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1st International Conference on Theoretical computer science and Discrete Mathematics, ICTCSDM 2016

作者： Sharma, B.K. Sharan, S. Tiwari, S.P. Department of Computer Science and Engineering Birla Institute of Technology Ranchi834001 India Department of Mathematics School of Advanced Sciences VIT University Vellore632014 India Dhanbad826004 India

ISBN: (纸本)9783319644189

The purpose of the present work is to introduce and study the concept of minimal deterministic automaton with rough output which recognizes the given rough languages. Specifically, we use two concepts for such construction, one is based on Myhill-Nerode’s theory and the other is on the basis of derivatives of the given rough language. Lastly, we discuss monoid representations of the given rough languages. © 2017, Springer International Publishing AG.

关键词： Algebra

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Customizable twitter bots for improved QoS in product marketing

Customizable twitter bots for improved QoS in product market...

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International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)

作者： Balabhadrapathruni Ramya Anush Baskaran Taruni Anand R Senthil Kumar N.Ch. S.N Iyengar School of Computer Science Engineering Vellore Institute of Technology Vellore Tamil Nadu VIT University Vellore Tamil Nadu IN

ISBN: (纸本)9781538618882

In recent times, users have started spending a significant amount of their time on social networking platforms (Twitter, Facebook, Orkut), sharing a plethora of personal information and opinions on different aspects of life. Internet users around the world make use of this powerful tool of communication a.k.a microblogging, using Twitter, a web application that provides dual benefits of microblogging and social networking. In this paper, we propose an application that uses the open structure of twitter to perform 2 main tasks: (1) analyze data for sentiment analysis and opinion mining of a particular product and classify this data into positive, neutral and negative reviews (2) use this data to create automated programs, known as bots, which are useful for generating benign tweets. We use this double-edged sword to provide companies with the opportunity to make use of these automated bots to generate the right tags to advertise products. This enhanced marketing opportunity provides Quality of Service in terms of cost, time and energy.

关键词： Twitter Sentiment analysis Data mining Data analysis Companies Unsolicited electronic mail

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Integrative computing method for the prediction of zinc-binding sites in proteins

Integrative computing method for the prediction of zinc-bind...

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International Joint Conference on Neural Networks (IJCNN)

作者： Hui Li Dechang Pi Yinghong Liang Chuanming Chen Yongzhi Liu College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Shool of Software Engineering Jinling Institute of Technology Nanjing Jiangsu China

ISBN: (纸本)9781509061839

A large number of metalloproteins contained in Protein Data Bank, taking metal ions as cofactors, have important biological functions. As the second most abundant bound trace metal elements in organism, zinc ion plays an important regulatory role in the biological growth and development, disease control, DNA synthesis. So, research on the area of zinc-binding protein sites has an important significance. Because of the availability of protein sequence information, a series of predictive tools based on sequence for zinc-binding sites in proteins have been developed. But presently, there is little research on the integration of these tools. Based on this, an integrative predictor termed meta-zincPrediction is presented in the paper to combine the predictive tools. The linear regression method is used in the integrated approach to combine the scores of different prediction tools, the parameters are adjusted and optimized until to the optimal. Tested on the non-redundant Zhao_dataset, AURPC value of meta-zincPrediction reached nearly 0.9, an increase of 2% -9% than other three predictors, and other performance indexes were also improved mostly. Moreover, the prediction ability of meta-zincPrediction was better than other three predictors, regardless of zinc-binding sites for all four types of residues, or zinc-binding sites for a single type of residues. Our method can not only be applied to large-scale identification of zinc-binding sites based on sequence information, but also be useful for the inference of protein function.

关键词： Proteins Tools Ions Metals Linear regression Machine learning algorithms Predictive models

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Smart chair

Smart chair

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International Conference on Inventive Computing and Informatics (ICICI)

作者： Sahil Singh Sodhi Akash Singh Kunwar Karan Dhingra G Suganya School of Computer Science and Engineering Vellore Institute of Technology University Chennai Tamil Nadu India VIT University Vellore Tamil Nadu IN

ISBN: (纸本)9781538640326

IoT (Internet of Things) is the network of physical devices which is embedded with the sensors to detect signals, software and actuators to take required action(s), electronics and network connectivity to collect and exchange data with other connected devices. These devices are also called smart devices. They are mostly connected remotely and can even send data to cloud. The concept of IoT can be implemented at homes, business, educational centers, medical fields and national security. This paper has implemented the concept of Internet of Things in schools or university classrooms where the attendance system is automated. With the help of a database, a student teacher interaction portal and physical devices, the paper aims to make an education institute smarter. In addition, our research also verifies the presence of a human being sitting on a chair using personal identification. The verification of the seat occupancy by a given individual can be confirmed from any part of the world at any given instance as the data is stored in cloud at all times. Sitting is the most prevalent conduct of human body in everyday life. People spend a lot of time sitting in a school chair, automobile seat or lounge chair in a day. It has been observed that as a result of some everyday activity or poor sitting postures can cause pains and other common complications for people like Endometriosis, Sacroiliac Joint Dysfunction, Degenerative Disc Disease and more. This paper aims to mitigate such issues, and in order to circumvent the adverse effects of improper sitting behavior. The smart chair will also try to promote a healthy lifestyle of the students by measuring the student sitting postures and suggesting to maintain a good healthy posture. The usability of the device can be improved by investing in powerful and more accurate sensors, smaller micro devices and better servers. Consequently, these improvements will help in reducing the overall size of the device; the device will be more

关键词： Radiofrequency identification Temperature sensors Servers Microcontrollers Databases Temperature measurement

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Leprosy lesion recognition using convolutional neural networks

Leprosy lesion recognition using convolutional neural networ...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Baweja, Harjatin Singh Parhar, Tanvir School of Computer Science Vellore Institute of Technology Vellore632014 India School of Electrical Engineering Vellore Institute of Technology Vellore632014 India

ISBN: (纸本)9781509003891

Leprosy, also known as Hansen's disease, is a debilitating and chronic bacterial infection. As per World Health Organization's report, there were 189,000 chronic cases of Leprosy in 2012 with 230,000 new diagnoses. Although curable at later stages, an early diagnosis prevents nerve involvement and the disabilities it incurs. The authors henceforth propose a Convolutional Neural Network based architecture for Leprosy lesion recognition. To train the network, authors use DermnetNz datasets along with web scraped images to achieve a best accuracy of 91.6% on a dataset split into 60% of training images, 20% of images are used for cross validation and 20% for testing. © 2016 IEEE.

关键词： Neural networks

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Notice of Violation of IEEE Publication Principles: The study of the effect of denoising on vectorized convolutional neural network

Notice of Violation of IEEE Publication Principles: The stud...

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International conference of Electronics, Communication and Aerospace technology (ICECA)

作者： G Prabhakar Reddy K Sai Prasad E Amareswar Ch. Susritha R Karthik M. Monica Subashini Department of Computer Science and Engineering MLR Institute of Technology Hyderabad India Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India School of Electrical Engineering VIT University Vellore India

Notice of Violation of IEEE Publication Principles "The Study of the Effect of Denoising on Vectorized Convolutional Neural Network" by G Prabhakar Reddy, K Sai Prasad, E Amareswar, Ch. Susritha, R Karthik, M. Monica Subashini in the Proceedings of the International Conference on Electronics, Communication and Aerospace technology, April 2017 After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles. This paper is a duplication of the original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission. Also, M. Monica Subashini was added as an author to the article but was not aware of the submission and did not agree to be listed as an author. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article: “Effect of Denoising on Vectorized Convolutional Neural Network for Hyperspectral Image Classification” by Deepa Merlin, Sowmya Vishvanathan, and Soman KP in Computational Signal Processing and Analysis, Springer, April 2018 pp. 305-313 The remotely sensed high dimensional hyperspectral imagery is a single capture of a scene at different spectral wavelengths. Since it contains an enormous amount of information, it has multiple areas of application in the field of remote sensing, forensic, biomedical etc. Hyperspectral images are very prone to noise due to atmospheric effects and instrumental errors. In the past, the bands which were affected by noise were discarded before further processing such as classification. Therefore along with the noise the relevant features present in the hyperspectral image are lost. To avoid this, researchers developed many denoising techniques. The goal of denoi

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Preface

Lecture Notes on Data Engineering and Communications Technol...

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Lecture Notes on Data engineering and Communications Technologies 2018年 14卷 vii-xii页

作者： Sangaiah, Arun Kumar Thangavelu, Arunkumar Sundaram, Venkatesan Meenakshi School of Computing Science and Engineering VIT University VelloreTamil Nadu India Department of Computer Science and Engineering National Institute of Technology Surathkal MangaloreKarnataka India

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A Three-Stage Defect Prediction Model for Cross-Project Defect Prediction

A Three-Stage Defect Prediction Model for Cross-Project Defe...

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International Conference on Dependable Systems and Their Applications (DSA)

作者： Song Huang Yaning Wu Haijin Ji Chengzu Bai PLA Military Training Software Testing and Evaluation Centre Nanjing Jiangsu Province China Shool of Computer Science and Technology Huaiyin Normal University Huaian Jiangsu Province China Cornmand Information Institute Army Engineering University of PLA Nanjing Jiangsu Province China Institute of Meteorology & Oceanography National University of Defense Technology Changsha China

Aiming at dealing with the problems of the data deficiency, data high dimensionality in software defect prediction (SDP), this paper proposes a novel three-stage defect prediction model. First we introduced the information flow algorithm (IFA) to do the causality analysis to choose the most representative feature subset. Then we utilized the nearest neighbor method in similarity measuring between the local dataset and the cross-project data, to construct a homogenous training dataset. Last we proposed a new Bayes classifier, which evolves the Naïve Bayes classifier with the vibration of string based diffusion function (VSDF).

关键词： Predictive models Data models Training Software Data preprocessing Computational modeling Software engineering

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Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017 (vol 395, pg 1779, 2020)

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LANCET 2020年第10239期395卷 1762-1762页

作者： Reiner, R. C., Jr. Hay, S., I Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health School of Medicine University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States College of Health and Medical Sciences Haramaya University Harar Ethiopia Department of Epidemiology and Biostatistics Haramaya University Harar Ethiopia Department of Medical Laboratory Sciences Haramaya University Harar Ethiopia School of Nursing and Midwifery Haramaya University Harar Ethiopia School of Pharmacy Haramaya University Harar Ethiopia School of Public Health Haramaya University Harar Ethiopia Haramaya University Harar Ethiopia Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Biology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Research Institute Tehran University of Medical Sciences Tehran Iran Department of Economics and Management Sciences for Health Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Department of Microbiology Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Hematology-Oncology and Stem Cell Transplantation Research Center Tehran University of Medical Sciences Tehran Iran Iran National Institute of Health Research Tehran University of Medical Sciences Tehran Iran Metabolomics and

Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d

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Development of a character recognition software to solve a Sudoku puzzle

Development of a character recognition software to solve a S...

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International Conference and Workshop on Computing and Communication (IEMCON)

作者： Akash Dutta Arunabha Ghosh Department of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9781509009978

An Image is a visual representation of any object, place, person etc. In the field of computer science a Digital Image is a numeric representation of a two-dimensional image. Often images may contain texts, which are a sequence of human-readable characters. Our general conundrum is extraction of texts from an image for processing and editing. In an image texts are defined by set of pixels just like any other object and thus cannot be processed or edited. In this work we have strived to develop a system which can extract texts from a digital image of a Sudoku puzzle, solve the puzzle, and then provide a solution. Our approach is specific but its application are varied.

关键词： Classification algorithms Character recognition Digital images Databases Optical character recognition software computer science

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