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Intelligent Machine Learning with Metaheuristics Based Sentiment Analysis and Classification

Computer Systems science & engineering 2023年第1期44卷 235-247页

作者： R.Bhaskaran S.Saravanan M.Kavitha C.Jeyalakshmi Seifedine Kadry Hafiz Tayyab Rauf Reem Alkhammash Department of Information Technology PSNA College of Engineering and TechnologyDindigul624622India Department of Electronics and Communication Engineering K.Ramakrishnan College of TechnologyTrichy621112India Department of Electronics and Communication Engineering K.Ramakrishnan College of TechnologyTiruchirappalli621112India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Computer Science Faculty of Engineering&InformaticsUniversity of BradfordBradfordUnited Kingdom English Department University CollegeTarabaTaif UniversityTaif21944Saudi Arabia

Sentiment Analysis(SA)is one of the subfields in Natural Language Processing(NLP)which focuses on identification and extraction of opinions that exist in the text provided across reviews,social media,blogs,news,and so *** has the ability to handle the drastically-increasing unstructured text by transform-ing them into structured data with the help of NLP and open source *** current research work designs a novel Modified Red Deer Algorithm(MRDA)Extreme Learning Machine Sparse Autoencoder(ELMSAE)model for SA and *** proposed MRDA-ELMSAE technique initially performs pre-processing to transform the data into a compatible ***,TF-IDF vec-torizer is employed in the extraction of features while ELMSAE model is applied in the classification of ***,optimal parameter tuning is done for ELMSAE model using MRDA technique.A wide range of simulation analyses was carried out and results from comparative analysis establish the enhanced effi-ciency of MRDA-ELMSAE technique against other recent techniques.

关键词： Sentiment analysis data classification machine learning red deer algorithm extreme learning machine natural language processing

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Fabrication and characterization of ceramic hollow shaped from the local kaolin intended for the filtration

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Materials Research Innovations 2023年第1期27卷 13-19页

作者： Asli, Boubekeur Mokhtar, Adel Belouatek, Aissa Department of Process Engineering Faculty of Science and Technology University of Relizane Relizane Algeria Faculty of Applied and Exact Sciences University of Oran1 Oran Algeria Structure Elaboration and Application of Molecular Materials Laboratory Faculty of Exact Sciences and Informatics Abdelhamid Ibn Badis University of Mostaganem Mostaganem Algeria

Ceramic membranes are one of the emerging separation technologies with extremely high separation factors. In this work, natural Kaolin clay collected from the western of Algeria was characterized in detail to see its feasibility in a ceramic membrane preparation. The ceramic membrane was prepared by solid-state reactive firing under the slip casting method. The aim is to favor the mullite phase, once the alumina is added a part will be dispersed in the mullite matrix to form a mullite-alumina composite. The mineralogical, morphological structure, particle size distribution, thermal stability, and chemical composition of prepared alumina oxide membrane were carried out using several techniques. They reveal the apparition of two main phases the mullite and the alumina. The kaolin provides the membrane with a well homogeneous morphology, good hydrophobicity, and thermal stability. The obtained membrane presented a mesoporous membrane character that can use successfully for ultrafiltration applications. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Kaolin

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Exploring the Use of Particle and Kalman Filters for Obstacle Detection in Mobile Robots

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2023年第4期67卷 384-393页

作者： Gyenes, Zoltán Bölöni, Ladislau Szádeczky-Kardoss, Emese Gincsainé Department of Control Engineering and Information Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Muegyetem rkp. 3. BudapestH-1111 Hungary Department of Computer Science University of Central Florida 4328 Scorpius St OrlandoFL32816-2362 United States

The present study aims to explore the adaptation of estimation methodologies, specifically Particle filters and Kalman filters, for the purpose of determining the position and velocity vector of obstacles within the operational workspace of mobile robots. These algorithms are commonly employed in the motion planning tasks of mobile robots for the estimation of their own position. The proposed methodology utilizes LiDAR sensor data to estimate the position vectors and calculate the velocity vectors of obstacles. Additionally, an uncertainty parameter can be determined using the introduced perception method. The performance of the newly adapted algorithms is evaluated through comparison of the absolute error in position and velocity vector estimations. © 2023 Budapest University of technology and Economics. All rights reserved.

关键词： Mobile robots

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Developing Engagement in the Learning Management System Supported by Learning Analytics

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Computer Systems science & engineering 2022年第7期42卷 335-350页

作者： Suraya Hamid Shahrul Nizam Ismail Muzaffar Hamzah Asad W.Malik Department of Information System Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Department of Computing School of Electrical Engineering and Computer Science(SEECS)National University of Sciences and Technology(NUST)IslamabadPakistan

Learning analytics is an emerging technique of analysing student par-ticipation and *** recent COVID-19 pandemic has signiﬁcantly increased the role of learning management systems(LMSs).LMSs previously only complemented face-to-face teaching,something which has not been possible between 2019 to *** date,the existing body of literature on LMSs has not analysed learning in the context of the pandemic,where an LMS serves as the only interface between students and ***,productive results will remain elusive if the key factors that contribute towards engaging students in learning are notﬁrst identiﬁ***,this study aimed to perform an exten-sive literature review with which to design and develop a student engagement model for holistic involvement in an *** required data was collected from an LMS that is currently utilised by a local Malaysian *** model was validated by a panel of experts as well as discussions with *** is our hope that the result of this study will help other institutions of higher learning determine factors of low engagement in their respective LMSs.

关键词： Engagement analysis learning analytics learning management system student engagement

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Estimation of the Maximum Permissible PV Power to be Connected to the MV Grid

Estimation of the Maximum Permissible PV Power to be Connect...

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2023 International Conference on Information and Digital Technologies, IDT 2023

作者： Szultka, Agata Szultka, Seweryn Czapp, Stanislaw Makowski, Kamil Sedlacek, Peter Energa-Operator Sa Gdansk Poland Gdansk University of Technology Faculty of Electrical and Control Engineering Gdansk Poland University of Zilina Faculty of Management Science and Informatics Zilina Slovakia

ISBN: (纸本)9798350305869

In recent decades, a significant increase in the share of renewable energy sources in power grids at various voltage levels has been observed. A number of articles have been published highlighting emerging problems in low-voltage grids with a large share of prosumers and in medium- and high-voltage grids to which photovoltaic (PV) plants are connected. The article analyzes the medium-voltage grid in terms of the possibility of connecting maximum PV power to it, while maintaining the criterion of the proper voltage level in the whole grid. The selection of suitable locations for PV power plants is analyzed, as well as the expected effect of the possible modernization of the grid - replacement of the main line with lines having a larger cross-section. As a result of the analysis, the percentage profits from both presented solutions (PV power plants optimal locations and main power line modernization) have been compared. © 2023 IEEE.

关键词： Electric power distribution

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IT-Security Risk Based Approach for Secure Operation of Distributed Data Platforms in Supply Chains

IT-Security Risk Based Approach for Secure Operation of Dist...

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2024 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2024

作者： Voß, Marvin Kallisch, Jonas Runge, Maxim Theus, Tobias Niemann, Karl-Heinz Wunck, Christoph Faculty I - Electrical Engineering and Information Technology University of Applied Sciences and Arts Hannover Germany Department of Engineering Section Electrical Engineering and Computer Science University of Applied Sciences Leer Emden Germany Faculty of Mathematics Informatics and Statistics Ludwig Maximilian University Munich Germany

ISBN: (纸本)9798350386097

This paper presents the development of a secure data platform designed to enhance operational efficiency and to facilitate cross-company collaboration within the manufacturing supply chain. The platform is designed to ease secure information exchange while maintaining the sovereignty of each participant, leveraging standardized security features and advanced technologies such as federated learning. Security measures are based on a comprehensive risk analysis, which methodically identifies, assesses, and mitigates potential threats. Moreover, federated learning models that are not transparent are utilized. This allows data owners to maintain control over sensitive information within the consortium. The described approach markedly enhances both security and operational collaboration across the industry, representing a crucial stride towards more integrated and efficient supply chain management in manufacturing. © 2024 IEEE.

关键词： Risk analysis

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Nudge Application Methods for Enhancing Information Security Countermeasures 13

Nudge Application Methods for Enhancing Information Security...

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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Tanimoto, Shigeaki Usami, Shinko Hatashima, Takashi Kanai, Atsushi Japan International University Ibaraki Japan Chiba Institute of Technology Chiba Japan Chiba Institute of Technology Faculty of Social System Science Chiba Japan Nippon Telegraph and Telephone Corporation Ntt Social Informatics Laboratories Tokyo Japan Hosei University Faculty of Science and Engineering Tokyo Japan

ISBN: (纸本)9798350355079

As information security threats become more diverse, it is important for users to take security countermeasures themselves and through the system to prevent such damage. However, the rate of security implementation in Japan is low, and there is a lack of interest in and awareness of security. These facts suggest that in order to improve security, it is necessary to introduce measures that change people's security awareness and behavior, in addition to technical security countermeasures. This study proposes a new security countermeasure using the concept of "nudges"proposed by Richard H. Thaler et al. to promote information security countermeasures from an intrinsic perspective, which is a finding of behavioral economics. For the top five threats in the IPA's "10 Major Threats to Information Security 2023", we propose a total of 30 security prevention countermeasures using the six principles of nudges. Specifically, we suggest offering incentives such as paid leave to employees who are not infected with malware, establishing a unified security policy for the entire supplier, and prioritizing countermeasures against cyber-attacks, etc. We qualitatively assessed the effectiveness of these security prevention countermeasures. These results suggest that the proposed method can contribute to the enhancement of information security countermeasures. © 2024 IEEE.

关键词： Information hiding

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Price Prediction of Seasonal Items Using Time Series Analysis

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Computer Systems science & engineering 2023年第7期46卷 445-460页

作者： Ahmed Salah Mahmoud Bekhit Esraa Eldesouky Ahmed Ali Ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business *** are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal *** lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series *** proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based ***,this research tuned a set of well-known predictive models on a real-life *** models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear ***,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are ***,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined *** obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

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Value Creation of Flue Gas for Hydrogen and Power Production Using RSOFC System 5th

Value Creation of Flue Gas for Hydrogen and Power Production...

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Proceedings of the 5th International Conference on Clean Energy and Electrical Systems - Proceedings of CEES 2023

作者： Mungkalasiri, Woranee Mungkalasiri, Jitti Chemical Engineering Department Engineering Faculty Thammasat School of Engineering Thammasat University Pathumthani Khlong Luang Thailand Technology and Informatics Institute for Sustainability National Science and Technology Development Agency Pathumthani Khlong Luang Thailand

ISBN: (纸本)9789819938872

Flue gas is an exhaust gas generated through the combustion process of fossil fuels which consisted of CO2. For low-carbon society, flue gas treatment or utilization should be considered. In this work, value creation of flue gas producing hydrogen and electrical power using reversible solid oxide fuel cell (RSOFC) was proposed. RSOFC is the integration of SOEC and SOFC operations. The SOEC operation requires electrical power to produce hydrogen and the SOFC operation consumes hydrogen to produce electrical power. The RSOFC was studied via process simulation by ASPEN Plus program. The objective was to evaluate the optimal operating conditions of RSOFC which can produced maximum net power. The results revealed that the RSOFC system with condition of minimum SOEC power consumption should be operated as it achieved electrical power benefit. The optimal operating conditions for RSOFC were 1000°C of SOEC temperature, 1 bar of SOEC pressure, 1000°C of SOFC temperature and 3 bar of SOFC pressure. The net power production of RSOFC was 0.88 kW/m2. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Flue gases

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Comparison of *** and Spring Boot in Web Development 15

Comparison of *** and Spring Boot in Web Development

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15th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2023

作者： Novac, Ovidiu Constantin Ghiurau, David Novac, Mihaela Cornelia Gordan, Cornelia Emilia Oproescu, Mihai Bujdoso, Gyongyi Mihalca, Vlad Ovidiu University of Oradea Electrical Engineering and Information Technology Faculty Department of Computers and Information Technology Oradea Romania University of Oradea Management in Information Technology Electrical Engineering and Information Technology Faculty Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electrical Engineering Oradea Romania University of Oradea Electrical Engineering and Information Technology Faculty Department of Electronics and Telecommunications Oradea Romania University of Pitesti Faculty of Electronics Communication and Computer Science Department of Electronics Computers and Electrical Engineering Pitesti Romania University of Debrecen Faculty of Informatics Department of Computer Science and Library and Information Science Debrecen Hungary School of Engineering Sciences University of Oradea Electrical Engineering and Information Technology Faculty Oradea Romania

ISBN: (纸本)9798350321388

In this paper we present two types of server implementation, we will look at the advantages and disadvantages of each technology. *** server application, built with ***, a single threaded server which will treat the requests in an asynchronous manner, with a non-blocking principle, whilst Spring Boot is a more robust and more common approach of a server technology with the benefits of having a strongly typed architecture and multiple threads available. These types of application will behave the same, making almost impossible to tell the difference between a *** and a Spring Boot web server. © 2023 IEEE.

关键词： Node.Js non-blocking single-multi threaded Spring Boot web server

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