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Construction of Cu7s4@Cuco2o4 Yolk-Shell Microspheres Composite and Elucidation of its Enhanced Photocatalytic Activity, Mechanism, and Pathway for Carbamazepine Degradation

SSRN

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SSRN 2022年

作者： He, Zuming Yang, Hanpei Wong, Ngie Hing Ernawati, Lusi Sunarso, Jaka Huang, Zhengyi Xia, Yongmei Wang, Yong Su, Jiangbin Fu, Xiaofei Wu, Mi Key Laboratory of Integrated Regulation and Resource Development on Shallow Lakes Ministry of Education College of Environment Hohai University Nanjing210098 China Huaide School Changzhou University Jingjiang214500 China School of Microelectronics and Control Engineering Changzhou University Changzhou213164 China Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Sarawak Kuching93350 Malaysia Department of Chemical Engineering Institut Teknologi Kalimantan Balikpapan76127 Indonesia School of Materials and Engineering Jiangsu University of Technology Changzhou213001 China School of Pharmaceutical and Materials Engineering Taizhou University Jiaojiang318000 China

Water pollution caused by the massive use of medicines has caused major environmental problems. This work first reported the synthesis and characterization of the Cu7S4/CuCo2O4 (CS/CCO) yolk-shell microspheres via hydrothermal and annealing methods, then investigated their photocatalytic performance in removing organic water pollutants. The 10-CS/CCO composite with yolk-shell microspheres exhibited the highest photodegradation rate of carbamazepine (CBZ), reaching 96.3% within 2 h. The 10-CS/CCO also demonstrated more than 2 times higher photodegradation rates than the pure (Cu7S4) CS and (CuCo2O4) CCO. This outstanding photocatalytic performance can be attributed to the unique yolk-shell structure and the Z-scheme charge transfer pathway, reducing multiple reflections of the acting light. These factors enhanced the light absorption efficiency and efficiently transferred photoexcited charge carriers. In-depth photocatalytic degradation pathways of CBZ were systematically evaluated via the identification of degradation intermediates with Fukui index calculation. © 2022, The Authors. All rights reserved.

关键词： Microspheres

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Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach

arXiv

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arXiv 2024年

作者： Zheng, Jiakang Zhang, Jiayi Du, Hongyang Zhang, Ruichen Niyato, Dusit Dobre, Octavia A. Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong The College of Computing and Data Science Nanyang Technological University Singapore Faculty of Engineering and Applied Science Memorial University Canada The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China

Cell-free (CF) massive multiple-input multiple-output (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Rate-splitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, which combines strengths and mitigates weaknesses of both approaches. Considering imperfect channel state information (CSI) resulting from both pilot contamination and noise, we derive a closed-form expression for the sum spectral efficiency (SE) of the RS-based CF massive MIMO system under a spatially correlated Rician channel. Moreover, we propose low-complexity heuristic algorithms based on statistical CSI for power-splitting of common messages and power-control of private messages, and genetic algorithm is adopted as a solution for upper bound performance. Furthermore, we formulate a joint optimization problem, aiming to maximize the sum SE of the RS-based CF massive MIMO system by optimizing the power-splitting factor and power-control coefficient. Importantly, we improve a generative AI (GAI) algorithm to address this complex and non-convexity problem by using a diffusion model to obtain solutions. Simulation results demonstrate its effectiveness and practicality in mitigating interference, especially in dynamic environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Hierarchical Learning for IRS-Assisted MEC Systems with Rate-Splitting Multiple Access

arXiv

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arXiv 2024年

作者： Wu, Yinyu Zhang, Xuhui Ren, Jinke Shen, Yanyan Yang, Bo Wang, Shuqiang Guan, Xinping Niyato, Dusit The Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong518055 China The University of Chinese Academy of Sciences Beijing100049 China The Shenzhen Future Network of Intelligence Institute The School of Science and Engineering The Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Guangdong Shenzhen518172 China Shenzhen University of Advanced Technology Guangdong518055 China The Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China The College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

Intelligent reflecting surface (IRS)-assisted mobile edge computing (MEC) systems have shown notable improvements in efficiency, such as reduced latency, higher data rates, and better energy efficiency. However, the resource competition among users will lead to uneven allocation, increased latency, and lower throughput. Fortunately, the rate-splitting multiple access (RSMA) technique has emerged as a promising solution for managing interference and optimizing resource allocation in MEC systems. This paper studies an IRS-assisted MEC system with RSMA, aiming to jointly optimize the passive beamforming of the IRS, the active beamforming of the base station, the task offloading allocation, the transmit power of users, the ratios of public and private information allocation, and the decoding order of the RSMA to minimize the average delay from a novel uplink transmission perspective. Since the formulated problem is non-convex and the optimization variables are highly coupled, we propose a hierarchical deep reinforcement learning-based algorithm to optimize both continuous and discrete variables of the problem. Additionally, to better extract channel features, we design a novel network architecture within the policy and evaluation networks of the proposed algorithm, combining convolutional neural networks and densely connected convolutional network for feature extraction. Simulation results indicate that the proposed algorithm not only exhibits excellent convergence performance but also outperforms various benchmarks. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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The Combination of Two control Strategies for Series Hybrid Electric Vehicles

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IEEE/CAA Journal of Automatica Sinica 2019年第2期6卷 596-608页

作者： Can Luo Zhen Shen Simos Evangelou Gang Xiong Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Cloud Computing Center Chinese Academy of Sciences IEEE Department of Electrical and Electronic Engineering Imperial College London Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries

With most countries paying attention to the environment protection, hybrid electric vehicles have become a focus of automobile research and development due to the characteristics of energy saving and low emission. Power follower control strategy(PFCS) and DC-link voltage control strategy are two sorts of control strategies for series hybrid electric vehicles(HEVs). Combining those two control strategies is a new idea for control strategy of series hybrid electric vehicles. By tuning essential parameters which are the defined constants under DClink voltage control and under PFCS, the points of minimum mass of equivalent fuel consumption(EFC) corresponding to a series of variables are marked for worldwide harmonized light vehicles test procedure(WLTP). The fuel economy of series HEVs with the combination control schemes performs better compared with individual control scheme. The results show the effects of the combination control schemes for series HEVs driving in an urban environment.

关键词： DC-Link voltage control power follower control strategy series hybrid electric vehicles tuning

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Initial Study on Implementation of Smoothing Filters for the Purpose of Bioimpedance Spectroscopy Parameters Classification

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IFAC-PapersOnLine 2022年第4期55卷 393-398页

作者： Aleksandra Kawala-Sterniuk Amir F. Al-Bakri Mariusz Pelc Katarzyna Cichoń Wojciech Chlewicki Stepan Ozana Radek Martinek Jakub Możaryn Volodymyr Khoma Halyna Kenyo Edward Jacek Gorzelańczyk Michał Podpora Jarosław Zygarlicki Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics 45-758 Opole Poland Department of Biomedical Engineering College of Engineering University of Babylon 51001 Babylon Iraq University of Greenwich School of Computing and Mathematical Sciences SE10 9LS London UK West Pomeranian University of Technology in Szczecin Faculty of Electrical Engineering 70-313 Szczecin Poland Faculty of Mechatronics Warsaw University of Technology 02-525 Warsaw Poland Lviv Polytechnic National University Institute of Computer Technologies Automation and Metrology Lviv Ukraine Institute of Philosophy Kazimierz Wielki University 85-092 Bydgoszcz Poland Faculty of Mathematics and Computer Science Adam Mickiewicz University in Poznań 61-614 Poznań Poland

Bioimpedance is a commonly used method for various conditions monitoring. In this paper, the authors carried out some research where they implemented various smoothing filters to enable identification of the bioimpedance spectroscopy parameters. The proposed filtering methods may also be used for application on embedded systems, which have smaller computing power but have become recently very popular. The obtained results with the implementation of smoothing filters were promising, however, some of the obtained results were unsatisfactory. This work also contains a brief introduction to bioimpedance spectroscopy and smoothing filters.

关键词： Bioimpedance Spectroscopy smoothing-filtering Savitzky-Golay Filter Median Filtering Moving-Average Filters

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The development of pineapple leaf diseases classification using convolutionary neural network for mobile apps

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AIP Conference Proceedings 2024年第1期3135卷

作者： Muhammad Najmi Hasnol Mizam Sulaiman Mahzan Siti Fairuz Nurr Sadikan Mohd Ab Malek Md Shah Mohd Aliff Afira Sani College of Computing Informatics & Mathematic Universiti Teknologi MARA Melaka Malaysia. Faculty of Plantation & Agrotechnology Universiti Teknologi MARA Melaka Malaysia. Department of Law Universiti Teknologi MARA Melaka Malaysia. Department of Instrumentation and Control Engineering Universiti Kuala Lumpur Johore Malaysia.

Pineapple diseases are linked to worms, viruses, bacteria, and fungi. Insects including ants, scales, mealybugs, and souring beetles are some of the most prevalent pests that can harm the pineapple industry over time if early pineapple leaf disease detection is not made There are many smallholders especially in the rural area who lack of latest technology, knowledge, and experience about pineapple disease treatment and management. Thus, lack of a precise diagnosis method prevents them from understanding the disease and creates an effective control for its spread. This issue further impacts the effectiveness of pineapple production, subsequently affecting their income and the country’s, as well as jeopardizing national food security. This study presents an innovative approach aimed at enhancing early detection and management of pineapple leaf diseases by integrating a Convolutional Neural Network (CNN) algorithm and import it using TensorFlow Lite into an android mobile. The CNN model achieved an impressive total accuracy of 98% in precisely classifying three types of pineapple leaf diseases: Leaf Spot, Mealybug Wilt, and Pink Disease. When implemented in the mobile application, the system attained an overall confidence of 83.33% by leveraging both camera-captured and gallery images. Although the accuracy gained is impressive, additional research and adjustments can be conducted to improve the system’s performance and achieve even higher levels of accuracy.

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Home monitoring of motor fluctuations in Parkinson’s disease patients

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Journal of Reliable Intelligent Environments 2019年第3期5卷 145-162页

作者： Borzì, Luigi Varrecchia, Marilena Olmo, Gabriella Artusi, Carlo Alberto Fabbri, Margherita Rizzone, Mario Giorgio Romagnolo, Alberto Zibetti, Maurizio Lopiano, Leonardo Department of Control and Computing Engineering Politecnico di Torino Turin Italy Department of Neuroscience Rita Levi Montalcini University Hospital Città della Salute e della Scienza Regional Reference Center for Parkinson’s Disease and Movement Disorders Turin Italy

In Parkinson’s disease, motor fluctuations (worsening of tremor, bradykinesia, freezing of gait, postural instability) affect up to 70% of patients within 9 years of L-dopa therapy. Nevertheless, the assessment of motor fluctuations is difficult in a medical office, and is commonly based on poorly reliable self-reports. Hence, the use of wearable sensors is desirable. In this preliminary trial, we have investigated bradykinesia and freezing of gait—FOG—symptoms by means of inertial measurement units. To this purpose, we have employed a single smartphone on the patient’s waist for FOG experiment (38 patients), and on patient thigh for LA (93 subjects). Given the sound performance achieved in this trial (AUC = 0.97 for FOG and AUC = 0.92 for LA), motor fluctuations may be estimated in domestic environments. To this end, we plan to perform measures and data processing on SensorTile, a tiny IoT module including several sensors, a microcontroller, a BlueTooth low-energy interface and microSD card, implementing an electronic diary of motor fluctuations, posture and dyskinesia during activity of daily living. © 2019, The Author(s).

关键词： Wearable sensors

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Exponential Sensitivity Revival of Noisy non-Hermitian Quantum Sensing with Two-photon Drives

arXiv

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arXiv 2023年

作者： Bao, Liying Qi, Bo Nori, Franco Dong, Daoyi Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Civil Aviation University of China Tianjin300300 China Theoretical Quantum Physics Laboratory RIKEN Saitama351-0198 Japan Quantum Computing Center RIKEN Saitama351-0198 Japan Physics Department The University of Michigan Ann ArborMI48109 United States School of Engineering Australian National University CanberraACT2601 Australia

Unique properties of multimode non-Hermitian lattice dynamics can be utilized to construct exponentially sensitive sensors. However, the impact of noise remains unclear, which may severely degrade their sensitivity. We analytically characterize and highlight the impact of loss and gain on the sensitivity revival and stability of non-Hermitian sensors. Defying the general belief that the superiority of quantum sensing will vanish in the presence of loss, we find that by proactively tuning the loss, the exponential sensitivity can be surprisingly regained when the sensing dynamics is stable. Furthermore, we prove that gain is crucial to fully revive the ideally exponential sensitivity and to ensure the stability of non-Hermitian sensing by making a balanced loss and gain. Our work opens a new way to significantly enhance the sensitivity by proactively tuning the loss and gain, which may promote future quantum sensing and quantum engineering. Copyright © 2023, The Authors. All rights reserved.

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Visual defect detection for historical building preservation

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Expert Systems with Applications 2025年 291卷

作者： Cheng, Mengqiu Zhang, Xinting Xia, Leihua Chen, Junming Xie, Jiayuan Ma, Zongfang Li, Qing School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Xi'an China School of Information and Control Engineering Xi'an University of Architecture and Technology Xi'an China Department of Computing Hong Kong Polytechnic University Hong Kong SAR China Faculty of Humanities and Arts Macau University of Science and Technology Macau China Department of Mathematics The University of Hong Kong Hong Kong SAR China

Advancements in automated building defect detection technology are essential for preserving historical architecture. Although existing intelligent technologies have made notable progress in detecting defects in modern residential buildings, their application to historical buildings faces significant challenges due to the complexity of structures, material diversity, and long-term natural and human-induced deterioration. This study focuses on historical buildings in Guangzhou, China, and introduces a dedicated task for detecting defects in such buildings. To support this task, a high-quality, customized dataset has been developed as a research foundation. To address challenges such as image blurriness during data collection and the complex structural characteristics of historical buildings, this study proposes a baseline model named Deblur-DetNet. The model employs a two-stage approach that integrates image deblurring and defect detection, significantly enhancing both accuracy and robustness. Experimental results demonstrate that the proposed method performs exceptionally well in the task of historical building defect detection, particularly in identifying fine-grained defects. This research provides robust technical support for the protection and restoration of historical buildings and establishes a solid foundation for further studies in cultural heritage preservation. Our dataset is available at https://***/file/d/1-9NiAw0hzomWHOA9RMEMXOOwIq5HScPx/view?usp=sharing. © 2025

关键词： Computer vision Defect detection Historical building Image deblurring technology

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Time-Domain-Multiplexed Measurement-Based Quantum Operations with 25-MHz Clock Frequency

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Physical Review Applied 2021年第3期16卷 034005-034005页

作者： Warit Asavanant Baramee Charoensombutamon Shota Yokoyama Takeru Ebihara Tomohiro Nakamura Rafael N. Alexander Mamoru Endo Jun-ichi Yoshikawa Nicolas C. Menicucci Hidehiro Yonezawa Akira Furusawa Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Centre for Quantum Computation and Communication Technology School of Engineering and Information Technology University of New South Wales Canberra Australian Capital Territory 2600 Australia Center for Quantum Information and Control Department of Physics and Astronomy University of New Mexico Albuquerque New Mexico 87131 USA Centre for Quantum Computation and Communication Technology School of Science RMIT University Melbourne Victoria 3001 Australia Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Wako Saitama 351-0198 Japan

Continuous-variable optical quantum computation has seen much progress in recent years. In particular, cluster states—the universal resource for measurement-based quantum computation—have been realized in a scalable fashion using the time-domain multiplexing method. To utilize the cluster states in actual quantum computation, the measurement bases need to be programmed according to the desired computation. In addition, as the information is encoded in time in the time-domain multiplexing method, the measurement bases must be dynamically changed in time to fully utilize the large-scale cluster states. Here we report demonstrations of quantum operations using time-domain-multiplexed cluster states with a clock frequency of 25 MHz. This is achieved by our combining the cluster-state-generation setup with the setup to change the measurement basis in the time domain. We also formulate a method to evaluate and verify continuous-variable operations where the quantum entanglements in the cluster states are utilized. Therefore, we demonstrate the implementation of quantum operations on scalable continuous-variable cluster-state architectures. The results in this work are compatible with the developing nonlinear feedforward and non-Gaussian state generation technology, which brings the realization of the large-scale fault-tolerant universal optical quantum computer closer to reality.

关键词： Entanglement detection Measurement-based quantum computing Optical quantum information processing Quantum computation Quantum gates Quantum information processing with continuous variables Quantum teleportation Homodyne & heterodyne detection

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