generated. The consistency between regional artifacts is checked for detecting image forgeries and locating composition boundaries.
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    Title: Survey on clustering web search documents with user search goals using feedback
    Authors: Rinal M. Khandelwal and Prof.Arati R. Deshpande
    Abstract: Nowadays use of internet is increasing rapidly. While searching on the internet using search engine each user may be having different goals of searching. Also for each topic each new user may have his different user goals. Hence the inference and analysis of the user search goals can improve the efficiency of the search engine and also reduce the time needed to search the query as unwanted data can not be seen by the user and user get only his goal oriented search results. Currently everyone is searching on the internet and internet provides ambiguous result of same things as it contains lot of information. The proposed method will provide the information related to the user goals. In this, a novel framework is proposed to cluster web document using user search goals and then generate the pseudo document to represent the clustering effectively.
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    Title: Survey Paper on Different Emotion Recognition Techniques on Text
    Authors: Gaurav G. Dalvi and Emmanuel M.
    Abstract: In today’s digital world all information cannot be inferred from statistics done by big data for better decision making. It also requires support of some review or opinion analysis of customers to provide better feedback. As most of the population are able to express their emotions in the form of text, research in textual analysis becomes a prime need. Many existing systems are being developed for emotion extraction using Keyword-spotting Approach, Statistical and machine learning approach, Rule Based Approach and Cause Extraction Approach. A thorough comparison of above approaches is reviewed and an effort is made to put a lime light on them.
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    Title: Analysis of Cardiovascular Heart Disease Prediction Using Data Mining Techniques
    Authors: Sharan Monica L and Sathees Kumar B
    Abstract: Hear diseases are the number one cause of death. The health industry is generally “Information rich” but “Knowledge poor” which is not possible to handle manually. The data mining is used to predict the disease from the datasets. Knowledge discovery in databases can help organizations turn their data into information. This research paper intends to provide a survey of current techniques of knowledge discovery in databases using data mining techniques which will be useful for medical practitioners to take important decisions. Data mining algorithms such as J48, NB Tree and Simple CART are used to predict the heart disease. The objective of this research work is to predict heart disease more accurately with reduced number of attributes.
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    Title: Image Fusion and its Various Techniques: A Review
    Authors: Er. Raman Kaur, Er. Manvinder Sharma and Er. Apneet Kaur
    Abstract: This paper provides the review on image fusion and its various techniques which provides the advancement in the field of image fusion. As image fusion provides more information about the image by combining the two or more images, thus this approach is used in research field at large scale. The two images are fused by various techniques and algorithms and the resultant image provide very useful information. The various techniques used in image fusion are simple maximum, simple minimum, averaging, principle component analysis (PCA), intensity hue saturation (IHS) discrete wavelet transforms (DWT) and stationary wavelet transforms (SWT). This paper provides the brief description of the techniques under spatial and transform domain such as PCA, IHS, DWT and SWT. The author explains the use of these techniques in various fields.
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    Title: A Survey on Different Techniques for Secure Data Sharing in Public Clouds
    Authors: Sushmita Jain and Emmanuel M.
    Abstract: A public cloud is one which provides public access to different application and storage to anyone on internet. Due to benefits of public clouds, there has been tremendous increase in its usage for secure sharing of data and its storage. To support the growing need of cloud storage, the public cloud system must solve the important and critical issue of data confidentiality. Shared sensitive data must be strongly secured from unauthorized accesses. Although public cloud storage improves efficiency and reduces cost it has many other challenges and reduces cost it has many other challenges and issues associated with it. In this paper various techniques for secure data sharing in public clouds are reviewed. This study will give the reader the information about various techniques of secure data sharing in public cloud.
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    Title: Enhancing Security in Mobile cloud computing using double-encryption model
    Authors:Mankiran Kaur and Manish mahajan
    Abstract: Cloud Computing provides services to the customers like infrastructure, Platform for performing complex operations, more storage to meet the real time demands of the users. With the tremendous rise in the use of Smartphones during the few years, every person now-days rely completely on the phones for each and every work which they used to do on their personal computers before like email, browsing internet, watching videos etc. With the increased used of cloud services by using smartphones anytime and anywhere, gave birth to Mobile cloud computing (MCC). MCC have removed the limitations of mobile devices but outsourcing of data from Smartphone is a concern that needs security. This paper have proposed a security approach which includes double encryption of data using AES and Ghost algorithm that ensures the security of data over the communication channel and data stored at the server.
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    Title: Forward Direction to Future Research for Big Data
    Authors:Dr. K.Prabu and Prof. K. Thamizhmaran
    Abstract: In this paper, we review current research issues and challenges and state-of-the-art of big data. Big data refers to data volumes in the range of exabytes (1018) and beyond. Such volumes exceed the capacity of current on-line storage systems and processing systems. Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using on-hand data management tools or traditional data processing applications. Big data is difficult to work with using most relational database management systems and desktop statistics and visualization packages, requiring instead "massively parallel software running on tens, hundreds, or even thousands of servers". We finally examine the several representative issues and challenges of big data, and current research activities towards forward direction to research in big data concepts.
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    Title: A Novel Feature Learning for Image Classification using Filter Approach in GA
    Authors:Purushottam Das, Ankur Singh Bist and Vinita Naudiyal
    Abstract: Image classification is one of the most complex areas in image processing. Image classification has many application areas ranging from multimedia information delivery to web search. Feature selection, an important aspect in image classification, used for dimensionality reduction of large datasets. An optimal subset of relevant features is needed for improving classification results. Information measures are used here in finding the goodness of feature. Mutual information is taken as the criterion for evaluating fitness of the feature.
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    Title: Spectrum Sensing and Dynamic Spectrum Access in Cognitive Radio: A Survey
    Authors:Er. Raman Kaur and Dr. Paras Chawla
    Abstract: The increasing demand of wireless application restrained the available radio spectrum. In fixed spectrum, large amount of spectrum remain unused. To overcome this problem of underutilization of spectrum band, a technology is used called as cognitive radio. Spectrum sensing is a main task of cognitive radio. The objective of spectrum sensing is to utilize, identify and making use of spectrum holes or white space. The process of accessing the spectrum holes or free spectrum dynamically is called dynamic spectrum access (DSA). This paper gives a brief review on spectrum sensing and its techniques such as energy detection, matched filter detection and cyclostationary feature extraction. Dynamic spectrum access and its three basic models i.e. interweave DSA model, underlay DSA model and overlay DSA model are discussed.
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