http://scholars.ntou.edu.tw/handle/123456789/217 Sat, 25 Apr 2026 05:23:48 GMT 2026-04-25T05:23:48Z http://scholars.ntou.edu.tw:80/retrieve/99/電機工程學系.jpg http://scholars.ntou.edu.tw/handle/123456789/217 http://scholars.ntou.edu.tw/handle/123456789/26524 標題: A Myoelectric Signal-Driven Intelligent Wheelchair System Incorporating Occlusal Control for Assistive Mobility 作者: Chang, Chih-Tsung; Hsu, Yi-Chieh; Pai, Kai-Jun; Chou, Chia-Yi; Xu, Fu-Hua 摘要: This paper proposes a novel electric wheelchair that uses the surface electromyographic signal (sEMG) signals generated by the occlusal muscles to control the wheelchair during occlusion, instead of the traditional electric wheelchair that requires users to use their hands or feet for control. In this work, the myoelectric signal controls the electric wheelchair so that users with limited mobility and paraplegia can operate the electric wheelchair using the myoelectric signal generated during clenching. This is achieved through the seamless transmission of user data and GPS paths to the cloud and is facilitated by the state-of-the-art Wi-Fi 6E communication technology. By leveraging cloud connectivity, the system can instantly relay critical information, such as the user's location and movement patterns, ensuring a prompt emergency response. Furthermore, several standard methods exist to set up the myoelectric signal electrodes and analyze the signals. This novel electric wheelchair can change the daily activities of many users who have difficulty walking. This work is presented as a proof-of-concept feasibility study rather than a comprehensive clinical validation. Wed, 01 Jan 2025 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/26524 2025-01-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/26480 標題: Low-Latency Channel Estimation for OFDM System in Fast-Fading Multipath Environments 作者: Lee, Huang-Chang; Chen, Yi-Ru; Lin, Lu-Chi; Wang, Jing-Teng; Lin, Mao-Chao 摘要: Although suffering from inter-carrier interference (ICI), the proposed method can accomplish the channel estimation for the orthogonal frequency division multiplexing (OFDM) systems in high-mobility wireless communication environments using the conventional equally-separated stand-alone pilot arrangements. Initially, rough channel estimation based on the pilots is used for decoding the multiple low-density parity-check (LDPC) codes in each OFDM symbol in the first iteration. Correct decoding results provide reliable decision feedback, and can be used to form pseudo pilots and be combined with the original pilots to enhance the channel estimation in the following iterations. Simulation results confirm that the proposed method can extend the applicability of the OFDM systems equipped with the conventional pilot arrangement in fast-fading channels. Wed, 01 Jan 2025 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/26480 2025-01-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/26464 標題: A neural network adaptation on neutrosophic triplets for robotic assembly line optimization in smart manufacturing 作者: Nafei, Amirhossein; Li, Zhi; Azizi, S. Pourmohammad 摘要: The decision-making process in smart manufacturing often involves complex, multi-criteria scenarios characterized by uncertainty and conflicting objectives. Traditional decision-making approaches face inherent limitations in managing indeterminacy, ensuring robustness, and addressing computational complexity, which compromise their reliability in dynamic manufacturing environments. This study introduces an innovative framework that integrates the VIKOR method, neural networks, and Neutrosophic Triplets (NTs) to address these challenges. The proposed approach is specifically designed to optimize robotic assembly line configurations by balancing key objectives such as cost, operational efficiency, and sustainability. VIKOR's compromise solution methodology is leveraged to evaluate trade-offs between group utility and individual regret, while Neutrosophic Triplets enhance the management of indeterminate information. Neural networks provide scalability and adaptability, enabling dynamic ranking refinement and reducing computational overhead. Additionally, a ranking strategy based on occurrence pattern analysis ensures robust and reliable decision-making outcomes. Validated through a case study on robotic assembly line optimization in a smart manufacturing environment, the framework demonstrates its effectiveness in improving productivity, adaptability, and sustainability. These results position the smart VIKOR method as a powerful and scalable solution for addressing the complexities of modern manufacturing systems. Wed, 01 Jan 2025 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/26464 2025-01-01T00:00:00Z http://scholars.ntou.edu.tw/handle/123456789/26455 標題: Electrically-Driven 2D Semiconductor Microcavity Laser 作者: Chen, Zheng-Zhe; Lin, Hsiang-Ting; Chang, Chiao-Yun; Adil, Muhammad; Tsai, Po-Cheng; Kao, Tsung Sheng; Chen, Chi; Lin, Shih-Yen; Shih, Min-Hsiung 摘要: 2D monolayered transition-metal dichalcogenides (TMDCs) are promising materials for realizing ultracompact, low-threshold semiconductor lasers. And the development of the electrical-driven TMDC devices is crucial for enhancing the integration potential of practical optoelectronic systems. However, at the current stage, the electrically-driven 2-D TMDC laser has never been realized. Herein, the first electrically-driven 2-D TMDC microcavity laser have been developed. In this device, an alternating current (AC) generates electroluminescence lasing in suspended monolayered WSe2 integrated on a microdisk cavity. The input-output curve, bandwidth narrowing, and second-order coherence is analyzed to confirm the lasing characteristics at room temperature. The realization of the room-temperature AC-driven 2-D TMDC laser establishes a new area of research on electrically pumped compact lasers and is likely to assist with the implementation of diverse TMDC-based practical photonic devices in the future. Wed, 01 Jan 2025 00:00:00 GMT http://scholars.ntou.edu.tw/handle/123456789/26455 2025-01-01T00:00:00Z