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IEEE Conference on Vehicular technology (VTC)

作者： Shihao Chen Helin Yang Liang Xiao Changyuan Xu Xianzhong Xie Wanting Yang Zehui Xiong Department of Information & Communication Engineering Xiamen University Xiamen China Chongqing Key Laboratory of Computer Network and Communication Technology Chongqing University of Posts and Telecommunications Chongqing China Pillar of Information System Technology & Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

The space-air-ground integrated network (SAGIN) is a crucial technology for sixth-generation (6G) wireless communication networks to achieve seamless coverage and high throughput. In this paper, we propose an unmanned aerial vehicle (UAV)-assisted SAGIN structure, where the UAV is responsible for collecting data from ground users (GUs) and transmitting it to low-earth orbit (LEO) satellites. This paper also formulates a joint energy-efficient and fair resource scheduling optimization problem under jamming attacks and limited energy constraints, where the line-of-sight (LoS) links between the UAV and GUs are susceptible to being jammed. Due to the non-convex problem and dynamic environments, a deep reinforcement learning (DRL)-based twin delayed deep deterministic policy gradient (TD3) is developed to search optimal UAV trajectory to maximize energy efficiency (EE) and fairness against jamming. Simulation results verify that the proposed intelligent resource scheduling algorithm outperforms the baseline algorithms in terms of EE and fairness index in different settings.

关键词： Wireless communication Vehicular and wireless technologies Simulation Autonomous aerial vehicles Space-air-ground integrated networks Energy efficiency Trajectory

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Smart Office Automation system for Covid Prevention 3

Smart Office Automation System for Covid Prevention

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Rajapaksha, R.A.D.S. Costa, L.S. Prasanna, P.L.U.S.C. Disanayaka, A.P.D. Senarathne, A.N. Wijekoon, Janaka L. Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9781665408622

Today, this coronavirus is spread all around the world. Most organizations and businesses start to think about how to continue their business in a situation like COVID-19 and their employees' health and business security. To avoid and be safe from this type of disease, there are some common rules to follow. Keeping a distance, wearing a mask, cleaning our hands, are some health guidelines from them. According to the current situation, many inventors are trying and have already given some solutions to avoid these kinds of situations aligning with health guidance' provided by WHO. With the advantage of advanced modern-day technologies and ideas, researchers started to think about how to face situations like these with the new technologies and found that many users are highly interested and motivated with automated systems. Thus, from this study, we aim to provide a fully automated office management system to prevent corona with advanced technology in combination with IoT technologies, Machine learning, Cloud technologies, and sensor technologies. Considering the security aspect, Controlling the main entrance, identifying, ensuring user's authentication before entering the building, and monitoring employee activities are very significant aspects of the study. As the result of the study, the combination of IoT technologies and Machine Learning with deep learning mechanisms have guaranteed organizational business continuity, employees' health, and security. © 2021 IEEE.

关键词： Health

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Research on Recognition of Facial Expressions and Micro-Expressions for Robot Design 25th

Research on Recognition of Facial Expressions and Micro-E...

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25th International Conference on Human-computer Interaction, HCII 2023

作者： Tawaki, Meina Yamamoto, Keiko Kanaya, Ichi School of Information Systems University of Nagasaki 1-1 Manabino Nagasaki Nagayo851-2195 Japan School of System Design and Technology Tokyo Denki University 5 Senju Asahi-cho Adachi-ku Tokyo120-8551 Japan School of Information and Data Sciences Nagasaki University 1-14 Bunkyomachi Nagasaki Nagasaki852-8521 Japan Pineapple Computer Tokyo Japan

ISBN: (纸本)9783031492143

It is said that humans make their first impressions of a person 7% by verbal communication and 93% by visual and auditory communication. When robots intervene in human society and need to communicate with humans, the face is considered to be the most important interface. However, it is unclear whether differences can be recognized in the subtle facial expressions that appear in daily life. Therefore, in this study, we investigate the synchronization of emotions for knowing whether we can recognize such micro expressions. Emotional synchronization means that the feelings of a person A and a person B are communicated and emotionally coupled. For example, when the person A likes the person B, the person B feels the same emotion toward the person A at the same time, they are emotionally synchronized. We believe that the study of emotional synchronization will be useful for designing more friendly robots. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Synchronization

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Comparative Analysis of Fault-Localization Techniques in Adder

Comparative Analysis of Fault-Localization Techniques in Add...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Muhammad Ali Akbar Jeong-A Lee Amine Bermak Division of Information and Computing Technology College of Sci. and Engineering Hamad Bin Khalifa University Doha Qatar Department of Computer Engineering Computer System Lab Chosun University Gawangju Korea

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Adder is a complex digital circuit because of its interconnectivity, which hinders fault detection and localization. This paper compares two approaches of fault localization in adders based on carry-free addition using signed digits (SD) representation and localized self-checking-full adders for ripple carry adders (RCA). The self-repairing SD adder approach requires computation with standard and shifted inputs toward left and right for fault localization. The resulting complexity caused by the shifting operation is unnecessary for the self-repairing RCA, which simultaneously achieves fault detection and localization. Moreover, the centralized checking mechanism of the SD adder results in system failure if the checker becomes faulty. However, in the case of self-repairing RCA, the failure of individual full adders will not create problems in the self-checking ability of other full adders owing to the distributed fault detection mechanism. It has been observed that the self-checking RCA implemented in FPGA is $\mathbf{6 2 \%}$ more area efficient than the self-checking signed digit adder in terms of LUTs.

关键词： Location awareness Wireless communication Fault detection Integrated circuit interconnections Table lookup Complexity theory Circuit faults

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INVERTIBLE MOSAIC IMAGE HIDING NETWORK FOR VERY LARGE CAPACITY IMAGE STEGANOGRAPHY

arXiv

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arXiv 2023年

作者： Chen, Zihan Liu, Tianrui Huang, Jun-Jie Zhao, Wentao Bi, Xing Wang, Meng College of Computer Science and Technology National University of Defense Technology China College of System Engineering National University of Defense Technology China School of Computer Science and Information Engineering Hefei University of Technology China

The existing image steganography methods either sequentially conceal secret images or conceal a concatenation of multiple images. In such ways, the interference of information among multiple images will become increasingly severe when the number of secret images becomes larger, thus restrict the development of very large capacity image steganography. In this paper, we propose an Invertible Mosaic Image Hiding Network (InvMIHNet) which realizes very large capacity image steganography with high quality by concealing a single mosaic secret image. InvMIHNet consists of an Invertible Image Rescaling (IIR) module and an Invertible Image Hiding (IIH) module. The IIR module works for downscaling the single mosaic secret image form by spatially splicing the multiple secret images, and the IIH module then conceal this mosaic image under the cover image. The proposed InvMIHNet successfully conceal and reveal up to 16 secret images with a small number of parameters and memory consumption. Extensive experiments on ImageNet-1K, COCO and DIV2K show InvMIHNet outperforms state-of-the-art methods in terms of both the imperceptibility of stego image and recover accuracy of secret image. Copyright © 2023, The Authors. All rights reserved.

关键词： Steganography

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning 22

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Cao, Weipeng Yao, Xuyang Xu, Zhiwu Pan, Yinghui Sun, Yixuan Li, Dachuan Qiu, Bohua Wei, Muheng Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (纸本)9798331527471

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model’s capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods. © 2024 IEEE.

关键词： Zero-shot learning

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Optical spatiotemporal vortices

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eLight 2023年第1期3卷 156-168页

作者： Chenhao Wan Andy Chong Qiwen Zhan School of Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan 430074HubeiChina Department of Physics Pusan National UniversityGeumjeong-GuBusan 46241South Korea Zhangjiang Laboratory 100 Haike RoadShanghai 201204China Shanghai Key Lab of Modern Optical System University of Shanghai for Science and TechnologyShanghai 200093China

Spatiotemporal vortices of light,featuring transverse orbital angular momentum(OAM)and energy circulation in the spatiotemporal domain,have received increasing attention *** experimental realization of the controllable generation of spatiotemporal vortices triggers a series of research in this *** review article covers the latest developments of spatiotemporal vortices of light ranging from theoretical physics,experimental generation schemes,and characterization methods,to applications and future *** new degree of freedom in photonic OAM endowed by spatiotemporal vortices paves the way to the discovery of novel physical mechanisms and photonic applications in light science.

关键词： Spatiotemporal optical vortex Orbital angular momentum Spin-orbit interaction Linear momentum density Toroidal vortex Topological charge

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The Dual Path Multi-Feature Fusion Model combining CNN and Transformer for Age Estimation of Caenorhabditis elegans

The Dual Path Multi-Feature Fusion Model combining CNN and T...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Mengqian Ding Jun Liu Yang Luo School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

The relatively simple genome, short life cycle, and easy observation of Caenorhabditis elegans (C. elegans) make it an excellent model organism for aging research. Age-stage prediction of C. elegans can help to assess the effectiveness of anti-aging interventions, better explore the role of individual differences in the aging process, and thus promote the development of medicine. However, there are still some problems in accurately predicting the age stages of C. elegans. On the one hand, there may be individual differences among C. elegans due to natural variation and environmental factors. On the other hand, nematode data sets are scarce and image information is complex. In this paper, we perform the age prediction task by studying the body contour morphology, biomarkers, and internal organ changes of C. elegans. Specifically, to address the effects of individual differences and datasets, this paper combines the body contour features, protein aggregation features, and pharyngeal terminal bulb features of C. elegans. In addition, considering the complex information of C. elegans images, this paper proposes a hybrid CNN and Transformer feature extraction method (DFCT), which can fully extract the global and local features of the image. A Dual Path Adaptive Feature Fusion Module (DAFM) is used to fuse the features. A series of experiments are conducted to verify the effectiveness of the proposed method. The experimental results show that the method proposed in this paper outperforms other methods in terms of accuracy and precision, especially in dividing 25 age stages into 3 categories, with an accuracy of 85.93%.

关键词： Proteins Hands Accuracy Estimation Biomarkers Aging Feature extraction Transformers Pharynx Biomedical imaging

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Research on emotional space for movie and TV drama videos

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The Journal of China Universities of Posts and Telecommunications 2022年第5期29卷 73-82页

作者： Li Yujie Zhang Jingjing Jiang Wei Wang Chunxiao Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China Beijing Key Laboratory of Modern Entertainment Technology Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China School of Computer and Cyber Sciences Communication University of ChinaBeijing 100024China

Emotional space refers to a multi-dimensional emotional model that describes a group of subjective feelings or emotions. Since the existing discrete emotional space is mainly aimed at human’s primary emotions, it cannot describe the complex emotions evoked when watching movies. In order to solve this problem, an emotional fusion space for videos was constructed by selecting movies and TV dramas with rich emotional semantics as the research objects. Firstly, emotional words based on movie and TV drama videos are acquired and analyzed by using subjective evaluation and semantic analysis methods. Then, the emotional word vectors obtained from the above analysis are fused, reduced dimension by t-distributed stochastic neighbor embedding(t-SNE) algorithm, and clustered by bisecting K-means clustering algorithm to get a discrete emotional space for movie and TV drama videos. This emotional fusion space can obtain different categories by changing the value of the emotion classification number without re-labeling and calculation.

关键词： emotional space movie and TV drama videos subjective evaluation words semantic analysis fusion space

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Corporate Reputation Risk in Social Media 2

Corporate Reputation Risk in Social Media

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2nd International Conference on computer Science and Engineering, IC2SE 2021

作者： Hamidi, Saidatul Rahah Akmar Ismail, Maizatul Shuhidan, Shuhaida Mohamed Faculty of Computer Science and Information Technology Department of Information System Kuala Lumpur50 603 Malaysia Faculty of Computer and Mathematical Sciences Department of Computer Science Shah Alam Selangor40450 Malaysia

ISBN: (纸本)9781665400459

In today's world, digital platforms such as social media have become one of the most influential media sources. This may give an impact on company reputation due to massive user-generated content. However, due to its vast volume and unstructured nature, manual classification of these digital contents is difficult. Previous studies, evaluate corporate reputation using machine learning-focused mostly on positive, neutral, and negative aspects and lacking the multidimensional nature of corporate reputation. Therefore, this paper aimed to explore the integration of the domain ontology approach with machine learning approaches to achieve multi-dimensional classification for online corporate reputation. Overall research route to measure corporate reputation in social media is discussed. The proposed research route starts from retrieving corporate content from digital media for selected domain, next preprocessing data before topics and bag-of-words generated from the extracted data and mapping according to corporate reputation dimensions. The proposed approach is expected to produce a framework for an online corporate reputation that can be used across multiple business domains. © 2021 IEEE.

关键词： Sentiment analysis

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