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Application framework for management and monitoring of heterogeneous 6LoWPAN deployment 11

Application framework for management and monitoring of heter...

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1st International Conference on Wireless Technologies for Humanitarian Relief, ACWR 2011

作者： Rajgopal, C. Peter, Rakesh Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamilnadu India

ISBN: (纸本)9781450310116

Large Scale Heterogeneous Wireless Sensor Networks require effective tools for monitoring and managing the network. In this paper, we discuss about the design and implementation of an application framework in order to monitor and manage a wireless sensor deployment, where the motes exchange IPv6 encapsulated information packets. The application framework is based on a three tier architecture with the nesC / TinyOS based firmware using 'blip' components forming the bottom layer, a middle layer implemented in Python and top layer which is a web interface created using Adobe Flex 4. The implemented features of the application framework include - sensor data acquisition and display, network activity detection of deployed motes, over-the-air programming for software re-visioning, as well as node localization and mapping. The application framework also extends to incorporate the software defined radio based gateway deployed using GNU Radio platform and Universal Software Radio Peripheral (USRP) which enables the testbed to bridge to other heterogeneous systems.

关键词： Software radio

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AMRITA-CEN@SAIL2015: Sentiment analysis in Indian languages 3rd

AMRITA-CEN@SAIL2015: Sentiment analysis in Indian languages

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3rd International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2015

作者： Se, Shriya Vinayakumar, R. Anand Kumar, M. Soman, K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Ettimadai Coimbatore India

ISBN: (纸本)9783319268316

The contemporary work is done as slice of the shared task in Sentiment Analysis in Indian Languages (SAIL 2015), constrained variety. Social media allows people to create and share or exchange opinions based on many perspectives such as product reviews, movie reviews and also share their thoughts through personal blogs and many more platforms. The data available in the internet is huge and is also increasing exponentially. Due to social media, the momentousness of categorizing these data has also increased and it is very difficult to categorize such huge data manually. Hence, an improvised machine learning algorithm is necessary for wrenching out the information. This paper deals with finding the sentiment of the tweets for Indian languages. These sentiments are classified using various features which are extracted using words and binary features, etc. In this paper, a supervised algorithm is used for classifying the tweets into positive, negative and neutral labels using Naive Bayes classifier. © Springer International Publishing Switzerland 2015.

关键词： Sentiment analysis

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Deep model for classification of hyperspectral image using restricted Boltzmann machine 14

Deep model for classification of hyperspectral image using r...

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2014 International Conference on Interdisciplinary Advances in Applied Computing, ICONIAAC 2014

作者： Midhun, E.M. Nair, Sarath R. Nidhin Prabhakar, T.V. Sachin Kumar, S. Centre for Excellence in Computational Engineering Networking Amrita Vishwa Vidyapeetham Coimbatore641112 India

ISBN: (纸本)9781450329088

This paper presents an improved classification of hyperspectral images using deep learning, by extracting meaningful representations at higher levels. Deep learning is a set of algorithm in machine learning that attempt to model high level abstraction of data by using architectures composed of multiple non-linear transformation. It allows artificial systems to discover re-usable features that capture structure in an environment. The ability of undirected graphical models like Restricted Boltzmann Machine, to capture distribution among pixels at the hidden level is utilized here to extract features for each band in the hyperspectral image. To enhance the quality of image a band-by-band non-linear diffusion is introduced as a preprocessing step which ensures increased class separability and noise reduction. After preprocessing, a powerful regenerative model Restricted Boltzmann Machine (RBM) is used for the feature extraction. The generated feature vectors is feed as input to different classifiers for the classification. A statistical comparison of accuracies, obtained with RBM under different conditions illustrates the effectiveness of proposed method. Hyperspectral dataset acquired by Airborne Visible/Infrared imaging Spectrometer is used for experimentation. Copyright 2014 ACM.

关键词： Image classification

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Author identification based on word distribution in word space

Author identification based on word distribution in word spa...

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International Conference on Advances in Computing, Communications and Informatics, ICACCI 2015

作者： Barathi Ganesh, H.B. Reshma, U. Anand Kumar, M. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore641112 India

ISBN: (纸本)9781479987917

Author attribution has grown into an area that is more challenging from the past decade. It has become an inevitable task in many sectors like forensic analysis, law, journalism and many more as it helps to detect the author in every documentation. Here unigram/bigram features along with latent semantic features from word space were taken and the similarity of a particular document was tested using Random forest tree, Logistic Regression and Support Vector Machine in order to create a global model. Dataset from PAN Author Identification shared task 2014 is taken for processing. It has been observed that the proposed model shows state-of-art accuracy of 80% which is significantly greater when compared to the Author Identification PAN results of the year 2014. © 2015 IEEE.

关键词： Support vector machines

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A robust watermarking method based on Compressed Sensing and Arnold scrambling

A robust watermarking method based on Compressed Sensing and...

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2012 International Conference on Machine Vision and Image Processing, MVIP 2012

作者： Veena, V.K. Jyothish Lal, G. Vishnu Prabhu, S. Sachin Kumar, S. Soman, K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore-641112 India

ISBN: (纸本)9781467323208

Watermarking is a technique for information hiding, which is used to identify the authentication and copyright protection. In this paper, a new method of watermarking scheme is proposed, which uses both Compressed Sensing and Arnold scrambling method for efficient data compression and encryption. Compressive sensing technique aims at the reconstruction of sparse signal using a small number of linear measurements. Compressed measurements are then encrypted using Arnold transform. The proposed encryption scheme is computationally more secure against investigated attacks on digital multimedia signals. © 2012 IEEE.

关键词： Compressed sensing

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AMRITA-CEN@FIRE2015: Automated story illustration using word embedding 7

AMRITA-CEN@FIRE2015: Automated story illustration using word...

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7th Workshops at the Forum for Information Retrieval Evaluation, FIRE-WS 2015

作者： Sanjay, S.P. Ezhilarasan, Nivedhitha Anand Kumar, M. Soman, K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Ettimadai Coimbatore India

Story books are copiously filled with image illustration in which the illustrations are essential to the enjoyment and understanding of the story. Often the photos themselves turn out to be more important than content. In such cases, our principle job is to locate the best pictures to show. Stories composed for kids must be improved with pictures to manage the enthusiasm of a tyke, for words usually can't do a picture justice. This system is built as a part of shared task of Forum of Information Retrieval and Evaluation (FIRE) 2015 workshop. In this system we provide a methodology for automatically illustrating a given Children's story using the Wikipedia ImageCLEF 2010 dataset, with appropriate images for better learning and understanding.

关键词： Image retrieval

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AMRITA-CEN-NLP@FIRE 2015:CRF based named entity extraction for Twitter microposts 7

AMRITA-CEN-NLP@FIRE 2015:CRF based named entity extraction f...

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7th Workshops at the Forum for Information Retrieval Evaluation, FIRE-WS 2015

作者： Sanjay, S.P. Anand Kumar, M. Soman, K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Ettimadai Coimbatore India

This proposed method implements the Named Entity Recognition (NER) for four dialects Such as English, Tamil, Malayalam, and Hindi. The results obtained from this work are submitted to a research evaluation workshop Forum for Information Retrieval and Evaluation (FIRE 2015). It is single-layered problem which is divided into multi-layered this step is called pre-processing;it has three levels of named entity tags which are referred as BIO format. This format is trained using Condition Random field(CRF) are used for implementing in NER system, the results obtained are grouped back to single-label or single-tagged referred as Format converting. In FIRE 2015, we developed English, Tamil, Malayalam, and Hindi NER system using CRF. The FIRE estimated the average precision for all the four languages.

关键词： Extraction

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A Combined Crypto-steganographic Approach for Information Hiding in Audio Signals Using Sub-band Coding, Compressive Sensing and Singular Value Decomposition

A Combined Crypto-steganographic Approach for Information Hi...

引用

International Symposium on Security in Computing and Communications, SSCC 2013

作者： Lal, G.Jyothish Veena, V.K. Soman, K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore 641112 India

ISBN: (纸本)9783642405754

In this paper, a new method of audio data security system is proposed, which uses the complementary services provided by steganography and cryptography. Here the audio data to be send secretly is encoded using the compressive measurements of the same and the resultant data is embedded in the perceptible band of the cover audio data using the SVD based watermarking algorithm. Thus the combination of these two methods enhances the protection against most serious attacks when audio signals are transmitted over an open channel. Decryption stage uses SVD based watermark extraction algorithm and L1 optimization. Experimental results show that the combined system enhances the security of the audio data embedded. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Singular value decomposition

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Noise robust zerocrossing rate computation for audio signal classification

Noise robust zerocrossing rate computation for audio signal ...

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2011 3rd International Conference on Trendz in Information Sciences and Computing, TISC 2011

作者： Kathirvel, P. Manikandan, M. Sabarimalai Senthilkumar, S. Soman, K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Tamilnadu-641112 India

ISBN: (纸本)9781467301329

Zero-crossing rate (ZCR) is one of the most important acoustic feature that has been widely used in voice activity detection, voiced/unvoiced speech classification, music/speech classification image processing, optics, biomedical engineering, radar and fluid mechanics. The conventional time-domain ZCR measurement is sensitive to nonstationary noise. In this paper, we present a noise robust zerocrossing rate computation method. The number of zerocrossings is computed in autocorrelation-domain rather than in time-domain. The accuracy of the proposed measurement method is evaluated using both sinusoidal and speech waveforms under different signal-to-noise ratios (SNRs). Experimental results show that the proposed ZCR measurement method achieves better accuracy than the conventional ZCR measurement methods in the literature. © 2011 IEEE.

关键词： Speech recognition

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Modeling of Cascade Regulation in Psoriasis: A Comprehensive Approach 1

Modeling of Cascade Regulation in Psoriasis: A Comprehensive...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Harishchander, A. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Tamil Nadu Coimbatore India

ISBN: (纸本)9781607685395

The implication of a successful mathematical model in applied genomics requires mathematical modeling of regulatory cascades in a gene-regulated network in autoimmune disorders (AIDs) such as Psoriasis is a difficult job to complete in the current age of applied genomics. There were four computational approaches used to address the Challenge: (a) Gene Assisted Cascade Regulation, (b) Differential Gene Expression Cascade, (c) Gene Variant Cascade, and (d) Biologic Cascade to identify a potential biomarker for treating AIDS in the future, and finally, the reconstructed network concerning activation and deactivation loops that were subjected to mathematical modeling to understand and identify the mechanism of regulatory cascade in pathogenesis. © The Electrochemical Society

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