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Developing phoneme-based lip-reading sentences system for silent speech recognition

CAAI Transactions on Intelligence Technology 2023年第1期8卷 129-138页

作者： Randa El-Bialy Daqing Chen Souheil Fenghour Walid Hussein Perry Xiao Omar HKaram Bo Li School of Engineering London South Bank UniversityLondonUK Faculty of Informatics and Computer Science British University in EgyptCairoEgypt School of Electronics and Informatics Northwestern Polytechnical UniversityXi'anChina

Lip-reading is a process of interpreting speech by visually analysing lip *** research in this area has shifted from simple word recognition to lip-reading sentences in the *** paper attempts to use phonemes as a classification schema for lip-reading sentences to explore an alternative schema and to enhance system *** classification schemas have been investigated,including characterbased and visemes-based *** visual front-end model of the system consists of a Spatial-Temporal(3D)convolution followed by a 2D *** utilise multi-headed attention for phoneme recognition *** the language model,a Recurrent Neural Network is *** performance of the proposed system has been testified with the BBC Lip Reading Sentences 2(LRS2)benchmark *** with the state-of-the-art approaches in lip-reading sentences,the proposed system has demonstrated an improved performance by a 10%lower word error rate on average under varying illumination ratios.

关键词： deep learning deep neural networks lip-reading phoneme-based lip-reading spatial-temporal convolution,transformers

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Classification of Arrhythmias 12-Lead ECG Signals Based on 1 Dimensional Convolutional Neural Networks

Classification of Arrhythmias 12-Lead ECG Signals Based on 1...

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2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024

作者： Kurniawan, Arief Triwibowo, Bayu Aditya Fandiantoro, Dion Hayu Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Computer Engineering Indonesia

ISBN: (纸本)9798350364101

Heart disease is the highest cause of death in the world. Arrhythmia is an abnormality in the rhythm of the heartbeat. The heart beats too fast, too slow, or irregularly. Arrhythmias are not always dangerous, e.g., someone who does excessive activity has a faster heart rate. Then, a diagnosis is needed to classify arrhythmias. One method used is ECG (Electrocardiogram) signal analysis. The ECG signal consists of P, QRS Complex, and T waves. The morphology of the QRS is used for arrhythmia classification. Currently, cardiologists analyze ECG signals by observing directly. This method is depending on the level of expertise of the cardiologist. Previous research classified arrhythmias based on the QRS morphology from a single ECG lead. As 12-lead ECG devices have now become standard in ECG examinations because abnormalities can be observed from multiple angles. This study proposes the classification of arrhythmias in 12-lead ECG signals based on the morphology of QRS complex waves using a deep learning 1-dimensional Convolutional Neural Network. The output of deep learning is the classification of arrhythmias into four classes, namely: Normal, Right Bundle Branch Block, Premature Ventricular Contraction, and Atrial Premature Beat. The outcome of the proposed system is that each QRS segment is used as input for deep learning, which can improve classification performance compared to the classification carried out by each lead. The experimental results show the method can be done well, with an average Accuracy, Precision, Sensitivity, and F1-Score were 98.8%, 99.2%, 99.2%, and 99.2%, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Enhancing Software Cost Estimation Using Feature Selection and Machine Learning Techniques

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computers, Materials & Continua 2024年第12期81卷 4603-4624页

作者： Fizza Mansoor Muhammad Affan Alim Muhammad Taha Jilani Muhammad Monsoor Alam Mazliham Mohd Su’ud Department of Software Engineering FAST-National University of Computer&Emerging SciencesKarachi75030Pakistan Faculty of Engineering Science and Technology IQRA UniversityKarachi72500Pakistan Department of Computer Science Bahria UnivesityKarachi74800Pakistan Faculty of Computing Riphah International UniversityIslamabad44600Pakistan Faculty of Computing and Informatics Multimedia University(MMU)Cyberjaya63100SelangorMalaysia

Software cost estimation is a crucial aspect of software project management,significantly impacting productivity and *** research investigates the impact of various feature selection techniques on software cost estimation accuracy using the CoCoMo NASA dataset,which comprises data from 93 unique software projects with 24 *** applying multiple machine learning algorithms alongside three feature selection methods,this study aims to reduce data redundancy and enhance model *** findings reveal that the principal component analysis(PCA)-based feature selection technique achieved the highest performance,underscoring the importance of optimal feature selection in improving software cost estimation *** is demonstrated that our proposed method outperforms the existing method while achieving the highest precision,accuracy,and recall rates.

关键词： Machine learning software cost estimation PCA hyper parameter feature selection

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Implementation of Multi Attribute Utility Theory Method for Government Assistance Recipient Recommendation System in Dadapayu Village, Semanu District, Gunung Kidul Regency 15

Implementation of Multi Attribute Utility Theory Method for ...

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15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Yumarlin, M.Z. Rahayu, Sri Bororing, Jemmy Edwin Kurniawan, Safar Dwi Fitriastuti, Fatsyahrina Rozak, Muhamad Department of Informatics Faculty of Engineering Universitas Janabadra Indonesia Diploma Program in Computer Engineering Politeknik Harapan Bersama Indonesia

ISBN: (纸本)9798331300579

The Indonesian government is furnishing help in the form of" Bantuan Langsung Tunai(BLT)" or the Direct Cash backing program in order to make up for the recent increase in the price of energy oil painting(BBM), which has easily had an impact on the lives of the destitute and the general public. The BLT program is enforced throughcross-sectoral collaboration, where institutions unite grounded on their separate functions and duties. Aid distribution opinions are grounded on multiple applicable rudiments and aren't primarily determined by one criterion when the MAUT fashion is applied. A system's recommended feasibility score of 78 is attained from the evaluation findings of system testing, which were carried out using a questionnaire exercising the System Usability Scale(SUS) approach. With a score in the "Acceptable" range, the system is supposed good since it's adequately satisfactory.. © Grenze Scientific Society, 2024.

关键词： Electric grounding

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Leveraging Artificial Intelligence for Active Cyber Defense Against to Advanced Persistent Threats to Homeland Security

Leveraging Artificial Intelligence for Active Cyber Defense ...

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2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Özbay, Recep Yavanoǧlu, Uraz Graduate School of Informatics Gazi University Dept. Of Computer Forensics Ankara Turkey Gazi University Faculty of Engineering Dept. of Computer Engineering Ankara Turkey

ISBN: (纸本)9798350364910

Increasing cyber threats have rendered traditional security solutions such as firewalls and intrusion-detection/prevention systems insufficient in providing adequate protection against advanced persistent threats to homeland security. To enhance protection, the implementation of active cyber defense is recommended, offering alternative yet effective measures against these threats. This paper examines the phases of the cyber kill chain, one of the cyber defense techniques, which has been enhanced to analyze and understand advanced persistent threats. It explains the use of deception, slowdown, and counterattacks for active cyber defense. Additionally, the utilization of artificial intelligence in active cyber defense techniques is discussed. Finally, the paper elucidates how these techniques can be employed within the scope of active cyber defense to enhance security. © 2024 IEEE.

关键词： Network intrusion

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Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

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computers, Materials & Continua 2023年第3期74卷 5035-5048页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Adel Sulaiman Muhammad Akram Ahmad Salman Khan Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO *** a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development *** frameworks have been developed focusing on guiding software systemmanagers concerning offshore software ***,none of these studies delivered comprehensive guidelines for managing the whole process of *** is a considerable lack of research working on managing OSMO from a vendor’s ***,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s *** study validated the preliminary OSMO process model via a case study research *** results showed that the OSMO process model is applicable in an industrial setting with few *** industrial data collected during the case study enabled this paper to extend the preliminary OSMO process *** refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.

关键词： Offshore outsourcing process model model validation vendor challenges case study

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Resilient TCP Variant Enabling Smooth Network Updates for Software-Defined Data Center Networks

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Tsinghua Science and Technology 2024年第5期29卷 1615-1632页

作者： Abdul Basit Dogar Sami Ullah Yiran Zhang Hisham Alasmary Muhammad Waqas Sheng Chen Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China and also with Department of Informatics and SystemsUniversity of Management and TechnologyLahore 54660Pakistan Department of Computer Science Shaheed Benazir Bhutto UniversitySheringalUpper Dir 18050Pakistan School of Computer Science Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha 61421Saudi Arabia Department of Computer Engineering Faculty of Information TechnologyUniversity of BahrainSakheer 32038Bahrainand also with School of EngineeringEdith Cowan UniversityPerth WA 6027Australia School of Electronics and Computer Science University of SouthamptonSouthamptonSO171BJUK

Network updates have become increasingly prevalent since the broad adoption of software-defined networks(SDNs)in data *** TCP designs,including cutting-edge TCP variants DCTCP,CUBIC,and BBR,however,are not resilient to network updates that provoke flow *** this paper,we first demonstrate that popular TCP implementations perform inadequately in the presence of frequent and inconsistent network updates,because inconsistent and frequent network updates result in out-of-order packets and packet drops induced via transitory congestion and lead to serious performance *** look into the causes and propose a network update-friendly TCP(NUFTCP),which is an extension of the DCTCP variant,as a *** are used to assess the proposed *** findings reveal that NUFTCP can more effectively manage the problems of out-of-order packets and packet drops triggered in network updates,and it outperforms DCTCP considerably.

关键词： software defined data center networks network updates DCTCP out-of-order packets packet drop SDN

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Improving SVM Performance in Determining Cost and Kernel Parameter Values Through Grid Search 2

Improving SVM Performance in Determining Cost and Kernel Par...

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2nd International Conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Sylvia, Visca Lydia, Maya Silvi Nasution, Benny Benyamin Universitas Sumatera Utara Faculty of Computer Science and Information Technology Medan Indonesia Politeknik Negeri Medan Department of Computer Engineering and Informatics Medan Indonesia

ISBN: (纸本)9798350351613

The purpose of this study is to improve the performance of Support Vector Machine (SVM) algorithm in sentiment analysis of trainee reviews through parameter optimization using Grid Search. Trainee reviews were taken from the Vocational and Productivity Training Center (BBPVP) Medan, which is the context of this study. The method used includes collection and preprocessing of review data, followed by the application of SVM for sentiment analysis. Grid Search is used to optimize the cost and kernel parameters of SVM. The results show that after optimization, the resulting SVM model shows significant performance improvement compared to the model before optimization. Accuracy increased from 68.75% to 71.96%, with improvements in other metrics such as precision, recall, and F1 score. These findings suggest that Grid Search is an effective method to optimize SVM parameters in sentiment analysis, providing a more accurate evaluation of the effectiveness of training programs at BBPVP Medan. This research makes an important contribution by applying hyperparameter optimization to SVM and suggests the application of this method for similar analysis in the future. © 2024 IEEE.

关键词： Support vector machines

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Comparative Analysis of Edge Detection Algorithms with Particle Swarm Optimization for Enhanced Image Processing 11

Comparative Analysis of Edge Detection Algorithms with Parti...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Rahayu, Sri Nurtantio Andono, Pulung Pujiono Zainul Fanani, Ahmad Dian Nuswantoro University Faculty of Computer Science Department of Informatics Engineering Semarang Indonesia Institut Teknologi Garut Computer Science Department Garut Indonesia

ISBN: (纸本)9798350389654

Edge detection plays an important role in various fields by identifying object boundaries and supporting advanced image analysis, such as segmentation, recognition, and tracking. Many edge detection algorithms, such as Canny, Laplacian, and Prewitt, have been developed to address issues such as noise sensitivity, computational complexity, and detection accuracy. This research compares the optimized algorithms using Particle Swarm Optimization (PSO). The results of this study show that the optimized algorithm provides better performance based on the evaluation conducted using entropy, Mean Squared Error (MSE), and computation time, and has practical implications. This research also determines the most effective edge detection technique in various image processing scenarios, thus contributing to the optimization of image analysis workflows in real-world contexts. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Factors Influencing Participation in Data Crowdsourcing: A Systematic Literature Review 8

Factors Influencing Participation in Data Crowdsourcing: A S...

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8th International Conference on informatics and Computing, ICIC 2023

作者： Panjaitan, Re. Miracle Setiawan, Budi Darma Brawijaya University Faculty of Computer Science Department of Informatics Engineering Malang Indonesia

ISBN: (纸本)9798350342604

Crowdsourcing is becoming a trending concept used by many organizations, without being limited to a particular field. As of 2018, crowdsourcing was used by 85% of the largest worldwide companies. This trend of crowdsourcing would be increasing as it offers numerous advantages to companies in achieving their goals, such as the capability of obtaining data and information from the crowd. The crowd-provided data and information contain the essence of human ingenuity, which enables companies to do problem-solving with a human-centered approach. The more contributors participate, the more likely the crowdsourcing program will succeed. Several studies give different lists of factors that influence the participation rate of the crowd. However, there's a lack of discussion about the factors and it leads to a situation where organizations need to examine many factors when developing a crowdsourcing platform to get great crowd engagement. Therefore, this study conducted a Systematic Literature Review (SLR) to perform screening and analysis of preceding research systematically. The factors in each of these literatures are generated by considering the case of the study or the region of the people related to the research. This diversity helps identify the factors influencing contributor participation in data crowdsourcing from research all over the world. A study reflecting on these research findings would help answer research questions thoroughly. This study found that there are 19 factors that positively influence contributor participation in data crowdsourcing out of 26 factors found in the 16 selected documents. © 2023 IEEE.

关键词： Crowdsourcing

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