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Apache Spark a Big Data Analytics Platform for Smart Grid

Procedia Technology 2015年 21卷 171-178页

作者： Shyam R. Bharathi Ganesh H.B. Sachin Kumar S. Prabaharan Poornachandran Soman K.P. Centre for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetha Coimbatore – 641112 India Amrita Center for Cyber Security Systems and Networks Amrita Vishwa Vidyapeetham Kollam India

Smart grid is a complete automation system, where large pool of sensors is embedded in the existing power grids system for controlling and monitoring it by utilizing modern information technologies. The data collected from these sensors are huge and have all the characteristics to be called as Big Data. The Smart-grid can be made more intelligent by processing and deriving new information from these data in real time. This paper presents Apache spark as a unified cluster computing platform which is suitable for storing and performing Big Data analytics on smart grid data for applications like automatic demand response and real time pricing.

关键词： Smart Grid Data Analytics Big Data Apache Spark

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Study of multirate systems and filter banks using GNU Radio

Study of multirate systems and filter banks using GNU Radio

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International Conference on Communications and Signal Processing

作者： S. Lekshmi Kiran Parvathy G. Mol P. M. Hisham R. Gandhiraj K. P. Soman Center of excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu IN Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu IN

Multirate digital signal processing finds application in various fields like speech processing, image processing and compression. A proper study of this subject is fundamental to incorporating an efficient design of these systems. A good theoretical explanation in this area is readily available at large numbers. But it is quite unfortunate that the present education system does not emphasize a proper visualization of the theoretical concepts. The significance of GNU Radio, which provides various signal processing blocks, is worth noticing since it can be used by a learner to design a flow graph and analyze its response. In this paper, we have implemented the perfect reconstruction filter using the concept of Quadrature mirror filter (QMF) bank in GNU Radio. Some basic concepts like aliasing and filter design have also been analyzed using GNU Radio. We appreciate the role played by GNU Radio since it is an easy-to-use software and also provides an excellant platform in analyzing a system.

关键词： Finite impulse response filters Phase distortion Speech Speech processing Image coding

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Dependency based multiword expression extraction towards NLP applications 14

Dependency based multiword expression extraction towards NLP...

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

作者： Sanjanaashree, P. Anand Kumar, M. Soman, K.P. Center for Excellence in Computational Engineering and Networking Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9781450329088

This paper explores the full-fledged supervised Machine Learning based approach for the automatic extraction of lexical chunks, commonly called as Multi-Word Expression (MWE). The concept of MWE concerns a variety of constructions in everyday language in the form of idioms, phrasal verbs and noun compounds. The pervasiveness of MWE in the NLP tasks that deals with real text, such as Machine Translation and Information retrieval should be provided with enough MWE treatment;if not, the system will fail to generate high-quality natural output. Here, we are extracting phrasal verbs from the English movie subtitle corpus based on their corresponding linguistic pattern and standard association scores. The extracted phrasal verbs have been used to train various machine learning algorithms for discriminating MWE. Two methods of linguistic pattern extraction are implemented, out of which one is proven to be effective. Here, we have demonstrated two major findings, 1) MWE extraction based on dependency information along with POS tag provides better accuracy than it had been extracted from the POS tag pattern alone. 2) The result obtained from extraction is used to train three different machine learning classifiers, out of which Random forest classifier is verified to be the suitable classifier for the application handled. Copyright 2014 ACM.

关键词： Support vector machines

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Direct parametric approach for cascaded systems with application in robot control

Direct parametric approach for cascaded systems with applica...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Guang-Ren Duan Center for Excellence in Computational Engineering and Networking

This paper considers the control of a system which is the cascaded result of a second-order nonlinear plant and a first-order actuator system. It is shown that such a system can be converted equivalently into a fully-actuated third-order quasi-linear system, and as soon as this is done, a simple complete general parametrization of the position-velocity-acceleration feedback controller can be immediately given, which provides, no matter the open loop system is linear or not, a constant linear closed-loop system with designed eigenstructure. Furthermore, the approach also provides all the degrees of design freedom represented by a stable matrix F; and another parameter matrix Z; which is in fact dense in the parameter space. They can be further optimized to achieve additional requirements on the closed-loop system.

关键词： Abstracts Joints

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An experimental study on channel estimation and synchronization to reduce error rate in OFDM using GNU Radio

An experimental study on channel estimation and synchronizat...

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IUTAM Symposium on the Dynamics of Extreme Events Influenced by Climate Change (2013)

作者： Anjana, C. Sundaresan, S. Zacharia, Tessy Gandhiraj, R. Soman, K.P. Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore641112 India Department of ECE Amrita School of Engineering Amrita Vishwa Vidyapeetham Coimbatore641112 India

Orthogonal Frequency Division Multiplexing (OFDM) is a particular case of multicarrier transmission in which, higher data rates are achieved using carriers that are densely packed. In this paper, implementation of OFDM communication system with channel estimation and synchronization is carried out and the bit error rate (BER) of OFDM system with and without channel estimation is observed and correspondingly a plot is traced. The choice has been made because of the advantages that OFDM and SDR has shown in terms of channel capacity and cost. Implementation of the prototype has been in GNU Radio;an open source software. © 2015 The Authors. Published by Elsevier B.V.

关键词： Orthogonal frequency division multiplexing

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Joint layer based deep learning framework for bilingual machine transliteration

Joint layer based deep learning framework for bilingual mach...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： P. Sanjanaashree M. Anand Kumar Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu IN

Between the growth of Internet or World Wide Web (WWW) and the emersion of the social networking site like Friendster, Myspace etc., information society started facing exhilarating challenges in language technology applications such as Machine Translation (MT) and Information Retrieval (IR). Nevertheless, there were researchers working in Machine Translation that deal with real time information for over 50 years since the first computer has come along. Merely, the need for translating data has become larger than before as the world was getting together through social media. Especially, translating proper nouns and technical terms has become openly challenging task in Machine Translation. The Machine transliteration was emerged as a part of information retrieval and machine translation projects to translate the Named Entities based on phoneme and grapheme, hence, those are not registered in the dictionary. Many researchers have used approaches such as conventional Graphical models and also adopted other machine translation techniques for Machine Transliteration. Machine Transliteration was always looked as a Machine Learning Problem. In this paper, we presented a new area of Machine Learning approach termed as a Deep Learning for improving the bilingual machine transliteration task for Tamil and English languages with limited corpus. This technique precedes Artificial Intelligence. The system is built on Deep Belief Network (DBN), a generative graphical model, which has been proved to work well with other Machine Learning problem. We have obtained 79.46% accuracy for English to Tamil transliteration task and 78.4 % for Tamil to English transliteration.

关键词： Training Vectors Joints Neurons Dictionaries Support vector machines Computers

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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Vibration based fault diagnosis of a hydraulic brake system using Variational Mode Decomposition (VMD)

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SDHM Structural Durability and Health Monitoring 2014年第1期10卷 81-97页

作者： Jegadeeshwaran, R. Sugumaran, V. Soman, K.P. School of Mechanical and Building Sciences VIT University Chennai Campus Chennai Tamil Nadu600 127 India Center of Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu641 112 India

In automobile, brake system is an essential part responsible for control of the vehicle. Vibration signals of a rotating machine contain the dynamic information about its health condition. Many research papers have reported the suitability of vibration signals for fault diagnosis applications. Many of them are based on (Fast Fourier Transform) FFT, which have their own drawback with non-stationary signals. Hence, there is a need for development of new methodologies to infer diagnostic information from such non stationary signals. This paper uses vibration signals acquired from a hydraulic brake system under good and simulated faulty conditions for the purpose of fault diagnosis. A new approach called Variational mode decomposition (VMD) was used in this study. VMD decomposes the signal into various modes by identifying a compact frequency support around its central frequency, such that adding all the modes reconstructs the original signal. VMD finds intrinsic mode functions on central frequencies using alternating direction multiplier method (ADMM). Descriptive statistical features were extracted from VMD processed signals and classified using a machine learning algorithm. For classification J48 decision tree algorithm was used. The results were compared with the statistical features extracted from raw signal using decision tree classifier. Copyright © 2014 Tech Science Press.

关键词： Variational mode decomposition

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2D Image data approximation using Savitzky Golay filter - Smoothing and differencing

2D Image data approximation using Savitzky Golay filter - Sm...

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2013 IEEE International Multi Conference on Automation, Computing, Control, Communication and Compressed Sensing, iMac4s 2013

作者： Gowri, B. Ganga Hariharan, V. Thara, S. Sowmya, V. Kumar, S. Sachin Soman, K.P. Center for Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore-641112 India

ISBN: (纸本)9781467350891

Smoothing and differencing is one of the major important and necessary step in the field of signal processing, image processing and also in the field on analytical chemistry. The search for an efficient image smoothing and edge detection method is a challenging task in image processing sector. Savitzky Golay Filters are one among the widely used filters for analytical chemistry. Even though they have exceptional features, they are rarely used in the field of image processing. The designed filter is applied for image smoothing and a mathematical model based on partial derivatives is proposed to extract the edges in images. The smoothing technique of SG filter offers an extremely simple aid in extracting the edge information. An approach using SG filter which can be applied in preserving edge information is one of the major tasks involved in the classification process in the domain of Optical Character Recognition. The paper is focused on designing the Savitzky Golay filter by using the concepts of linear algebra. The main objective of the paper is to portray a clear cut idea about Savitzky Golay filter and to study the design of Savitsky Golay filters based on the concepts of Linear Algebra. © 2013 IEEE.

关键词： Least squares approximations

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2D Image data approximation using Savitzky Golay filter — Smoothing and differencing

2D Image data approximation using Savitzky Golay filter — S...

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International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)

作者： B Ganga Gowri V Hariharan S Thara V Sowmya S Sachin Kumar K. P. Soman Center For Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore-641112 India Center For Excellence in Computational Engineering and Networking Amrita Vishwa Vidyapeetham Coimbatore India

关键词： Image edge detection Vectors Smoothing methods Noise Polynomials Least squares approximations

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