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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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Development of Automated Detection Methods for Calculating Blood Vessel Width and Stenosis Rate in Cardiac Catheterization Imaging 24

Development of Automated Detection Methods for Calculating B...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Huang, Hsien-Cheng Chang, Hsiao-Huang Ke, Xiang-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Cardiovascular Surgery Department Taipei Veterans General Hospital Taipei City Taiwan Taipei Medical University Taipei City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Coronary artery disease is the most prevalent type of heart disease and has a considerable mortality rate. In diagnosing and assessing coronary artery disease, physicians must integrate a variety of clinical information and test results to evaluate the degree of coronary artery obstruction and continually learn and improve their skills in clinical practice to ensure the most accurate assessment of patients. Currently, the use of information technology to assist medical staff allows more effective and accurate analysis of symptoms. This approach not only serves as an auxiliary standard for physician diagnosis, thereby reducing the possibility of misdiagnosis, but also significantly improves patient treatment outcomes and medical quality while reducing the time burden on physicians for diagnosing patients. This study utilized image processing techniques and thinning algorithms to automate the detection of coronary artery width and, following the recommended methods of physicians in related fields, used specific vessel widths to calculate the degree of coronary artery narrowing. This provides a more accurate and efficient assessment method for evaluating the degree of vascular constriction in patients with coronary artery disease. © 2024 Copyright ACM.

关键词： Patient treatment

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Development of a Mixed-Reality Dual-User Training System for Robot Laparoscopic Surgery

Development of a Mixed-Reality Dual-User Training System for...

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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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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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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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Enhancement of Antenna Gain With M&W Slot Model on EBG Reflector Structure Utilizing Reflection Phase Diagram Analysis

Enhancement of Antenna Gain With M&W Slot Model on EBG Refle...

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13th International electrical engineering Congress, iEECON 2025

作者： Chakunna, Payu Phusam, Nopphadon Mahatthanajatuphat, Pisit Lee, Wilaiporn Suangun, Thanakarn University of Phayao School of Engineering Phayao Thailand Yothinburana School Regular Program in Mathematics-Science Bangkok Thailand King Mongkut's University of Technology North Bangkok Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331543952

This research demonstrates the improvement in antenna gain by utilizing an EBG reflector. The EBG reflector includes a unit cell with grooves shaped like the letters M and W to mitigate surface waves at a frequency of 2.45 GHz. The suggested EBG reflector is constructed on an FR-4 substrate exhibiting a uniform dielectric constant of 4.3, a loss tangent of 0.025, and a thickness of 1.6 mm. Furthermore, the impact of boosting the antenna gain can be analyzed by the reflection phase diagram, which exhibits values ranging from +90° to -90° at the resonant frequency of the reflector. The proposed EBG reflector comprises 5x5 unit cells. The testing results of the reflector's performance, when integrated with a general dipole antenna, indicate that it can effectively respond to the resonant frequency of 2.45 GHz, with a |S11| level below -10 dB within the frequency range of 2.2 GHz to 2.6 GHz, thereby adequately covering the IEEE 802.11 b/g/n band. The suggested EBG reflector exhibits a gain of around 6.5 dBi at 2.45 GHz, indicating its efficacy in enhancing gain relative to the standard PEC reflector. Moreover, the radiation pattern is also directional. © 2025 IEEE.

关键词： Antenna reflectors

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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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UpCycling: Semi-supervised 3D Object Detection without Sharing Raw-level Unlabeled Scenes

UpCycling: Semi-supervised 3D Object Detection without Shari...

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International Conference on computer Vision (ICCV)

作者： Sunwook Hwang Youngseok Kim Seongwon Kim Saewoong Bahk Hyung-Sin Kim Department of Electrical and Computer Engineering Seoul National University SK Telecom Seoul Korea Graduate School of Data Science Seoul National University

Semi-supervised Learning (SSL) has received increasing attention in autonomous driving to reduce the enormous burden of 3D annotation. In this paper, we propose UpCycling, a novel SSL framework for 3D object detection with zero additional raw-level point cloud: learning from unlabeled de-identified intermediate features (i.e., "smashed" data) to preserve privacy. Since these intermediate features are naturally produced by the inference pipeline, no additional computation is required on autonomous vehicles. However, generating effective consistency loss for unlabeled feature-level scene turns out to be a critical challenge. The latest SSL frameworks for 3D object detection that enforce consistency regularization between different augmentations of an unlabeled raw-point scene become detrimental when applied to intermediate features. To solve the problem, we introduce a novel combination of hybrid pseudo labels and feature-level Ground Truth sampling (F-GT), which safely augments unlabeled multi-type 3D scene features and provides high-quality supervision. We implement UpCycling on two representative 3D object detection models: SECOND-IoU and PV-RCNN. Experiments on widely-used datasets (Waymo, KITTI, and Lyft) verify that UpCycling outperforms other augmentation methods applied at the feature level. In addition, while preserving privacy, UpCycling performs better or comparably to the state-of-the-art methods that utilize raw-level unlabeled data in both domain adaptation and partial-label scenarios.

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Hybrid Full-Bridge Phase-Shift and Half-Bridge LLC Resonant Converter Based on Dual Transformers

Hybrid Full-Bridge Phase-Shift and Half-Bridge LLC Resonant ...

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International Conference on Applied System Innovation (ICASI)

作者： Chih-Chiang Hua Ching-Chun Chuang Min-Rui Hong Jian-Min Wang Department of Electrical Engineering National Yunlin University of Science and Technology Douliou Taiwan R.O.C. Department of Electrical Engineering National Kaohaiung University of Science and Technology Kaohsiung City Taiwan Computer Science and Information Engineering National Formosa University Taiwan Graduate Institute of Vehicle Engineering National Formosa University Taiwan

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

This paper proposes a hybrid full-bridge phase-shift and half-bridge LLC resonant converter based on dual transformers with different output voltages. In the proposed LLC resonant circuit, the power switches can achieve zero-voltage switching, which reduces power losses caused by traditional hard switching. Additionally, the converter continuously operates at the resonant frequency, enabling zero-current switching for the rectifier diodes and enhancing overall converter efficiency. The prototype circuit operates at an input voltage of 400V and fixed frequency with a constant duty ratio. By adjusting the phase shift between PWM square waves to change the output power, the proposed converter achieves a wide range of output voltages from 250V to 450V and a rated capacity of 1kW. The experimental results show that the proposed converter achieves a maximum conversion efficiency of 92.01% at an output voltage of 250V and a maximum conversion efficiency of 93.78% at an output voltage of 450V.

关键词： Legged locomotion Technological innovation Resonant frequency Rectifiers RLC circuits Switches Resonant converters

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