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International Conference on Control and Automation (ICCA)

作者： Zhaorong Zhang Juanjuan Xu Minyue Fu Xun Li School of Computer Science and Technology Shandong University Qingdao China School of Control Science and Engineering Shandong University Jinan China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Department of Applied Mathematics the Hong Kong Polytechnic University Hong Kong SAR China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Decentralized strategies have been extensively applied to LQ optimal control problems, whereas, stochastic systems with unknown random parameters have not been comprehensively studied. In this paper, we consider a class of stochastic systems with a decentralized configuration consisting of multiple controllers which have access to Gaussian noises with unknown statistical information. The stabilizing and optimal control strategies are acquired by designing a novel stochastic approximation algorithm recursively evaluating the zero points of certain matrix equations, which is confirmed to be equivalent with solving the corresponding Riccati equations. The proof of convergence and boundness of the proposed algorithm is presented.

关键词： Q-learning Automation Stochastic systems Gaussian noise Riccati equations Optimal control Approximation algorithms

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Physics-informed Neural Network for system identification of rotors ⁎

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IFAC-PapersOnLine 2024年第15期58卷 307-312页

作者： Xue Liu Wei Cheng Ji Xing Xuefeng Chen Zhibin Zhao Rongyong Zhang Qian Huang Jinqi Lu Hongpeng Zhou Wei Xing Zheng Wei Pan The National Key Laboratory of Aerospace Power System and Plasma Technology and School of Mechanical Engineering Xi’an Jiaotong University Xi’an China China Nuclear Power Engineering Co. Ltd. Beijing China Shanghai Apollo Machinery Co. Ltd. Shanghai China Department of Computer Science University of Manchester Manchester United Kingdom School of Computer Data and Mathematical Sciences Western Sydney University Sydney Australia

The condition of the rotor system remains difficult to assess due to system nonlinearity and nosiy measurements. To deal with the problem, we proposed a hierarchical physics-informed neural network (HPINN) to discover the ordinary differential equation (ODE) of a healthy/faulty rotor system from noise measurements and then assess the machine condition based on the discovered ODE. Specifically, the ODE of a healthy rotor system is first stably identified from noise measurement through HPINN guided by rotor dynamics. Based on the identified healthy ODE, the extra fault terms in the ODE of the faulty rotor system are then sparsely regressed from the predefined library embedded in HPINN. Moreover, with the mathematical terms of discovered fault, the potential fault and the health indicator (HI) are diagnosed and constructed to assess the condition of the rotor system, respectively. Finally, the effectiveness of the proposed method is verified by the data set collected on the circulating water test bench, showing the potential for practical applications.

关键词： rotor system fault diagnosis health indicator physics-informed neural network

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Comparative analysis of network forensic tools and network forensics processes 2

Comparative analysis of network forensic tools and network f...

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2nd International Conference on Smart Computing and Electronic Enterprise, ICSCEE 2021

作者： Ghabban, Fahad M Alfadli, Ibrahim M Ameerbakhsh, Omair Abuali, Amer Nizar Al-Dhaqm, Arafat Al-Khasawneh, Mahmoud Ahmad Taibah University College of Computer Science and Engineering Information System Department Madinah Saudi Arabia University Technology Malaysia Faculty of Engineering School of Computing Johor Malaysia Al-Madinah International University Faculty of Computer Information Technology Shah Alam Malaysia

ISBN: (纸本)9781665432221

Network Forensics (NFs) is a branch of digital forensics which used to detect and capture potential digital crimes over computer networked environments crime. Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs) have abilities to examine networks, collect all normal and abnormal traffic/data, help in network incident analysis, and assist in creating an appropriate incident detection and reaction and also create a forensic hypothesis that can be used in a court of law. Also, it assists in examining the internal incidents and exploitation of assets, attack goals, executes threat evaluation, also by evaluating network performance. According to existing literature, there exist quite a number of NFTs and NTPs that are used for identification, collection, reconstruction, and analysing the chain of incidents that happen on networks. However, they were vary and differ in their roles and functionalities. The main objective of this paper, therefore, is to assess and see the distinction that exist between Network Forensic Tools (NFTs) and Network Forensic Processes (NFPs). Precisely, this paper focuses on comparing among four famous NFTs: Xplico, OmniPeek, NetDetector, and NetIetercept. The outputs of this paper show that the Xplico tool has abilities to identify, collect, reconstruct, and analyse the chain of incidents that happen on networks than other NF tools. © 2021 IEEE.

关键词： computer crime

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Analysis of EMI Mitigation Techniques in High Speed Printed Circuit Board

Analysis of EMI Mitigation Techniques in High Speed Printed ...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： M. Anandan L. P. Sajitha S. Geerthik Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Department of Information Technology Agni College of technology Chennai Department of Computer Science and Business System R.M.K Engineering College Chennai

To serve the numerous services, today’s wireless communication devices require microwave network systems with multiband and multifunctional capabilities. A growing number of microwave circuits and parts that can handle several frequency bands and larger bandwidths are needed to support the unprecedented systems. The issues in EMI/EMC have grown as a result of research and advances in contemporary wireless network communication equipment. Generally speaking, there are several ways to reduce different EMI issues. Therefore, the necessary tunable and downsized components are required to make these systems smaller, lighter, and less expensive. Most studies on emission measurements have been done in the time domain recently and one of the widely used techniques is the creation of EMI band pass filters. This article presents band pass filters with HIDDS (Hybrid Inter Digital Defected Ground Structure). Additionally, a number of uses for the hybrid S-parameters are provided by fusing Agilent ADS circuit tool and full-wave EM solvers. To provide a complete EM response of the filter construction, 3D EM simulations are performed. The analysis of the simulated findings with the results of previous experiments has revealed that HIDDS (Hybrid Inter Digital Defected ground Structure) provides minimal insertion loss and a larger range of stop band frequencies. Therefore, wireless systems might benefit from the band pass filters with HIDDS that have been proposed.

关键词： Band-pass filters Magnetic separation Wireless networks Electromagnetic interference Insertion loss Microwave communication Microwave theory and techniques

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Research on high-precision silicon-based integrated optical temperature sensor

Research on high-precision silicon-based integrated optical ...

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2021 Applied Optics and Photonics China: Optoelectronics and Nanophotonics, AOPC 2021

作者： Wang, Yimeng Shu, Haowen Han, Xiuyou School of Optoelectronic Engineering and Instrumentation Science Dalian University of Technology Dalian116024 China State Key Laboratory of Advanced Optical Communications System and Networks Department of Electronics School of Electronics Engineering and Computer Science Peking University Beijing100871 China

ISBN: (纸本)9781510649996

Integrated optical temperature sensor nowadays has attracted extensive interests thanks to its merits of high accuracy, electromagnetic immunity, and compact size compared with the traditional solutions. So far, most of the state-of-art integrated optical temperature sensors work by spectrum detection of a resonant cavity, which has certain limitations in terms of response time and cost, and it is difficult to achieve high level integration of the overall system. To solve the above problems, in this paper we use silicon-based integrated micro-ring array technology for high-precision real-time temperature sensing. By constructing a monotonic relationship between the output light intensity of the micro-ring array with the variation of the temperature, rapid and high-precision temperature measurement could be realized. Depending on different practical scenarios, the system can be customized to adapt specific temperature measurement range and resolution. Through the optimized design, the system accuracy could be better than 60mK covering temperature range of 297K∼415K, with response time better than 20μs. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Temperature measurement

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An IoT Based Healthcare using ECG 21

An IoT Based Healthcare using ECG

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21st International Arab Conference on Information Technology, ACIT 2020

作者： Hodrob, Rami Obaid, Mahmoud Abdulsalam Mansour, Abdulsalam Mansour Sawahreh, Ali Naghnagheah, Mokhles Abushanab, Shatha Sail Arab American University Department of Computer Science Jenin Palestine Arab American University Department of Computer System Engineering Jenin Palestine Department of Computer Engineering Palestine

ISBN: (纸本)9781728188553

the reliance of an electrocardiogram system in heart patients is paramount. It is essential to note that electrocardiography is a medical tactic used by doctors to assess the blood circulatory systems of their patients. In this paper we proposed a novel health care based Internet of Things (IoT) system that measures the ECG signal using Healthy-pi HAT, the system measures vital signs and ECG using Raspberry-pi, after that, the data will be sent to a cloud system to analyze it and the data will be saved in the database system. The proposed system has an android app used by the customer, and a web application used by the doctor. Likewise, the framework will advise the nearest clinical center if there should be an occurrence of the patient's unexpected wellbeing disintegration, an SMS for the patient location using GPS will be sent. The way toward investigating the ECG signal depends on extricating its highlights, this will be performed by perusing the P-wave, QRS-complex, and T-wave, these are the three principle waves that ECGs comprise, and a large number of arrhythmia diagnosing depends on these qualities. © 2020 IEEE.

关键词： Electrocardiograms

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A Smart and Privacy-Preserving Logistics system Based on IoT and Blockchain Technologies

A Smart and Privacy-Preserving Logistics System Based on IoT...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Mohammed Balfaqih Zain Balfagih Akram A. Almohammedi Khaled M. Alfawaz Department of Computer and Network Engineering University of Jeddah Jeddah Saudi Arabia Computer of Science Department Effat University Jeddah Saudi Arabia Management Information System Department King Abdulaziz University Jeddah Saudi Arabia Automobile Transportation Department Sotuh Ural State University Chelyabinsk Russia Electrical & Electronics Engineering Department Karabiik University Karabiik Turkey

ISBN: (数字)9781665472753

ISBN: (纸本)9781665472760

The smart city concept serves the well-being of the urban population in order to improve quality of life in different life aspects including logistic services. However, the continuous growth of logistics volume combined with information opaqueness and process complexity led to challenging issues related to managing the services and information of logistics. Hence, efficient management of logistics activities with traceability and condition monitoring capabilities is required to ensure quality and safe delivery. It is necessary also to ensure the accuracy and dependability of distribution data. In this context, this paper proposes a smart and privacy-preserving logistics system for high-price goods distribution. An intelligent parcel (iParcel) containing piezoresistive sensors is developed to pack delivered goods during shipping process for violation detection such as severe fall or theft. Moreover, smart contracts based on blockchain is also developed for automatic approval and payment with the consideration of distributing the shipping information between legitimate logistics parties only. A zero-knowledge proof is used to conceal blockchain address and prove the authentication. iParcels are automatically tracked and traced in which upon violation occurrence, the contract is cancelled, and the payment is refunded. The transaction fee per party is reasonable for high-price products in the pay of guarantee successful shipment.

关键词： Condition monitoring Technological innovation Smart cities Sociology Authentication Blockchains Statistics

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First Demonstration of HZO/β-Ga2O3 Ferroelectric FinFET with Improved Memory Window

arXiv

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arXiv 2024年

作者： Park, Seohyeon Yoo, Jaewook Song, Hyeojun Lee, Hongseung Lim, Seongbin Kim, Soyeon Park, Minah Kim, Bongjoong Heo, Keun Ye, Peide D. Bae, Hagyoul Electronic Engineering Jeonbuk National University Jeonju54896 Korea Republic of School of Electrical and Computer Engineering Purdue University West LafayetteIN68588 United States Department of Semiconductor Science & Technology Jeonbuk National University Jeonju54896 Korea Republic of Department of Mechanical & System Design Engineering Hongik University Seoul04066 Korea Republic of

We have experimentally demonstrated the effectiveness of beta-gallium oxide (β-Ga2O3) ferroelectric fin field-effect transistors (Fe-FinFETs) for the first time. Atomic layer deposited (ALD) hafnium zirconium oxide (HZO) is used as the ferroelectric layer. The HZO/β-Ga2O3 Fe-FinFETs have wider counterclockwise hysteresis loops in the transfer characteristics than that of conventional planar FET, achieving record-high memory window (MW) of 13.9 V in a single HZO layer. When normalized to the actual channel width, FinFETs show an improved ION/IOFF ratio of 2.3×107 and a subthreshold swing value of 110 mV/dec. The enhanced characteristics are attributed to the low-interface state density (Dit), showing good interface properties between the β-Ga2O3 and HZO layer. The enhanced polarization due to larger electric fields across the entire ferroelectric layer in FinFETs is validated using Sentaurus TCAD. After 5×106 program/erase (PGM/ERS) cycles, the MW was maintained at 9.2 V, and the retention time was measured up to 3×104 s with low degradation. Therefore, the ultrawide bandgap (UWBG) Fe-FinFET was shown to be one of the promising candidates for high-density non-volatile memory devices. © 2024, CC BY.

关键词： Energy gap

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Resolving Spurious Temporal Location Dependency for Video Corpus Moment Retrieval

Resolving Spurious Temporal Location Dependency for Video Co...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yishuo Zhang Lanshan Zhang Zhizhen Zhang Ziyi Wang Xiaohui Xie Wendong Wang School of Computer Science (National Pilot Software Engineering School) Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and Telecommunications Beijing China Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Video Corpus Moment Retrieval aims to retrieve the relevant video from a large corpus and localize the corresponding moment within the target video based on a specific query. Existing methods have achieved promising accuracy and efficiency through dedicated model designs. However, we suggest these methods overly exploit dataset biases instead of semantics. This will lead to exaggerated performances on biased datasets and implicit a significant deficiency in generalizability, which is an important metric yet not considered in existing studies. In this paper, we observe the degradation caused by a spurious dependency and design a model to mitigate this harm. Specifically, we generate an Out-Of-Distributed (OOD) test set from a widely used TV Retrieval dataset, revealing the existing models' erroneous dependency on the temporal locations of target moments. Therefore, we utilize a theoretical Structural Causal Model (SCM) to dig into the roots of this dependency by constructing causal paths for the models. Furthermore, we propose a concrete Clip Location Deconfounding Model (CLDM) to disentangle the confounded video features into the content part and the location confounder part, then produce results with causal intervention. Experiments show that CLDM significantly alleviates the impact brought by dataset biases thus providing advanced generalizability among existing works.

关键词： Measurement Degradation TV Accuracy Semantics Cybernetics

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Language-Queried Target Sound Extraction Without Parallel Training Data

Language-Queried Target Sound Extraction Without Parallel Tr...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Hao Ma Zhiyuan Peng Xu Li Yukai Li Mingjie Shao Qiuqiang Kong Ju Liu School of Information Science and Engineering Shandong University Qingdao China Department of Computer Science North Carolina State University North Carolina USA ARC Lab Tencent PCG Key Laboratory of System and Control AMSS Chinese Academy of Sciences Beijing China The Chinese University of Hong Kong China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Language-queried target sound extraction (TSE) aims to extract specific sounds from mixtures based on language queries. Traditional fully-supervised training schemes require extensively annotated parallel audio-text data, which are labor-intensive. We introduce a parallel-data-free training scheme, requiring only unlabelled audio clips for TSE model training by utilizing the contrastive language-audio pre-trained model (CLAP). In a vanilla parallel-data-free training stage, target audio is encoded using the pre-trained CLAP audio encoder to form a condition embedding, while during testing, user language queries are encoded by CLAP text encoder as the condition embedding. This vanilla approach assumes perfect alignment between text and audio embeddings, which is unrealistic. Two major challenges arise from training-testing mismatch: the persistent modality gap between text and audio and the risk of overfitting due to the exposure of rich acoustic details in target audio embedding during training. To address this, we propose a retrieval-augmented strategy. Specifically, we create an embedding cache using audio captions generated by a large language model (LLM). During training, target audio embeddings retrieve text embeddings from this cache to use as condition embeddings, ensuring consistent modalities between training and testing and eliminating information leakage. Extensive experiment results show that our retrieval-augmented approach achieves consistent and notable performance improvements over existing state-of-the-art with better generalizability.

关键词： Training Large language models Training data Signal processing Information leakage Acoustics Data models Data mining Speech processing Overfitting

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