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IAENG International Journal of Computer Science 2021年第1期48卷 1-15页

作者： Mahdi, Mohammed Najah Ahmad, Abdul Rahim Ismail, Roslan Buhari, Adamu Muhammad Universiti Tenaga Nasional Malaysia Universiti Tenaga Nasional Malaysia Software Engineering Department College of College of Computing and Informatics Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia Faculty of Engineering Multimedia University Malaysia

As the web grows, finding information from large data repositories has become increasingly difficult not only due to inadequate number of results that are relevant, but also due to poor sorting of relevant results from those irrelevant. The present search engines (SEs) use the query and response lookup process that does not provide precise results. Thus, researchers have gone beyond the paradigm to explore a new class of method to seek information, which is called exploratory research that is open-ended and its faceted search can improve the overall search process. Besides, many studies have begun tapping into enhancement of web search results relevancy. The web reflects vast heterogeneity, varying structure, and massive in volumes. Therefore, it is rather difficult to seek accurate outcomes as desired. As such, visualisation and interactive graphics have been proposed as methods to manage massive amounts of results and to project essential features for the web pages. Additionally, search engine controls reconstruction and reformulation of queries. As such, a search engine is presented in this study by developing it on the cloud computing platform environment The search engine is based on the idea of improving visual exploratory search (VExSearch) while exploring information in the web. This particular notion reflects the process of seeking and combing through the vast information by using the coordinated visualisation method, apart from minimising the effort spent in seeking information per query. The VExSearch was evaluated for its capability and performance and later compared with IMDb SE and CloudMining SE. The comparative results showed that the VExSearch was 66% more accurate than the other SEs. VExSearch also seemed to provide the most relevant results among all the three SEs, aside from attaining an average improvement of 20% in terms of recall. © 2021, IAENG International Journal of Computer Science. All rights reserved.

关键词： Search engines

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Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need 38

Unlearnable 3D Point Clouds: Class-wise Transformation Is Al...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC. © 2024 Neural information processing systems foundation. All rights reserved.

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Hybrid Transfer Learning Approach for Emotion Analysis of Occluded Facial Expressions 6th

Hybrid Transfer Learning Approach for Emotion Analysis of ...

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6th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2023

作者： Pamod, Dilshan Charles, Joseph Hewarathna, Ashen Iranga Vigneshwaran, Palanisamy Lekamge, Sugeeswari Thuseethan, Selvarajah Department of Computing and Information Systems Sabaragamuwa University of Sri Lanka Belihuloya Sri Lanka Erlangen Germany Department of Software Engineering Sabaragamuwa University of Sri Lanka Belihuloya Sri Lanka School of Information Technology Deakin University Geelong Australia

ISBN: (纸本)9783031530814

The ability to recognise and interpret emotional expressions is crucial since emotions play a significant role in our daily lives. Emotions are multifaceted phenomena that affect our behavior, perception, and cognition. As a result, numerous machine-learning and deep-learning algorithms for emotion analysis have been studied in previous works. Finding emotion in an obscured face, such as one covered by a scarf or hidden in shadow, is considerably harder than in a complete face, though. This study explores the effectiveness of deep learning models in occluded facial emotion analysis through a transfer learning approach. The performance of two individual pre-trained models, MobileNetV2 and EfficientNetB3, is compared alongside a hybrid model that combines both approaches. This comparison is conducted using the FER-2013 dataset. The dataset consists of 35,887 images and categorizes emotions into seven emotional categories. The results indicate that the hybrid model attained the highest accuracy, with a score of 93.04% for faces occluded at the top and 92.63% for faces occluded at the bottom. Additionally, the study suggests that top-occluded faces displayed more pronounced emotional expressions in comparison to bottom-occluded faces. Overall, these findings imply that hybrid architecture, which was developed as a state-of-the-art model in the study, proves to be effective for analyzing emotions in facial expressions that are partially obscured. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning algorithms

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Research on PCB tiny displacement estimation method for ORB feature-guided FREAK descriptor enhancement 4

Research on PCB tiny displacement estimation method for ORB ...

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2024 4th International Conference on Artificial Intelligence and Industrial Technology Applications, AIITA 2024

作者： Yang, Duo Su, Yang Wu, Hongwei Yi, Pengfei Key Laboratory for Advanced Design and Intelligent Computing Ministry of Education School of Mechanical Engineering and Software Engineering Dalian University Dalian116622 China Olympic Circuit Technology Co. Ltd. Guangdong Jiangmen529700 China Co. Ltd. Dalian116622 China

Given the hurdles posed by existing techniques for identifying microscopic offsets in miniature printed circuit boards (PCBs), including their low accuracy and high iteration count, this study presents an innovative approach that measures micrometer offsets by utilizing the ORB feature-guided FREAK descriptor enhancement. It improves matching outcomes with a brute-force matcher and RANSAC via ORB feature extraction to guide FREAK descriptors for better feature uniqueness. A PCB small offset detection algorithm is developed with a homography matrix and a theoretical offset model. A novel distance threshold performance evaluation method for this suggested matching algorithm that objectively evaluates matching results is also proposed in this article. The proposed matching method outperforms alternative algorithms in precision and recall, according to its experiments. This research conducts simulation detection of PCB calibration bare boards and instance verification of real PCB boards by constructing a PCB tiny offset detection experimental system. The results show that micron-level detection precision can be achieved without iteration. © Published under licence by IOP Publishing Ltd.

关键词： engineering education

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Optimization Study of BP Neural Network Based on Genetic Algorithm

Optimization Study of BP Neural Network Based on Genetic Alg...

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2023 IEEE International Conference on Electrical, Automation and Computer engineering, ICEACE 2023

作者： Cai, Yongheng Zhou, Zhuye Li, Zehui School of Computing Zhuhai College of Science and Technology Zhuhai China School of Data Sciences Zhejiang University of Finance & Economics Hangzhou China School of Automation and Software Engineering Shanxi University Taiyuan China

ISBN: (纸本)9798350309614

In today's era of big data, neural networks play a pivotal role in fields such as image recognition and natural language processing. However, traditional Backpropagation (BP) neural networks often encounter challenges when dealing with complex problems, including slow convergence and getting stuck in local optima. To address these issues, this study employs a genetic algorithm as an optimization technique to optimize the weights and thresholds of BP neural networks. Training is conducted on a set of highly nonlinear mapping datasets to obtain the optimal weight and threshold configurations for the GA-BP model. Experimental results demonstrate that compared to traditional BP neural networks, the GA-BP model exhibits a 19.8% improvement in prediction accuracy, an approximately 9.20% increase in the coefficient of determination (R2), a reduction of approximately 62.50% in mean squared error (MSE), and a decrease of about 38.76% in root mean squared error (RMSE). Furthermore, the GA-BP model displays significantly accelerated convergence. The contribution of this research lies in proposing an optimization method that combines genetic algorithms with BP neural networks. This model not only enhances prediction accuracy compared to the standalone BP neural network but also significantly strengthens its generalization capabilities. As a result, it demonstrates substantial practical application potential across diverse datasets and application scenarios. © 2023 IEEE.

关键词： BP neural network genetic algorithm optimization algorithm

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Simulation of Computer Network Information Security Assessment Model Based on Data Mining 2

Simulation of Computer Network Information Security Assessme...

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2nd International Conference on Artificial Intelligence and Autonomous Robot Systems, AIARS 2023

作者： Liu, Yanjia Yong, Xi Hua, Baojian Yang, Jianhua Institute of Computing Technology Chinese Academy of Sciences Beijing100086 China Ministry of Water Resources Information Centre Beijing100053 China University of Science and Technology of China School of Software Engineering Jiangsu Suzhou215123 China Beijing Sinohonour Computing Technology Beijing100029 China

ISBN: (纸本)9798350324358

With the continuous growth of scie & tech, network technology has been widely used, which has brought great convenience to people's life and work. However, the rapid improvement of network technology has also given network viruses an opportunity, which has caused harm to the information security of computer users. In order to improve the adaptability to the network environment, it is more effective to use data mining (DM) to prevent and control viruses. Through the use of this technology, the control effect of network security management can be improved, and the effective support for the later network security development can be realized. This article will discuss the related modes of DM, study the practical application of DM to computer network virus defense, and build a computer network information security assessment model based on DM. The simulation results show that the proposed model can achieve a recall rate of 94.8% and an accuracy rate of 95.5%, both of which are better than the random forest model. DM has been effectively applied in the stage of protecting computer network virus, which greatly improves the security of computer network system, and then ensures the stability of computer system operation. © 2023 IEEE.

关键词： Data mining

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Enhancing SEO Compliance of JavaScript Web Frameworks through Automated Testing inside CI/CD Pipelines 11

Enhancing SEO Compliance of JavaScript Web Frameworks throug...

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11th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Ágh, Ján Makarova, Irina Dakić, Pavle Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 Slovakia Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia

This article aims to incorporate search engine optimization validation into the development process of JavaScript-based web applications, thus connecting two sides of optimizations, namely the selection of appropriate practices and their correct implementation. We summarize strategies for achieving search engine optimization (SEO) compliance in single-page applications (SPAs) and propose two distinct testing solutions aimed at addressing SEO concerns in modern web apps. Both approaches are incorporated into CI/CD pipelines, making it possible to enforce existing SEO strategies. The issue of visibility in search engines is especially characteristic for JavaScript-based frameworks. This is because of the way they load and render their content, are mostly unable to achieve satisfactory SEO scores and rankings. Due to the ever-increasing popularity of these frameworks, it is essential to identify and compare available optimization techniques to address this subject adequately. Here, we take a closer look at the SEO-friendly features of *** and *** frameworks and evaluate their capabilities using two mock e-commerce websites as examples. To fulfill our second objective, an approach to continuous SEO testing is presented. We discuss the results of similar CI/CD pipeline setups using distinct technologies and tools, in particular Jenkins and GitHub actions. The results show that by integrating specific tests focused on SEO into CI/CD pipelines, developers can identify crucial shortcomings of their product and eliminate them before they cause harm in the production environment. © 2024 Copyright for this paper by its authors.

关键词： Search engines

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Integration of Metaverse Recordings in Multimedia Information Retrieval 24

Integration of Metaverse Recordings in Multimedia Informatio...

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13th International Conference on software and Computer Applications, ICSCA 2024

作者： Steinert, Patrick Wagenpfeil, Stefan Frommholz, Ingo Hemmje, Matthias L. University Of Hagen Faculty Of Mathematics And Computer Science Hagen Germany Pfh Private University Of Applied Sciences Faculty Of Business Computing And Software Engineering Göttingen Germany University Of Wolverhampton School Of Mathematics And Computer Science Wolverhampton United Kingdom

ISBN: (纸本)9798400708329

This paper addresses the challenges in integrating Metaverse Recordings in Multimedia Information Retrieval as a new type of multimedia. Specifically, we describe the characteristics of video content and explain the key differences of a metaverse to other videos. We present a specialized process to analyze and index Metaverse Recordings. We demonstrate that existing techniques can be used for metaverse-specific retrieval, but need content-specific adaptions. Furthermore, we evaluate a prototypical implementation based on the proposed methods with respect to the impact on the retrieval process. © 2024 Owner/Author.

关键词： Multimedia systems

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K-Banhatti Sombor Invariants of Certain Computer Networks

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Computers, Materials & Continua 2022年第10期73卷 15-31页

作者： Khalid Hamid Muhammad Waseem Iqbal Abaid Ur Rehman Virk Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Mathematics University of SialkotSialkot51013Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Any number that can be uniquely determined by a graph is called a graph *** the last twenty years’countless mathematical graph invariants have been characterized and utilized for correlation ***,no reliable examination has been embraced to decide,how much these invariants are related with a network graph or molecular *** this paper,it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science,mathematics,chemistry,pharmacy,informatics and biology in context with physical and chemical structures and networks,because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or *** study solved the topology of a bridge graph/networks of three different types with two invariants KBanhatti Sombor Indices and its reduced *** deduced results can be used for the modeling of computer networks like Local area network(LAN),Metropolitan area network(MAN),and Wide area network(WAN),backbone of internet and other networks/structures of computers,power generation,bio-informatics and chemical compounds synthesis.

关键词： Bridge networks invariants k-banhatti sombor indices maple network graph molecular graph

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Optimization of Arrhythmia-based ECG-lead Selection for Computer-interpreted Heart Rhythm Classification

Optimization of Arrhythmia-based ECG-lead Selection for Comp...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Serhii Reznichenko Shijie Zhou Department of Computer Science and Software Engineering College of Engineering and Computing Miami University Oxford OH USA Department of Chemical Paper and Biomedical Engineering and Department of Computer Science and Software Engineering College of Engineering and Computing Miami University Oxford OH USA

The 12-lead ECG only has 8 independent ECG leads, which leads to diagnostic redundancy when using all 12 leads for heart arrhythmias classification. We have previously developed a deep learning (DL)-based computer-interpreted ECG (CIE) approach to identify an optimal 4-lead ECG subset for classifying heart arrhythmias. However, the clinical diagnostic criteria of cardiac arrhythmia types are often lead-specific, so this study is going to explore the selection of arrhythmia-based ECG-lead subsets rather than one general optimal ECG-lead subset, which could improve the classification performance for the CIE. The DL-based CIE model previously developed was used to learn 4 common types of heart arrhythmias (LBBB, RBBB, AF, and I-AVB) for identifying corresponding optimal ECG-lead subsets. A public dataset that splits into training (approx. 70%), validation (approx. 15%), and test (approx. 15%) sets from the PhysioNet Cardiology Challenge 2020 was used to explore the study. The results demonstrated that the DL-based CIE model identified an optimal ECG-lead subset for each arrhythmia: I, II, aVR, aVL, V1, V3, and V5 for I-AVB; I, II, aVR, and V3 for AF; I, II, aVR, aVF, V1, V3, and V4 for LBBB; and I, II, III, aVR, V1, V4, and V6 for RBBB. For each arrhythmia classification, the DL-based CIE model using the optimal ECG-lead subset significantly outperformed the model using the full 12-lead ECG set on the validation set and on the external test *** results support the hypothesis that using an optimal ECG-lead subset instead of the full 12-lead ECG set can improve the classification performance of a specific arrhythmia when using the DL-based CIE *** Relevance— Using an arrhythmia-based optimal ECG-lead subset, the classification performance of a deep-learning-based model can be achieved without loss of accuracy in comparison with the full 12-lead set (p<0.05).

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