检索结果-内蒙古大学图书馆

The Impact of Transient and Stable Patterns of Functional Connectivity in Emotion Recognition

The Impact of Transient and Stable Patterns of Functional Co...

IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Yinghao Huang Xucheng Liu Ye Li Chio-In Ieong Yong Hu Feng Wan Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China Department of Electrical and Computer Engineering Faculty of Science and Technology Centre for Cognitive and Brain Sciences Institute of Collaborative Innovation University of Macau Macau China Shenzhen Institute of Advanced Technology Chinese Academy Sciences Shenzhen China Guangdong Institute of Intelligence Science and Technology Zhuhai China Department of Orthopaedics and Traumatology The University of Hong Kong Hong Kong China

ISBN: (数字)9798350322996

ISBN: (纸本)9798350323009

The achievement of emotional functions relies on the interactions of various functional systems of the human brain. Numerous studies tried to explore the mechanism of the emotions based on the functional connectivity. However, the contribution of the transient and stable patterns of brain communication in brain emotions was still unclear. The recently proposed activation network framework assumed the activity of functional connectivity (AFC) and background of functional connectivity (BFC) to respectively represent transient and stable patterns of functional connectivity. In this paper, we employed the activation network framework to SEED-IV dataset to achieve the emotion recognition and evaluate the performance of the transient and stable patterns in emotional activities. The top 100 critical connections of each subject were extracted by a data-driven feature selection strategy. The critical connections across all subjects of both AFC and BFC suggested the importance of Gamma band in emotion recognition. Especially, the AFC and BFC showed the different communication modes during the emotions. Finally, the subject-independent classification was employed on each subject’s critical connections to achieve the emotion recognition. The BFC showed the best classification accuracy of 78.71% ± 1.73% (mean ± std). The findings demonstrated that human emotions were mostly influenced by the consistent brain communication patterns. The findings of this investigation offer a new insight on the studies of human emotion.

关键词： Emotion recognition Accuracy Virtual environments Feature extraction Electroencephalography Transient analysis Computational intelligence

来源：评论

学校读者我要写书评

暂无评论

Modular Self-Lock Origami: design, modeling, and simulation to improve the performance of a rotational joint

arXiv

引用

arXiv 2023年

作者： Zare, Samira Spaeth, Alex Suresh, Sandya Teodorescu, Mircea Department of Electrical and Computer Engineering University of California Santa Cruz United States SIP program University of California Santa Cruz United States Department of Computer Science and Engineering United States

Origami structures have been widely explored in robotics due to their many potential advantages. Origami robots can be very compact, as well as cheap and efficient to produce. In particular, they can be constructed in a flat format using modern manufacturing techniques. Rotational motion is essential for robotics, and a variety of origami rotational joints have been proposed in the literature. However, few of these are even approximately flat-foldable. One potential enabler of flat origami rotational joints is the inclusion of lightweight pneumatic pouches which actuate the origami’s folds;however, pouch actuators only enable a relatively small amount of rotational displacement. The previously proposed Four-Vertex Origami is a flat-foldable structure which provides an angular multiplier for a pouch actuator, but suffers from a degenerate state. This paper presents a novel rigid origami, the Self-Lock Origami, which eliminates this degeneracy by slightly relaxing the assumption of flat-foldability. This joint is analysed in terms of a trade-off between the angular multiplier and the mechanical advantage. Furthermore, the Self-Lock Origami is a modular joint which can be connected to similar or different joints to produce complex movements for various applications;three different manipulator designs are introduced as a proof of concept. Copyright © 2023, The Authors. All rights reserved.

关键词： Manipulators

来源：评论

学校读者我要写书评

暂无评论

The Impact of ICN/CCN Cache Decision Policies on Video and Audio Transmission QoE

The Impact of ICN/CCN Cache Decision Policies on Video and A...

引用

Australasian Telecommunication Networks and Applications Conference, ATNAC

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

ISBN: (数字)9781665471039

ISBN: (纸本)9781665471046

This paper considers video and audio transmission in ICN (Information-Centric Networking) CCN (Content- Centric Networking), in which each intermediate node can cache content. LCE (Leave Copy Everywhere) has been known as a generic cache decision policy. However, because LCE caches at all the intermediate nodes, the cache of intermediate nodes can be duplicated. Therefore, various cache decision policies that eliminate redundancy have been proposed. In this paper, we evaluate the effect of the cache decision policies on QoE of video and audio transmission in ICN/CCN. We assess application-level QoS using a computer simulation with a tree network and QoE by means of subjective experiment.

关键词： computer simulation Redundancy Information-centric networking Quality of service Liquid crystal displays Communications technology Quality of experience

来源：评论

学校读者我要写书评

暂无评论

HSI: Human Saliency Imitator for Benchmarking Saliency-Based Model Explanations 10th

HSI: Human Saliency Imitator for Benchmarking Saliency-Based...

引用

10th AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2022

作者： Yang, Yi Zheng, Yueyuan Deng, Didan Zhang, Jindi Huang, Yongxiang Yang, Yumeng Hsiao, Janet H. Cao, Caleb Chen Huawei Research Hong Kong Hong Kong Department of Psychology University of Hong Kong Hong Kong Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong State Key Laboratory of Brain and Cognitive Sciences University of Hong Kong Hong Kong Institute of Data Science University of Hong Kong Hong Kong

ISBN: (纸本)9781577358787

Model explanations are generated by XAI (explainable AI)methods to help people understand and interpret machine learning models. To study XAI methods from the human perspective, we propose a human-based benchmark dataset, i.e., human saliency benchmark (HSB), for evaluating saliency based XAI methods. Different from existing human saliency annotations where class-related features are manually and subjectively labeled, this benchmark collects more objective human attention on vision information with a precise eyetracking device and a novel crowdsourcing experiment. Taking the labor cost of human experiment into consideration, we further explore the potential of utilizing a prediction model trained on HSB to mimic saliency annotating by humans. Hence, a dense prediction problem is formulated, and we propose an encoder-decoder architecture which combines multimodal and multi-scale features to produce the human saliency maps. Accordingly, a pretraining-finetuning method is designed to address the model training problem. Finally, we arrive at a model trained on HSB named human saliency imitator(HSI).We show, through an extensive evaluation, that HIS can successfully predict human saliency on our HSB dataset, and the HSI-generated human saliency dataset on Image Netshow cases the ability of benchmarking XAI methods both qualitatively and quantitatively. © 2022, Association for the Advancement of Artificial Intelligence.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

Non-Hermitian selective thermal emitter for thermophotovoltaics

Non-Hermitian selective thermal emitter for thermophotovolta...

引用

2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Prasad, Ciril S. Raphaelson, Samuel C. Naik, Gururaj V. Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Department of Material Science and NanoEngineering Rice University HoustonTX United States

ISBN: (纸本)9781957171258

Selective thermal emitters can boost the efficiency of heat-to-electricity conversion in thermophotovoltaic systems only if their spectral selectivity is high. We demonstrate a non-Hermitian metasurface-based selective emitter operating at 1200 K in a GaSb-thermophotovoltaic cell. © Optica Publishing Group 2023 © 2023 The Author(s)

关键词： III-V semiconductors

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection in Pediatric and Adults Brain MRI with Generative Model 46

Anomaly Detection in Pediatric and Adults Brain MRI with Gen...

引用

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

作者： Chen, Chaojun Namdar, Khashayar Wagner, Matthias W. Ertl-Wagner, Birgit B. Khalvati, Farzad Department of Mechanical and Industrial Engineering University of Toronto Canada Institute of Medical Science University of Toronto Canada Neurosciences & Mental Health Research Program SickKids Research Institute TorontoON Canada Department of Diagnostic & Interventional Radiology The Hospital for Sick Children TorontoON Canada Department of Diagnostic and Interventional Neuroradiology University Hospital Augsburg Germany Department of Medical Imaging University of Toronto Canada Department of Computer Science University of Toronto Canada Vector Institute TorontoON Canada

ISBN: (纸本)9798350371499

Magnetic Resonance Imaging (MRI) serves as a valuable tool for detecting abnormalities in brain structures. However, a notable 5-10% of pathologies remain unnoticed in MRI scans. To address this challenge and reduce the burden on radiologists, machine learning methods have been used to automate anomaly detection. In this work, we propose to use Denoising Diffusion Probabilistic Model (DDPM) for anomaly detection in MRI. DDPM learns to reconstruct healthy brain MRI and generates anomaly maps to facilitate the classification of the input MRI as healthy or unhealthy. The proposed model correctly differentiated all healthy or unhealthy test patients. Additionally, localized regions of interest in the generated anomaly maps, and the diffusion model achieved a Dice coefficient of 0.376, outperforming other generative models such as generative adversarial network (GAN). © 2024 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Mechanism of Threshold Voltage Instability in Double Gate α-IGZO Nanosheet TFT under Bias and Temperature Stress

引用

IEEE Journal of the Electron Devices Society 2024年 12卷 464-471页

作者： Aslam, Muhammad Chang, Shu-Wei Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Lee, Wen-Hsi Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan City701401 Taiwan Institute of Pioneer Semiconductor Innovation Industry Academic Innovation School National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Amorphous indium gallium zinc oxide (a-IGZO)-based thin film transistors (TFTs) are increasingly becoming popular because of their potential in futuristic applications, including CMOS technology. Given the demand for CMOS-compatible, ultra-scaled, reliable, and high-performing devices, we fabricate and analyze scaled-channel a-IGZO-TFTs with an optimal double-gate structure, a thin nanosheet-based channel, and an effective high- κ dielectric namely HfO2. The reliably reported double gate IGZO nanosheet TFTs (DG-IGZO-NS-TFTs) are tested under positive and negative bias stress at variant temperatures, and the resulting modulations are analyzed critically. The reported DG-IGZO-NSTFTs exhibit a negative side threshold voltage shift (Δ Vth) accompanied by an increase in Ion/Ion(0) under negative bias temperature stress (NBTS) at elevated temperatures, which indicates the presence of additional charges. An anomalous negative side shifting of the Vth is observed under positive bias temperature stress (PBTS), where diffused hydrogen atoms are identified as introducing excess n-type carriers into the channel and causing the observed Δ Vth. The spectroscopic analysis is performed to establish evidence for the assumed mechanisms, and the role of individual gates is investigated in the context of performance variance under temperature-bias stress. Moreover, the partial reversibility of the stress-induced degradation is experimentally established and methodically discussed. Overall, the reported results offer a comprehensive understanding of scaled-channel DG-NS-IGZO-TFTs, which help shape performance-enhancement strategies, control degradation mechanisms, and define appropriate application scenarios. © 2013 IEEE.

关键词： Thin film transistors

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach to IoT- Based Water Quality Monitoring

Machine Learning Approach to IoT- Based Water Quality Monito...

引用

IEEE Eurasia Conference on Biomedical engineering, Healthcare and Sustainability (ECBIOS)

作者： Chin-Chih Chang Chi-Hung Wei Min-Tien Lin Sz-Chwun John Hwang Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan Program in Engineering Science Chung Hua University Hsinchu City Taiwan Department of Landscape Architecture Chung Hua University Hsinchu Taiwan

Water resources are inevitable for human survival but untreated wastewater harms the environment. Thus, ongoing monitoring of water quality is necessary to identify pollution sources and prevent further damage. For such monitoring, an IoT water quality monitoring system was developed using Arduino technology to collect and transmit data to MQTT Brokers and store it in a database. The data is presented on a monitoring webpage. Three machine learning methods (Random Forest, ANN, and LightGBM) were used for backend analysis and prediction. LightGBM was found to have the highest prediction accuracy for NH3, pH, ORP, and temperature. The research contributes to reducing the need for frequent and costly data collection by using an IoT system for real-time monitoring and employing machine learning predictions to compensate for missing data. This approach provides a more efficient and effective method for analyzing and predicting water quality.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse

引用

IEEE Transactions on Mobile Computing 2025年

作者： Liu, Guangyuan Du, Hongyang Wang, Jiacheng Niyato, Dusit Kim, Dong In Nanyang Technological University College of Computing and Data Science Energy Research Institute @ NTU Interdisciplinary Graduate Program Singapore University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Nanyang Technological University College of Computing and Data Science Singapore Sungkyunkwan University Department of Electrical and Computer Engineering Korea Republic of

The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation of high-quality, photorealistic images to enhance user experience. However, generating these images, especially through Generative Diffusion Models (GDMs), in mobile edge computing environments presents significant challenges due to the limited computing resources of edge devices and the dynamic nature of wireless networks. This paper proposes a novel framework that integrates contract-inspired contest theory, Deep Reinforcement Learning (DRL), and GDMs to optimize image generation in these resource-constrained environments. The framework addresses the critical challenges of resource allocation and semantic data transmission quality by incentivizing edge devices to efficiently transmit high-quality semantic data, which is essential for creating realistic and immersive images. The use of contest and contract theory ensures that edge devices are motivated to allocate resources effectively, while DRL dynamically adjusts to network conditions, optimizing the overall image generation process. Experimental results demonstrate that the proposed approach not only improves the quality of generated images but also achieves superior convergence speed and stability compared to traditional methods. This makes the framework particularly effective for optimizing complex resource allocation tasks in mobile edge Metaverse applications, offering enhanced performance and efficiency in creating immersive virtual environments. © 2002-2012 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Improving Candle Direction Classification in Forex Market Using Support Vector Machine with Hyperparameters Tuning

Improving Candle Direction Classification in Forex Market Us...

引用

International Conference on Informatics and Computing (ICIC)

作者： Raymond Sunardi Oetama Yaya Heryadi Lukas Wayan Suparta Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Indonesia

ISBN: (纸本)9798350345728

Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned.

关键词： Support vector machines Training Exchange rates Market research Data models Kernel Informatics

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：