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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Cai, Qiuquan Meng, Lianghui Wang, Ling Ren, Jing Yang, Jiajia Ming, Dong Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin 300072 China Brain-Computer Interaction and Human-Machine Fusion Haihe Laboratory Tianjin University Tianjin 300072 China Tianjin Key Laboratory of Brain Science and Neural Engineering Tianjin University Tianjin 300072 China

ISBN: (纸本)9798350371499

Exploring new effective treatments for depression holds important social significance and clinical value. Low-intensity focused ultrasound stimulation (LIFUS) has been proven to have significant neuroprotective effects on depression. However, the specific genes regulated by LIFUS in depressive mice remain unclear. We established a depression mice model using chronic restraint stress (CRS) and applied LIFUS to the medial prefrontal cortex (mPFC) following CRS. We explored the impact of modeling and treatment on gene expression changes through transcriptomics, revealing that the therapeutic effect of LIFUS may be associated with the improvement of the activity of calcium signaling pathway and synaptic plasticity. The study provides preclinical evidence and a theoretical basis for applying LIFUS for depression treatment. © 2024 IEEE.

关键词： Mammals

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DynaButtons: Fast Interactive Soft Buttons with Analog Control

DynaButtons: Fast Interactive Soft Buttons with Analog Contr...

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International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (HAPTICS)

作者： Tucker Rae-Grant Chris Harrison Craig Shultz Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA USA Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Champaign IL USA

While mechanical buttons are ubiquitous, their haptic response is fxed, reducing interface fexibility and precluding an avenue for rich feedback. Here, we describe a new type of dynamic button, or DynaButton, which can vary its visual and haptic response via rapid shape change. To achieve this, we made several advances in the performance of embedded electroosmotic pumps: we increased core pump speed >300% over prior work, demonstrated closed-loop control, and investigated analog output that varies in response to pressure and force inputs. We validated our system with a physical characterization and performed a series of stimuli recognition studies to validate the expressivity and discriminability of three regimes of button interaction.

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Recognizing Adenoid Hypertrophy from Facial Images with Multi-scale Feature Fused State Space Model 18th

Recognizing Adenoid Hypertrophy from Facial Images with Mu...

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18th Chinese Conference on Biometric Recognition, CCBR 2024

作者： Ma, Shuai He, Jinrong Wang, Yao Bi, Yingzhou Yang, Li College of Mathematics and Computer Science Yan’an University Yan’an716000 China Yan’an University Affiliated Hospital Yan’an716000 China Guangxi Key Lab of Human-Machine Interaction and Intelligent Decision Nanning Normal University Nanning530100 China School Hospital Yan’an University Yan’an716000 China

ISBN: (纸本)9789819610709

Early diagnosis of pediatric adenoidal hypertrophy is crucial for timely identification of respiratory obstructions, thereby preventing declines in sleep quality that can lead to impaired growth, development, and cognitive function. Currently, the most common clinical diagnostic methods involve nasopharyngeal endoscopy and X-ray imaging assessments, which are time-consuming, labor-intensive, and costly. This paper presents an intelligent diagnostic model based on natural light facial images, employing a state space model (SSM). The model combines the local feature extraction capability of convolutional layers with the SSM’s ability to capture long-range dependencies for facial feature extraction. Furthermore, it incorporates a feature fusion strategy to enhance the features of facial images. Experimentation on a self-constructed dataset of adenoid facies images demonstrated that the model achieves an accuracy of 86.55% and an F1-score of 86.21%. The data and code are available at https://***/hejinrong/AF-SSM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Medical imaging

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CL-GAN: Contrastive Learning-Based Generative Adversarial Network for Modality Transfer with Limited Paired Data 17th

CL-GAN: Contrastive Learning-Based Generative Adversarial Ne...

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17th European Conference on computer Vision, ECCV 2022

作者： Emami, Hajar Dong, Ming Glide-Hurst, Carri Department of Computer Science Wayne State University DetroitMI United States Department of Human Oncology University of Wisconsin Madison DetroitMI United States

ISBN: (纸本)9783031250651

Separate acquisition of multiple modalities in medical imaging is time-consuming, costly and increases unnecessary irradiation to patients. This paper proposes a novel deep learning method, contrastive learning-based Generative Adversarial Network (CL-GAN) for modality transfer with limited paired data. We employ CL-GAN to generate synthetic PET (synPET) images from MRI data, and it has a three-phase training pipeline: 1) intra-modality training for separate source (MRI) and target (PET) domain encoders, 2) cross-modality encoder training with MRI-PET pairs and 3) GAN training. As obtaining paired MRI-PET training data in sufficient quantities is often very costly and cumbersome in clinical practice, we integrate contrastive learning (CL) in all three training phases to fully leverage paired and unpaired data, leading to more accurate and realistic synPET images. Experimental results on benchmark datasets demonstrate the superior performance of CL-GAN, both qualitatively and quantitatively, when compared with current state-of-the-art methods. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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SentinelMet: Enhancing Metaverse Security through Deep Learning Techniques in 6G 18

SentinelMet: Enhancing Metaverse Security through Deep Learn...

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18th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Rajput, Dikshant Singh, Sunil K. Kumar, Sudhakar Vashisht, Harshit Chui, Kwok Tai Gupta, Brij B. Chandigarh College of Engineering and Technology Chandigarh India Hong Kong Hong Kong Asia University Department of Computer Science and Information Engineering Taichung413 Taiwan University of Economics and Human Science Warsaw Poland

ISBN: (纸本)9798350391725

With the increasing demand for robust security in the rapidly expanding metaverse within 6 G networks, advanced intrusion detection systems (IDS) are becoming essential. This paper introduces a novel hybrid intrusion detection framework that combines Gaussian Mixture Clustering with Random Forest classifiers and KMeans Clustering with Random Forest classifiers. These models are evaluated for their effectiveness in identifying complex intrusion patterns. The hybrid approaches demonstrated high detection rates, with the Gaussian Mixture Clustering ensemble achieving a detection rate of 99.5-99.6%, while the KMeans clustering model achieved a detection rate of {9 8 - 9 9 %}. Comparative analysis shows that these models enhance detection performance while maintaining robustness in a dynamic and diverse metaverse landscape. © 2024 IEEE.

关键词： Network intrusion

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GPT4ESG: Streamlining Environment, Society, and Governance Analysis with Custom AI Models 4

GPT4ESG: Streamlining Environment, Society, and Governance A...

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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Lin, Lydia Hsiao-Mei Ting, Fang-Kai Chang, Ting-Jui Wu, Jun-Wei Tsai, Richard Tzong-Han National Taipei University of Technology Department of Interaction Design Taipei City Taiwan National Central University Department of Computer Science and Information Engineering Taoyuan City Taiwan Center for Gis Research Center for Humanities and Social Sciences Academia Sinica Taipei City Taiwan

ISBN: (纸本)9798350360721

Many companies now prioritize Environment, Society, and Governance (ESG) and financial performance due to concerns about climate change. We created GPT4ESG, a quick method to analyze a company's ESG investment and influence. GPT4ESG is a model system architecture based on BERT and GPT with five parts:(1) Data cleaning: The data is cleaned and preprocessed to ensure it is in a suitable format for the model. (2) Tokenizer adaptation: A customized GPT assistant is used to assist in scoring, and results are given after expert review. (3) Model adjustment: A classification layer is added to the output. (4) Fine-tuning: The pre-trained model is fine-tuned according to the ESG field know-how. (5) Evaluation and Testing: The model was tested on a validation set during training and then on a testing set. We collected ESG reports of well-known listed companies in the technology industries in the United States as a data set. The experimental results showed that the customized GPT4ESG model was more effective than ESG-BERT in classifying ESG data. This model simplifies ESG reporting for stakeholders to make responsible decisions. © 2024 IEEE.

关键词： Climate change

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Effect of Data Degradation on Motion Re-Identification

Effect of Data Degradation on Motion Re-Identification

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IEEE International Symposium on World of Wireless Mobile and Multimedia Networks (WoWMoM)

作者： Vivek Nair Mark Roman Miller Rui Wang Brandon Huang Christian Rack Marc Erich Latoschik James F. O’Brien Computer Science UC Berkeley Berkeley USA Computer Science Illinois Institute of Technology Chicago USA Carnegie Mellon University Pittsburgh USA UC Berkeley Berkeley USA Human-Computer Interaction University of Würzburg Würzburg Germany

ISBN: (数字)9798350394665

ISBN: (纸本)9798350394672

The use of virtual and augmented reality devices is increasing, but these sensor-rich devices pose risks to privacy. The ability to track a user’s motion and infer the identity or characteristics of the user poses a privacy risk that has received significant attention. Existing deep-network-based defenses against this risk, however, require significant amounts of training data and have not yet been shown to generalize beyond specific applications. In this work, we study the effect of signal degradation on identifiability, specifically through added noise, reduced framerate, reduced precision, and reduced dimensionality of the data. Our experiment shows that state-of-the-art identification attacks still achieve near-perfect accuracy for each of these degradations. This negative result demonstrates the difficulty of anonymizing this motion data and gives some justification to the existing data- and compute-intensive deep-network based methods.

关键词： Degradation Wireless communication Privacy Accuracy Tracking Noise Training data

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Integrating Image Recognition and Board Games into Financial Education 16

Integrating Image Recognition and Board Games into Financial...

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16th Asia-Pacific Workshop on Mixed and Augmented Reality, APMAR 2024

作者： Hung, Yu-Han Chao, Hao-Bin Liou, Jie-Sin Han, Ping-Hsuan Hsieh, Yi-Zeng Fan, Ping-Lin Chou, Chien-Hsing Department of Mathematics and Information Education National Taipei University of Education Taiwan Department of Interaction Design National Taipei University of Technology Taiwan Department of Electrical and Computer Engineering National Taiwan University of Science and Technology Taiwan Department of Digital Technology Design National Taipei University of Education Taiwan

As financial products diversify and market structures become more complex, promoting financial education has become increasingly important. Given that the foundation of financial literacy should be established from childhood, how to cultivate students' correct financial management concepts from a young age has become a significant issue in modern society. Considering the substantial advantages of game-based learning in providing high interactivity and real-world scenario simulations, this paper aims to develop an innovative financial education board game that incorporates elements of risk assessment and insurance planning, and digitalizes it. With the assistance of an app and the application of image recognition technology, we could enhance the convenience and fun of the gameplay. Research results show that integrating digital apps into board games as a game-based learning strategy significantly improves the learning outcomes and motivation of upper elementary school students in the areas of risk and insurance knowledge, compared to traditional lecture methods. It also enhances their understanding and application abilities. Students hold a positive attitude toward this teaching approach, demonstrating its potential and advantages in financial education. © 2024 Copyright for this paper by its authors.

关键词： Decentralized finance

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Flexible computational photodetectors for self-powered activity sensing

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npj Flexible Electronics 2022年第1期6卷 45-52页

作者： Dingtian Zhang Canek Fuentes-Hernandez Raaghesh Vijayan Yang Zhang Yunzhi Li Jung Wook Park Yiyang Wang Yuhui Zhao Nivedita Arora Ali Mirzazadeh Youngwook Do Tingyu Cheng Saiganesh Swaminathan Thad Starner Trisha L.Andrew Gregory D.Abowd School of Interactive Computing Georgia Institute of TechnologyAtlantaGAUSA School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGAUSA Department of Electrical and Computer Engineering Northeastern UniversityBostonMAUSA Department of Chemistry University of Massachusetts AmherstAmherstMAUSA Department of Electrical and Computer Engineering University of CaliforniaLos AngelesCAUSA Human-Computer Interaction Institute Carnegie Mellon UniversityPittsburghPAUSA Departments of Chemistry and Chemical Engineering University of Massachusetts AmherstAmherstMAUSA

Conventional vision-based systems,such as cameras,have demonstrated their enormous versatility in sensing human activities and developing interactive ***,these systems have long been criticized for incurring privacy,power,and latency issues due to their underlying structure of pixel-wise analog signal acquisition,computation,and *** this research,we overcome these limitations by introducing in-sensor analog computation through the distribution of interconnected photodetectors in space,having a weighted responsivity,to create what we call a computational *** photodetectors can be used to extract mid-level vision features as a single continuous analog signal measured via a two-pin *** develop computational photodetectors using thin and flexible low-noise organic photodiode arrays coupled with a self-powered wireless system to demonstrate a set of designs that capture position,orientation,direction,speed,and identification information,in a range of applications from explicit interactions on everyday surfaces to implicit activity detection.

关键词： everyday overcome photodetector

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Suicidal Tendency and Depression Diagnosing Medical Agent Using fNIRS and VFT

Suicidal Tendency and Depression Diagnosing Medical Agent Us...

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2023 IEEE International Conference on Agents, ICA 2023

作者： Yoo, Joo Hun Jeong, Harim An, Ji Hyun Jeon, Hong Jin Chung, Tai-Myoung Sungkyunkwan University Department of Artificial Intelligence Suwon Korea Republic of Sungkyunkwan University Department of Interaction Science Seoul Korea Republic of Sungkyunkwan University School of Medicine Department of Psychiatry Seoul Korea Republic of Sungkyunkwan University Department of Computer Science and Engineering Suwon Korea Republic of

ISBN: (纸本)9798350312782

Functional Near-Infrared Spectroscopy (fNIRS) is a technique for measuring blood flow in the brain, specifically focusing on changes in the frontal lobe. It has found valuable applications in psychiatry, particularly in diagnostic processes. This study explores the potential of fNIRS data and verbal fluency test (VFT) data, both collected during fNIRS measurements, as tools for diagnosing the severity of major depressive disorder, a significant mental health condition. Beyond merely detecting depression, our research introduces a medical support agent model to identify signs of suicidal tendencies in individuals with severe depression. By integrating data collection, preprocessing techniques, feature extraction, and multimodal classification methods for fNIRS and VFT data, our study suggests these artificial intelligence-based medical agents could enhance diagnostic accuracy and provide valuable support in clinical judgments. © 2023 IEEE.

关键词： Infrared devices

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