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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Nico Surantha Vito Vincentdo BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Department of Electrical Faculty of Scienc and EngineeringElectronics and Communication Engineering Tokyo City University Japan

The rapid population growth and industrial development in developing countries harm the agricultural sector because many agricultural lands are converted into residential or industrial areas. Applying modern agriculture technologies such as hydroponic could help to overcome the problem. However, hydroponics requires special attention in adjusting the pH and nutrient levels to maximize plant growth, so an automated system is needed to manage the process. In this research, a smart hydroponic system is proposed by applying Adaptive Networkbased Fuzzy Inference System (ANFIS) and Internet-of-Things. The IoT system consists of sensor, actuator, and data processing layer is designed to monitor and control the condition of pH and nutrition of the observed plants. Then, the ANFIS algorithm is designed to control the level of pH and nutrition. The experiment results show that the system can automatically adjust the pH and nutrient levels to the expected range for growing plants, and the fuzzy controller made using ANFIS are more accurate and stable than the fuzzy controller made using Sugeno. This study shows that ANFIS has excellent performance when controlling multiple actuators, as long as the data set has great granularity and well defined.

关键词： Fuzzy logic Training Actuators Adaptive systems Hydroponics Media Control systems

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Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities

arXiv

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arXiv 2024年

作者： Liu, Guangyuan Van Huynh, Nguyen Du, Hongyang Hoang, Dinh Thai Niyato, Dusit Zhu, Kun Kang, Jiawen Xiong, Zehui Jamalipour, Abbas In Kim, Dong The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The Department of Electrical Engineering and Electronics University of Liverpool Liverpool L69 3GJ United Kingdom The School of Electrical and Data Engineering University of Technology Sydney Australia The School of Computer Science and Engineering Nanyang Technological University Singapore College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Electrical and Information Engineering University of Sydney Australia The College of Information and Communication Engineering Sungkyunkwan University Korea Republic of

With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans. However, learning and coordinating movements and actions for a large number of unmanned vehicles in complex and dynamic environments introduce significant challenges to conventional AI methods. Generative AI (GAI), with its capabilities in complex data feature extraction, transformation, and enhancement, offers great potential in solving these challenges of unmanned vehicle swarms. For that, this paper aims to provide a comprehensive survey on applications, challenges, and opportunities of GAI in unmanned vehicle swarms. Specifically, we first present an overview of unmanned vehicles and unmanned vehicle swarms as well as their use cases and existing issues. Then, an in-depth background of various GAI techniques together with their capabilities in enhancing unmanned vehicle swarms are provided. After that, we present a comprehensive review on the applications and challenges of GAI in unmanned vehicle swarms with various insights and discussions. Finally, we highlight open issues of GAI in unmanned vehicle swarms and discuss potential research directions. © 2024, CC BY.

关键词： Metadata

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High-Resolution Hydrogen Molecule Detection Utilizing a Nanocandle-Based Optical Sensor

High-Resolution Hydrogen Molecule Detection Utilizing a Nano...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Nu-Ri Park Min-Joong Kim Jongsu Lee Minah Seo Yong-Sang Ryu Myung-Ki Kim KU-KIST Graduate School of Converging Science and Technology Korea University Seoul Republic of Korea Sensor System Research Center Korea Institute of Science and Technology Seoul Republic of Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA School of Biomedical Engineering Korea University Seoul Republic of Korea Interdisciplinary Program in Precision Public Health Korea University Seoul Republic of Korea

Our research introduces a novel method for safe hydrogen detection. We've developed an advanced nano-candle sensor, combining Pd with nano-candles, enabling accurate detection of low-concentration hydrogen (<3%... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Electric potential Accuracy Hydrogen Lasers and electrooptics Optical sensors Electro-optical waveguides

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Impact of CLAHE-based image enhancement for diabetic retinopathy classification through deep learning

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Procedia computer Science 2023年 216卷 57-66页

作者： Mira Hayati Kahlil Muchtar Roslidar Novi Maulina Irfan Syamsuddin Gregorius Natanael Elwirehardja Bens Pardamean Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Telematics Research Center (TRC) Universitas Syiah Kuala Banda Aceh 23111 Indonesia Faculty of Medicine Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Computer and Networking Engineering Politeknik Negeri Ujung Pandang Makassar 90245 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Diabetic retinopathy (DR) is a type of diabetes mellitus that attacks the retina of the eye. DR will cause patients to experience blindness slowly. Generally, DR can be detected by using a special instrument called an ophthalmoscope to view the inside of the eyeball. However, in conditions where there is a very small difference between the normal image and the DR image, computer-based assistance is needed for maximizing image reading value. In this research, a method of image quality improvement will be carried out which will then be integrated with a classification algorithm based on deep learning. The results of image improvement using Contrast Limited Adaptive Histogram Equalization (CLAHE) shows that the average accuracy of the method on several models is very competitive, 91% for the VGG16 model, 95% for InceptionV3, and 97% for EfficientNet compared to the results original image which only has an accuracy of 87% for VGG16 model, 90% for InceptionV3 model, and 95% for EfficientNet. However, in ResNet34 better accuracy is obtained in the original image with an accuracy of 95% while in the CLAHE image the accuracy value is only 84%. The results of this comprehensive evaluation and recommendation of famous backbone networks can be useful in the computer-aided diagnosis of diabetic retinopathy.

关键词： Diabetic retinopathy Deep Learning CNN Image Enhancement CLAHE

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Non-Hermitian metasurface with non-trivial topology

Non-Hermitian metasurface with non-trivial topology

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CLEO: QELS_Fundamental Science, QELS 2022

作者： Prasad, Ciril S. Yang, Frank Li, Weijian Lach, Rosemary Everitt, Henry O. 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 U.S. Army DEVCOM Army Research Laboratory-South HoustonTX United States

The synergy between topology and non-Hermiticity in photonics holds potential for optical devices that are robust against defects. We demonstrate a non-Hermitian plasmonic-dielectric metasurface in the visible with no... 详细信息

ISBN: (纸本)9781557528209

关键词： Topology

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Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using a Deep Learning Approach

Enhancing Diagnostic Accuracy for Knee Osteoarthritis Using ...

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International Symposium on Applied Science 2024, ISAS 2024

作者： Raza, Aquib Ching, Congo Tak Shing Liu, Peng-Ta Phan, Thien-Luan Tran, Ngoc-Luan Nguyen, Ha Anh T. Rameez, Mohammad Li, Hung-Chung Linh, Dao Nguyen Phuong Van Hieu, Nguyen Tran, Trung Nghia National Taiwan University Taipei City10673 Taiwan Research Center for Information Technology Academia Sinica Taipei City11529 Taiwan Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Electrical Engineering National Chi Nan University Nantou County Taiwan Advanced Plant and Food Crop Biotechnology Center National Chung Hsing University Taichung402 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan Fall Prevention Center Department of Physical Medicine & Rehabilitation Changhua Christian Hospital Changhua500 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University - Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Department of Computer Science University of York York HeslingtonYO10 5DD United Kingdom Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan Ho Chi Minh City72409 Viet Nam HCMUT Vietnam National University Ho Chi Minh City Thu Duc Ho Chi Minh City71308 Viet Nam

This research introduces a deep learning framework that combines convolutional neural networks with autoencoders to improve the diagnostic accuracy of knee osteoarthritis. The study utilized a publicly available dataset from the Mendeley Data repository, where knee joint images were preprocessed using Contrast Limited Adaptive Histogram Equalization to enhance contrast and ensure consistent image sizing. Initially, an autoencoder was employed in an unsupervised manner to learn compressed representations of the data. These representations were then used to train a CNN to classify knee images into 'healthy' and 'osteoarthritic' categories. The model was trained using an 80:20 split for training and testing data, incorporating early stopping and data augmentation techniques to prevent overfitting and enhance generalization. Performance metrics such as accuracy, precision, recall, and the area under the Receiver Operating Characteristic curve (ROCAUC) were used to evaluate the model, resulting in a high test accuracy of 98.95%. The high precision and recall rates further confirmed the model's robustness in diagnosing KOA. To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to identify critical regions in the images that influenced the model's decisions. Additionally, t-Distributed Stochastic Neighbor Embedding (t-SNE) was used to visualize the high-dimensional encoded features in a two-dimensional space, providing deeper insights into how the model differentiates between classes. The promising results of this deep learning approach suggest its potential for broader applications in medical imaging diagnostics. By providing healthcare professionals with a tool that enhances diagnostic accuracy and operational efficiency, this framework lays the foundation for developing scalable, AI-driven diagnostic systems for various complex medical conditions. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Joints (anatomy)

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Performance comparison of InGaN-based 40–80 μm micro-LEDs fabricated with and without plasma etching

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Materials Today Advances 2024年 22卷

作者： Lo, Yu-Yun Chen, Yi-Ho Hsu, Yun-Cheng Lee, Tzu-Yi Hung, Yu-Ying Kao, Yu-Cheng Zan, Hsiao-Wen Wuu, Dong- Sing Kuo, Hao-Chung Samukawa, Seiji Horng, Ray-Hua Institute of Electronics National Yang Ming Chiao Tung University 1001 University Road Hsinchu30010 Taiwan Department of Photonics College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan Department of Materials Science and Engineering National Chung Hsing University Taichung40227 Taiwan Department of Applied Materials and Optoelectronic Engineering National Chi Nan University Nantou54561 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan

The fabrication of InGaN-based blue 4✕4 array micro-LEDs (μLEDs) with 40 μm ✕40 μm chip size and 2✕2 array μLEDs with 80 μm ✕80 μm chip size etching by the inductive coupled plasma reactive ion etching (ICPRIE) and defect-free neutral beam etching (NBE) processes was studied in this work. In μLEDs of this size, the influence of defects formation in the sidewalls on EQE was evaluated. There was almost no difference in EQE between μLEDs array etched by the NBE process no matter 40 μm ✕40 μm and 80 μm ✕80 μm, but the dependence was observed in the ICPRIE. Even with this size, it was found that the size effect of EQE is smaller than that in case of using ICPRIE for defect-free neutral beam etching. This impact is substantial since μLED predominantly operated at low current density, around 1–5 A/cm2. Consequently, the reduction of defect density, encompassing both internal and sidewall defects, becomes imperative even in 40–80 μm InGaN-based μLEDs. This not only improves the overall efficiency of μLEDs but also fortifies the brightness stability of μLED displays if process etching by NBE. It was also found that the etching shape had an influence on EQE. It could be attributed to fact that the etching profile angle of NBE was more vertical than that of ICPRIE. Because the different angles of the mesa resulted in different light intensity. The μLEDs emitting with a wavelength of 450 nm, the light extraction efficiency and intensity at a mesa angle 58° of NBE etching μLEDs was about 8% lower than those of an angle (38°) of ICPRIE etching μLEDs by simulation. © The Authors

关键词： Light emitting diodes

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In Regard to Gouveia et al.

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International Journal of Radiation Oncology Biology Physics 2023年第1期115卷 247-248页

作者： Chang, En-Wei Liu, Chia-Wen Dong, Chen Kao, Yung-Shuo Ma, Kevin Sheng-Kai Wei, James Cheng-Chung School of Medicine Chung-Shan Medical University Taichung Taiwan Department of Radiation Oncology China Medical University Hospital Taichung Taiwan Center for Global Health Perelman School of Medicine University of Pennsylvania Philadelphia Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan Department of Dentistry Chung Shan Medical University and Chung Shan Medical University Hospital Taichung Taiwan Department of Allergy Immunology & Rheumatology Chung Shan Medical University Hospital Taichung Taiwan Institute of Medicine Chung Shan Medical University Taichung Taiwan Graduate Institute of Integrated Medicine China Medical University Taichung Taiwan

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Giant Deep-Ultraviolet Circular Dichroism in Synthetic Architectures of Ordered Carbon Nanotubes

Giant Deep-Ultraviolet Circular Dichroism in Synthetic Archi...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Doumani, Jacques Lou, Minhan Dewey, Oliver Hong, Nina Fan, Jichao Baydin, Andrey Pasquali, Matteo Yomogida, Yohei Yanagi, Kazuhiro Saito, Riichiro Kono, Junichiro Gao, Weilu Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX United States Department of Electrical and Computer Engineering The University of Utah Salt Lake CityUT United States Carbon Hub Rice University HoustonTX United States Department of Chemical and Biomolecular Engineering Rice University HoustonTX United States J.A. Woollam Co. LincolnNE United States The Smalley-Curl Institute Rice University HoustonTX United States Department of Chemistry Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States Department of Physics and Astronomy Tokyo Metropolitan University Tokyo Japan Department Physics Tohoku University Sendai Japan Department Physics and Astronomy Rice University HoustonTX United States

We demonstrate tunable, giant, and structure-induced deep-ultraviolet circular dichroism in macroscopically chiral assemblies of racemic carbon nanotubes prepared using two approaches: mechanical-rotation-assisted vac... 详细信息

ISBN: (纸本)9781957171258

关键词： Dichroism

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Chiral exceptional point enhanced active tuning and nonreciprocity in micro-resonators

arXiv

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arXiv 2024年

作者： Lee, Hwaseob Chang, Lorry Kecebas, Ali Mao, Dun Xiao, Yahui Li, Tiantian Alù, Andrea Özdemir, Sahin K. Gu, Tingyi Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Engineering Science and Mechanics Pennsylvania State University University ParkPA16802 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical and Computer Engineering Saint Louis University Saint LouisMO63103 United States

Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors with better responsivity. A recently demonstrated route to chiral EPs via lithographically defined symmetric Mie scatterers on the rim of resonators has not only provided the much-needed mechanical stability for studying chiral EPs, but also helped reduce losses originating from nanofabrication imperfections, facilitating the insitu study of chiral EPs and their contribution to the dynamics and tunability of resonators. Here, we use asymmetric Mie scatterers to break the rotational symmetry of a microresonator, to demonstrate deterministic thermal tuning across a chiral EP, and to demonstrate EP-mediated chiral optical nonlinear response and efficient electro-optic tuning. Our results indicate asymmetric electro-optic modulation with up to 17dB contrast at GHz and CMOS-compatible voltage levels. Such wafer-scale nano-manufacturing of chiral electro-optic modulators and the chiral EP-tailored tunning may facilitate new micro-resonator functionalities in quantum information processing, electromagnetic wave control, and optical interconnects. © 2024, CC BY.

关键词： Microresonators

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