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Petri Net Control Method for Pipe-line systems and Its Implementation via CIF3 ⁎

IFAC-PapersOnLine 2019年第24期52卷 261-266页

作者： YuHao Fu JiLiang Luo Huifeng Wu Jianhong Ye Yi-sheng Huang College Information Science and Engineering Huaqiao University Xiamen 361021 China College Information Science and Engineering Huaqiao University Xiamen 361021 China and also with Fujian Engineering Research Center of Motor Control and System Optimal Schedule Xiamen 361021 China Institute of Intelligent and Software Technology Hangzhou Dianzi University Hangzhou 310018 China Computer Science and Technology Huaqiao University Xiamen 361021 China and also with Fujian Provincial Key Laboratory of Data Intensive Computing Quanzhou 362000 China Department of Electrical Engineering National Ilan University Taiwan

As for a pipe-line system subjected to complex operations, an approach is proposed to synthesize the controller via Petri nets (PNs) such that the plant is run as concurrently as possible and the loads of equipments are balanced. A P-timed and labeled PN is designed to model the whole process of a pipe-line system, where tasks, including transporting material from one tank to another and cleaning tank, are represented by operational places, and level sensors amounted in tanks are represented by labels assigned to transitions. Further, monitor places are designed to resolve the conflict relations among tasks due to the shared valves and pipes. An method is presented to translate an PN controller into a CIF3 (Compositional Interchange Format) model, which can be converted into a PLC program in the CIF3 tool. A beer filtration plant is taken as an example to illustrate the approach, and its simulation experiments are carried out to verify the theoretic results.

关键词： Chemical plant Valve control Petri net CIF3

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The simulation models for human pedestrian movement of a departure process in an airport

The simulation models for human pedestrian movement of a dep...

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2018 International Conference on Innovation and Intelligence for Informatics, Computing, and technologies, 3ICT 2018

作者： Bakar, Noor Akma Abu Fauzan, Anis Izzati Ab Majid, Mazlina Abdul Allegra, Mario Fakhreldin, M. Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Pahang Malaysia Italian National Research Council CNR Institute for Educational Technology ITD Palermo Italy Faculty of Computer Science and Information Technology Jazan University Saudi Arabia

ISBN: (纸本)9781538692073

The emergence of simulating human movement and behaviour rose in order to imitate and replace human interference with this complex demeanour. It is so diverse and uncontrollable to the extent it is almost impossible to undergo exhaustive experiments. Hence, simulating this model is crucial. Especially in designing a public area where human density is too much concentration and the need for properly planned traffic or human movement is very much needed. For that, simulations and modelling are always the best options for investigating human behaviour. In this research work, the aim is to investigate how effective and to what extent the Agent-Based Simulation (ABS), Discrete Event Simulation (DES) and hybrid of both give benefits to the society adequately. Its expected results will be an improved and better version of human pedestrian movement in the airport of the departure process simulation model. © 2018 IEEE.

关键词： Discrete event simulation

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MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

arXiv

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arXiv 2020年

作者： Cai, Hanshu Gao, Yiwen Sun, Shuting Li, Na Tian, Fuze Xiao, Han Li, Jianxiu Yang, Zhengwu Li, Xiaowei Zhao, Qinglin Liu, Zhenyu Yao, Zhijun Yang, Minqiang Peng, Hong Zhu, Jing Zhang, Xiaowei Gao, Guoping Zheng, Fang Li, Rui Guo, Zhihua Ma, Rong Yang, Jing Zhang, Lan Hu, Xiping Li, Yumin Hu, Bin Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University Institute of Semiconductors Chinese Academy of Sciences China Open Source Software and Real-Time System Lanzhou University Ministry of Education China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Lanzhou University Second Hospital China

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation;the 3-electrode EEG signals of 55 subjects were recorded in resting state;the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

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NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

arXiv

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arXiv 2022年

作者： Li, Yawei Zhang, Kai Timofte, Radu Van Gool, Luc Kong, Fangyuan Li, Mingxi Liu, Songwei Du, Zongcai Liu, Ding Zhou, Chenhui Chen, Jingyi Han, Qingrui Li, Zheyuan Liu, Yingqi Chen, Xiangyu Cai, Haoming Qiao, Yu Dong, Chao Sun, Long Pan, Jinshan Zhu, Yi Zong, Zhikai Liu, Xiaoxiao Hui, Zheng Yang, Tao Ren, Peiran Xie, Xuansong Hua, Xian-Sheng Wang, Yanbo Ji, Xiaozhong Lin, Chuming Luo, Donghao Tai, Ying Wang, Chengjie Zhang, Zhizhong Xie, Yuan Cheng, Shen Luo, Ziwei Yu, Lei Wen, Zhihong Wu, Qi Li, Youwei Fan, Haoqiang Sun, Jian Liu, Shuaicheng Huang, Yuanfei Jin, Meiguang Huang, Hua Liu, Jing Zhang, Xinjian Wang, Yan Long, Lingshun Li, Gen Zhang, Yuanfan Cao, Zuowei Sun, Lei Alexander, Panaetov Wang, Yucong Cai, Minjie Wang, Li Tian, Lu Wang, Zheyuan Ma, Hongbing Liu, Jie Chen, Chao Cai, Yidong Tang, Jie Wu, Gangshan Wang, Weiran Huang, Shirui Lu, Honglei Liu, Huan Wang, Keyan Chen, Jun Chen, Shi Miao, Yuchun Huang, Zimo Zhang, Lefei Ayazoglu, Mustafa Xiong, Wei Xiong, Chengyi Wang, Fei Li, Hao Wen, Ruimian Yang, Zhijing Zou, Wenbin Zheng, Weixin Ye, Tian Zhang, Yuncheng Kong, Xiangzhen Arora, Aditya Zamir, Syed Waqas Khan, Salman Hayat, Munawar Khan, Fahad Shahbaz Gao, Dandan Zhou, Dengwen Ning, Qian Tang, Jingzhu Huang, Han Wang, Yufei Peng, Zhangheng Li, Haobo Guan, Wenxue Gong, Shenghua Li, Xin Liu, Jun Wang, Wanjun Zeng, Kun Lin, Hanjiang Chen, Xinyu Fang, Jinsheng Zhang, Shuhao Zhang, Yuhao Sinha, Abhishek Kumar Moorthi, S. Manthira Dhar, Debajyoti Yang, Hao-Hsiang Huang, Zhi-Kai Chen, Wei-Ting Chang, Hua-En Kuo, Sy-Yen Tan, Wei Chen, Hao Xu, Qian Narang, Pratik Singh, Usneek Sameen, Syed Khaitan, Harsh Yinghua, Liu Tianlin, Zhang Xiaoming, Zhang Meng, Dingxuan Tian, Chunwei Morshed, Mashrur M. Ahsan, Ahmad Omar Computer Vision Lab ETH Zurich Switzerland University of Würzburg Germany ByteDance Shenzhen China State Key Laboratory for Novel Software Technology Nanjing University China ByteDance Inc China NetEase Inc. China Shenzhen Institutes of Advanced Technology CAS China University of Macau China Shanghai AI Lab Shanghai China Nanjing University of Science and Technology China Amazon Web Services United States China Alibaba DAMO Academy EFC Yuhang District Zhejiang Hangzhou China East China Normal University China Youtu Lab Tencent China Megvii Technology China University of Electronic Science and Technology of China China School of Artificial Intelligence Beijing Normal University China Alibaba Group China Bilibili AI China Nankai-Baidu Joint Lab Nankai University Tianjin China Platform Technologies Tencent Online Video China Higher School of Economics Russia Huawei Moscow Research Center Russia Hunan University China Xidian University China Xilinx Technology Beijing Limited China College of Information Science and Engineering Xinjiang University Urumqi China Department of Electronic Engineering Tsinghua University Beijing China Nanjing University China McMaster University Canada School of Telecommunication Engineering Xidian University Xi’an China School of Computer Science Wuhan University Wuhan China School of Mathematical Science University of Electronic Science and Technology of China Chengdu China School of Computer Science The University of Sydney Sydney Australia Aselsan Research Ankara Turkey School of Electronic and Information Engineering South-Central University for Nationalities Wuhan China Guangdong University of Technology China Fujian Normal University Fuzhou University Jimei University China Design Group China Abu Dhabi United Arab Emirates Monash University Melbourne Australia Mohamed bin Zayed University of AI United Arab Emirates North China Electric Power University Changping District Beijing China The School of Art

This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of ×4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution. © 2022, CC BY.

关键词： Chemical activation

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Correction to: Industrial-iot-hardware security-improvement using plan load optimization method in cloud

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International Journal of system Assurance engineering and Management 2021年第6期13卷 3108-3108页

作者： Basheer, Shakila Gopu, Magesh Mathew, Rincy Merlin Bivi, Maryam Aysha Prabu, M. Department of Information System College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia Department of Software and Systems Engineering Vellore Institute of Technology Vellore India Computer Science Department College of Science and Arts King Khalid University Khamis Mushayt Abha Saudi Arabia Department of Computer Science College of Computer Science King Khalid University Abha Saudi Arabia Department of Computer Science Christ University Bangalore India

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CRNN Based Jersey-Bib Number/Text Recognition in Sports and Marathon Images

CRNN Based Jersey-Bib Number/Text Recognition in Sports and ...

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International Conference on Document Analysis and Recognition

作者： Sauradip Nag Raghavendra Ramachandra Palaiahnakote Shivakumara Umapada Pal Tong Lu Mohan Kankanhalli Department of Computer Science & Engineering Kalyani Government Engineering College Kalyani India Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Norway Faculty of Computer System and Information Technology University of Malaya Malaysia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University China Department of computer science National University of Singapore Singapore

The primary challenge in tracing the participants in sports and marathon video or images is to detect and localize the jersey/Bib number that may present in different regions of their outfit captured in cluttered environment conditions. In this work, we proposed a new framework based on detecting the human body parts such that both Jersey Bib number and text is localized reliably. To achieve this, the proposed method first detects and localize the human in a given image using Single Shot Multibox Detector (SSD). In the next step, different human body parts namely, Torso, Left Thigh, Right Thigh, that generally contain a Bib number or text region is automatically extracted. These detected individual parts are processed individually to detect the Jersey Bib number/text using a deep CNN network based on the 2-channel architecture based on the novel adaptive weighting loss function. Finally, the detected text is cropped out and fed to a CNN-RNN based deep model abbreviated as CRNN for recognizing jersey/Bib/text. Extensive experiments are carried out on the four different datasets including both bench-marking dataset and a new dataset. The performance of the proposed method is compared with the state-of-the-art methods on all four datasets that indicates the improved performance of the proposed method on all four datasets.

关键词： Text recognition Sports Image recognition Hip Thigh Torso Biological system modeling

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On safeguarding privacy and security in the framework of federated learning

arXiv

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arXiv 2019年

作者： Ma, Chuan Li, Jun Ding, Ming Yang, Howard H. Shu, Feng Quek, Tony Q.S. Vincent, H. School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China Department of Software Engineering Institute of Cybernetics National Research Tomsk Polytechnic University Tomsk634050 Russia Data61 CSIRO Australia Information System Technology and Design Pillar Singapore University of Technology and Design Department of Electrical Engineering Princeton University PrincetonNJ08544 United States

Motivated by the advancing computational capacity of wireless end-user equipment (UE), as well as the increasing concerns about sharing private data, a new machine learning (ML) paradigm has emerged, namely federated learning (FL). Specifically, FL allows a decoupling of data provision at UEs and ML model aggregation at a central unit. By training model locally, FL is capable of avoiding data leakage from the UEs, thereby preserving privacy and security to some extend. However, even if raw data are not disclosed from UEs, individual's private information can still be extracted by some recently discovered attacks in the FL architecture. In this work, we analyze the privacy and security issues in FL, and raise several challenges on preserving privacy and security when designing FL systems. In addition, we provide extensive simulation results to illustrate the discussed issues and possible solutions. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Optimal control of free-floating autonomous underwater vehicles for manipulation tasks in shallow sea culture collection

Optimal control of free-floating autonomous underwater vehic...

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ASABE 2018 Annual International Meeting

作者： Li, Daoliang Du, Ling Bao, Jianhua Rauschenbach, Thomas Li, Pu Karimanzira, Divas College of Information and Electrical Engineering China Agricultural University Beijing100083 China AST Fraunhofer Institute of Optronics System Technologies and Image Am Vogelherd 50 Ilmenau98693 Germany Technical University of Ilmenau Postfach 100565 Ilmenau98684 Germany

There is an urgent demand for collection operations in the shallow sea cultivation. However, there have been very few investigations on underwater robots for this purpose. The overall objective of this paper is to investigate approaches for combined free-floating AUV and manipulation arm systems to autonomously collect shallow sea culture under complicated underwater conditions. For this purpose, following targets will be gained: 1）Development of new approaches for fast and precise identification and positioning of shallow sea culture (e.g. sea cucumber, dead fish) under complicated underwater conditions (e.g. convoluted terrain, weak light, fluctuating stream);2）Development of a detailed dynamic model for the combined AUV and manipulator system (UVMS) which can be applied for stable and reliable control to autonomously collect sea culture under complicated underwater conditions;3）Development of an optimal control strategy to realize operations for the combined AUV and manipulation arm to autonomously collect shallow sea culture subject to multiple operating constraints. The above objectives can be fulfilled by answering the following questions. A system design to to reliably identify the target object, which need imaging data processing, segmentation and classification, to estimate its position relative to the object, which calls for a position estimator that fuses imaging data (e.g., sonar, vision) with IMU measurements, to control its position relative to the object for station-keeping and the tool at the end of the arm system need to be set in the right position and orientation. The dynamics of both the AUV and the arm system (MS), their interactions with the environment need to be modeled, and to minimize the time, minimum energy, minimum error and smoothness to a target position. © 2018 American Society of Agricultural and Biological Engineers. All rights reserved.

关键词： Attitude control

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Device for detection of the phase current asymmetry in the three-phase lines of non-traction consumers

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IOP Conference Series: Materials Science and engineering 2020年第1期734卷

作者： A M Safarov S Kh Jumaboyev Kh A Sattarov Power supply railways Department Tashkent institute of railway engineering Tashkent Uzbekistan Adilkhodjayev Street 1 Power supply system Department Tashkent university of information technologies Tashkent Uzbekistan A. Timur Street 108

electrified railway transport receives power from the power system and operates on a single-phase current, which leads to uneven loading of networks of the traction power supply system. There is a danger of overload and additional losses of active power and electrical energy of three-phase electric motors by reverse sequence currents, therefore, any information obtained about the values (phase currents and voltages) allows carrying out corrective actions for the level of asymmetry. In this paper, discuss the design of the device for detecting the asymmetry of phase currents in three-phase lines is proposed. It is shown that the device can convert the DC current difference and measure three linear currents in a three-wire three-phase circuit.

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Characterizing Android App Signing Issues

Characterizing Android App Signing Issues

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IEEE International Conference on Automated software engineering (ASE)

作者： Haoyu Wang Hongxuan Liu Xusheng Xiao Guozhu Meng Yao Guo Beijing University of Posts and Telecommunications Beijing China Key Lab of High-Confidence Software Technologies (MOE) Peking University China Case Western Reserve University Chinese Academy of Sciences SKLOIS Institute of Information Engineering China School of Cyber Security University of Chinese Academy of Sciences China

In the app releasing process, Android requires all apps to be digitally signed with a certificate before distribution. Android uses this certificate to identify the author and ensure the integrity of an app. However, a number of signature issues have been reported recently, threatening the security and privacy of Android apps. In this paper, we present the first large-scale systematic measurement study on issues related to Android app signatures. We first create a taxonomy covering four types of app signing issues (21 anti-patterns in total), including vulnerabilities, potential attacks, release bugs and compatibility issues. Then we developed an automated tool to characterize signature-related issues in over 5 million app items (3 million distinct apks) crawled from Google Play and 24 alternative Android app markets. Our empirical findings suggest that although Google has introduced apk-level signing schemes (V2 and V3) to overcome some of the known security issues, more than 93% of the apps still use only the JAR signing scheme (V1), which poses great security threats. Besides, we also revealed that 7% to 45% of the apps in the 25 studied markets have been found containing at least one signing issue, while a large number of apps have been exposed to security vulnerabilities, attacks and compatibility issues. Among them a considerable number of apps we identified are popular apps with millions of downloads. Finally, our evolution analysis suggested that most of the issues were not mitigated after a considerable amount of time across markets. The results shed light on the emergency for detecting and repairing the app signing issues.

关键词： Security Google Taxonomy Computer bugs Malware Tools systematics

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