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arXiv 2023年

作者： Thomas, Annie Graduate Program in Computer Science Faculty of Graduate Studies The University of Western Ontario LondonON Canada

A new three dimensional approach to the chaos game representation of protein sequences is explored in this thesis. The basics of DNA, the synthesis of proteins from DNA, protein structure and functionality and sequence alignment techniques are presented. The mathematical background needed for understanding the chaos game representation and fractal analysis are briefly discussed. An account of the existing literature on the chaos game representation of DNA sequences and a detailed account of the chaos game representation of protein sequences in two dimensions with its advantages and limitations are presented. We explore a new three dimensional approach to the chaos game representation of protein sequences (3D-CGR) and study its ability a) to determine protein sequence similarity and differences, b) to study the effect of dinucleotide biases at amino acid level on the 3D-CGR derived protein homology, and c) to identify sequence similarity based on shuffled motifs that could be used for studying protein evolution due to exon shuffling. © 2023, CC BY-NC-ND.

关键词： Proteins

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TAGE: Trustworthy Attribute Group Editing for Stable Few-shot Image Generation 16

TAGE: Trustworthy Attribute Group Editing for Stable Few-sho...

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16th International Conference on Signal Processing Systems, ICSPS 2024

作者： Zhang, Ruicheng Huang, Guoheng Huo, Yejing Yuan, Xiaochen Zhou, Zhizhen Wu, Shiting Zhong, Guo School of Computer Science and Technology Guangdong University of Technology Guangzhou510006 China Faculty of Applied Sciences Macao Polytechnic University China Huizhou Boluo Power Supply Bureau Guangdong Power Grid Co. Ltd. 516001 China School of Information Science and Technology Guangdong University of Foreign Studies Guangzhou510006 China

ISBN: (纸本)9781510689251

Generative Adversarial Networks (GANs) have emerged as a prominent research focus for image editing tasks, leveraging the powerful image generation capabilities of the GAN framework to produce remarkable results. However, prevailing approaches are contingent upon extensive training datasets and explicit supervision, presenting a significant challenge in manipulating the diverse attributes of new image classes with limited sample availability. To surmount this hurdle, we introduce TAGE, an innovative image generation network comprising three integral modules: the Codebook Learning Module (CLM), the Code Prediction Module (CPM) and the Prompt-driven Semantic Module (PSM). The CPM module delves into the semantic dimensions of category-agnostic attributes, encapsulating them within a discrete codebook. This module is predicated on the concept that images are assemblages of attributes, and thus, by editing these category-independent attributes, it is theoretically possible to generate images from unseen categories. Subsequently, the CPM module facilitates naturalistic image editing by predicting indices of category-independent attribute vectors within the codebook. Additionally, the PSM module generates semantic cues that are seamlessly integrated into the Transformer architecture of the CPM, enhancing the model’s comprehension of the targeted attributes for editing. With these semantic cues, the model can generate images that accentuate desired attributes more prominently while maintaining the integrity of the original category, even with a limited number of samples. We have conducted extensive experiments utilizing the Animal Faces, Flowers, and VGGFaces datasets. The results of these experiments demonstrate that our proposed method not only achieves superior performance but also exhibits a high degree of stability when compared to other few-shot image generation techniques. © 2025 SPIE.

关键词： Image coding

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Self-Evaluation of Large Language Model based on Glass-box Features

Self-Evaluation of Large Language Model based on Glass-box F...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Huang, Hui Qu, Yingqi Liu, Jing Yang, Muyun Xu, Bing Zhao, Tiejun Lu, Wenpeng Faculty of Computing Harbin Institute of Technology Harbin China Baidu Inc. Beijing China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Jinan China

ISBN: (纸本)9798891761681

The proliferation of open-source Large Language Models (LLMs) underscores the pressing need for evaluation methods. Existing works primarily rely on external evaluators, focusing on training and prompting strategies. However, a crucial aspect - model-aware glass-box features - is overlooked. In this study, we explore the utility of glass-box features under the scenario of self-evaluation, namely applying an LLM to evaluate its own output. We investigate various glass-box feature groups and discovered that the softmax distribution serves as a reliable quality indicator for self-evaluation. Experimental results on public benchmarks validate the feasibility of self-evaluation of LLMs using glass-box features. © 2024 Association for Computational Linguistics.

关键词： Open systems

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The Effect of Cache Decision Policies on QoE in Multiple Video and Audio Streaming over ICN/CCN

The Effect of Cache Decision Policies on QoE in Multiple Vid...

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Communications and Networking (MeditCom), IEEE International Mediterranean Conference on

作者： Keisuke Kobayashi Toshiro Nunome Department of Engineering Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350309485

ISBN: (纸本)9798350309492

This paper considers video and audio transmission in ICN (information-Centric Networking)/ CCN (ContentCentric Networking), where each intermediate node can cache content. We have proposed LCD with Prob, combining traditional policies: LCD (Leave Copy Down) and probabilistic caching. This paper assumes a case where multiple video and audio streams exist simultaneously. We assess application-level QoS (Quality of Service) and QoE (Quality of Experience) of video and audio transmission utilizing LCD with Prob. We also add a mechanism for further QoE enhancement called “LCD with Prob deletion.” We assess application-level QoS using a computer simulation with a tree network and QoE by means of a subjective experiment. From the assessment result, we show the effectiveness of LCD with Prob deletion against existing policies.

关键词： Network topology Scalability Redundancy Quality of service Streaming media Probabilistic logic Liquid crystal displays

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Visualization of Judicial Precedents on Power Harassment Issues Using Relationship Chart

Visualization of Judicial Precedents on Power Harassment Iss...

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Thematic area Human Interface and the Management of information, HIMI 2022 Part of the 24th HCI International Conference, HCII 2022

作者： Tanaka, Soichiro Kano, Toru Akakura, Takako Department of Information and Computer Technology Graduate School of Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Department of Information and Computer Technology Faculty of Engineering Tokyo University of Science 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan

ISBN: (纸本)9783031064234

Power harassment has become a problem in Japan recently. However, it has been found that reading judicial precedents is one of the ways to prevent it. In this paper, in order to promote the reading of judicial precedents, we visualized the relationships between people in judicial precedents, which are not easy for non-experts to read. We first extracted the words from the text of judicial precedents that represent people using morphological analysis. Next, we then extracted information about the relationship between the persons using dependency analysis. We then determined the direction of the extracted relationship. Finally, based on the automatically extracted relations between the persons, we visualized the structure of the case as relationship charts and fishbone diagrams. To confirm the usefulness of the proposed diagrams in reading judicial precedents, we conducted an evaluation experiment using both judicial precedents and diagrams on six Tokyo University of science students. The results suggest that diagrams make it easier to read judicial precedents. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphic methods

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Enhanced Broad Siamese Network for Facial Emotion Recognition in Human-Robot Interaction

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2021年第5期2卷 413-423页

作者： Li, Yikai Zhang, Tong Philip Chen, C.L. The School of Computer Sciences and Engineering South China University of Technology Guangzhou510006 China The Pazhou Lab Guangzhou510335 China The Department of Computer and Information Science Faculty of Science and Technology University of Macau China

Robotics is one important domain of artificial intelligence applications. Proliferation of robotics makes our lives more convenient and colorful. Emotion recognition is one important task for a robot to communicate with human beings. Although different works have been proposed to complete the task of emotion recognition, conventional methods often require a lot of time and memory resources. Since a robot is often required to react timely and equipped with limited resources, we propose an enhanced Siamese network algorithm to resolve such a problem. We combine Siamese network with broad learning system while further improving mechanism of similarity metric. Experiment results show that our method can achieve a comparable performance to conventional deep learning method while reducing consumption of computing time and memory resources. © 2021 IEEE.

关键词： Emotion Recognition

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Digital Nudge Evaluation on COVID-19 tracing Application 9

Digital Nudge Evaluation on COVID-19 tracing Application

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9th International Conference on information and Communication technology, ICoICT 2021

作者： Sukmaningsih, Dyah Wahyu Abdurachman, Edi Purwandari, Betty Trisetyarso, Agung Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Depok Indonesia

ISBN: (纸本)9781665404471

Nudge is considered as an intervention to change user behavior and influence decision-making. Mobile apps have become a part of our everyday life. In this pandemic era, governments use mobile apps' technology to control the spread of COVID-19 infection. Many governments implemented COVID-19 tracing apps, and citizens are forced to use the apps to record their contact tracing and alert them if they have contact with an infected person. The key to control the increasing spread of the virus also depends on citizens adhere to health protocol. Government has experience difficulty in enforcing the protocol without strict surveillance. Therefore, building awareness of risk is essential-this study attempt to design nudge intervention into COVID-19 tracing apps. From the evaluation of the original apps, four nudge interventions can be applied in the application. © 2021 IEEE.

关键词： COVID-19

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Modeling of computer Virus Propagation with Fuzzy Parameters

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computers, Materials & Continua 2023年第3期74卷 5663-5678页

作者： Reemah M.Alhebshi Nauman Ahmed Dumitru Baleanu Umbreen Fatima Fazal Dayan Muhammad Rafiq Ali Raza Muhammad Ozair Ahmad Emad E.Mahmoud Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics and Statistics University of LahoreLahore54590Pakistan Department of Mathematics Cankaya UniversityBalgatAnkara06530Turkey Department of Medical Research China Medical UniversityTaichung406040TaiwanChina Institute of Space Sciences Magurele-Bucharest077125Romania Department of Computer Science University of LahoreLahore54590Pakistan Department of Mathematics School of ScienceUniversity of Management and TechnologyLahore54000Pakistan Department of Mathematics Faculty of Science and TechnologyUniversity of Central PunjabLahore54000Pakistan Department of Mathematics Near East University TRNCMersin10Turkey Department of Mathematics Government Maulana Zafar Ali Khan Graduate College WazirabadPunjab Higher Education Department(PHED)Lahore5400Pakistan Department of Mathematics and Statistics College of ScienceTaif UniversityP O Box11099Taif21944Saudi Arabia

Typically,a computer has infectivity as soon as it is *** is a reality that no antivirus programming can identify and eliminate all kinds of viruses,suggesting that infections would persevere on the *** understand the dynamics of the virus propagation in a better way,a computer virus spread model with fuzzy parameters is presented in this *** is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity,which depends on the quantity of *** this,the parametersβandγbeing functions of the computer virus load,are considered fuzzy *** fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical *** essential features of the model,like reproduction number and equilibrium analysis,are discussed in fuzzy ***,with fuzziness,two numerical methods,the forward Euler technique,and a nonstandard finite difference(NSFD)scheme,respectively,are developed and *** the evidence of the numerical simulations,the proposed NSFD method preserves the main features of the dynamic *** can be considered a reliable tool to predict such types of solutions.

关键词： SIR model fuzzy parameters computer virus NSFD scheme stability

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Fostering Digital Innovation in Indonesia: The Role of STEM-AI Skills in Overcoming Talent Deficits and Gender Stereotypes

Fostering Digital Innovation in Indonesia: The Role of STEM-...

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Intelligent Cybernetics technology & Applications (ICICyTA), International Conference on

作者： Erwin Halim Amalia Zahra Maryani Lili Ayu Wulandhari Devi Fitrianah Virienia Puspita Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Communication Department BINUS Graduate Program Master of Strategic Marketing Communication Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

This research explores the optimization of digital talent in advanced industries, particularly in the context of rapid digital transformation. Despite the increasing importance of digital talent for gaining a competitive edge, several challenges persist. In Indonesia, for example, there is a significant shortage of digitally skilled workers, with the World Bank reporting a gap of 9 million skilled individuals over the past 15 years. Additionally, artificial intelligence (AI) is expected to impact 9.5 million jobs, further exacerbating the demand for digital skills. Furthermore, the employability of graduates remains low, largely due to inadequate training, poor language proficiency, and limited cultural sensitivity. Many companies face difficulties in finding qualified individuals, quickly upskilling their workforce, and fostering an innovative organizational culture. This study seeks to evaluate the factors influencing digital talent performance in the context of these challenges. It examines seven key variables: digital readiness, digital technology adoption, relevance of AI, digital skills, individual performance, problem-solving ability, and overall digital talent performance. Hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data was collected from 378 participants, primarily students with STEM backgrounds, in the Jabodetabek area of Indonesia in November 2024. The findings reveal that all hypotheses are significant, with results indicating that user satisfaction and the perceived value of digital talent in Indonesia have a notable impact on continued usage intentions in digital roles.

关键词： Training Industries Technological innovation Sensitivity Mathematical models Problem-solving Artificial intelligence Optimization Faces Gender issues

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Unified Approach to Video-Based AI Inference Tasks in Augmented Reality Systems Assisted by Mobile Edge Computing 31

Unified Approach to Video-Based AI Inference Tasks in Augmen...

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31st International Conference on Software, Telecommunications and computer Networks, SoftCOM 2023

作者： Sousa, Alexandre Ladeira De Okey, Ogobuchi Daniel Rosa, Renata Lopes Saadi, Muhammad Rodriguez, Demostenes Zegarra Federal University of Lavras Department of Computer Science Minas Gerais Lavras Brazil Federal University of ABC Graduate Program in Information Engineering Sao Paulo Santo Andre Brazil University of Central Punjab Department of Electrical Enginnering Punjab Pakistan Federal University of Lavras Computer Science Department Minas Gerais Lavras Brazil

ISBN: (纸本)9798350301076

In the rapidly evolving field of Augmented Reality (AR), delivering real-time, immersive experiences places a significant demand on computational resources, particularly in the context of video-based Artificial Intelligence (AI) inference tasks. Some solutions explorate optimize the tasks using the potential of Mobile Edge Computing (MEC), in which MEC brings the advantages of reduced latency and network congestion, which are critical for AR systems. In this work, we designed a novel algorithm named AR-MEC Optimization for the distribution of AI inference tasks among edge servers while considering several factors including task complexity, server capacity, and network conditions. Our approach not only ensures low-latency responses but also improves overall system efficiency and the user's Quality of Experience (QoE). Experimental results demonstrate that our unified approach significantly outperforms traditional cloud-based methods in terms of response time and computational efficiency, thereby highlighting the potential of MEC-assisted AR systems for real-world applications. © 2023 University of Split, FESB.

关键词： Augmented reality

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