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Aspect Level Songs Rating Based Upon Reviews in English

computers, Materials & Continua 2023年第2期74卷 2589-2605页

作者： Muhammad Aasim Qureshi Muhammad Asif Saira Anwar Umar Shaukat Atta-ur-Rahman Muhammad Adnan Khan Amir Mosavi Department of Computer Science Bahria University Lahore54000Pakistan Lahore Institute of Science and Technology Lahore 54792Pakistan Department of Multidisciplinary Engineering Texas A&M UniversityCollege Station77843USA Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam 31441Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

With the advancements in internet facilities,people are more inclined towards the use of online *** service providers shelve their items for *** users post their feedbacks,reviews,ratings,*** the use of the *** enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these *** Analysis(SA)is a technique that performs such decision *** research targets the ranking and rating through sentiment analysis of these reviews,on different *** a case study,Songs are opted to design and test the decision *** aspects of songs namely music,lyrics,song,voice and video are *** the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a *** machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are *** performed the best with 74.99%*** are validated using K-Fold.

关键词： Machine learning natural language processing songs reviews:sentiment analysis songs rating aspect level sentiment analysis reviews analysis text classification music

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A Fused Machine Learning Approach for Intrusion Detection System

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computers, Materials & Continua 2023年第2期74卷 2607-2623页

作者： Muhammad Sajid Farooq Sagheer Abbas Atta-ur-Rahman Kiran Sultan Muhammad Adnan Khan Amir Mosavi School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam 31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of *** interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and *** learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit *** intrusion detection system controls the flow of network traffic with the help of computer *** deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network *** this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network *** Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious *** proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

关键词： Fused machine learning heterogeneous network intrusion detection

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Senkerik, Roman Byrski, Aleksander Guzowski, Hubert Janku, Peter Kadavy, Tomas Oplatkova, Zuzana Kominkova Matusu, Radek Pluhacek, Michal Pekar, Libor Smolka, MacIej Viktorin, Adam Tomas Bata University A.I. Lab Faculty of Applied Informatics Department of Informatics and Artificial Intelligence Zlin Czech Republic Tomas Bata University Faculty of Applied Informatics Department of Automation and Control Engineering Zlin Czech Republic Institute of Computer Science Agh University of Science and Technology Krakow Poland

ISBN: (纸本)9798350337020

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics. © 2023 IEEE.

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Steel Billet Continuous Induction Heating–Numerical Model and Advanced Control

Steel Billet Continuous Induction Heating–Numerical Model a...

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2013 International Conference on applied Mechanics,Materials,and Manufacturing(AMMM 2013)

作者： Juraj Kapusta Juraj Camber Gabriel Hulkó Institute of Automation Measurement and Applied InformaticsFaculty of Mechanical EngineeringSlovak University of Technology

Nowadays,the achievement of proper steel billets temperature profile is not the only design priority of induction heaters for hot forming applications. Due to its high operating costs,its design is constantly improving in terms of electrical and thermal efficiency. Therefore the more efficient multi-coil design starts to be more used in industrial practice. Numerical model of mentioned heater based on partial differential equations were solved by finite element method in virtual software environment. Primary goal of computer modeling was to investigate the thermal dynamics of four-module heater working in steady-state operation regime. Obtained data were applied to design an advanced control circuit based on distributed parameter systems theory. This may open up the opportunity to make further progress in induction heaters design.

关键词： Induction heating of steel Material properties Virtual software environments Temperature field Control Distributed parameter system

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Extruder Barrel Temperature Field Control Using the Lumped Input and Distributed Output Approach

Extruder Barrel Temperature Field Control Using the Lumped I...

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International Conference on Process Control

作者： Slavomir Lipar Pavol Noga Gabriel Hulko Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology

ISBN: (纸本)9781479909261

Modeling and control of the extruder temperature field is discussed, a process governed by a nonlinear partial differential equation. Utilizing finite element approximation a discretized input/output representation of the system is created with the inputs being powers of heaters and output the extruder temperature field. Local linearization is applied at the operating point and the controller is designed based on the lumped-input and distributed-parameter-output systems approach, using the time-space decoupling of system's dynamics. Results are verified experimentally.

关键词： Distributed parameter systems Extrusion Finite element method Nonlinear partial differential equations Temperature control

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Control of Continuous Steel Billet Induction Heater as Distributed Parameter System

Control of Continuous Steel Billet Induction Heater as Distr...

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International Conference on Process Control

作者： Juraj Camber Juraj Kapusta Gabriel Hulko Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology

ISBN: (纸本)9781479909261

Industrial induction heating represents the environmentally clean, contactless method of steel heating. Same time it has high energy consumption, so in recent years, more efficient modular topology of heaters were introduced. Due to its multiple power modules, there is a possibility to apply the distributed parameter system control theory. By the usage of COMSOL Multiphysics solution, the model in the form of lumped-input and distributed-parameter-output system has been built. The process control is performed on the relations between the coil currents fed into four separate modules of heating device and desired billet temperature profile.

关键词： Distributed parameter system Induction heating Temperature field Control COMSOL Virtual software environments

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Development of a remote access control laboratory using xPC Target and virtual reality modeling language

Development of a remote access control laboratory using xPC ...

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2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010

作者： Lee, Ka Wai Truong, Nguyen-Vu Rhodes, Brad McLaren, James Wang, Liuping School of Electrical and Computer Engineering RMIT University Melbourne Australia Institute of Applied Mechanics and Informatics Vietnam Academy of Science and Technology Ho Chi Minh city Viet Nam

ISBN: (纸本)9781424466238

In this paper, we present the development of a remote access control laboratory at RMIT university which allows users to perform experiments on real hardware through the internet. The web based system consists of an internal server linked to an xPC Target real time machine which communicates with a DC Motor control module via relevant DAQ interfaces. In this set up, we attempt to replace the expensive setup of IP camera or video server by a realistic virtual reality model. This enhances the experiment's flexibility and reduces the cost of implementation while providing more interactive visualization and reality feeling of the real system to the users. In addition, the software also features with multiple login database system allowing students to observe or perform experiments under supervision remotely from the admin server.

关键词： DC motors

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Data Communication and Networks 1

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丛书名： Advances in Intelligent Systems and Computing

1000年

作者： Lakhmi C. Jain George A. Tsihrintzis Valentina E. Balas Dilip Kumar Sharma

ISBN: (数字)9789811501326

ISBN: (纸本)9789811501319

This book gathers selected high-quality papers presented at the International Conference on Computing, Power and Communication Technologies 2019 (GUCON 2019), organized by Galgotias university, India, in September 2019. The content is divided into three sections – data mining and big data analysis, communication technologies, and cloud computing and computer networks. In-depth discussions of various issues within these broad areas provide an intriguing and insightful reference guide for researchers, engineers and students alike.

关键词： Communications engineering, Networks Mobile and Network Security Data Mining and Knowledge Discovery Big Data Data engineering

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Using Semantic Web Mining technologies for personalized e-Learning experiences

Using Semantic Web Mining technologies for personalized e-Le...

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4th IASTED International Conference on Web-Based Education, WBE 2005

作者： Markellou, Penelope Mousourouli, Ioanna Spiros, Sirmakessis Tsakalidis, Athanasios Research Academic Computer Technology Institute 61 Riga Feraiou str. 26221 Patras Greece University of Patras Computer Engineering and Informatics Department 26504 Patras Greece Technological Education Institute of Messolongi Department of Applied Informatics in Administration and Economics 30200 Messolongi Greece

ISBN: (纸本)0889864802

The challenge of the Semantic Web Mining technologies in the e-Learning domain can relate to the provision of personalized experiences for the users. Particularly, these applications can take into consideration the individual needs and requirements of learners. In this paper, we propose a framework for personalised e-Learning based on aggregate usage profiles and a domain ontology. We have distinguished two stages in the whole process, one of offline tasks that includes data preparation, ontology creation and usage mining and one of online tasks that concerns the production of recommendations.

关键词： Ontology

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Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

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computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique Mohamed Habib Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting *** is why an automated weapon detection system is *** automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good ***,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection *** models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance *** research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key *** proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur *** proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 *** results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are *** reached 0.010 s per frame compared to the 0.17 s of the Faster *** is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

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