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IEEE International Conference on Systems, Man and Cybernetics

作者： Ting-You Chen Kuu-Young Young Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electrical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

As robot surgery becomes more popular these days, it consequently solicits a high demand on its training system. Currently, most of the systems are intended for personal training, while it may be more effective if an experienced expert can also be involved. It thus motivates us to propose a dual-user robotic surgical training system that can closely link the mentor and trainee together. The system is developed in a mixed-reality environment that integrates the information from both the virtual and real worlds. The haptic feedback and virtual fixtures are employed for assistance during skill transfer. The proposed system can assess the proficiency level of the trainee for the mentor to provide proper assistance during training. The experimental results demonstrate that the proposed system is capable of enhancing the trainee's ability for surgery. Especially, similar effectiveness is observed during comparative studies with direct hands-on guidance frequently adopted for skill transfer during sport training.

关键词： Training Minimally invasive surgery Medical robotics Robot kinematics Fixtures Virtual reality Haptic interfaces Cybernetics Sports

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Automated classification of renal tumors on ultrasound images using deep neural network

Automated classification of renal tumors on ultrasound image...

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International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign)

作者： Wei-Chieh Wu Te-Mei Chiang Zhi-Ren Tsai Program in Artificial Intelligence College of Information and Electrical Engineering Asia University Taichung City Taiwan Department of Radiation Oncology Asia University Hospital Taichung City Taiwan Department of Computer Science & Information Engineering Asia University

ISBN: (数字)9798350363043

ISBN: (纸本)9798350363050

Kidney cancer is one of the most common cancers worldwide. The major types of malignant renal tumors are renal cell carcinoma and urothelial carcinoma. Although the majority of renal tumors are malignant, up to $20\%$ are benign, most commonly renal cyst and angiomyolipomas. Ultrasound is the most accessible imaging tool in medical practice, but it highly depends on operator skill, which may lead to high false-negative rate in diagnosis. The purpose of this study was to develop a predictive model for the automated classification of renal tumors on ultrasound images using deep neural network. A total of 880 kidney ultrasound images were used for training and testing. Transfer learning was used to the ten Convolution neural network models. The kidney ultrasound images were classified as benign or malignant tumors. The classification performance of the model was evaluated by sensitivity and specificity. The research results show that VGG18 yielded the best performance, with a sensitivity of $79 \%$, and a specificity of $86 \%$.

关键词： Training Ultrasonic imaging Sensitivity Convolution Transfer learning Artificial neural networks Sensitivity and specificity Kidney Cancer Testing

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Global distribution of forest classes and leaf biomass for use as alternative foods to minimize malnutrition

World Food Policy

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World Food Policy 2021年第2期7卷 128-146页

作者： Fist, Tim Adesanya, Adewale A. Denkenberger, David Pearce, Joshua M. Alliance to Feed the Earth in Disasters (ALLFED) Environmental and Energy Program Social Science Department Michigan Technological University Department of Mechanical Engineering University of Alaska Fairbanks Department of Electrical and Computer Engineering Western University

Due to the ready availability of tree leaves in many geographies, the alternative food of leaf concentrate currently has the potential to alleviate hunger in over 800 million people. It is therefore potentially highly impactful to determine the edibility of leaf concentrates, which are in the same regions as the world's most undernourished populations. Unfortunately, the toxicity of leaf concentrate for most common tree leaf types has not been screened and the cost of doing so demands a prioritization. This preliminary study explores this potential solution to world hunger by finding the forest classes most likely to offer proximate access to the world's hungry, thus providing the basis for a prioritized list of leaf types to screen for toxicity. Specifically, this study describes a novel methodology for mapping available green leaf biomass and corresponding forest classes (e.g., tropical moist deciduous forest), and their spatial relationship to the global distribution of people who are underweight. These results will be useful for developing a targeted list of tree species to conduct leaf toxicity analysis on, in the interest of developing leaves as an alternative food source for both current malnutrition problems and global catastrophic scenarios. © 2021 Policy Studies Organization.

关键词： agriculture edible leaves forests GIS global catastrophic risk hunger

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Is Attention All You Need for EEG to Predict Neurological Outcomes in Cardiac Arrest?

Is Attention All You Need for EEG to Predict Neurological Ou...

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2024 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2024

作者： Dionisio, Jefferson Rizwan, Muhammad Suzuki, Hidetaka Hassan, Kazi Mahmudul Chanpornpakdi, Ingon Lin, Lian-Yu Tanaka, Toshihisa Lin, Che Tokyo University of Agriculture and Technology Tokyo Japan Japanese Red Cross Musashino Hospital Department of Emergency and Critical Care Tokyo Japan National Taiwan University College of Medicine and Hospital Division of Cardiology Department of Internal Medicine Taipei Taiwan Artificial Intelligence of Things Taiwan International Graduate Program Academia Sinica Taipei Taiwan National Taiwan University Department of Electrical Engineering Taipei Taiwan Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan National Taiwan University Center for Advanced Computing and Imaging in Biomedicine Taipei Taiwan Department of Smart Medicine and Health Informatics National Taiwan University Taipei Taiwan

ISBN: (纸本)9798350351552

Sudden cardiac arrest (SCA) poses a significant health challenge, necessitating accurate predictions of neurological outcomes in comatose patients, where good outcomes are defined as the recovery of most cognitive functions. Electroencephalogram (EEG) serves as a valuable biomarker for monitoring neurological states due to its rich, time-dependent information. This study aims to predict neurological outcomes using early EEG data by employing the Transformer model, which leverages multi-headed attention to identify patterns in lengthy sequences such as hour-long EEG recordings. Unlike traditional methods that use subsampled EEG epochs, we utilize the entire EEG sequences, subdivided into time steps, allowing our model to capture detailed temporal patterns via the attention mechanism. Moreover, we trained our proposed model using each EEG recording as an individual data sample but evaluated our model through aggregated patient-wise predictions. This approach allows us to boost the data sample size. Our results demonstrate promising predictive performance, achieving an AUROC of 0.82 and AUPRC of 0.90 on the holdout test set and an AUROC of 0.73 and AUPRC of 0.93 on an external test set with patient-wise predictions. This study highlights the potential of utilizing attention mechanisms to capture important time series progressions across EEG sequences for improving SCA prognosis. © 2024 IEEE.

关键词： Electroencephalography

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Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models 9

Digital Forensics Investigation and Incident Response in Int...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Ahdan, Syaiful Zaki Hamidi, Eki Ahmad Riskiono, Sampurna Dadi Negara, Ridha Muldina Mayasari, Ratna Ramadona, Suci Nurhayati, Ade Sucipto, Adi Jupriyadi Nurkahfi, Galih Nugraha Farahiyah, Dzata Naseer, Muchammad Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science Lampung35132 Indonesia Uin Sunan Gunung Djati Bandung Electrical Engineering Department Bandung40614 Indonesia School of Electrical Engineering Telkom University Bandung40257 Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau28265 Indonesia Institut Teknologi Telkom Jakarta Faculty of Engineering Jakarta11710 Indonesia Bandung40135 Indonesia Universitas Islam Indonesia Yogyakarta Faculty of Industrial Technology Yogyakarta55584 Indonesia Sekolah Tinggi Teknologi Bandung Informatics Department Bandung40235 Indonesia

ISBN: (纸本)9798350305029

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article. © 2023 IEEE.

关键词： Internet of things

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Terahertz Time-Domain Imaging for Radiotherapy Treatment Monitoring in Pancreatic Ductal Adenocarcinoma

Terahertz Time-Domain Imaging for Radiotherapy Treatment Mon...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Debamitra Chakraborty Bradley N. Mills Jing Cheng Ivan Komissarov Scott Gerber Roman Sobolewski Materials Science Graduate Program University of Rochester Rochester New York Laboratory for Laser Energetics University of Rochester Rochester New York Department of Surgery University of Rochester Medical Center Rochester New York Department of Electrical and Computer Engineering University of Rochester Rochester New York

ISBN: (纸本)9798350369311

Terahertz time-domain imaging was performed of stereotactic body radiotherapy-treated murine pancreatic ductal adenocarcinoma (PDAC) with a high spatial resolution. To generate 2D maps of the tissue samples, the refractive index and absorption coefficient were used as imaging markers extracted with the maximum a-posteriori probability (MAP) estimation algorithm. The results were then compared with the terahertz maps of untreated murine PDAC tissue samples and demonstrated that terahertz imaging can probe physical changes with high sensitivity in the tissue post treatment.

关键词： Maximum a posteriori estimation Terahertz wave imaging Laser theory Sensitivity Refractive index Radiation therapy Time-domain analysis Spatial resolution Probes Monitoring

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Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and More

arXiv

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arXiv 2024年

作者： Bu, Fanchen Jo, Hyeonsoo Lee, Soo Yong Ahn, Sungsoo Shin, Kijung School of Electrical Engineering KAIST Daejeon Korea Republic of Kim Jaechul Graduate School of Artificial Intelligence KAIST Seoul Korea Republic of Graduate School of Artificial Intelligence POSTECH Pohang Korea Republic of Department of Computer Science and Engineering Pohang Korea Republic of

Combinatorial optimization (CO) is naturally discrete, making machine learning based on differentiable optimization inapplicable. Karalias & Loukas (2020) adapted the probabilistic method to incorporate CO into differentiable optimization. Their work ignited the research on unsupervised learning for CO, composed of two main components: probabilistic objectives and derandomization. However, each component confronts unique challenges. First, deriving objectives under various conditions (e.g., cardinality constraints and minimum) is nontrivial. Second, the derandomization process is underexplored, and the existing derandomization methods are either random sampling or naive rounding. In this work, we aim to tackle prevalent (i.e., commonly involved) conditions in unsupervised CO. First, we concretize the targets for objective construction and derandomization with theoretical justification. Then, for various conditions commonly involved in different CO problems, we derive nontrivial objectives and derandomization to meet the targets. Finally, we apply the derivations to various CO problems. Via extensive experiments on synthetic and real-world graphs, we validate the correctness of our derivations and show our empirical superiority w.r.t. both optimization quality and speed. © 2024, CC BY.

关键词： Combinatorial optimization

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Provably Efficient Algorithm for Nonstationary Low-Rank MDPs

arXiv

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arXiv 2023年

作者： Cheng, Yuan Yang, Jing Liang, Yingbin Integrative Sciences and Engineering Programme NUS Graduate School Singapore School of Electrical Engineering and Computer Science The Pennsylvania State University University ParkPA16802 United States Department of Electrical and Computer Engineering The Ohio State University OH43210 United States

Reinforcement learning (RL) under changing environment models many real-world applications via nonstationary Markov Decision Processes (MDPs), and hence gains considerable interest. However, theoretical studies on nonstationary MDPs in the literature have mainly focused on tabular and linear (mixture) MDPs, which do not capture the nature of unknown representation in deep RL. In this paper, we make the first effort to investigate nonstationary RL under episodic low-rank MDPs, where both transition kernels and rewards may vary over time, and the low-rank model contains unknown representation in addition to the linear state embedding function. We first propose a parameter-dependent policy optimization algorithm called PORTAL, and further improve PORTAL to its parameter-free version of Ada-PORTAL, which is able to tune its hyper-parameters adaptively without any prior knowledge of nonstationarity. For both algorithms, we provide upper bounds on the average dynamic suboptimality gap, which show that as long as the nonstationarity is not significantly large, PORTAL and Ada-PORTAL are sample-efficient and can achieve arbitrarily small average dynamic suboptimality gap with polynomial sample complexity. Copyright © 2023, The Authors. All rights reserved.

关键词： Markov processes

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Optical Wireless Integrated Sensing and Communication Based on Optical Phased Array: Performance Metric and Optimal Beamforming

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IEEE Transactions on Wireless Communications 2025年

作者： Wen, Yunfeng Yang, Fang Song, Jian Han, Zhu Tsinghua University Department of Electronic Engineering Beijing100084 China State Key Laboratory of Widegap Semiconductor Optoelectronic Materials and Technologies Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Optical wireless integrated sensing and communication (OW-ISAC) is emerging as a crucial technology to complement and augment its radio-frequency counterpart. In this paper, we propose an optical phased array (OPA)-based OW-ISAC framework to enable concurrent multi-user communication and environment imaging. The optical beamforming and atmospheric propagation are first elaborated to introduce the principles of OPA-based OW-ISAC. In addition, the investigation into the multi-beam property, direct detection scheme, and sensing task of imaging for OW-ISAC yields dedicated signal-to-interference-plus-noise ratio and contrast metrics for communication and sensing sub-systems, respectively. Moreover, the precoding matrices and photodiode orientations are jointly optimized to achieve optimal beamforming. Subsequently, numerical simulations illustrate the relationships between communication and sensing performance metrics. Furthermore, the proposed OW-ISAC scheme is substantiated in a realistic scenario with the optimized beamforming. The demonstrated high-precision sensing and reliable communication capabilities of OPA-based OW-ISAC can serve plentiful future applications in the era of connection and intelligence. © 2002-2012 IEEE.

关键词： Optical communication

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Self-polarized RGB device realized by semipolar micro-LEDs and perovskite-in-polymer films for backlight applications

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Opto-Electronic Advances 2024年第3期7卷 35-49页

作者： Tingwei Lu Yue Lin Tianqi Zhang Yue Huang Xiaotong Fan Shouqiang Lai Yijun Lu Hao-Chung Kuo Zhong Chen Tingzhu Wu Rong Zhang School of Electronic Science and Engineering Fujian Engineering Research Center for Solid-State LightingXiamen UniversityXiamen 361005China Innovation Laboratory for Sciences and Technologies of Energy Materials of Fujian Province(IKKEM) Xiamen 361005China Department of Photonics and Graduate Institute of Electro-Optical Engineering College of Electrical and Computer EngineeringYang Ming Chiao Tung UniversityHsinchu 30010China Semiconductor Research Center Hon Hai Research InstituteTaipei 11492China.

In backlighting systems for liquid crystal displays,conventional red,green,and blue(RGB)light sources that lack polarization properties can result in a significant optical loss of up to 50%when passing through a *** address this inefficiency and optimize energy utilization,this study presents a high-performance device designed for RGB polarized *** device employs an array of semipolar blueμLEDs with inherent polarization capabilities,coupled with mechanically stretched films of green-emitting CsPbBr3 nanorods and red-emitting CsPbI3-Cs4PbI6 hybrid *** CsPbBr3 nanorods in the polymer film offer intrinsic polarization emission,while the aligned-wire structures formed by the stable CsPbI3-Cs4PbI6 hybrid nanocrystals contribute to substantial anisotropic emissions,due to their high dielectric *** resulting device achieved RGB polarization degrees of 0.26,0.48,and 0.38,respectively,and exhibited a broad color gamut,reaching 137.2%of the NTSC standard and 102.5%of the Rec.2020 *** compared to a device utilizing c-plane LEDs for excitation,the current approach increased the intensity of light transmitted through the polarizer by 73.6%.This novel fabrication approach for polarized devices containing RGB components holds considerable promise for advancing next-generation display technologies.

关键词： halide perovskite light-emitting-diodes polarized emission nanocrystals stability

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