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TECHNICAL ERA: An Online Web Application

IOP Conference Series: Materials science and Engineering 2019年第1期590卷

作者： M.D.V Ajay N Adithya A Mary Posonia U.G Student Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Assistant Professor School of Computing Sathyabama Institute of Science and Technology Chennai

The web has significantly affected all parts of every one of our students. As our students depend increasingly on the web, the constancy of web applications has turned out to be progressively critical. To make these applications more tried and true, we will make a web application with respect to placement training. In general we have Indiabix and placement season are providing a wide range of both technical and aptitude questions in order to prepare a student for the placement. But somehow those questions are repeatedly asked are the standard questions are given. To improve this situation, in this paper, we propose a model of a web application. This structure utilizes the offline application capacity with all the questions are put away in the database and the questions will be refreshed progressively on a period premise with the assistance of the placement coordinator in the college. Every student can sign up and practice all the questions that are provided with respect to the subjects.

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Is leakage power a linear function of temperature?

arXiv

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arXiv 2018年

作者： Sultan, Hameedah Varshney, Shashank Sarangi, Smruti R. School of Information Technology Indian Institute of Technology Delhi VLSI Design Tools and Technology Indian Institute of Technology Delhi Computer Science and Engineering Joint Professor in Electrical Engineering Indian Institute of Technology Delhi

In this work, we present a study of the leakage power modeling techniques commonly used in the architecture *** further provide an analysis of the error in leakage power estimation using the various modeling techniques. We strongly believe that this study will help researchers determine an appropriate leakage model to use in their work, based on the desired modeling accuracy and speed. Copyright © 2018, The Authors. All rights reserved.

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A Heuristic Network for Predicting the Percentage of Gross Domestic Product Distribution

A Heuristic Network for Predicting the Percentage of Gross D...

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International Symposium on Advanced Intelligent Informatics (SAIN)

作者： Emmilya Umma Aziza Gaffar Irwan Gani Haviluddin Achmad Fanany Onnilita Gaffar Rayner Alfred Department of Economic Study Mulawarman University East Kalimantan Indonesia Faculty of Computer Science and Information Technology Mulawarman University East Kalimantan Indonesia Associate Professor of Computer Science Faculty of Computing and Informatics University Malaysia Sabah East Kalimantan Indonesia

ISBN: (纸本)9781538652817;9781538652800

In a country, economic growth indicators are measured by GDP growth rates. In order to predict GDP growth then, economic situation and economic development strategy have always been used. In this study, GDP contribution at the current price by the industrial sector has been predicted by using heuristic network method. There were nine GDP growth variables including (1) Agriculture, Livestock, Forestry, Fishery, (2) Mining & Quarrying, (3) Manufacturing Industry, (4) Electricity, Gas, Water supply, (5) Construction, (6) Trade, Hotel, Restaurant, (7) Transport& Communication, (8) Finance, Real Estate & Business Services, and (9) Services in the period 2001-2016 have been analyzed. Experimental results show that the error rate forecasting in 2017 is less than 10%. The results show that intelligent computing method (heuristic network) can be an alternative method for predicting the contribution of GDP. This method predicts fairly quickly, significantly and produces an acceptable error prediction.

关键词： Economic indicators Training Data models Time series analysis Agriculture Informatics

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A Comprehensive Survey on Various key Management Schemes in WSN

A Comprehensive Survey on Various key Management Schemes in ...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： G Manikandan U Sakthi Assistant Professor St.Joseph’s College of Engineering Sathyabama Institute of Science and Technology Chennai India Department of Computer Science and Engineering St.Joseph’s Institute of Technology Chennai India

ISBN: (纸本)9781538614433;9781538614426

A numbers of distributed autonomous sensor nodes are deployed in a wireless sensor network environment for carrying out multiple tasks. Data packets transmitted in wireless sensor network needs to be protected. Security keys can be generated and used to transmit data securely. These security key generation task needs to be properly managed in WSN. Efficient key management assists in providing confidentiality, integrity to the transmitted information. The security keys, if properly managed, blocks unauthorized users from accessing the transmitted data. Numerous key management mechanisms have been proposed in research literature. This proposed work presents a detailed survey performed on the current set of widely practiced key management techniques in WSNs. Both asymmetric encryption and hybrid type of encryption techniques are applied in key management. The survey presented analyzes the various key management techniques pertaining to computational overhead, communication complexity, energy consumption, robustness and scalability. The survey will be helpful for researchers in selecting the appropriate key management technique specific to their application needs.

关键词： Wireless sensor networks Cryptography Task analysis Memory management Base stations Conferences

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Installation of IR Camera in Smart Watches for Facial Expression Recognition

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Journal of Physics: Conference Series 2019年第1期1362卷

作者： K. Sathish Shaikh Mojamill G. Sai Priya Raguram B. S. Krishna Sapna Sahoo Assistant Professor(O.G.) Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai-600089 Tamil Nadu India UG Scholar Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai-600089 Tamil Nadu India

IR camera, with its various advantages, can be found in many different fields. The most important application of an IR camera is that it can be used even in the dark, unlike an ordinary camera. Using this plus point, we can integrate this with other technologies to help us locate obstacles in the dark. This is due to the fact that IR cameras can detect heat instead of just capturing and since everything on this planet gives off heat, these IR cameras can detect these obstacles. Many methods have been implemented to deal with such problems but there are not easily available and are quite expensive. IR camera have been used in as surveillance cameras and also in movies to make the inanimate idealistic. However, they have not been integrated with smart watches which are easily available nowadays and are much cheaper than any other alternatives. The idea is to integrate this IR camera with a smart watch that would make it portable and easy to use anywhere. Not only is this technology aimed to help the general public but also the blind. Detection of any facial expression would alert the watch wearer that someone is in vicinity. Since IR camera can sense heat, they would be better recognizers of different expressions. This would not only allow them to navigate on their own, but also inform about the whereabouts of the user to their close friends and family in case of emergency.

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Interaction concepts for collaborative visual analysis of scatterplots on large vertically-mounted high-resolution multi-touch displays 10

Interaction concepts for collaborative visual analysis of sc...

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10th Forum Media technology, FMT 2017 and 3rd All Around Audio Symposium

作者： Chegini, Mohammad Shao, Lin Lehmann, Dirk J. Andrews, Keith Schreck, Tobias Institute of Computer Graphics and Knowledge Visualisation Graz University of Technology Austria University of Magdeburg Germany Institute of Interactive Systems and Data Science Graz University of Technology Austria

Large vertically-mounted high-resolution multitouch displays are becoming increasingly available for interactive data visualisation. Such devices are well-suited to small-team collaborative visual analysis. In particular, the visual analysis of large high-dimensional datasets can benefit from high-resolution displays capable of showing multiple coordinated views. This paper identifies some of the advantages of using large, high-resolution displays for visual analytics in general, and introduces a set of interactions to explore high-dimensional datasets on large vertically-mounted high-resolution multi-touch displays using scatterplots. A set of touch interactions for collaborative visual analysis of scatterplots have been implemented and are presented. Finally, three perception-based level of detail techniques are introduced for such displays as a concept for further implementation.

关键词： Data visualization

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Fall classification based on sensor data from smartphone and smartwatch

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AIP Conference Proceedings 2019年第1期2112卷

作者： Surya Suresh Mihir Jain Radha Ramadoss Department of Computer Science and Engineering SRM Institute of Science and Technology Kancheepuram Dt. Tamil Nadu Kattankulathur-603203 India Department of Computer Science and Engineering SRM Institute of Science and Technology Kancheepuram Dt. Tamil Nadu Kattankulathur-603203 India Assistant Professor Department of Computer Science and Engineering SRM Institute of Science and Technology Kancheepuram Dt. Tamil Nadu Kattankulathur-603203 India

A fall is an unintentional event in which a person comes to rest on the ground/floor/a lower level. Falls are the second driving cause of inadvertent injury deaths around the world. Falls pose a major health risk to children and the elderly (especially above the age of 65). Injuries from falls make it difficult for an individual to move around, do regular activities, or live on their own. Hence, studies on methods able to recognize Activities of Daily Living (ADLs) and to identify falls is on the rise. The acknowledgment of ADLs may permit to gather the sum of physical activity that a subject performs daily, whilst the timely identification of falls may aid in diminishing their consequences. To improve the accuracy of the classifier, the data from smartwatches and smartphones are combined. There are not many publicly accessible datasets incorporating data from both smartwatchesand smartphones. Hence, the data will be collected independently. The Decision tree (J48) classifier will be used to classify the falls. The evaluation metrics include: Precision, Recall, F1 Score and the confusion matrix.

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Preface

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Journal of computer science & technology 2019年第3期34卷 507-508页

作者： Shi-Min Hu Hongbo Fu Marcus Magnor Department of Computer Science and Technology Tsinghua University.Beijing School of Creative Media City University of Hong KongHong Kong Computei Graphics Laboratory Braunschweig University of TechnologyBraunschweig

The Computational Visual Media (CVM) conference series is intended to provide a major international forum for exchanging novel research ideas and significant computational methods that either underpin or apply visual media. The primary goal is to promote cross-disciplinary research to amalgamate aspects of computer graphics, computer vision, machine learning, image and video processing, visualization and geometric computing. The main topics of interest to CVM include classification, composition, retrieval, synthesis, cognition and understanding of visual media (e.g., images, videos, 3D geometry).

关键词： Preface Computational Visual Media(CVM) primary goal

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Comparative cellular analysis of motor cortex in human, marmoset and mouse (vol 598, pg 111, 2021)

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NATURE 2022年第7904期604卷 E8-E8页

作者： Bakken, Trygve E. Jorstad, Nikolas L. Hu, Qiwen Lake, Blue B. Tian, Wei Kalmbach, Brian E. Crow, Megan Hodge, Rebecca D. Krienen, Fenna M. Sorensen, Staci A. Eggermont, Jeroen Yao, Zizhen Aevermann, Brian D. Aldridge, Andrew I. Bartlett, Anna Bertagnolli, Darren Casper, Tamara Castanon, Rosa G. Crichton, Kirsten Daigle, Tanya L. Dalley, Rachel Dee, Nick Dembrow, Nikolai Diep, Dinh Ding, Song-Lin Dong, Weixiu Fang, Rongxin Fischer, Stephan Goldman, Melissa Goldy, Jeff Graybuck, Lucas T. Herb, Brian R. Hou, Xiaomeng Kancherla, Jayaram Kroll, Matthew Lathia, Kanan van Lew, Baldur Li, Yang Eric Liu, Christine S. Liu, Hanqing Lucero, Jacinta D. Mahurkar, Anup McMillen, Delissa Miller, Jeremy A. Moussa, Marmar Nery, Joseph R. Nicovich, Philip R. Niu, Sheng-Yong Orvis, Joshua Osteen, Julia K. Owen, Scott Palmer, Carter R. Pham, Thanh Plongthongkum, Nongluk Poirion, Olivier Reed, Nora M. Rimorin, Christine Rivkin, Angeline Romanow, William J. Sedeno-Cortes, Adriana E. Siletti, Kimberly Somasundaram, Saroja Sulc, Josef Tieu, Michael Torkelson, Amy Tung, Herman Wang, Xinxin Xie, Fangming Yanny, Anna Marie Zhang, Renee Ament, Seth A. Behrens, M. Margarita Bravo, Hector Corrada Chun, Jerold Dobin, Alexander Gillis, Jesse Hertzano, Ronna Hof, Patrick R. Hollt, Thomas Horwitz, Gregory D. Keene, C. Dirk Kharchenko, Peter V. Ko, Andrew L. Lelieveldt, Boudewijn P. Luo, Chongyuan Mukamel, Eran A. Pinto-Duarte, Antonio Preiss, Sebastian Regev, Aviv Ren, Bing Scheuermann, Richard H. Smith, Kimberly Spain, William J. White, Owen R. Koch, Christof Hawrylycz, Michael Tasic, Bosiljka Macosko, Evan Z. McCarroll, Steven A. Ting, Jonathan T. Zeng, Hongkui Zhang, Kun Feng, Guoping Ecker, Joseph R. Linnarsson, Sten Lein, Ed S. Allen Institute for Brain Science Seattle WA USA Department of Physiology and Biophysics University of Washington Seattle WA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Bioengineering University of California San Diego La Jolla CA USA The Salk Institute for Biological Studies La Jolla CA USA Epilepsy Center of Excellence Department of Veterans Affairs Medical Center Seattle WA USA Stanley Institute for Cognitive Genomics Cold Spring Harbor Laboratory Cold Spring Harbor NY USA Department of Genetics Harvard Medical School Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA LKEB Department of Radiology Leiden University Medical Center Leiden The Netherlands Pattern Recognition and Bioinformatics group Delft University of Technology Delft The Netherlands J. Craig Venter Institute La Jolla CA USA Department of Pathology University of California San Diego CA USA Division of Vaccine Discovery La Jolla Institute for Immunology La Jolla CA USA Genomic Analysis Laboratory The Salk Institute for Biological Studies La Jolla CA USA Computer Science and Engineering Program University of California San Diego La Jolla CA USA Howard Hughes Medical Institute The Salk Institute for Biological Studies La Jolla CA USA Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla CA USA Institute for Genomes Sciences University of Maryland School of Medicine Baltimore MD USA Center for Epigenomics Department of Cellular and Molecular Medicine University of California San Diego La Jolla CA USA Ludwig Institute for Cancer Research La Jolla CA USA Department of Computer Science University of Maryland College Park College Park MD USA Sanford Burnham Prebys Medical Discovery Institute La Jolla CA USA Biomedical Sciences Program School of Medicine University of California San Diego La Jolla CA USA University of Connecticut Storrs CT USA Department

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Goal Programming Model for Optimizing Working Capital Management: Case of Tire Retreading Company

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Journal of Operations and Strategic Planning 2018年第2期1卷 148 - 167页

作者： Arunkumar O. N. Divya D. Tony Mathew Associate Professor Department of Mechanical Engineering Sree Narayana Gurukulam College of Engineering Kadayiruppu Kolenchery Ernakulam Kerala India. Assistant Professor Department of Computer Science and Engineering Adi Shankara Institute of Engineering and Technology Vidya Bharathi Nagar Mattoor Kalady Ernakulam District Kerala India. Assistant Professor Department of Mechanical Engineering Kottayam Institute of Technology and Science Kottayam Kerala India.

This article discusses goal programming model for optimizing working capital management (WCM) of a tire manufacturing company. The mathematical model is run for the years 2008–2009 to 2012–2013 and values of the respective goals are taken from it. The validation for the model values with the actual values from the financial data are carried out to check the significance of the model values. The significance test is carried out in one sample t-test. It is observed that all the values got from the model are significant. The sales of the company for the year 2013–2014 is forecasted from the past data by linear regression using Microsoft Excel as a trend line. The model is used to 2analyze the values of variables of WCM for the year 2013–2014 to achieve a 30 percent return on assets (ROA) for the forecasted sales.

关键词： Working capital management goal programming LINGO tire manufacturing firm

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