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16th IEEE International Conference on Intelligent systems and Knowledge engineering, ISKE 2021

作者： Tang, Weijian Wang, Keming Southwest Jiaotong University School of Information Science and Technology Chengdu610031 China School of Computing and Artificial Intelligence Southwest Jiaotong University Chengdu610031 China National-Local Joint Engineering Laboratory of System Credibility Automatic Verification Chengdu610031 China

ISBN: (纸本)9781665405539

The reliability of a train control system depends on the consistency between the system under the test cases and the design specification. It is vital to ensure consistency by verifying that the functions of the train control system meet the design specifications. This paper introduces a novel and formal approach of test cases generation that guarantees the reliability of a train control system. The proposed methodology is effectively applied to a reactive, concurrent and complex case study of the train control system, namely the level transition, and uses multi-agent systems to describe each system component as an intelligent agent. We use the model check tool, NuSMV, that supports formal specifications, modelling the communication among agents. Furthermore, this paper combines computation tree logic with modified condition/decision coverage to design the trap properties. Based on the model checking technology, the test sequence is automatically generated by verifying the trap properties. Lastly, a set of functional test cases that satisfy the transition coverage are obtained by revising the test sequence. The research results show that the method in this paper can be used to generate test cases that are executed to verify the consistency between the system under testing and the design specification. © 2021 IEEE.

关键词： Multi agent systems

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Vision-Guided Attention-Enhanced Network for Predicting Microvascular Invasion in Hepatocellular Carcinoma

Vision-Guided Attention-Enhanced Network for Predicting Micr...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jing Liu Jing Ma Yang Ai Jiayue Zhao Fang Wang Lanfen Lin Ruofeng Tong Yen-Wei Chen Jingsong Li Zhejiang Lab Research Center for Healthcare Data Science Hangzhou China College of Information Science and Engineering Ritsumeikan University Shiga Japan Department of Radiology Sir Run Run Shaw Hospital Zhejiang University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China

As the most common malignant tumor worldwide, hepatocellular carcinoma (HCC) has a high rate of death and recurrence, and microvascular invasion (MVI) is considered to be an independent risk factor affecting its early recurrence and poor survival rate. Accurate preoperative prediction of MVI is of great significance for the formulation of individualized treatment plans and long-term prognosis assessment for HCC patients. However, as the mechanism of MVI is still unclear, existing studies use deep learning methods to directly train CT or MR images, with limited predictive performance and lack of explanation. We map the pathological "7-point" baseline sampling method used to confirm the diagnosis of MVI onto MR images, propose a vision-guided attention-enhanced network to improve the prediction performance of MVI, and validate the prediction on the corresponding pathological images reliability of the results. Specifically, we design a learnable online class activation map (CAM) to guide the network to focus on high-incidence regions of MVI guided by an extended tumor mask. Further, an attention-enhanced module is proposed to force the network to learn image regions that can explain the MVI results. The generated attention maps capture long-distance dependencies and can be used as spatial priors for MVI to promote the learning of vision-guided module. The experimental results on the constructed multi-center dataset show that the proposed algorithm achieves the state-of-the-art compared to other models.

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Expectation-Maximization clustering of states based on crime cases against children

Expectation-Maximization clustering of states based on crime...

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International Conference on Computing and Networking technology (ICCNT)

作者： Lalitha Saroja Thota Isharath Sultana Yerraginnela Shravani Suresh Babu Changalasetty Syed Asif Basha Sreelasya Changalasetty Pulime Satyanarayana Firdouse Banu Department of CSE Shadan Womens College of Engineering and Technology Hyderabad India Department of CSE Sri Indu College of Engineering Hyderabad India College of Computer Science King Khalid University Abha Saudi Arabia Department of CSE Vellore Institute of Technology Vellore India Department of CSE Samskruthi College of Engineering and Technology Hyderabad India Dept of Applied Information System Applied College Khamis Mushaiyt King Khalid University Saudi Arabia

A child is the utmost innocent and vulnerable human being. Yet, children fall easy target to many types of violence, all over the place and each single day. Globally, one billion children face certain form of emotional, physical or sexual crimes each single year. To prevent and address crimes against children, a multifaceted approach combining law enforcement, healthcare workers, educators, researchers and social service providers is necessary. Modern technology and advanced tools are widely in use for criminal investigations from crime data. Although crime data set solely comprises the number of crimes reported in each state for various years, clustering can still be used to group states in India according to the crime cases against children. In this paper, we apply Expectation-Maximization (EM) cluster methodology in WEKA platform to find patterns and trends in child crime rate data and cluster states in India based on crime cases against children which may help to create efficient interventions to stop and deal with crimes against children.

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Nonlinear Control Technique for Proton Exchange Membrane Fuel Cells: An In-Depth Assessment under Diverse Operational Conditions

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IFAC-PapersOnLine 2024年第13期58卷 769-773页

作者： A.O. Elgharib M. Benzaouia S. Benzaouia A. Rabhi M.F. Moussa Basic and Applied Science Department Arab Academy for Science Technology and Maritime Transport (AASTMT) Giza Egypt National School of Applied Sciences Mohamed First University Renewable Energy Embedded System and Data Processing Laboratory Morocco Oujda Capgemini Engineering Direction Research & Innovation F -31700 Blagnac France University of Picardie Jules Verne 3 rue Saint Leu Laboratory of Modelization Information and Systems 80039 Amiens Cedex 1 France

In the pursuit of enhancing and optimizing the efficiency of Proton Exchange Membrane Fuel Cell (PEMFC) systems, the utilization of linear controllers for DC/DC converters is a prevalent practice. However, the use of these classical controllers introduces the issue of slow response time, under/overshooting, and highly oscillatory dynamics during system responses. In light of these drawbacks, this paper presents the design and assessment of a non-linear approach based on a Sliding Mode Control with Exponential Reaching Law (SMC-ERL) as a viable solution. The stability of the closed-loop control is ensured through the Lyapunov approach. The efficacy of the proposed control methodology has been assessed via comparative analysis within the Matlab/Simulink environment, encompassing two distinct scenarios, response to dynamic variations in current references and load fluctuations. The obtained results prove that the designed SMC-ERL achieves the fastest convergence with a reduction of steady-state error compared to the PI controller allowing for robust and precise control.

关键词： Proton Exchange Membrane Fuel Cell (PEMFC) DC/DC converter Control PID SMC Lyapunov analysis

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Design of an Integrated A/D Converter for Dissolved Oxygen Sensor Interface in Aquaculture

Design of an Integrated A/D Converter for Dissolved Oxygen S...

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2022 International Conference on Mechanisms and Robotics, ICMAR 2022

作者： Zuo, Qu Tian, YunChen Ma, GuoQiang Li, ZhenZhong Sun, ZhenLong School of Computer and Information Engineering Tianjin Agricultural University Tianjin300384 China Tianjin Key Lab of Aqua-ecology and aquaculture Tianjin300384 China Shandong Dongrun Instrument Science and Technology Co. Ltd Shandong264003 China Nantong Longyang Aquaculture Co. Ltd Jiangsu226600 China

ISBN: (纸本)9781510657328

China is a big country in aquaculture, but not a strong country, and the need for transformation and upgrading is urgent. The rapid development of intensive and large-scale aquaculture has put forward new requirements for online monitoring of water quality and automatic control of equipment. The current water quality monitoring IoT system has multiple brands of dissolved oxygen sensor equipment is not compatible, the application cost of replacing the dissolved oxygen sensor is high. In this research, an integrated A/D converter device for dissolved oxygen sensor interface is designed, without changing the premise of water quality monitoring IOT system architecture, to achieve different brands of dissolved oxygen sensor "plug and play". This research analyzes the mainstream brand dissolved oxygen sensors and designs the system architecture of the integrated A/D converter device. The integrated A/D converter device takes STM32F103C8T6 as the control core, is composed of power module, processing chip module, data storage module, signal acquisition module and data transmission module, and introduces the function and structure of each module in detail. Then a prototype was built, and the testing of the prototype was completed by building a test platform. The test result shows that the prototype can operate normally. Finally, areas for improvement and next works for the article are given. © 2022 SPIE.

关键词： Data acquisition

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Generalization of CNNs on Relational Reasoning with Bar Charts

arXiv

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arXiv 2025年

作者： Cui, Zhenxing Chen, Lu Wang, Yunhai Haehn, Daniel Wang, Yong Pfister, Hanspeter School of Computer Science and Technology Shandong University China State Key Lab of CAD&CG Zhejiang University China School of Information Renmin University of China China College of Science and Mathematics University of Massachusetts Boston United States College of Computing and Data Science Nanyang Technological University Singapore School of Engineering and Applied Sciences Harvard University United States

This paper presents a systematic study of the generalization of convolutional neural networks (CNNs) and humans on relational reasoning tasks with bar charts. We first revisit previous experiments on graphical perception and update the benchmark performance of CNNs. We then test the generalization performance of CNNs on a classic relational reasoning task: estimating bar length ratios in a bar chart, by progressively perturbing the standard visualizations. We further conduct a user study to compare the performance of CNNs and humans. Our results show that CNNs outperform humans only when the training and test data have the same visual encodings. Otherwise, they may perform worse. We also find that CNNs are sensitive to perturbations in various visual encodings, regardless of their relevance to the target bars. Yet, humans are mainly influenced by bar lengths. Our study suggests that robust relational reasoning with visualizations is challenging for CNNs. Improving CNNs’ generalization performance may require training them to better recognize task-related visual properties. Copyright © 2025, The Authors. All rights reserved.

关键词： Convolutional neural networks

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人类泛基因组参考图谱发布开启基因组学领域的新篇章

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science Bulletin 2023年第14期68卷 1484-1487页

作者：王博党宁馨杨晓飞徐书华叶凯 School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China MOE Key Lab for Intelligent Networks&Networks Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Genetic Engineering Human Phenome InstituteZhangjiang Fudan International Innovation CenterCenter for Evolutionary BiologySchool of Life SciencesFudan UniversityShanghai 200032China Ministry of Education Key Laboratory of Contemporary Anthropology Collaborative Innovation Center for Genetics and DevelopmentFudan UniversityShanghai 200032China Department of Liver Surgery and Transplantation Liver Cancer InstituteZhongshan HospitalFudan UniversityShanghai 200032China School of Life Science and Technology Shanghai Tech UniversityShanghai 201210China

The significance of DNA sequencing in advancing medicalresearch,improving healthcare practices,and enhancing ourunderstanding of human evolution cannot be *** yearmarks the 20th anniversary of the completion of the Human Genome Project(HGP)in 2003,with the draft human genome reference published in 2001[1,2].However,even with the latesthuman reference genome,GRCh38,there remain gaps totalingapprox.150 Mb,involving complex sequence in the pericentromeric and subtelomeric regions,as well as recent segmentalduplications and both ampliconic gene and ribosomal DNA(rDNA)arrays[3].A groundbreaking achievement was recently accomplished by the Telomere-to-Telomere(T2T)consortium whosuccessfully closed the remaining gaps and completed the firstend-to-end assembly of a human haploid genome,known as T2TCHM13[3].

关键词：基因组学 breaking accomplished

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Hexagonally ordered microbowl arrays decorated with ultrathin CuInS_(2) nanosheets for enhanced photoelectrochemical performance

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Journal of Energy Chemistry 2020年第12期29卷 134-142页

作者： Ming Li Le Chen Yanjie Su Huan Yin Kexiang Hu State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyKey Laboratory of Optoelectronic Information Processing of Guangxi Colleges and Uniy/ersitiesGuilin 541004GuangxiChina Key Laboratory for Thin Film and Microfabrication of the Ministry of Education Department of Micro/Nano ElectronicsSchool of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China National and Local Joint Engineering Laboratory of Internet Technology on Mine School of Information and Control EngineeringChina University of Mining and TechnologyXuzhou 221008JiangsuChina School of Physics and Telecommunication Engineering Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulin 537400GuangxiChina

This paper demonstrates the design and fabrication of three-dimensional(3 D) hexagonally ordered microbowl arrays(MBAs) decorated with Cu In S2 nanosheets for enhanced photoelectrochemical(PEC) performance. The 3 D MBAs are fabricated by a micro-fabrication technique. The ultrathin CuInS2 nanosheets are grown on the 3 D electrodes by solvothermal transformation of Cu film. The photocurrent density of 3 D photocathode(CuInS2@MBAs) is about two times higher than that of the planar counterpart(CuInS2@Planar). The improved PEC performance can be ascribed to the elevated light trapping ability and the increased surface area for loading photocatalysts. In addition, CdS quantum dots as cocatalysts are modified onto the Cu In S2 nanosheets to further enhance the PEC activity because the formed p-n heterojunction can accelerate the separation of photogenerated carriers. As a result, the 3 D photocathode of CuInS2/CdS@MBAs shows an optimal incident photon to current efficiency of 10% at the wavelength of400 nm. It is believed that this work can be generalized to design other hierarchical 3 D photoelectrodes for improved solar water splitting.

关键词： Microbowl array CuInS_(2) Nanosheet Photocathode Photoelectrochemical performance

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On Secure mmWave RSMA systems

arXiv

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arXiv 2024年

作者： Lei, Hongjiang Zhou, Sha Chen, Xinhu Ansari, Imran Shafique Li, Yun Pan, Gaofeng Alouini, Mohamed-Slim The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing Key Lab of Mobile Communications Technology Chongqing400065 China James Watt School of Engineering University of Glasgow GlasgowG12 8QQ United Kingdom The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China Thuwal23955-6900 Saudi Arabia

Millimeter-wave (mmWave) communication is one of the effective technologies for the next generation of wireless communications due to the enormous amount of available spectrum resources. Rate splitting multiple access (RSMA) is a powerful multiple access, interference management, and multi-user strategy for designing future wireless networks. In this work, a multiple-input-single-output mmWave RSMA system is considered wherein a base station serves two users in the presence of a passive eavesdropper. Different eavesdropping scenarios are considered corresponding to the overlapped resolvable paths between the main and the wiretap channels under the considered transmission schemes. The analytical expressions for the secrecy outage probability (SOP) are derived respectively through the Gaussian-Chebyshev quadrature method. Monte Carlo simulation results are presented to validate the correctness of the derived analytical expressions and demonstrate the effects of system parameters on the SOP of the considered mmWave RSMA systems. © 2024, CC BY.

关键词： Millimeter waves

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From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation systems: Survey, Taxonomy and Performance Evaluation

arXiv

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arXiv 2024年

作者： Shahin, Nada Ismail, Leila Intelligent Distributed Computing and Systems Lab Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates Emirates Center for Mobility Research United Arab Emirates University Abu Dhabi United Arab Emirates

With the growing Deaf and Hard of Hearing population worldwide and the persistent shortage of certified sign language interpreters, there is a pressing need for an efficient, signs-driven, integrated end-to-end translation system, from sign to gloss to text and vice-versa. There has been a wealth of research on machine translations and related reviews. However, there are few works on sign language machine translation considering the particularity of the language being continuous and dynamic. This paper aims to address this void, providing a retrospective analysis of the temporal evolution of sign language machine translation algorithms and a taxonomy of the Transformers architectures, the most used approach in language translation. We also present the requirements of a real-time Quality-of-Service sign language machine translation system underpinned by accurate deep learning algorithms. We propose future research directions for sign language translation *** Codes I.2, I.2.7, I.4, I.4.9 © 2024, CC BY.

关键词： Neural machine translation

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