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2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021

作者： Vanijkachorn, Pavarit Visutsak, Porawat Kmutnb Faculty of Applied Science Department of Computer and Information Science Bangkok10800 Thailand

ISBN: (纸本)9781665416566

Activity analysis systems or activity recognition systems for the elderly is recently a part of the smart home systems design. This assisted system normally helps the elderly to live alone in a house, safely and improve a quality of life. Therefore, learning to recognize which activities are safe is necessary for classifying the activity of the elderly. Furthermore, this information will give us some insights to understand the basic daily lives of the elderly and it also helps us to monitor activity and health information of the elderly. In this paper, we collected activities data using the multi-sensor motion sensors embedded inside the smartwatch (Fitbit). We also present the novel method for detecting and recognizing the activity using Deep Convolutional LSTM. In brief, this paper shows that the proposed method yields 88.425% of accuracy for activity classification. The paper also compares the results with our previous work which used Backpropagation Neural Networks as a classifier (78% of accuracy). © 2021 IEEE.

关键词： COVID-19

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Neighborhood Modularization‑based Artificial Bee Colony Algorithm for Disassembly Planning with Operation Attributes

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Chinese Journal of Mechanical Engineering 2022年第6期35卷 165-177页

作者： Hongfei Guo Linsheng Zhang Yaping Ren Leilei Meng Zhongwei Zhou Jianqing Li GBA and B&R International Joint Research Center for Smart Logistics School of Intelligent Systems Science and EngineeringInstitute of Physical InternetJinan University(Zhuhai Campus)Zhuhai 519070China School of Computer Science Liaocheng UniversityLiaocheng 252059China Faculty of Information Technology Macao University of Science and TechnologyMacao 999078China

The recycling and remanufacturing of end-of-life products are significant for environmental protection and resource *** is an essential process of remanufacturing end-of-life *** disassembly plans help improve disassembly efficiency and reduce disassembly *** paper studies a disassembly planning problem with operation attributes,in which an integrated decision of the disassembly sequence,disassembly directions,and disassembly tools are ***,a mathematical model is formulated with the objective of minimizing the penalty cost caused by the changing of operation ***,a neighborhood modularization-based artificial bee colony algorithm is developed,which contains a modular optimized ***,two case studies with different scales and complexities are used to verify the performance of the proposed approach,and experimental results show that the proposed algorithm outperforms the two existing methods within an acceptable computational time.

关键词： End-of-life products Disassembly planning Artificial bee colony Neighborhood modularization

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Distributed Reaction systems Viewed as Multi-Agent systems 22

Distributed Reaction Systems Viewed as Multi-Agent Systems

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22nd IEEE International Symposium on Intelligent systems and Informatics, SISY 2024

作者： Mitrana, Victor Paun, Andrei Paun, Mihaela Polytechnic University of Madrid Department of Information Systems Madrid Spain National Institute of R&D for Biological Sciences Department of Bioinformatics Bucharest Romania University of Bucharest Bucharest Faculty of Mathematics and Computer Science Bucharest Romania University of Bucharest Faculty of Administration and Business Bucharest Romania

ISBN: (纸本)9798350385601

A reaction system is defined by three sets formed by the abstractions of the chemicals existing in a cell involved in a reaction, namely the set of reactants, which facilitate the reaction, the set of inhibitors, which are substances that block the reaction, and the set of products resulting during the reaction. We define a distributed reaction system, which is formed by several reaction systems and an environment, and advocate a strong connection with multi-agent systems, especially with the blackboard model. We briefly discuss how these systems might be used for simulating the function of thalamus in animals. Finally, we propose two possible ways of using distributed reaction systems for computing sets of numbers and sets of strings. © 2024 IEEE.

关键词： Multi agent systems

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An overview of common emotion models in computer systems 45

An overview of common emotion models in computer systems

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45th Jubilee International Convention on information, Communication and Electronic Technology, MIPRO 2022

作者： Horvat, M. Stojanovic, A. Kovacevic, Z. University of Zagreb Faculty of Electrical Engineering and Computing Department of Applied Computing Zagreb Croatia Zagreb University of Applied Sciences Department of Computer Science and Information Technology Zagreb Croatia

ISBN: (纸本)9789532331035

Emotions are an omnipresent and important factor in the interaction and communication between people. Since emotions are an indispensable part of human life, it would accelerate the progress of artificial intelligence and other fields of science that require data about emotions if they could be adequately described by computer systems. Today there are many different theories of affect, but few of them are used in affective computing. Other areas of computing also benefit from structured and expressive data models of the affective domain, such as human-computer interaction and brain-computer interfaces. Typical tasks include automated recognition and analysis of emotional states, mental fatigue, individual motivation, vigilance and stress resilience. In this paper four often used models of emotion and cognitive behavior are listed and their properties explained: discrete, dimensional, appraisal and action tendency models. For each model, algorithms are provided for similarity measures that can be used to determine the relatedness between different stimulation and estimation artefacts in their respective emotion spaces. The goal of this article is to help professionals find the optimal emotion model for their research and quickly become familiar with data modelling of affective states. © 2022 Croatian Society MIPRO.

关键词： Brain computer interface

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Blockchain-Powered e-Wallet: Enhancing Security and Fraud Detection in Online Payments 1

Blockchain-Powered e-Wallet: Enhancing Security and Fraud De...

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1st International Conference on Cryptography and information Security, VCRIS 2024

作者： Bui-Huu, Dong Le-Nhat, Tan Nguyen-An, Khuong Ho Chi Minh University of Banking Faculty of Management Information Systems Department of Computer Science Ho Chi Minh City Viet Nam Fulbright Vietnam University Undergraduate Faculty Ho Chi Minh city Viet Nam Faculty of Computer Science and Engineering Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Ho Chi Minh City Viet Nam

ISBN: (纸本)9798331529949

Cashless payment has been emphasized in many countries, especially since the outbreak of the COVID-19 pandemic. Various payment methods have emerged, among which electronic wallets (e-wallets) have become a popular online payment method due to their convenience, flexibility, and time and cost savings for users. However, alongside the growth in the number and value of transactions, e-wallets face challenges from increasingly sophisticated and complex security threats, fraud, and forgery, originating both internally and externally, causing severe financial losses and diminishing customer trust. To ensure the safety of e-wallet, we propose an architecture developed based on the permissioned blockchain platform-Hyperledger Fabric, following a microservice model with high-performance APIs that can be easily integrated into e-wallet systems at an optimal cost without requiring complex infrastructure investments. Thanks to blockchain's immutable, transparent, and decentralized storage nature, this solution effectively monitors and supports real-time fraud detection and forgery prevention, ensuring the safety, security, and integrity of users' online payment transactions. Furthermore, this solution also provides users with immediate notifications via Email or SMS when an attack or fraud is detected on the e-wallet. © 2024 IEEE.

关键词： Blockchain

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Two-Mode Biomedical Sensor Build-up:Characterization of Optical Amplifier

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computers, Materials & Continua 2022年第3期70卷 5487-5501页

作者： Usman Masud Fathe Jeribi Mohammed Alhameed Faraz Akram Ali Tahir Mohammad Yousaf Naudhani Faculty of Electrical and Electronics Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Electrical Communication Engineering University of KasselKassel34127Germany College of Computer Science&Information Technology Jazan UniversityJazan45142Saudi Arabia Faculty of Engineering and Applied Sciences Riphah International UniversityIslamabad44000Pakistan Faculty of Information&Communication Technology Balochistan University of Information TechnologyEngineering and Management SciencesQuetta

Intracavity absorption spectroscopy is a strikingly sensitive technique that has been integrated with a two-wavelength setup to develop a sensor for human *** factors are considered in such a scenario,out of which Relative Intensity Noise(RIN)has been exploited as an important parameter to characterize and calibrate the said *** the performance of an electrical based assessment arrangement which has been developed in the laboratory as an alternative to the expensive Agilent setup,the optical amplifier plays a pivotal role in its development and operation,along with other components and their ***,the investigation and technical analysis of the amplifier in the system has been explored in *** algorithm developed for the automatic measurements of the system has been effectively deployed in terms of the laser’s *** this in perspective,a frequency dependent calibration has been pursued in depth with this scheme which enhances the sensor’s efficiency in terms of its *** this way,our investigation helps us in a better understanding and implementation perspective of the proposed system,as the outcomes of our analysis adds to the precision and accuracy of the entire system.

关键词： Biomedical sensor cavity optomechanics spectroscopy relative intensity noise semiconductor laser diode

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Fast Learning Network Algorithm for Voice Pathology Detection and Classification

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Multimedia Tools and Applications 2025年第17期84卷 18567-18598页

作者： Albadr, Musatafa Abbas Abbood Ayob, Masri Tiun, Sabrina AL-Dhief, Fahad Taha Al-Daweri, Muataz Salam Homod, Raad Z. Abbas, Ali Hashim Department of Petroleum Project Management College of Industrial Management of Oil and Gas Basrah University for Oil and Gas Al-Basrah Iraq Faculty of Information Science and Technology CAIT Universiti Kebangsaan Malaysia Selangor Bangi Malaysia Department of Communication Engineering School of Electrical Engineering Universiti Teknologi Malaysia UTM Johor Bahru Johor Malaysia Department of Information Systems College of Economics Management & Information Systems University of Nizwa Nizwa Oman Department of Oil and Gas Engineering Basrah University for Oil and Gas Al-Basrah Iraq Department of Computer Technical Engineering College of Information Technology Imam Ja’afar Al-Sadiq University Al-Muthanna Iraq

The utilisation of ML (Machine Learning) techniques in the detection of the VP (Voice Pathology) has recently gained a lot of consideration. However, these efforts still have several drawbacks such as: I) the accuracy rates of most previous works are still not promising and need more improvement. II) The majority of the previous works have concentrated on the task of VP detection only and disregarded the task of VP classification. III) Most of the previous works have been assessed based on a single voice data only like the vowel /a/, and the other vowels (/i/, and /u/) and sentences were disregarded. IV) The majority of the previous works performance were assessed utilising a limited evaluation metrics. Recently, one of the utmost effective ML techniques is FLN (Fast Learning Network), it is an efficient technique for data classification. However, the FLN classifier has not been implemented to the problem of VP detection and classification. Therefore, this research proposes the FLN classifier with MFCC (Mel-Frequency Cepstral Coefficient) features in order to enhance the accuracy of the VP detection and classification. The FLN classifier has the ability to a) solve both binary and multiclass classification issues, b) eliminate overfitting, as well as c) operate akin to a NN (Neural Network) structure while employing the principles of a kernel-based SVM (Support Vector Machine). In this research, the SVD (Saarbrucken Voice Database) dataset was utilised to assess the FLN classifier performance in the VP detection and classification. The assessment of the proposed FLN classifier was conducted based on two phases: the first phase includes all the voice samples of the SVD dataset with the sentences and vowels (i.e., /a/, /i/, and /u/) which are pronounced in neutral, high, and low pitches. While the second phase uses the voice samples of the utmost common 3 pathology types (i.e., paralysis, polyp, and cyst) based on the vowel /a/ that is pronounced in neutral pitch. The

关键词： Classification (of information)

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Enable Business Users to Embed Dynamic Database Content in Existing Web-Based systems UsingWeb Components and GenericWeb Services 20

Enable Business Users to Embed Dynamic Database Content in E...

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20th International Conference on Web information systems and Technologies, WEBIST 2024

作者： Schmidt, Andreas Münch, Tobias Karlsruhe Germany Department of Computer Science and Business Information Systems Karlsruhe University of Applied Sciences Karlsruhe Germany Münch Ges. für IT Solutions MbH Gewerbering 1 Lohne49393 Germany Chemnitz University of Technology Chemnitz Germany

ISBN: (纸本)9789897587184

In our digitalized world and under the economic pressure of competition, every company must react flexibly to opportunities and problems that arise. One way to cope with these challenges is to use web-based Enterprise Resource Planning (ERP) or Customer Relationship Management (CRM) systems, which provide significant functionality inside their system range. Third-party systems often have to be integrated with ERP or CRM systems but cannot be connected, for instance, because of limited Application Programming Interfaces (API) or data structures. Therefore, such tasks are complex and time-consuming and must be done by software engineers, who are limited resources in today's enterprise context. However, HTML documents can be integrated with web-based systems such as ERP or CRM, and HTML creation is not limited to the software engineering workforce. Our low-code environment, which is based on W3C web components standards and RESTful web services with state-of-the-art authentication approaches, could solve the shortage because we empower business developers to embed dynamic database content declaratively in static HTML pages or web-based systems such as WordPress or SoftEngine ERP-Suite. Our system also allows the declarative integration of forms for creating/modifying and deleting data records (CRUD functionality). The low-code web components access the database via the RESTful service. The API of the RESTful service abstracts the database manufacturerspecific characteristics, such as the storage format of the metadata. Copyright © 2024 by SCITEPRESS.

关键词： HTML

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EEG and fMRI Artifact Detection Techniques: A Survey of Recent Developments

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SN computer science 2023年第5期4卷 528页

作者： Mili, Rahma Bouaziz, Bassem Maalel, Ahmed Gargouri, Faiez Multimedia InfoRmation Systems and Advanced Computing Laboratory (MIRACL) Faculty of Economics and Management of Sfax University of Sfax Sfax 3021 Tunisia Multimedia InfoRmation Systems and Advanced Computing Laboratory (MIRACL) Higher Institute of Computer and Multimedia of Sfax Sfax 3021 Tunisia RIADI Laboratory National School of Computer Sciences University of Manouba Manouba 2010 Tunisia Higher Institute of Applied Sciences and Technology University of Sousse Sousse 4003 Tunisia

The evolution of different techniques for exploring cerebral activity and the development of signal processing and analysis methods have enabled a better understanding of the dynamic cerebral mechanisms in favor of fine diagnosis and characterization of certain diseases such as dementia and epilepsy. Integration of functional magnetic resonance imaging (fMRI) with electroencephalography (EEG) has offered the possibility of understanding new insights into neuroscientific studies because of the higher temporal and spatial measurements of brain activity when compared with the use of each technique separately. However, the experimental limitations of fMRI/EEG are mainly the numerous artifacts, mainly due to switching of magnetic field gradients and cardiac activity. To provide a comprehensive overview of this research area, a systematic mapping study has been conducted. This mapping study aims to identify the topics studied within the artifacts’ detection in EEG and fMRI data, as well as examine the adopted research methodologies, identify the gaps in the current research and point to directions for future research. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Artifacts Deep learning EEG fMRI Systematic mapping study

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Research on the Relationship between Mobile Network Data and COVID-19 Cases 14

Research on the Relationship between Mobile Network Data and...

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14th IEEE International Conference on computer Research and Development, ICCRD 2022

作者： Tian, Jianmeng Zhao, Haoyuan Information Science and Technology University Computer School of Beijing Beijing China Fraser University Faculty of Applied Sciences of Simon VancouverBC Canada

ISBN: (纸本)9781728177212

During this nearly two-years-long pandemic period, the COVID-19 impacts people's lives dramatically, many people were forced to stay at home by the government's lockdown policy, and they also need to work and study at home. Therefore, there is an equivalent impact on networks as people are more dependent on them. But there are only a limited number of research has been done in this intersection area between the pandemic and networks. So, we want to fill this gap. In this paper, we will study the mobile network data from U.S. Federal Communications Commission (FCC) and COVID-19 cases data from the U.S. centers for disease control and prevention (CDC), then use machine learning to investigate the relationship between mobile network data and COVID-19 cases. We will discuss other related works, which used other methods or investigated this topic in other regions, then we will introduce our machine learning methods, experiments and give the conclusion. © 2022 IEEE.

关键词： COVID-19

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