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2nd International Conference on Electronics and Renewable systems, ICEARS 2023

作者： Venusamy, Kanagaraj Kannadhasan, S. Prakash, E. Priyadarsini, K. Study World College of Engineering Department of Electronics and Communication Engineering Chennai Coimbatore India Rajalakshmi Engineering College Department of Mechatronics Engineering Chennai India School of Computing Srm Institute of Science & Technology Department of Data Science and Business Systems Chennai Kattankulathur India

ISBN: (纸本)9798350346640

Free space optical communication being an emerging technology, has Fog as a primary challenge on its way which makes fog modelling necessary to manage wireless networks. In this paper, an analytical study was made on the performance of five mathematical fog models employing the NRZ-OOK modulation scheme for transmission and a Si PIN photodiode as the photo receptor. This article focuses on numerous performance specifications including Signal to noise ratio [SNR], Bit error rate [BER] and channel capacity all against visibility under fog for propagations wavelengths of 850 nm and 1550 nm and simulations were carried out in MATLAB. The results indicate that the wavelength of 1550nm as more advantageous option over the others for FSO wireless links and an investigation on different models and their characteristics define their suitability for implementation. © 2023 IEEE.

关键词： Visibility

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RIVER: Reconfigurable flow and fabric for real-time signal processing on FPGAs

RIVER: Reconfigurable flow and fabric for real-time signal p...

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作者： Brugger, Christian Hillenbrand, Dominic Balzer, Matthias Microelectronic Systems Design Research Group University of Kaiserslautern Germany Green Computing Systems Research and Development Center Department of Computer Science and Engineering Waseda University Tokyo Japan Institute for Data Processing and Electronics Karlsruhe Institute of Technology Germany

For high-performance embedded hard-real-time systems, ASICs and FPGAs hold advantages over generalpurpose processors and graphics accelerators (GPUs). However, developing signal processing architectures from scratch requires significant resources. Our design methodology is based on sets of configurable building blocks that provide storage, dataflow, computation, and control. Based on our building blocks, we generate hundreds of thousands of our dynamic streaming engine processors that we call DSEs. We store our DSEs in a repository that can be queried for (online) design space exploration. From this repository, DSEs can be downloaded and instantiated within milliseconds on FPGAs. If a loss of flexibility can be tolerated then ASIC implementations are feasible as well. In this article we focus on FPGA implementations. Our DSEs vary in cores, computational lanes, bitwidths, power consumption, and frequency. To the best of our knowledge we are the first to propose online design space exploration based on repositories of precompiled cores that are assembled of common building blocks. For demonstration purposes we map algorithms for image processing and financial mathematics to DSEs and compare the performance to existing highly optimized signal and graphics accelerators. © 2014 ACM.

关键词： Field programmable gate arrays (FPGA)

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Execution of Convolution Coding Method for FPGA in Industrial Automation using VERILOG HDL 7

Execution of Convolution Coding Method for FPGA in Industria...

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7th International Conference on computing Methodologies and Communication, ICCMC 2023

作者： Venusamy, Kanagaraj Kannadhasan, S. Vimalesh, A. Chandramohan, P. Shanmugam, M. Priyadarsini, K. Department of Mechatronics Engineering Rajalakshmi Engineering College Chennai India Department of Electronics and Communication Engineering Study World College of Engineering Coimbatore Chennai India Department of Data Science and Business Systems School of Computing SRM Institute of Science & Technology Kattankulathur Chennai India

ISBN: (纸本)9781665464086

In this paper, the performance study of the FPGA-based encoder is delivered and received with little errors given the large number of applications that employ digital communication to store and retrieve data recently. Forward Error Correction units a wireless communication system region that is essential. Several types of encryption methods have been measured, and the error is completely different. Convolution code writing approach, an honest technique used to rectify mistakes during the data transfer. Convolutional encoder area unit compelled to provide the output in the kind of register style with specified positions in the register. The areas in which the region is entirely arranged are likewise shown as arrows. The position of the registers provides probable state transitions wherein example, L is the register's length. Using these facts, the best way to execute of data transmission in digital communication channels is to correct errors in codes. FPGA device utilized in convolutional encoder's hardware implementation. Vivado and XILINX ISE are usedfor performance analysis. © 2023 IEEE.

关键词： Convolution

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A Model of the Russia's Agriculture Readiness for Digital Transformation 13

A Model of the Russia's Agriculture Readiness for Digital Tr...

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13th International Conference Management of Large-Scale System Development, MLSD 2020

作者： Kulba, Vladimir Medennikov, Viktor V.A. Trapeznikov Institute of Control Sciences of Ras Laboratory of Modular Data Processing and Control Systems Moscow Russia Federal Research Center "computer Science and Control" of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (纸本)9781728110943

The paper discusses the problems of the effective implementation of digital technology in Russia's agriculture and how to solve the same by comprehensive and integrative methods. We present a mathematical model of Russia's agricultural readiness for digital transformation. We consider the results of calculating several development scenarios of the sector digitalization. © 2020 IEEE.

关键词： Agriculture

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Exploring the Impact of Herbal Remedies on Autism Spectrum Disorder Using AGLSTM Analysis

Exploring the Impact of Herbal Remedies on Autism Spectrum D...

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Innovative computing, Intelligent Communication and Smart Electrical systems (ICSES), International Conference on

作者： Bagiyalakshmi N T. Veeramakali Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur

Autism is a personality disorder that can cause significant emotional, intellectual, and behavioral deficits. Autism is recognized as an illness on the spectrum because, while certain kids might have mild symptoms, others may have extensive life-challenging abnormalities. However, autistic people have unique characteristics and health goals and may react differently to conventional or herbal therapy than others. Herbal medications might be a possible approach to helping autistic people's bodies and brains. However, further research is needed to determine whether herbal therapy is useful for autistic individuals. To gain insight into how people think regarding herbal medication for autism, data must be processed promptly as it is generated, which may be accomplished using sentiment assessment, which analyzes polarization in writings. This paper proposes the AGLSTM Model, a hybrid model that solves the sentiment evaluation issue by combining LSTM with agglomerative clustering. The suggested system signifies text data into numerical vectors that illustrate text features such as the frequency of words and embeddings of phrases using the TF-IDF technique and the word2vec model. Every word becomes assigned to a cluster using a method known as clustering based on how similar it is to the cluster nucleus or other texts in the region. The outcome of the experiment is a set of clusters composed of sentences with comparable emotional content. The LSTM framework can detect long-term correlations between word patterns and classify feedback as positive or negative.

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Exploring Sentiment Detection in Healthcare: An Exhaustive Analysis

Exploring Sentiment Detection in Healthcare: An Exhaustive A...

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Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE), International Conference on

作者： Bagiyalakshmi N T. Veeramakali Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur

In our daily lives, sentiment analysis is essential. People usually make decisions after seeking advice from others. We used to rely on our judgments before the internet on the advice of our friends and relatives. But now, we have high-performance source sentiment analysis, which collects and analyses opinions from a variety of channels, including social media. To correctly represent emotion in a phrase, we must concentrate on idioms, sarcasm, negations, and context terms. A range of deep learning and machine learning techniques can be used to overcome the aforementioned issues. The aforementioned parameter will be used by the algorithm to identify the polarity of a statement. This study proposal covers the problems with sentiment analysis as well as its numerous levels. The review talks about the challenges and particularities of sentiment analysis. These have to do with issues like textual information, peculiarities of language, emotional vocabulary relevant to particular domains, and security and confidentiality of data. The report also emphasizes how sentiment analysis might promote public healthcare initiatives, boost pharmaceutical methods for making choices, as well as improve patient care.

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Spatial resolution for forest carbon maps

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science (New York, N.Y.) 2025年第6732期387卷 370-371页

作者： Laura Duncanson Neha Hunka Tommaso Jucker John Armston Nancy Harris Lola Fatoyinbo Christopher A Williams Jeff W Atkins Brett Raczka Shawn Serbin Michael Keller Ralph Dubayah Chad Babcock Mark A Cochrane Andrew Hudak George C Hurtt Paul M Montesano L Monika Moskal Taejin Park Sassan Saatchi Carlos A Silva Hao Tang Rodrigo Vargas Aaron Weiskittel Konrad Wessels Scott J Goetz Geographical Sciences University of Maryland College Park MD USA. School of Biological Sciences University of Bristol Bristol UK. World Resources Institute Washington DC USA. NASA Goddard Space Flight Center Greenbelt MD USA. Graduate School of Geography Clark University Worcester MA USA. US Department of Agriculture (USDA) Forest Service Southern Research Station New Ellenton SC USA. Department of Biology Virginia Commonwealth University Richmond VA USA. Computational and Information Systems Lab Data Assimilation Research Section National Center for Atmospheric Research Boulder CO USA. International Institute of Tropical Forestry USDA Forest Service Rio Piedras PR USA. Forest Resources Department University of Minnesota St. Paul MN USA. University of Maryland Center for Environmental Science Frostburg MD USA. Rocky Mountain Research Station USDA Forest Service Moscow ID USA. NASA Goddard Space Flight Center ADNET Systems Greenbelt MD USA. School of Environmental and Forest Sciences University of Washington WA USA. Bay Area Environmental Research Institute Moffett Field CA USA. NASA Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA. CTrees Pasadena CA USA. Forest Biometrics Remote Sensing and Artificial Intelligence Lab (SilvaLab) School of Forest Fisheries and Geomatics Science University of Florida Gainesville FL USA. Department of Geography National University of Singapore Singapore. Department of Plant and Soil Sciences University of Delaware Newark DE USA. Center for Research on Sustainable Forests University of Maine Orono ME USA. Geography and Geoinformation Science George Mason University Fairfax VA USA. School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff AZ USA.

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Revolutionizing Public Transport: RFID-Enabled Occupancy Monitoring and Frequency Analysis System

Revolutionizing Public Transport: RFID-Enabled Occupancy Mon...

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2024 International Conference on Communication, computing and Internet of Things, IC3IoT 2024

作者： Mageswaran, J. Uma Indumathi, G. Kalpana, A.V. Elangovan, G. Lalitha, S.D. Nalini, S. Sohanda, Mayank Kumar Dept. of Computer Science Engineering Amrita School of Computing Vengal Campus Tiruvallur DistTamil Nadu India Srm Institute Of Science And Technology Ramapuram India Srm Institute Of Science And Technology Department Of Data Science And Business Systems Kattankulathur India R.M.K Engineering College Department Of Computer Science And Engineering India Srm Institute Of Science And Technolog Department Of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350352689

Public bus stops in India are becoming more crowded due to the country's fast population expansion. People wait a long time for buses to come, then suddenly congregate around them when they do, packing the buses with people and pushing them up into the footboards, which causes accidents. An additional concern of overcrowding is theft. All of this is the result of numerous bus stops not having adequate information on when busses would arrive. The proposed work paves a very important role for the passengers. The passengers will be provided with the information of the arrival of next bus, seat occupancy and the total passengers inside the bus. The information about the seat occupancy, in-passengers and out-passengers is done with the help of Radio Frequency Identification (RFID) tags. The arrival of the next bus is determined by calculating the duration of the buses that are near using RFID readers placed in different bus stations. The count and the frequency will be interfaced in the web application. The passengers can check the application to know the occupancy and today's society where people can catch the right bus at the station and at the right time. This will solve the problems like waiting in bus stops and wasting time and going in a crowded bus. © 2024 IEEE.

关键词： Buses

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BAT: A Versatile Bipartite Attention-based Approach for Comprehensive Truth Inference in Mobile Crowdsourcing

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IEEE Transactions on Mobile computing 2025年

作者： Liu, Jiacheng Tang, Feilong Liu, Hao Chen, Long Yu, Yichuan Zhu, Yanmin Yu, Jiadi Hou, Xiaofeng Heng, Pheng-Ann The Chinese University of Hong Kong Department of Computer Science and Engineering 999077 Hong Kong Shanghai Jiao Tong University School of Computer Science Shanghai200240 China East China Normal University School of Data Science and Engineering China Simon Fraser University School of Computing Science Canada Huawei Technologies Co. Ltd China Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China

The proliferation of smart mobile devices has catalyzed the growth of Mobile CrowdSourcing (MCS) as a distributed problem-solving paradigm. MCS platforms heavily rely on advanced truth inference techniques to extract reliable information from diverse and potentially noisy crowd-contributed data. Existing truth inference models often made simplified assumptions about workers or tasks, employing complex Bayesian models or stringent data aggregation methods. These approaches tend to be task-specific, primarily limited to categorical labeling, making adaptations to other mobile computing scenarios labor-intensive. To address these limitations, we introduce the Bipartite Attention-driven Truth (BAT), a versatile approach tailored for mobile computing environments. BAT utilizes an Attributed Bipartite Graph (ABG) to holistically model the MCS process, with workers and tasks as nodes connected by edges representing answer-specific attributes. The approach employs a bipartite graph neural network with an innovative attention mechanism to assess the importance of different answers. BAT extends beyond categorical tasks to support numerical ones by incorporating novel feature representations and model extensions. Theoretical analyses clarify the link between answer similarity and worker expertise. Extensive experiments using diverse real-world datasets demonstrate BAT's superior performance compared to state-of-the-art categorical and numerical truth inference models, highlighting its effectiveness in mobile computing scenarios. © 2002-2012 IEEE.

关键词： Graph neural networks

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Discovering Personalized Characteristic Communities in Attributed Graphs 40

Discovering Personalized Characteristic Communities in Attri...

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40th IEEE International Conference on data Engineering, ICDE 2024

作者： Niu, Yudong Li, Yuchen Karras, Panagiotis Wang, Yanhao Li, Zhao School of Computing and Information Systems Singapore Management University Singapore University of Copenhagen Department of Computer Science Copenhagen Denmark School of Data Science and Engineering East China Normal University Shanghai China Zhejiang Lab Hangzhou China

ISBN: (纸本)9798350317152

What is the widest community in which a person exercises a strong impact? Although extensive attention has been devoted to searching communities containing given individuals, the problem of finding their unique communities of influence has barely been examined. In this paper, we study the novel problem of Characteristic cOmmunity Discovery (COD) in attributed graphs. Our goal is to identify the largest community, taking into account the query attribute, in which the query node has a significant impact. The key challenge of the COD problem is that it requires evaluating the influence of the query node over a large number of hierarchically structured communities. We first propose a novel compressed COD evaluation approach to accelerate the influence estimation by eliminating redundant computations for overlapping communities. Then, we further devise a local hierarchical reclustering method to alleviate the skewness of hierarchical communities generated by global clustering for a specific query attribute. Extensive experiments confirm the effectiveness and efficiency of our solutions to COD: they find characteristic communities better than existing community search methods by several quality measures and achieve up to 25 x speedups against well-crafted baselines. © 2024 IEEE.

关键词： attributed graph characteristic community community hierarchy influence

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