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General Optimal Trajectory Planning:Enabling Autonomous Vehicles with the Principle of Least Action

engineering 2024年第2期33卷 63-76页

作者： Heye Huang Yicong Liu Jinxin Liu Qisong Yang Jianqiang Wang David Abbink Arkady Zgonnikov School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China Department of Cognitive Robotics Faculty of MechanicalMaritime and Materials Engineering(3mE)Delft University of TechnologyDelft 2628Netherlands Department of Software Technology Faculty of Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft 2628Netherlands Xi’an Institute of High-Technology Xi’an 710051China

This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road *** coordinates are then transformed to achieve the curvature continuity of the generated *** the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate ***,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and *** simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic ***,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.

关键词： Autonomous vehicle Trajectory planning Multi-performance objectives Principle of least action

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Hybrid robust fault detection and isolation of satellite reaction wheel actuators

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Journal of Control and Decision 2024年第1期11卷 117-131页

作者： H.Abbasi Nozari S.J.Sadati Rostami Paolo Castaldi Silvio Simani Faculty of Electrical and Computer Engineering Babol Noshirvani University of TechnologyBabolIran Department of Electrical Electronic and Information EngineeringUniversity of BolognaCesenaItaly Department of Engineering University of FerraraFerraraItaly

In this paper,a combined robust fault detection and isolation scheme is studied for satellite system subject to actuator faults,external disturbances,and parametric *** proposed methodology incorporates a residual generation module,including a bank of filters,into an intelligent residual evaluation ***,residual filters are designed based on an improved nonlinear differential algebraic approach so that they are not affected by external *** residual evaluation module is developed based on the suggested series and parallel ***,a new ensemble classification scheme defined as blended learning integrates heterogeneous classifiers to enhance the performance.A wide range of simulations is carried out in a high-fidelity satellite simulator subject to the constant and time-varying actuator faults in the presence of disturbances,manoeuvres,uncertainties,and *** obtained results demonstrate the effectiveness of the proposed robust fault detection and isolation method compared to the traditional nonlinear differential algebraic approach.

关键词： Robust fault detection and isolation reaction wheels blended learning series and parallel fault detection and isolation forms satellite attitude control system

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Towards robust and efficient intrusion detection in IoMT: a deep learning approach addressing data leakage and enhancing model generalizability

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Multimedia Tools and Applications 2024年 1-20页

作者： Bouke, Mohamed Aly El Atigh, Hayate Abdullah, Azizol Department of Communication Technology and Network Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang43400 Malaysia Departement of Computer Engineering Faculty of Computer Engineering Bandirma Onyedi Eylul University Balikesir10200 Turkey

The Internet of Medical Things (IoMT) brings advanced patient monitoring and predictive analytics to healthcare but also raises cybersecurity and data privacy issues. This paper introduces a deep-learning model for IoMT intrusion detection, utilizing the WUSTL EHMS 2020 dataset, which focuses on cyber threats like man-in-the-middle attacks and data injection. Our sequential model, trained with TensorFlow, surpasses traditional predictive accuracy and efficiency methods. It achieves 99% accuracy with reduced loss and excels in precision, recall, F1 Score, and ROC AUC. The model uses 25 key features from 45, preventing overfitting and addressing data leakage in preprocessing. These steps ensure the model's reliability for IoMT cybersecurity, demonstrating its effectiveness in real-world scenarios. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Cybersecurity

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Scheduling a Single-Arm Multi-Cluster Tool With a Condition-Based Cleaning Operation

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IEEE/CAA Journal of Automatica Sinica 2023年第10期10卷 1965-1983页

作者： Qinghua Zhu Hongpeng Li Cong Wang Yan Hou School of Computer Science and Technology Guangdong University of TechnologyGuangzhou 510006China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102-1982 USA

As wafer circuit widths shrink less than 10 nm,stringent quality control is imposed on the wafer fabrication processes. Therefore, wafer residency time constraints and chamber cleaning operations are widely required in chemical vapor deposition, coating processes, etc. They increase scheduling complexity in cluster tools. In this paper, we focus on scheduling single-arm multi-cluster tools with chamber cleaning operations subject to wafer residency time constraints. When a chamber is being cleaned, it can be viewed as processing a virtual wafer. In this way, chamber cleaning operations can be performed while wafer residency time constraints for real wafers are not violated. Based on such a method, we present the necessary and sufficient conditions to analytically check whether a single-arm multi-cluster tool can be scheduled with a chamber cleaning operation and wafer residency time constraints. An algorithm is proposed to adjust the cycle time for a cleaning operation that lasts a long cleaning ***, algorithms for a feasible schedule are also *** an algorithm is presented for operating a multi-cluster tool back to a steady state after the cleaning. Illustrative examples are given to show the application and effectiveness of the proposed method.

关键词： Chamber cleaning multi-cluster tools scheduling semiconductor manufacturing

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Cultural Heritage Monitoring and Predictive Maintenance using Internet of Things: Assessment and Future Aspects

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Journal of Mobile Multimedia 2024年第6期20卷 1211-1250页

作者： Um-E-habiba Shaikh, Faisal Karim Chowdhry, Bhawani Shankar Department of Computer Science Shaheed Zulfikar Ali Bhutto Institute of Science and Technology Hyderabad Pakistan Telecommunication Engineering Department Mehran University of Engineering and Technology Jamshoro Pakistan Faculty of Electrical Electronics and Computer Engineering Mehran University of Engineering and Technology Jamshoro Pakistan

This study presents a detailed survey on the use of the Internet of Things (IoT) for predictive maintenance and monitoring of cultural heritage, focusing on museums and exhibitions. The integration of IoT in these fields offers significant potential for optimizing maintenance and supervision of heritage resources while also enhancing maintenance strategies. This review examines the application of IoT devices, data analysis, and predictive algorithms in monitoring the state of heritage resources to improve tourist experiences and conserve cultural resources. Key enabling technologies can enable adaptive interactions and engagement with enhanced navigation. Visualization technologies are also common, offering hands-on displays. The study also emphasizes the value of accessibility and interactivity, providing personalization and content sharing features. Several initiatives prioritize the delivery of digital content through mobile applications, internet browsers, and downloadable *** study examines how IoT-enabled predictive maintenance systems can recognize potential hazards, like resource decay or environmental dangers, enabling immediate action. This survey also highlights trends, challenges, and future research in IoT and cultural heritage monitoring. © 2025 River Publishers.

关键词： heritage monitoring IoTs predictive maintenance trends

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Development of a Closed Chamber System for Cultivating Lion's Mane Mushrooms using an Internet of Things System to Increase Yield and Economic Value 10

Development of a Closed Chamber System for Cultivating Lion'...

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10th International Conference on Digital Arts, Media and technology and 8th ECTI Northern Section Conference on electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2025

作者： Suntornmeth, Pakorn Homjun, Kanitha Fankam-Ai, Worawit Karnjanapiboon, Charnyut Sanguansri, Atigorn Deenoi, Athiphong Kaewsirirung, Sirilux Rajamangala University of Technology Lanna Nan Faculty of Science and Agricultural Technology Department of Computer Science Nan Thailand Rajamangala University of Technology Lanna Nan Faculty of Engineering Department of Electrical Engineering Nan Thailand

ISBN: (纸本)9798331543273

This research investigates the development and implementation of an Internet of Things (IoT)-based closedsystem prototype for cultivating Yamabushitake (Lion's Mane) mushrooms, addressing the challenges of achieving optimal yields in Thailand's climate. Conducted at Saengkaew Mushroom Farm located in Nan Province, the study focuses on precise environmental control within the prototype chamber. The system employs an ESP32-IOXESP32U microcontroller and an AM2315 sensor to monitor and manage temperature, humidity, and airflow. A comparative analysis with a traditional evaporative cooling system reveals the closed system's superior performance in achieving higher yields and improved energy efficiency. The assessment of economic feasibility is conducted via a Cost-Benefit Analysis (CBA), demonstrating the potential for increased profitability and sustainable mushroom cultivation. This research offers significant findings regarding the utilization of IoT technology to enhance mushroom production and advance sustainable agricultural practices in Thailand. © 2025 IEEE.

关键词： Sustainable development

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DeepOCL:A deep neural network for Object Constraint Language generation from unrestricted nature language

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CAAI Transactions on Intelligence technology 2024年第1期9卷 250-263页

作者： Yilong Yang Yibo Liu Tianshu Bao Weiru Wang Nan Niu Yongfeng Yin School of Software Beihang UniversityBeijingChina College of Computer Science and Technology Guizhou UniversityGuiyangGuizhouChina Faculty of Information Technology Beijing University of TechnologyBeijingChina Department of Electrical Engineering and Computer Sciences University of CincinnatiCincinnatiOhioUSA

Object Constraint Language(OCL)is one kind of lightweight formal specification,which is widely used for software verification and validation in NASA and Object Management Group *** OCL provides a simple expressive syntax,it is hard for the developers to write correctly due to lacking knowledge of the mathematical foundations of the first-order logic,which is approximately half accurate at the first stage of devel-opment.A deep neural network named DeepOCL is proposed,which takes the unre-stricted natural language as inputs and automatically outputs the best-scored OCL candidates without requiring a domain conceptual model that is compulsively required in existing rule-based generation *** demonstrate the validity of our proposed approach,ablation experiments were conducted on a new sentence-aligned dataset named *** experiments show that the proposed DeepOCL can achieve state of the art for OCL statement generation,scored 74.30 on BLEU,and greatly outperformed experienced developers by 35.19%.The proposed approach is the first deep learning approach to generate the OCL expression from the natural *** can be further developed as a CASE tool for the software industry.

关键词： deep learning OCL software engineering

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A 69MHz-Bandwidth 40V/μ s-Slew-Rate 3n V/√Hz-Noise 4.5 μ V-Offset Chopper Operational Amplifier

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IEEE Transactions on Circuits and Systems I: Regular Papers 2024年第7期71卷 2977-2988页

作者： Koolivand, Yarallah Rezaeiyan, Yasser Zamani, Milad Akbari, Meysam Shoaei, Omid Tang, Kea-Tiong Moradi, Farshad Khajeh Nasir Toosi University of Technology Faculty of Electrical Engineering Tehran16317-14191 Iran Aarhus University Department of Electrical and Computer Engineering Aarhus8000 Denmark University of Kurdistan Department of Engineering Sanandaj66177-15177 Iran University of Tehran Department of Electrical and Computer Engineering Tehran*** Iran National Tsing Hua University Faculty of Electrical Engineering Hsinchu300044 Taiwan

This paper presents a chopper-stabilized three-stage operational amplifier (OpAmp) with a unity gain bandwidth of 69 MHz and an input referred noise density of 3 nV√Hz. The proposed design achieves a stable unity gain by proposing a new pole and zero scheme with very low power consumption, drawing only 3.3 mA from a 1.8 V power supply while driving a load capacitor as large as 100pF. To achieve rail-to-rail input swing, the design uses both NMOS and PMOS differential pairs at the input and biases them in the subthreshold region to provide an identical net trans-conductance over the rail-to-rail input common mode. Furthermore, an adaptive biasing is employed and the current sources are kept ON during large signal transitions at the input, thus eliminating crossover distortion and providing a high slew rate of 40 V/μs at a 100 pF load capacitor. The design employs chopping at 2.5 MHz and is enhanced with a local ripple reduction loop, making the OpAmp suitable for high gain and wide bandwidth applications with less filtering required. The design also reduces the input bias current significantly from 500 nA to 1.5 nA by buffering the input and applying it to the modified bootstrap switches. The proposed OpAmp, fabricated in a 0.18μm CMOS process, exhibits a maximum offset of 4.5μV , a flicker noise corner frequency of 246 Hz, a DC gain of 146 dB, a power supply rejection ratio of 123 dB, and a common mode rejection ratio of 116 dB. © 2004-2012 IEEE.

关键词： Operational amplifiers

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Extensive Numerical Analysis of PDF Parameters for Wind Energy in Brazil: A Study Across 27 Cities for 60 Years Wind Speed

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IEEE Access 2025年 13卷 84555-84568页

作者： Badawi, Ahmed Souza, Amaury Elzein, I.M. Ali, Hassan Zyoud, Alhareth College of Engineering Technology University of Doha for Science and Technology Qatar Federal University of Mato Grosso do Sul Brazil Birzeit University Faculty of Engineering Department of Electrical and Computer Engineering Birzeit Ramallah Palestine

This research conducts a comprehensive numerical assessment of wind energy potential across Brazil, leveraging six decades of wind speed data collected from 27 cities to analyze Probability Density Function (PDF) parameters and enhance wind resource mapping. The study employs the Weibull distribution, defined by its shape factor k and scale factor c, to represent variations in wind speed. A total of nine numerical practices and methods including the Maximum Likelihood Method (MLM), Method of Moments (MM), Empirical Method (EM), Standard Deviation Method (STDM), Modified Maximum Likelihood Method (MMLM), Second Modified Maximum Likelihood Method (SMMLM), Graphical Method (GM), Least Mean Square Method (LSM), and Energy Pattern Factor Method (EPF) were utilized to achieve optimal parameter estimation. Statistical analysis was performed using various metrics such as the Index of Agreement (IA), Root Mean Square Error (RMSE), Chi-square test (X2), Mean Absolute Percentage Error (MAPE), and Relative Root Mean Square Error (RRMSE). The findings indicated that MLM was the most precise method, followed by STDM, EM, MM, and EPF, while GM and LSM demonstrated lower effectiveness. The analysis determined a scale factor range of 2.17-2.36 m/s and a shape factor of 2.5-2.78, resulting in a bell-shaped Gaussian PDF. The Mean Wind Speed (MWS) was recorded at 2.06 m/s, which, despite being categorized as low, indicates the potential for effective deployment of small-scale wind turbines for energy production. This study offers significant insights for wind energy development in Brazil, presenting a methodological approach for optimizing the placement of wind turbines and minimizing electricity generation costs. © 2013 IEEE.

关键词： Weibull distribution

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Multilevel chaotic encryption model with cyclic redundancy check for medical data

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Neural Computing and Applications 2025年第5期37卷 3581-3603页

作者： Sharma, Suvita Rani Singh, Birmohan Kaur, Manpreet Department of Computer Science and Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal148106 India Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal148106 India

In telemedicine applications, it is crucial to ensure the authentication, confidentiality, and privacy of medical data due to its sensitive nature and the importance of the patient information it contains. Communication through open networks is insecure and has many vulnerabilities, making it susceptible to unauthorized access and misuse. Encryption models are used to secure medical data from unauthorized access. In this work, we propose a bit-level encryption model having three phases: preprocessing, confusion, and diffusion. This model is designed for different types of medical data including patient information, clinical data, medical signals, and images of different modalities. Also, the proposed model is effectively implemented for grayscale and color images with varying aspect ratios. Preprocessing has been applied based on the type of medical data. A random permutation has been used to scramble the data values to remove the correlation, and multilevel chaotic maps are fused with the cyclic redundancy check method. A circular shift is used in the diffusion phase to increase randomness and security, providing protection against potential attacks. The CRC method is further used at the receiver side for error detection. The performance efficiency of the proposed encryption model is proved in terms of histogram analysis, information entropy, correlation analysis, signal-to-noise ratio, peak signal-to-noise ratio, number of pixels changing rate, and unified average changing intensity. The proposed bit-level encryption model therefore achieves information entropy values ranging from 7.9669 to 8.000, which is close to the desired value of 8. Correlation coefficient values of the encrypted data approach to zero or are negative, indicating minimal correlation in encrypted data. Resistance against differential attacks is demonstrated by NPCR and UACI values exceeding 0.9960 and 0.3340, respectively. The key space of the proposed model is 1096, which is substantially mor

关键词： Telemedicine

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