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Identifying Negative Interactions in Protein-Protein Interaction Network Using Weak Edge-edge Domination Set

Procedia Technology 2016年 24卷 1423-1430页

作者： Sminu Izudheen Sheena Mathew Assistant Professor Department of Computer Science & Engineering Rajagiri School of Engineering & Technology Kerala India Professor Division of Computer Engineering School of Engineering Cochin University of Science & Technology Kerala India

Link prediction has recently attracted the attention of many researchers as an effective technique to understand the associations between proteins. But most of the work in this area was concentrated on predicting existence of links in future. Very few works has explored the prediction of links that might disappear in future. Also, links predicted by these methods may contain high levels of wrong interactions. In this paper, we propose a method to optimize the negative link predicted in protein network through Weak Edge-Edge Domination (WEED) set. We have tested our model using different standard prediction methods and the results obtained assert that our method can be used as an effective method to reduce false positive rate of negative links predicted in protein network.

关键词： Link Prediction Protein Protein Interactions Domination Set Weak Edge Edge Domination Set.

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Sandhi Splitter for Malayalam Using MBLP Approach

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Procedia Technology 2016年 24卷 1522-1527页

作者： M. Nisha P.C. Reghu Raj Mtech Scholar Department of Computer Science and Engineering Government Engineering College Sreekrishnapuram Palakkad Kerala Assistant Professor Department of Computer Science and Engineering Government Engineering College Sreekrishnapuram Palakkad Kerala

The morphological richness and the agglutinative nature of Malayalam make it necessary to retrieve the root word from its inflected form in most of the NLP tasks. This paper presents an approach to identify the suffixes of Malayalam words using MBLP approach. The idea here is to use Memory Based Language Processing (MBLP) algorithm for Malayalam suffix identification. MBLP is an approach to language processing based on exemplar storage during learning and analogical reasoning during processing. Sandhi splitting is essential for morphological analysis, document indexing and topic modeling. Suffix separation improves the quality of machine translated text. Training instances created from words are manually annotated for their segmentation and the system is trained using TiMBL (Tilberg Memory Based Learner). The paper presents memory-based model of Malayalam suffix identification and its generalization accuracy.

关键词： Malayalam Morphology Memory Based Learning Memory Based Language Processing

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Integration of internet of things to reduce various losses of jatropha seed supply chain

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IOP Conference Series: Materials science and engineering 2017年第1期211卷

作者： S P Srinivasan J Anitha R Vijayakumar Professor and Head Department of Mechanical Engineering Rajalakshmi Engineering College India Assistant Professor Department of Information Technology Rajalakshmi Engineering College India Assistant Professor Department of Computer Science & Engineering Rajalakshmi Engineering College India

The evolution of bio fuel supply chain has revolutionized the organization by restructuring the practices of the traditional management. A flexible distribution system is becoming the need of our society. The main focus of this paper is to integrate IoT technologies into a cultivation, extraction and management of Jatropha seed. It was noticed that major set-back of farmers due to poor supply chain integration. The various losses like information about the Jatropha seed availability, the location of esterification plants and distribution details are identified through this IoT. This enables the farmers to reorganize the land resources, yield estimation and distribution functions. The wastage and the scarcity of energy can be tackled by using the smart phone technologies. This paper is proposes a conceptual frame work on various losses involved in the supply chain of Jatropha seed.

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An Invisible Logo Watermarking Using Arnold Transform

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Procedia computer science 2016年 93卷 808-815页

作者： N. Saikrishna M.G. Resmipriya PG Scholar Department of Computer Science & EngineeringAmal Jyothi College of Engineering Kanjirapally Kottayam686518 Assistant Professor Department of Computer Science & EngineeringAmal Jyothi College of Engineering Kanjirapally Kottayam686518

Digital watermarking is the process of hiding information into the digital content. The method of embedding a smaller logo image into the host image is called logo watermarking. The system proposes an invisible and secure watermarking. The key entered initially determine the location of embedding and thus classified the host image to white and black textured regions. The logo image is then transformed using Arnold transform. Discrete Wavelet Transform (DWT) technique is employed for embedding the transformed logo into the white textured regions. Watermark extraction is done by entering the same key which was already entered during embedding. The system is secure and the logo is imperceptible within the host image. Finally for analysis, PSNR value has been used as a metric for determining the quality of the recovered image.

关键词： Arnold Transformation Histogram Oriented Gradients(Hog) Discrete Wavelet Transform (DWT)

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Challenges and Techniques for Testing of Big Data

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Procedia computer science 2016年 85卷 940-948页

作者： Naveen Garg Sanjay Singla Surender Jangra Research Scholar Department of Computer Science Engineering I.K. Gujral Punjab Technical University Jalandhar India Assistant Professor Amity University Uttar Pradesh India Professor & HoD Department of Computer Science Engineering IET Bhaddal India Assistant Professor Department of IT Engineering HCTM Kaithal India

Big Data, the new buzz word in the industry, is data that exceeds the processing and analytic capacity of conventional database systems within the time necessary to make them useful. With multiple data stores in abundant formats, billions of rows of data with hundreds of millions of data combinations and the urgent need of making best possible decisions, the challenge is big and the solution bigger, Big Data. Comes with it, new advances in computing technology together with its high performance analytics for simpler and faster processing of only relevant data to enable timely and accurate insights using data mining and predictive analytics, text mining, forecasting and optimization on complex data to continuously drive innovation and make the best possible decisions. While Big Data provides solutions to complex business problems like analyzing larger volumes of data than was previously possible to drive more precise answers, analyzing data in motion to capture opportunities that were previously lost, it poses bigger challenges in testing these scenarios. Testing such highly volatile data, which is more often than not unstructured generated from myriad sources such as web logs, radio frequency Id (RFID), sensors embedded in devices, GPS systems etc. and mostly clustered data for its accuracy, high availability, security requires specialization. One of the most challenging things for a tester is to keep pace with changing dynamics of the industry. While on most aspects of testing, the tester need not know the technical details behind the scene however this is where testing Big Data Technology is so different. A tester not only needs to be strong on testing fundamentals but also has to be equally aware of minute details in the architecture of the database designs to analyze several performance bottlenecks and other issues. Like in the example quoted above on In-Memory databases, a tester would need to know how the operating systems allocate and de-allocate memory and u

关键词： Big Data Testing Verasity Hadoop

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Gesture Control Using Single Camera for PC

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Procedia computer science 2016年 78卷 146-152页

作者： N. Lalithamani Assistant Professor (SG) - Department of Computer Science and Engineering Amrita School of Engineering AMRITA VISHWA VIDYAPEETHAM (University) Coimbatore India

In the past decade, more stress has been given to user interface since technology is made available to every human being. This includes advancement of touch technology over buttons and many more gesture control mechanisms. These technologies enable even a laymen to better use the day-to-day technologies like cell phone and personal computer easily with navigation. This work focuses on one such technology that can be implemented on a PC (Personal computer). We use single web camera as input device to recognize gestures of hand. Some of these gestures include controlling the mouse cursor, the clicking actions, and few shortcuts for opening specific applications. This work includes Face Recognition model as an replacement for default lock screen. The Face Recognition model uses Viola and Jones method for detection of face and PCA (Principal Component Analysis) for recognition and identification of algorithms.

关键词： Gesture recognition Face recognition PC

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COGOM: Cognitive Theory Based Ontology Matching System

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Procedia computer science 2016年 85卷 301-308页

作者： K. Saruladha S. Ranjini Pondicherry Engineering College Senior Assistant Professor Department Of Computer Science Pondicherry-605008 Pondicherry Engineering College M.Tech Department Of Computer Science Pondicherry-605008

Ontology matching systems take a prominent position in solving semantic heterogeneity problems to facilitate sharing and reuse of ontologies. The process of generating ontology alignments through ontology matching techniques purely lies on how the concepts and relationships are modeled. This paper focuses on designing an ontology matching system in which concepts are modeled based on cognitive units of knowledge comprising of objects, attributes and relationships. The proposed cognitive based ontology matching system(COGOM) identifies semantically related concepts by aggregating the attribute similarity degree, structural similarity degree and semantic conception degree. The similarity computation is adapted from the Tversky psychological model of similarity. The proposed ontology matching system is adaptive in nature because of the cognitive based knowledge expression and the computational overhead of generating alignments is improved by forming quality clusters of semantically correlating concepts thus reducing the concept match space. The precision and recall metrics are used for evaluation of the proposed system using the benchmark data sets of OAEI 2015.

关键词： Semantic heterogeneity COGOM Tversky Quality clusters Precision Recall

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Door Security using Face Detection and Raspberry Pi

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IOP Conference Series: Materials science and engineering 2018年第1期331卷

作者： Venkatesh Bhutra Harshav Kumar Santosh Jangid L Solanki Student Department of Electronics and Communication BKBIET Pilani Rajasthan India 333031. Student Department of Computer Science & Engineering BKBIET Pilani Rajasthan India 333031. Assistant Professor Department of Electronics and Communication BKBIET Pilani Rajasthan India 333031 Principal (Academics) BKBIET Pilani Rajasthan India 333031.

With the world moving towards advanced technologies, security forms a crucial part in daily life. Among the many techniques used for this purpose, Face Recognition stands as effective means of authentication and security. This paper deals with the user of principal component and security. PCA is a statistical approach used to simplify a data set. The minimum Euclidean distance found from the PCA technique is used to recognize the face. Raspberry Pi a low cost ARM based computer on a small circuit board, controls the servo motor and other sensors. The servo-motor is in turn attached to the doors of home and opens up when the face is recognized. The proposed work has been done using a self-made training database of students from B.K. Birla Institute of engineering and Technology, Pilani, Rajasthan, India.

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Applying Separation of Concern for Developing Softwares Using Aspect Oriented Programming Concepts

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Procedia computer science 2016年 85卷 906-914页

作者： Anil Kumar Arvind Kumar M. Iyyappan Department of Computer Science & Engineering Ph. D. Scholar SRM University Sonepat-131029 India Department of Computer Science & Engineering Assistant Professor SRM University Sonepat-131029 India

Aspects provide a means of separating cross-cutting concerns from our core implementation code into separate modules. Cross-cutting concerns are pieces of functionality that are used across multiple parts of a system. They cut across, as opposed to standing alone. For example if every method of our program requires logging information for identification then a logging aspect can be applied to methods external to the method implementation without using logging information with the methods internally. It's a powerful technique to help employ the principle of separation of concerns within code. Aspect Oriented Programming (AOP) is a methodology that provides separation of crosscutting concerns by introducing a new unit of modularization—an aspect . Each aspect focuses on a specific crosscutting functionality.

关键词： Aspects Crosscutting Concern AOP AspectJ

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Wireless Sensor Network Topology Control Sing Clustering

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Procedia computer science 2016年 79卷 893-902页

作者： K. Hari Krishna Y. Suresh Babu Tapas Kumar Ph.D -Research Scholar- Lingaya's university & Assistant Professor Department Of Computer Science & Engineering Bharat Institute of Engineering and Technology Professor P.G Dept of Computer Science JKC College Guntur Professor & Dean & H.O.D Department Of Computer Science & Engineering Lingaya's University Faridabad

A wireless sensor network consists of many wireless nodes forming a network which are used to monitor certain physical or environmental conditions, such as humidity, temperature, sound etc. Some of the popular applications of sensor network are area monitoring, environment monitoring (such as pollution monitoring), and industrial and machine health monitoring, waste water monitoring and military surveillance. Topology control in WSNs is a technique of defining the connections between nodes in order to reduce the interference between them, save energy and extend network lifetime. The Objective of my paper is to Maximize the network lifetime. The algorithm proposed is a modification to the CLTC framework first we form clusters of nodes using K-Means, in second phase we do intra-cluster topology control using Relative Neighbourhood Graph, and in third phase we do inter-cluster topology control ensuring connectivity. The simulations were carried out using Omnet++ as a simulator and Node Power Depletion and Node Lifetime as parameters.

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