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38th IEEE Region 10 Conference, TENCON 2023

作者： Nunome, Toshiro Takada, Yoshiyuki Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350302196

In this paper, we exploit caches on intermediate nodes for QoE enhancement of multi-view video and audio transmission over ICN/CCN by controlling the content request start timing of consumers. We assume the selected single viewpoint transmission method;a consumer receives video and audio streams of a requested viewpoint. We perform a simple experiment with two consumers. When the consumers play video and audio with the time difference, we assess the effect of cached content by the former consumer's request on the output quality of the latter consumer. We deal with two types of viewpoint change strategies for the former consumer, which affect the efficiency of cache utilization. From the assessment results, we see that cache utilization has an important factor in enhancing QoE. © 2023 IEEE.

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Into 3D-Reconstructed Apparel over Virtual Try-On with Virtual Reality

Into 3D-Reconstructed Apparel over Virtual Try-On with Virtu...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Doungtap, Surasachai Petchhan, Jirayu Phanichraksaphong, Varinya Wang, Jenq-Haur International Graduate Program of Electrical Engineering and Computer Science Taiwan National Taiwan University of Science & Technology Dept. of Electrical Engineering Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Virtualization technologies are still growing bigger and faster. Despite the greatness of its advancement, the costume industry is still very accessible when it comes to real trials. Off-the-shelf stuff are inadequate details for the desired individual to assess its in-depth utility for each garment trying on for a second, including custom stuff are much harder to try out right away. To this end, 2D image-based 3D reconstruction inclusive of touchable-virtualized space is accessible easier to stuff details for mans' decision making in purchasing. We establish the overall end-to-end pipeline from reconstruction until visualization for one instance to be triable on its stuff for a moment. As an expectation, our proposed approach can bring objects into the experimental area and use them immediately without any obstacle. © 2023 IEEE.

关键词： Virtual reality

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Resilient Software Defined Satellite Networks: Combining Clustering Techniques with Efficient Routing Protocols 11

Resilient Software Defined Satellite Networks: Combining Clu...

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11th IEEE International Conference on Software Defined Systems, SDS 2024

作者： Da Silva, Juliano Antonio Mendes, Paulo De Freitas, Edison Pignaton Federal University of Rio Grande Do Sul Graduate Program in Computer Science Porto Alegre Brazil Central Research and Technology Airbus Munich Germany

ISBN: (纸本)9798331518325

Low Earth Orbit satellite constellations are highly mobile and thus have time-varying network topologies. Such time-varying networks face various challenges due to intermittently available links and devices. Consequently, many routing algorithms that work well on the terrestrial Internet may not be suitable for Low Earth Orbit (LEO) constellations. This paper provides an analysis of the impact that different types of routing algorithms may have on the performance of LEO constellations. The provided study analyses not only link-state routing algorithms, as used in well-known routing protocols for LEO constellations such as Contact Graph Routing (CGR), which follows a Software Defined Networking (SDN) approach, but also distance-vector algorithms, as well as the potential combination of link-state and distance-vector algorithms when network clusters are used in a LEO constellation. © 2024 IEEE.

关键词： Routing algorithms

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Gender-Based Bimodal Analysis of Speech and Text in Non-Contextual Emotion Recognition

Gender-Based Bimodal Analysis of Speech and Text in Non-Cont...

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Informatics International Conference (BTS-I2C), Beyond Technology Summit on

作者： Abby Rasya Angkasa Amalia Zahra Wai-Keung Fung Computer Science Department BINUS Graduate Program - Master of Computer Science Jakarta Indonesia Engineering Department Cardiff Metropolitan University - Cardiff School of Technologies Cardiff United Kingdom

ISBN: (数字)9798331508579

ISBN: (纸本)9798331508586

Emotion recognition can help human-computer interactions by enabling systems to respond empathetically and adapt to users' emotional conditions. This capability improves user experience, supporting the development of a more intuitive and emotionally responsive communication system. This study analyzes a bimodal approach based on gender (male and female) to recognize emotions without contextual information in dialogue analysis. Utilizing the Multimodal EmoryNLP dataset extracted from the TV series Friends with acted speech, we focused on four primary emotions: Angry, Neutral, Joy, and Scared. The model used in this study for text classification is RoBERTa, and wav2vec 2.0 is used for audio feature extraction with the Bi-LSTM model for classification. The experiment results using weighted F1-score reveal that data augmentation enhanced the performance of analyzing the original dataset from 0.46% to 0.52% and the male dataset from 0.43% to 0.51 %. In comparison, the female dataset remained consistent at 0.46%. The weighted F1-score and Unweighted Averaged Recall (UAR) from the male dataset are higher, 51 % and 48%, respectively, than those from the female dataset, 46% and 47%, respectively. Gender-based analysis indicated that male and female datasets exhibited distinct performance patterns, highlighting variations in emotional expression and recognition between genders. These findings underscore the effectiveness of multimodal strategies in emotion recognition and suggest that gender-specific factors play a significant role in enhancing classification performance. While these results highlight performance trends, further validation through repeated trials and statistical analyses could provide stronger generalizations and insights into gender-based differences.

关键词： Emotion recognition TV Statistical analysis Text categorization Speech recognition Linguistics Feature extraction Data augmentation Market research User experience

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QoE Assessment of Audiovisual Streaming over a Full-Duplex Wireless LAN with Interference Traffic

QoE Assessment of Audiovisual Streaming over a Full-Duplex W...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Nunome, Toshiro Deguchi, Daiki Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350324174

This paper evaluates the QoE of video and audio transmission over a full-duplex wireless LAN with interference traffic through a computer simulation and a subjective experiment. We employ a simulation environment with a pair of audiovisual transmission and reception terminals and a pair of interference traffic transmission and reception ones. We investigate the effect of the transmission rate of interference traffic and communication distance in a wireless channel on the output quality of the video and audio stream at the reception terminal. We perform a subjective experiment with the output timing of video and audio obtained by the simulation. © 2023 IEEE.

关键词： Wireless local area networks (WLAN)

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Efficient Node Reduction Heuristic for GNN-Based Traffic Speed Forecasting 11

Efficient Node Reduction Heuristic for GNN-Based Traffic Spe...

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11th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2024

作者： Inokuchi, Yuto Gonzalez, Pedro Henrique Aritsugi, Masayoshi Mendonca, Israel Kumamoto University Graduate School of Science and Technology Kumamoto Japan Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350367300

In this paper, we aim to reduce the number of nodes from Graph Neural Networks (GNNs), thereby simplifying models and reducing computational costs. GNNs are highly effective for various tasks, such as prediction, classification, and clustering, due to their ability to learn node and edge attributes and relationships, and they have been utilized for intelligent transportation systems recently by converting sensor networks into graph structures. Deep spatio-temporal neural networks, including Spatio-Temporal Graph Convolutional Networks (STGCNs), capture spatial and temporal dependencies, making them suitable for traffic speed forecasting, traffic demand prediction, and travel time estimation. Despite their success, GNNs face challenges in industrial applications due to significant memory usage and time consumption. In this paper, we propose a new approach to node reduction that outperforms existing methods in computational efficiency. Our experiments on two real-world traffic datasets demonstrate that using the heuristic and edge information to reduce nodes can cut computation time of optimization up to 95% and, by eliminating noise, can even enhance prediction accuracy. © 2024 IEEE.

关键词： Graph neural networks

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The Effect of Bitrate Control Methods of MPEG-DASH Streaming on Multi-View Video and Audio QoE

The Effect of Bitrate Control Methods of MPEG-DASH Streaming...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Nunome, Toshiro Wakayama, Yamato Nagoya Institute of Technology Computer Science Program Department of Engineering Graduate School of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350324174

This paper investigates the effect of bitrate control methods on QoE of multi-view video and audio streaming with MPEG-DASH. We adopt three bitrate control methods for conventional single-view video streaming to the MVV-A system with MPEG-DASH. We conduct a subjective experiment changing available network bandwidth and investigate the effect of the methods on QoE. © 2023 IEEE.

关键词： Video streaming

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Toward Digital Transformation Adoption: A Conceptual Framework from Transformational Leadership Perspective 7

Toward Digital Transformation Adoption: A Conceptual Framewo...

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7th Information Systems International Conference, ISICO 2023

作者： Marcel Gaol, Ford Lumban Supangkat, Suhono Harso Ranti, Benny Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Smart Cities and Communities Innovation Center Faculty of Digital Communication and Hotel & Tourism Institute of Technology Bandung Bandung Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia Information System Department Universitas Kristen Krida Wacana Jakarta Indonesia

Digital transformation is about transforming processes, business models, domains, and culture. Studies show that the failure rate of digital transformation is quite high up to 90%. Studies show that the transformational leadership model has a significant impact on digital transformation adoption. This paper identifies the positive and negative attributes of transformational leadership including the components that support and are affected for successful adoption of digital transformation. Furthermore, the paper combines several findings related to the attributes and components in the form of a conceptual framework. The conceptual framework can serve as a guide for organizations for their digital transformation journey. © 2023 The Authors. Published by Elsevier B.V.

关键词： Failure rate

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Privacy-Enhanced Data Deduplication Computational Intelligence Technique for Secure Healthcare Applications

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computers, Materials & Continua 2022年第2期70卷 4169-4184页

作者： Jinsu Kim Sungwook Ryu Namje Park Department of Convergence Information Security Graduate SchoolJeju National University63294Korea Master’s Program in Future Strategy Korea Advanced Institute of Science and Technology34141Korea Department of Computer Education Teachers CollegeJeju National University63294Korea

A significant number of cloud storage environments are already implementing deduplication *** to the nature of the cloud environment,a storage server capable of accommodating large-capacity storage is *** storage capacity increases,additional storage solutions are *** leveraging deduplication,you can fundamentally solve the cost ***,deduplication poses privacy concerns due to the structure *** this paper,we point out the privacy infringement problemand propose a new deduplication technique to solve *** the proposed technique,since the user’s map structure and files are not stored on the server,the file uploader list cannot be obtained through the server’s meta-information analysis,so the user’s privacy is *** addition,the personal identification number(PIN)can be used to solve the file ownership problemand provides advantages such as safety against insider breaches and sniffing *** proposed mechanism required an additional time of approximately 100 ms to add a IDRef to distinguish user-file during typical deduplication,and for smaller file sizes,the time required for additional operations is similar to the operation time,but relatively less time as the file’s capacity grows.

关键词： Computational intelligence cloud multimedia data deduplication

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Analyzing STEM Women’s Employability: A Machine Learning Framework with Clustering and Multi-Target Classification

Analyzing STEM Women’s Employability: A Machine Learning Fr...

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computer sciences, Engineering, and Technology Innovation (ICoCSETI), International Conference on

作者： Nadzla Andrita Intan Ghayatrie Wina Permana Sari Devi Fitrianah Esyin Chew 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 Cardiff School of Technology Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

The gender gap in science, Technology, Engineering, and Mathematics (STEM) fields highlights significant research opportunities, particularly in examining the employability of female graduates. This study introduces a novel machine learning framework integrating Clustering and Multi-target Classification to analyze employment waiting time and job linearity among women STEM alumni. Using K-Means Clustering and Multi-Target Logistic Regression, the framework achieved a classification accuracy of 77% and a silhouette score of 0.61, demonstrating its effectiveness in predictive analysis. Beyond these results, the framework offers a robust methodology for integrating Clustering with Classification, enabling a nuanced understanding of the employability challenges faced by women in STEM. This approach identifies key patterns in employment data, paving the way for targeted interventions and actionable insights. Furthermore, the findings aim to inform data-driven policymaking and future research to improve employability outcomes. This work contributes to addressing systemic challenges and fostering gender diversity in STEM careers while enhancing opportunities for women.

关键词： Logistic regression Technological innovation Accuracy Computational modeling Employment Linearity Machine learning Predictive analytics STEM Gender issues

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