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arXiv 2024年

作者： Joloudari, Javad Hassannataj Maftoun, Mohammad Nakisa, Bahareh Alizadehsani, Roohallah Yadollahzadeh-Tabari, Meisam Department of Computer Engineering Faculty of Engineering University of Birjand Iran Department of Computer Engineering Babol Branch Islamic Azad University Babol Iran Tehran*** Iran Department of Artificial Intelligence Technical and Engineering Faculty South Tehran Branch Islamic Azad University Tehran Iran School of Information Technology Faculty of Science Engineering and Built Environment Deakin University GeelongVIC Australia Deakin University Waurn Ponds Australia

The Complex Emotion Recognition System (CERS) deciphers complex emotional states by examining combinations of basic emotions expressed, their interconnections, and the dynamic variations. Through the utilization of advanced algorithms, CERS provides profound insights into emotional dynamics, facilitating a nuanced understanding and customized responses. The attainment of such a level of emotional recognition in machines necessitates the knowledge distillation and the comprehension of novel concepts akin to human cognition. The development of AI systems for discerning complex emotions poses a substantial challenge with significant implications for affective computing. Furthermore, obtaining a sizable dataset for CERS proves to be a daunting task due to the intricacies involved in capturing subtle emotions, necessitating specialized methods for data collection and processing. Incorporating physiological signals such as Electrocardiogram (ECG) and Electroencephalogram (EEG) can notably enhance CERS by furnishing valuable insights into the user's emotional state, enhancing the quality of datasets, and fortifying system dependability. A comprehensive literature review was conducted in this study to assess the efficacy of machine learning, deep learning, and meta-learning approaches in both basic and complex emotion recognition utilizing EEG, ECG signals, and facial expression datasets. The chosen research papers offer perspectives on potential applications, clinical implications, and results of CERSs, with the objective of promoting their acceptance and integration into clinical decision-making processes. This study highlights research gaps and challenges in understanding CERSs, encouraging further investigation by relevant studies and organizations. Lastly, the significance of meta-learning approaches in improving CERS performance and guiding future research endeavors is underscored. © 2024, CC BY-NC-SA.

关键词： Electroencephalography

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An Offline Assistance Tool for Visually Impaired People Based on Image Captioning

An Offline Assistance Tool for Visually Impaired People Base...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Guo, Yu Chen, Yue Xie, Yuanyan Ban, Xiaojuan Obaidat, Mohammad S. University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China University of Science and Technology Beijing Shunde Innovation School Foshan China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China King Abdullah Ii School of Information Technology University of Jordan Amman Jordan Amity University UP Noida India

ISBN: (纸本)9781665468190

Eye defects of visually impaired people bring great inconvenience to daily lives. With the rapid development of computers and artificial intelligence, some assistance tools and wearable devices have provided convenience to a certain extent, but they still possess many shortcomings, such as high prices, limited functionality, poor real-time performance, the inability to be used offline and so on. This paper designs an offline assistance tool specifically for visually impaired people that can help them perceive their surrounding environments by taking photos and reading the descriptions output by an image captioning model. Considering that the photos taken by visually impaired people may be incomplete, an improved image stitching method based on a genetic algorithm is proposed to obtain high-quality stitched images as the inputs of the image captioning model. An improved model pruning algorithm is also designed to compress and accelerate the image captioning model to meet the offline and real-time deployment requirements of portable devices. Experimental results and a practical tool show that the developed system based on an image captioning model and pruning can quickly and accurately describe environments, thus assisting visually impaired people anytime and anywhere. © 2022 IEEE.

关键词： Genetic algorithms

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Initial Investigations of Pinhole Numbers and Projection Views in Multi-pinhole Brain SPECT

Initial Investigations of Pinhole Numbers and Projection Vie...

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2021 IEEE Nuclear science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Huang, Wenbo Mok, Greta S. P. University of Macau Faculty of Science and Technology The Center for Cognitive and Brain Sciences Institute of Collaborative Innovation Department of Electrical and Computer Engineering Taipa China

ISBN: (纸本)9781665421133

SPECT is a powerful tool for diagnosing neurological diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD), while multi-pinhole (MPH) SPECT could offer superior resolution-detection efficiency trade-off. Here we aim to investigate the relationship of pinhole numbers and projection views in MPH brain SPECT for a conventional dual-head SPECT scanner. The NCAT brain phantom was used to simulate 2 activity distributions, i.e., 99mTc-HMPAO for AD and 99mTc-TRODAT for PD. The target system spatial resolution was set to 12 mm for a 200 mm FOV to cover the whole patient's head. We used a 3D analytical MPH projector to generate 64, 32, 16, 8, 4 and 2 noise free projections for 1-15 pinholes and noisy projections for 1-20 pinholes respectively. The noise levels for different pinholes were modelled by scaling the clinical count level for 2 brain applications obtained from a LEHR parallel hole collimator. Noise free and noisy projections were reconstructed using the ML-EM algorithm up to data convergence. Normalized mean square error (NMSE) was calculated over the whole brain region for HMPAO and striatum region for TRODAT in both noise free and noisy simulation, respectively. Based on the noise-free NMSE analysis for 64 to 2 projections, the optimum pinhole number increased from 3 to 11 for HMPAO and from 1 to 10 for TRODAT. While for noisy data, the optimum pinhole number increased from 5 to 18 for HMPAO and from 2 to 13 for TRODAT for 64 to 2 projections. We conclude that more number of pinholes are needed as the number of projections decreases. More number of pinholes are needed for HMPAO as compared to TRODAT. © 2021 IEEE.

关键词： Brain

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Dynamic Path Allocation Based on Reinforcement Learning in Iot Systems

Dynamic Path Allocation Based on Reinforcement Learning in I...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Y. Alekya Rani Asa Jyothi G T. Parameswaran Alone Vinod N Byram Anand Ramya Maranan Department of Computer Science and Engineering (AIML) CVR College of Engineering Hyderabad Telangana India ECE Departmeny Malla Reddy Engineering College Hyderabad Telangana India Computer Science and Engineering School of Engineering and Technology CMR University Bangalore Bangalore Karnataka India Computer Engineering Department VPPCOE & VA Sion Mumbai India Management Department of Management Pondicherry University Pondicherry India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

The Internet of Things (IoT) expands Internet accessibility to billions of IoT devices around the world, where the devices collect and provide data to represent the actual state of the world. On the other hand, over a long period of time, the Independent Control Framework (ACS) carries out control functions on the actual systems without external interference. The intelligent dynamic framework, which can provide useful route information to transport and assist with diverse boats through distant organizations, plays a key role in the transport path arranging. In any case, lengthy path planning and low security difficulties have a negative impact on current plans. This article uses the static global path layout for the first requirement and the dynamic near path layout for the second requirement to provide a model for the transport path layout for the second requirement. In particular, you'll begin by making a raster map utilizing ArcGIS. A worldwide pass format on the raster map is then performed utilizing the Dyna-Sarsa (A) model, which changes the capability succession and Dyna structure in the Sarsa calculation. In particular, qualified sequences have a temporary memory of orientation, which may speed up model integration.

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Cost-Effective Network Packet Manipulation and Error-Detection Device

Cost-Effective Network Packet Manipulation and Error-Detecti...

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Alexander F. K. Janus Steffen Moser Frank Slomka Faculty of Engineering Computer Science and Psychology Institute of Embedded System/Real-Time Systems School of Advanced Professional Studies Ulm University Ulm Germany

Real-time multimedia communication applications like video conferencing and screen sharing tools are an integral part of our daily communications. These time-critical services are handled via the Internet, a packet-switched and essentially best-effort network, not explicitly designed for robust real-time communication. From a video conferencing service provider's perspective, network issues cause a lot of user complaints due to various reasons: lossy WLAN channels, poorly configured home routers, or crowded carrier-grade network address translation devices. All of these issues have in common that they are often time-variant and non-deterministic. Furthermore, the end-to-end transmission in these highly inhomogeneous networks often suffers from a mixture of more than one error source. To enable a detailed and impartial analysis of multimedia service quality, it is necessary to analyze packets in defective online scenarios and introduce a broadly similar error pattern in an otherwise stable lab network. In this paper, we present SEDER, a hardware-software design of a layer two transparent Ethernet bridge that can be used for two purposes: error detection and error recreation. Implemented on low-cost hardware, the bridge can be easily deployed anywhere to allow debugging, even at a user's site. It is possible to parameterize our bridge to imitate almost all possible network effects, including complex combinations of more than one effect. In addition, we present two case studies, firstly emphasizing the capabilities of SEDER and secondly showing the need to use SEDER to harden open source Video Conferencing Tools against errors.

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Comparison of Rating Scale and Pairwise Comparison Methods for Measuring Human Co-worker Subjective Impression of Robot during Physical Human-Robot Collaboration

Comparison of Rating Scale and Pairwise Comparison Methods f...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Qiao Wang Ziqi Wang Marc G. Carmichael Dikai Liu Chin-Teng Lin Robotics Institute Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia Australian Artificial Intelligence Institute School of Computer Science Faculty of Engineering and Information Technology University of Technology Sydney Ultimo NSW Australia

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The Rating Scale method has been long deemed the standard for measuring subjective perceptions. However, in the field of physical human-robot collaboration (pHRC), its aptness should be put under scrutiny due to inherent challenges such as response bias, between-subject variations, and the granularity *** variances can introduce significant bias in the rating scale results. A high granularity in the scale could overwhelm participants, leading to unclear and biased responses, while a low granularity may gloss over the fine nuances of human feelings. Additionally, there’s a notable risk of receiving careless responses, which compromise data reliability. Recognizing these challenges, this paper proposes the application of Pairwise Comparison (PC) in pHRC — an alternative survey technique that emphasizes direct comparisons between items on the defined criteria. By using the NASA Task Load Index (NASA-TLX) as a template, RS and PC questionnaires are designed and used in a series of pHRC experiments. Our preliminary findings suggest that PC is more precise and robust than the rating scale method. Compared to RS, PC fosters authentic participant interests in the experiment by intuitive question design and reducing the experimental duration. Besides, the accuracy and reliability of PC are also found to be consistent regardless of the variations in our experimental procedure design.

关键词： Surveys Accuracy NASA Collaboration Reliability engineering Particle measurements Task analysis

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LFNAT 2023 Challenge on Light Field Depth Estimation: Methods and Results

LFNAT 2023 Challenge on Light Field Depth Estimation: Method...

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2023 IEEE/CVF Conference on computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Sheng, Hao Liu, Yebin Yu, Jingyi Wu, Gaochang Xiong, Wei Guo, Longzhao Xie, Yanlin Zhang, Shuo Chang, Song Lin, Youfang Chao, Wentao Wang, Xuechun Wang, Guanghui Duan, Fuqing Wang, Tun Yang, Da Cui, Zhenglong Wang, Sizhe Zhao, Mingyuan Wang, Qiong Chen, Qianyu Liang, Zhengyu Wang, Yingqian Yang, Jungang Yang, Xueting Deng, Junli Cong, Ruixuan Chen, Rongshan State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University China Beihang Hangzhou Innovation Institute Yuhang China Faculty of Applied Sciences Macao Polytechnic University China Tsinghua University China Shanghaitech University China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University China Beijing Meet Yuan Co. Ltd China Beijing Key Laboratory of Traffic Data Analysis and Mining School of Computer and Information Technology Beijing Jiaotong University China Beijing Normal University China Toronto Metropolitan University Canada College of Computer Science and Technology Zhejiang University of Technology China National University of Defense Technology China School of Information and Communication Engineering Communication University of China China

ISBN: (纸本)9798350302493

This paper reviews the 1st LFNAT challenge on light field depth estimation, which aims at predicting disparity information of central view image in a light field (i.e., pixel offset between central view image and adjacent view image). Compared to multi-view stereo matching, light field depth estimation emphasizes efficient utilization of the 2D angular information from multiple regularly varying views. This challenge specifies UrbanLF [20] light field dataset as the sole data source. There are two phases in total: submission phase and final evaluation phase, in which 75 registered participants successfully submit their predicted results in the first phase and 7 eligible teams compete in the second phase. The performance of all submissions is carefully reviewed and shown in this paper as a new standard for the current state-of-the-art in light field depth estimation. Moreover, the implementation details of these methods are also provided to stimulate related advanced research. © 2023 IEEE.

关键词： Stereo image processing

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Generating Distributed Representations of Words from Japanese Wiktionary with BERT

Generating Distributed Representations of Words from Japanes...

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IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Ryota Nishiura Seiji Tsuchiya Hirokazu Watabe Dept. of Information and Computer Science Graduate School of Science and Engineering Doshisha University Kyo-Tanabe Kyoto Japan Dept. of Intelligent Information Engineering and Science Faculty of Science and Engineering Doshisha University Kyo-Tanabe Kyoto Japan

In this paper, we introduce a novel approach to create distributed representations of words. While existing methods such as Word2Vec learn from unstructured datasets of plain text, our approach leverages the structured contents of Wiktionary. It employs a pre-trained BERT model to obtain representation vectors of individual Wiktionary headwords by text embedding the corresponding contents of Wiktionary entries. We demonstrate that our proposed method outperforms a Word2Vec model in a XABC test result, potentially due to its ability to leverage both the quality of a pre-trained BERT model and expert-moderated Wiktionary, whereas further research is needed to fully understand the effectiveness of our proposed method under various conditions.

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Book Recommendation System using R Programming - A Comparative Study.

Book Recommendation System using R Programming - A Comparati...

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Innovative Practices in Technology and Management (ICIPTM), International Conference on

作者： Sandhiya. B K. N. Meera Said Broumi Dept. of Computer Science and Engineering Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India Dept. of Mathematics Amrita School of Engineering Bengaluru Amrita Vishwa Vidyapeetham India Laboratory of Information Processing Faculty of Science Ben M’Sik University of Hassan II Casablanca Morocco

ISBN: (数字)9798350307757

ISBN: (纸本)9798350307764

A Recommendation System (also known as Recommender System) is built for the purpose of recommending similar items to the user based on their interest. The item can be anything like movies, music, books, songs, etc. Many famous platforms such as Netflix and YouTube also use recommendation system. This paper focuses on comparing and studying the performance of the Recommender System for books that uses various different techniques such as k-means Clustering, PCA, Feature Selection, etc.

关键词： Video on demand Data analysis Accuracy Clustering algorithms Programming Motion pictures Feature extraction

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Efficient and Privacy-Preserving Logistic Regression Prediction over Vertically Partitioned Data

Efficient and Privacy-Preserving Logistic Regression Predict...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Jiaqi Zhao Hui Zhu Fengwei Wang Rongxing Lu Hui Li School of Cyber Engineering Xidian University Xi'an China Faculty of Computer Science University of New Brunswick Fredericton Canada

The explosive growth of data scales has recently drawn extensive attention to machine learning (ML) prediction services for achieving effective and efficient decision-making. However, the potential risk of model or data leakage, as well as vertically partitioned query data in real-world scenes, bring many challenges to ML prediction. Therefore, this paper proposes an efficient and privacy-preserving logistic regression prediction scheme, through which query institutions with vertically partitioned data can enjoy secure, fast, and high-accuracy prediction services from one cloud service provider. Specifically, we take the efficiency advantage of the trusted execution environments (TEE) technique under a semi-honest model, and design a series of masking and recovery methods based on homomorphic encryption to guarantee privacy inside and outside the enclave. Moreover, the ciphertext packing technique is integrated into our scheme for processing predictions parallelly, which further reduces communication and computational overhead. As a result, our scheme will not introduce additional strong security assumptions to TEE; meanwhile, it achieves a trade-off between security and efficiency. Based on the simulation-based paradigm, we formally prove the selective security of our scheme. Extensive experiments on real-world and synthetic datasets show that our prediction accuracy is comparable with plaintext prediction, and our scheme has at least a 30× running speedup compared to the existing representative schemes.

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