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16th IEEE International Conference on Intelligent systems and Knowledge Engineering, ISKE 2021

作者： Fen, Li Fen Lei, Zhou Ting, Chen Huaiyin Institute of Technology Faculty of Computer and Software Engineering Research Center for Logic and Intelligent Computation National-Local Joint Engineering Lab of System Credibility Automatic Verification Huaian China

ISBN: (纸本)9781665405539

Aiming at the problem of low accuracy of simple classification model, based on the drinking water data set of kaggle official website, integrated learning models is proposed, which improves the precision and accuracy of binary classification of drinking water quality. K-fold cross validation was performed to measure model consistency. The effect of set classifier is higher than that of simple classifier. © 2021 IEEE.

关键词： Water quality

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Fast Division Algorithm for Finite Real Number 16

Fast Division Algorithm for Finite Real Number

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16th IEEE International Conference on Intelligent systems and Knowledge Engineering, ISKE 2021

作者： Chen, Ting Li, Fenfen Lin, Jinbao National-Local Joint Engineering Lab of System Credibility Automatic Verification Huaiyin Institute of Technology Faculty of Computer and Software Engineering Research Center for Logic and Intelligent Computation Huai'an China

ISBN: (纸本)9781665405539

The data representation and division for finite real number in computers has always been a hot topic in the fields of scientific research and engineering technology. With the research of existing real number division algorithm, design, improvement and adjustment for data structure, algorithm and programming language, and realize the fast division for finite real number. The algorithm can apply to the engineering requirement of finite real number of 506 bits. It replaces the commonly used trial division method with a comparison method, reducing the time complexity of the algorithm. The experimental results demonstrate the correctness and efficiency of the algorithm. The division of the algorithm uses comparison instead of trial division, which reduces the time complexity of the algorithm from O(n2) to O(n). The experimental results show that the algorithm is correct and efficient. © 2021 IEEE.

关键词： Computational complexity

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Aspect Extraction in Sentiment Analysis Based on Emotional Affect Using Supervised Approach 4

Aspect Extraction in Sentiment Analysis Based on Emotional A...

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4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Maitama, Jaafar Zubairu Idris, Norisma Abdi, Asad Bimba, Andrew Thomas Universiti Malaya Faculty of Computer Science and Information Technology Department of Artificial Intelligence Kuala Lumpur50603 Malaysia University of Twente Department of Industrial Engineering and Business Information System Netherlands

ISBN: (纸本)9780738131702

Aspect based sentiment analysis (ABSA) is regards as the most demanding area of research in the field of text mining and natural language processing. In the last decade, people tend to be more interested in consulting online media outlets to make decisions concerning products or events. However, the existing ABSA approaches alone are not sufficient in providing comprehensive information required to make an informed decision. Most of the early studies focused on the binary classification of 'positive' and 'negative' to predict an overall sentiment of a review, which reduced the effectiveness in decision making towards the entities. Even though earlier studies on SA are centered on aspect extraction, there are limited works that effectively combine aspect extraction with emotional affects such as surprise, sadness and happiness, which consequently leads to incomplete meaning of a content. In this paper, we investigate a problem involving aspects in relation to emotional affects. To propose a novel supervised approach for the aspect extraction with their associated emotion classes in sentiment analysis (SA), we conducted an analysis of some prominent ABSA approaches. This research work will lead to a more accurate results of SA and could assist both novice and prominent researchers in comprehending the relationship between aspects and emotions in SA considering its sematic role in business intelligence. © 2021 IEEE.

关键词： Sentiment analysis

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EDGE COLORING OF PRODUCTS OF SIGNED GRAPHS

arXiv

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arXiv 2023年

作者： Janczewski, Robert Turowski, Krzysztof Wróblewski, Bartlomiej Department of Algorithms and System Modeling Faculty of Electronics Telecommunication and Informatics Gdańsk University of Technology ul. Narutowicza 11/12 Gdańsk Poland Theoretical Computer Science Department Faculty of Mathematics and Computer Science Jagiellonian University ul. Lojasiewicza 6 Kraków Poland

In 2020, Behr defined the problem of edge coloring of signed graphs and showed that every signed graph (G, σ) can be colored using exactly ∆(G) or ∆(G) + 1 colors, where ∆(G) is the maximum degree in graph G. In this paper, we focus on products of signed graphs. We recall the definitions of the Cartesian, tensor, strong, and corona products of signed graphs and prove results for them. In particular, we show that (1) the Cartesian product of ∆-edge-colorable signed graphs is ∆-edge-colorable, (2) the tensor product of a ∆-edge-colorable signed graph and a signed tree requires only ∆ colors and (3) the corona product of almost any two signed graphs is ∆-edge-colorable. We also prove some results related to the coloring of products of signed paths and cycles. © 2023, CC BY.

关键词： Graphic methods

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A Mobile Cloud Architecture for M-Commerce Business Application’s Execution Performance

A Mobile Cloud Architecture for M-Commerce Business Applicat...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Sadaf Yasmin Swati Mishra Asharul Islam Rashid Hussain Faculty of Management Suresh Gyan Vihar University Jaipur India Department of Information System College of Computer Science King Khalid University Abha K.S.A Moti Babu Instute of Technology Bihar Engineering University Bihar India

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Many researchers have come up with different ways to build a business model architecture for efficient services to run m-commerce applications. The framework for developing mobile commerce applications needs to change at the same time as the IT expansion and business transformation. We are pursuing a theoretical business framework to find an optimal solution for the seamless service-oriented m-commerce application performance. In this approach, we identify the components of m -commerce applications that could reduce mobility barriers and improve application execution time and device energy efficiency. This led us to propose a framework for m-commerce application performance that uses the Mobile Cloud Computing (MCC) solutions. This plan focuses on making the application run faster and use less energy, and making it easier for users to move around. We help mobile commerce application developers make smart RDMCA (Resource-Demanding M-commerce Applications) that provide good services for mobile commerce businesses and consumers. A theoretical proposed business framework is being set up to find an optimal solution for service-oriented m -commerce application performance. In this way, we find the important parts of the m -commerce system (signal range determiner) that help make the application run faster, use less energy, and make it easier to move around. We think that improving this framework will help mobile commerce app developers to make RDMCA’s that provide good services for both mobile commerce enterprises and end users.

关键词： Performance evaluation Cloud computing Energy consumption Image processing computer architecture Energy efficiency Computational efficiency

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Ant: An Efficient Lossless Compression Algorithm for IoT Time Series Data

Ant: An Efficient Lossless Compression Algorithm for IoT Tim...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Junhui Li Guangping Xu Hongzhang Yang Yulei Wu School of Computer Science and Engineering Tianjin University of Technology Tianjin China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin China Key Laboratory of Computer Vision and System Ministry of Education China Faculty of Science and Engineering University of Bristol Bristol U.K

In various applications in Internet of Things like industrial monitoring, large amounts of floating-point time series data are generated at an unprecedented rate. Efficient compression algorithms can effectively reduce the size of data, enhance transmission performance and storage efficiency, and simultaneously lower storage costs. Therefore, there is a need for lightweight and efficient stream compression algorithms. In this paper, we propose a novel lossless floating-point data compression algorithm called Ant. The main idea is to encode double-precision floating-point numbers into integer form, calculate the delta between adjacent values, and then convert the delta into unsigned integers. This encoding method effectively reduces storage costs and improves data compression efficiency. Extensive experiments on real-world datasets demonstrate that our algorithm achieves compression speeds at least as fast as state-of-the-art streaming methods, and a 63% relative improvement in average compression rate.

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Performance Evaluation Customer Access Network Using Difference Modulation Technique 1st

Performance Evaluation Customer Access Network Using Differe...

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1st International Symposium on systems Modelling and Simulation, SMS 2024

作者： Mugunthan, Sivaguru Abdul Rahman, Juwairiyyah Abu Hassan, Hasliza Muslim, Norliana Ab Rahman, Mohammad Syuhaimi Department of Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronic and System Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia

ISBN: (纸本)9789819646128

Modeling Fiber To The Home (FTTH) networks involves several technical aspects and design considerations to enable effective and high-quality service delivery. This research seeks to boost the received signal quality for end-users inside a FTTH network. In order to create suitable and high-quality FTTH networks, this study will simulate FTTH networks utilizing network feasibility criteria, with an emphasis on BER and Q-factor. The signal distribution inside access networks is improved using Wavelength Division Multiplexing (WDM) and 10G-Passive Optical Network (PON) technology is used since it can deliver a fourfold improvement in downstream data transfer rates per user. Simulation result using Optisystem 21 software, by setting transmitter wavelengths of 1490 nm and 1550 nm with a loss of 0 dB for a maximum of 2 users for total access based on the Q-factor calculation, which must be more than 6, while the BER must be less than 1 × e−9. system performance parameters that demonstrate Q-factor and Bit Error Rate (BER) give good quality and good performance is also shown by eye pattern in optical simulation. For 1490 nm, the highest Q-factor for 2 users is 35.8226, with a minimum BER of 2.4360 × 10−281. For 1550 nm, the highest Q-factor is 15.3668 (in phase) and 14.8087 (in quadrature), with minimal BER values of 1.3674 × e−53 (in phase) and 6.4291 × e−50 (in quadrature). Good performance is also shown by eye pattern in optical simulation that displays amplitude signals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Q factor measurement

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A Cloud-Based Offloading Process for MCommerce Application’s Performance in Cloud Environment

A Cloud-Based Offloading Process for MCommerce Application’...

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International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

An interest in cloud computing is transforming and developing information technology continuously for business and personal needs. Most e-commerce companies are migrating and converting services and applications for the rich resources provided through cloud platforms. This is a new business era that helps change the cloud. A process, state, or concept is defined as transformation. Through a dynamic process, it shows the technological transformation as the world changes and adapts to external and internal forces. Companies invest their capital in developing IT infrastructure, maintaining, and updating hardware, and software, and improving their services. The cloud-based transformation is an excellent method for establishing a fresh service-oriented, value-effective, adaptable, and adaptable technologies. Switching from the IT infrastructure to services as a pay-per-use business model is done using the IT service model. The latest trends in cloud computing technology and next-generation models are rented. Moreover, m-commerce applications are based on mobile execution performance, which is the major concern of e-commerce industries. As we know, there are three major obstacles of mobile devices natures: (1) Resource constraint device (2) Client mobility and (3) High energy consumption, moreover this is the major m-commerce applications performance challenges. When doing complicated computer work, the device battery will run out quickly and need to be charged again and again. We want to provide an overview of the concept, process, and research area of offloading computation for the energy efficiency of smartphones. The issues and challenges in computing offloading for mobile cloud environments are discussed.

关键词： Performance evaluation Cloud computing Adaptation models Computational modeling Companies Switches Software

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A Development of Object Detection system based on Deep Learning Approach to Support the Laparoscope Manipulating Robot (LMR)

A Development of Object Detection System based on Deep Learn...

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2022 International Electrical Engineering Congress, iEECON 2022

作者： Sonsilphong, Suphachoke Sonsilphong, Amornthep Hormdee, Daranee Khampitak, Kovit Khon Kaen University Data Science Health Informatics Program Academic Affairs Faculty of Medicine Khon Kaen Thailand Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Embedded System RD Group Department of Computer Engineering Faculty of Engineering Khon Kean Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

This paper presents the development of an object detection system based on the deep learning approach of computer vision to support the laparoscopic surgical robotic position control system. The system comprises two main phases, the training phase, and the real-time operating phase. In the training phase, a modified YOLOv4 algorithm is proposed to be adopted within the Darknet framework for training the weights of detection models. The best detection model is then selected to be assigned to the object detector in the real-time operating phase. The validation result of the detection model across the experiment datasets is 90% accuracy on average during the training phase. To validate the viability of real-time object detection, the proposed system was implemented in two test-cases of gynecologic surgery with the soft-body cadavers. © 2022 IEEE.

关键词： Laparoscopy

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Alert and Response of Earthquake and Tsunami for Community Based Disaster Risk Reduction 2

Alert and Response of Earthquake and Tsunami for Community B...

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2nd International Conference on Sciences and technology Applications, ICOSTA 2020

作者： Retno Susilorini, Rr M. I. Pamudji, Andre Kurniawan Sanjaya, Ridwan Ismail, Amrizarois Amasto, Ardhito Hayyu Department of Infrastructure and Environmental Engineering Faculty of Environmental Science and Technology Soegijapranata Catholic University Semarang Indonesia Master Program of Environmental and Urban Studies Faculty of Environmental Science and Technology Soegijapranata Catholic University Semarang Indonesia Department of Information System Faculty of Computer Science Soegijapranata Catholic University Semarang Indonesia

Indonesia had been suffered by earthquake and tsunami for many centuries. Since many lives have taken by tsunami strikes, alert and response system are very important as important part of Disaster Risk Reduction, especially in area with high population density. This research conducted in Kangkung fishing village in Bandar Lampung coastal area which is an earthquake and tsunami prone area. The aim of the research is to study alert and response of Community Based Disaster Risk Reduction. The research conducted by qualitative method and purposive-descriptive approach. There were 53 respondents which participated in the survey and interview. It is reported that "Smart Resilient City"model suitable for community needs of alert and response of earthquake and tsunami disaster. This research meets conclusion that "Smart Resilient City"model may become a great solution in Community Based Disaster Risk Reduction to cope with the hazard of earthquake and tsunami comprehensively and sustainably. © Published under licence by IOP Publishing Ltd.

关键词： Surveys

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