人工智能技术学报(英文)Pub Date : 2022-03-02DOI: 10.37965/jait.2022.0083
Zijian Jia, Wenrui Wang, Jiaming Zhang
{"title":"Contact High Temperature Strain Automatic Calibration and Precision Compensation Technology","authors":"Zijian Jia, Wenrui Wang, Jiaming Zhang","doi":"10.37965/jait.2022.0083","DOIUrl":"https://doi.org/10.37965/jait.2022.0083","url":null,"abstract":"In order to solve the problem of contact high temperature strain precision measure-ment, this paper established an automatic calibration device for high temperature strain gauges. The temperature of the high temperature furnace was automatically con-trolled by the temperature control device. The electric cylinder was driven by the servo motor to apply the load to the calibration beam. The output signal of the high temperature strain gauge, the thermocouple signal and the displacement signal of the grat-ing ruler were collected at the same time. The deformation measurement results obtained after temperature correction were used to calculate the theoretical mechanical strain, which were fed back to control the loading action to complete the automatic calibration process. Based on the above calibration device, the high temperature strain measurement accuracy correction software was developed to calibrate the high temperature strain gauge with multi-parameters, and the curves of sensitivity coefficient, thermal output, zero drift and creep characteristics with temperature were obtained, and a strain measurement accuracy compensation model was established. The high temperature strain measurement experiment was carried out to verify that the modified model can meet the requirements in each temperature range.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42969432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Problem- Based Cybersecurity Lab with Knowledge Graph as Guidance","authors":"Yuli Deng, Zhengping Zeng, Kritshekhar Jha, Dijiang Huang","doi":"10.37965/jait.2022.0066","DOIUrl":"https://doi.org/10.37965/jait.2022.0066","url":null,"abstract":"Lecture-based teaching paired with laboratory-based exercises is most commonly used in cybersecurity instruction. However, it focuses more on theories and models but fails to provide learners with practical problem-solving skills and opportunities to explore real-world cybersecurity challenges. Problem-based Learning (PBL) has been identified as an efficient pedagogy for many disciplines, especially engineering education. It provides learners with real-world complex problem scenarios, which encourages learners to collaborate with classmates, ask questions and develop a deeper understanding of the concepts while solving real-world cybersecurity problems. This paper describes the application of the PBL methodology to enhance professional training-based cybersecurity education. The authors developed an online laboratory environment to apply PBL with Knowledge-Graph (KG) based guidance for hands-on labs in cybersecurity training.Learners are provided access to a virtual lab environment with knowledge graph guidance to simulated real-life cybersecurity scenarios. Thus, they are forced to think independently and apply their knowledge to create cyber-attacks and defend approaches to solve problems provided to them in each lab. Our experimental study shows that learners tend to gain more enhanced learning outcomes by leveraging PBL with knowledge graph guidance, become more aware of cybersecurity and relevant concepts, and also express interest in keep learning of cybersecurity using our system.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41376303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2022-01-25DOI: 10.37965/jait.2022.01
Sami Mian
{"title":"Foundations of Artificial Intelligence and Applications","authors":"Sami Mian","doi":"10.37965/jait.2022.01","DOIUrl":"https://doi.org/10.37965/jait.2022.01","url":null,"abstract":"The latest generation of artificial intelligence (AI) is based on today’s cutting-edge technologies, including big data processing, cloud computing, machine learning, robotics, service-oriented computing, quantum computing, and Internet of Things (IoT). On one side, AI is supported and improved by these cutting-edge technologies. On the other side, AI is applied in many domains to augment the performance and capacities of many applications. Both the usefulness of AI in these domains and the inherent improvements that have been made in the pursuit of these large-scale technologies has caused an exponential increase in modern AI capabilities. In the following sections, we will present an overview of the papers in this issue that support the development of AI and apply AI to extend and improve performance and capacities in several application domains. These papers include both academic research papers and industrial application papers.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41797459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-12-27DOI: 10.37965/jait.2021.12005
Xuan Zhang, Guohui Wang
{"title":"Stud Pose Detection Based on Photometric Stereo and Lightweight YOLOv4","authors":"Xuan Zhang, Guohui Wang","doi":"10.37965/jait.2021.12005","DOIUrl":"https://doi.org/10.37965/jait.2021.12005","url":null,"abstract":"There are hundreds of welded studs in a car. The posture of a welded stud determines the quality of the body assembly thus affecting the safety of cars. It is crucial to detect the posture of the welded studs. Considering the lack of accurate method in detecting the position of welded studs, this paper aims to detect the weld stud’s pose based on photometric stereo and neural network. Firstly, a machine vision-based stud dataset collection system is built to achieve the stud dataset labeling automatically. Secondly, photometric stereo algorithm is applied to estimate the stud normal map which as input is fed to neural network. Finally, we improve a lightweight YOLOv4 neural network which is applied to achieve the detection of stud position thus overcoming the shortcomings of traditional testing methods. The research and experimental results show that the stud pose detection system designed achieves rapid detection and high accuracy positioning of the stud. This research provides the foundation combining the photometric stereo and deep learning for object detection in industrial production.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45633511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-12-07DOI: 10.37965/jait.2021.12003
Shuangxia Bai, Shaomei Song, Shiyang Liang, Jianmei Wang, Bo Li, E. Neretin
{"title":"UAV maneuvering decision -making algorithm based on Twin Delayed Deep Deterministic Policy Gradient Algorithm","authors":"Shuangxia Bai, Shaomei Song, Shiyang Liang, Jianmei Wang, Bo Li, E. Neretin","doi":"10.37965/jait.2021.12003","DOIUrl":"https://doi.org/10.37965/jait.2021.12003","url":null,"abstract":"Aiming at intelligent decision-making of UAV based on situation information in air combat, a novel maneuvering decision method based on deep reinforcement learning is proposed in this paper. The autonomous maneuvering model of UAV is established by Markov Decision Process. The Twin Delayed Deep Deterministic Policy Gradient(TD3) algorithm and the Deep Deterministic Policy Gradient (DDPG) algorithm in deep reinforcement learning are used to train the model, and the experimental results of the two algorithms are analyzed and compared. The simulation experiment results show that compared with the DDPG algorithm, the TD3 algorithm has stronger decision-making performance and faster convergence speed, and is more suitable forsolving combat problems. The algorithm proposed in this paper enables UAVs to autonomously make maneuvering decisions based on situation information such as position, speed, and relative azimuth, adjust their actions to approach and successfully strike the enemy, providing a new method for UAVs to make intelligent maneuvering decisions during air combat.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45794566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-12-01DOI: 10.37965/jait.2021.12002
Gennaro De Luca
{"title":"Survey of NISQ Era Hybrid Quantum-Classical Machine Learning Research","authors":"Gennaro De Luca","doi":"10.37965/jait.2021.12002","DOIUrl":"https://doi.org/10.37965/jait.2021.12002","url":null,"abstract":"Quantum computing is a rapidly growing field that has received a significant amount of support in the past decade in industry and academia. Several physical quantum computers are now freely available to use through cloud services, with some implementations supporting upwards of hundreds of qubits. These advances mark the beginning of the Noisy Intermediate-Scale Quantum (NISQ) era of quantum computing, paving the way for hybrid quantum-classical systems. This work provides an introductory overview of gate-model quantum computing through the Visual IoT/Robotics Programming Language Environment and a survey of recent applications of NISQ era quantum computers to hybrid quantum-classical machine learning.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47833081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-12-01DOI: 10.37965/jait.2021.12001
Prem Kumar Singh
{"title":"Data with Non-Euclidean Geometry and its Characterization","authors":"Prem Kumar Singh","doi":"10.37965/jait.2021.12001","DOIUrl":"https://doi.org/10.37965/jait.2021.12001","url":null,"abstract":"Recently, dealing the Non-Euclidean data and its characterization is considered as one of the major issues by researchers. The first problem arises while distinction of among Euclidean and non-Euclidean geometry. The second problem arises with dealing the Non-Euclidean geometry in true, false and uncertain regions. The third problem arises while investigating some pattern in Non-Euclidean data sets. This paper focused on tackling these issues with some real life examples.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45250898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-10-12DOI: 10.37965/jait.2021.0021
Mohammad Osman Tokhi
{"title":"Special Issue on the Emerging Mobile Robotics","authors":"Mohammad Osman Tokhi","doi":"10.37965/jait.2021.0021","DOIUrl":"https://doi.org/10.37965/jait.2021.0021","url":null,"abstract":"","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44570898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-10-01DOI: 10.37965/jait.2021.0018
Amin Rezaeipanah, Musa Mojarad
{"title":"Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach","authors":"Amin Rezaeipanah, Musa Mojarad","doi":"10.37965/jait.2021.0018","DOIUrl":"https://doi.org/10.37965/jait.2021.0018","url":null,"abstract":"This paper presents a new, bi-criteria mixed-integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system. The objective of this model is to minimize the makespan and inter-cell movements simultaneously, while considering sequence-dependent cell setup times. In the CMS design and planning, three main steps must be considered, namely cell formation (i.e., piece families and machine grouping), inter and intra-cell layouts, and scheduling issue. Due to the fact that the Cellular Manufacturing Systems (CMS) problem is NP-Hard, a Genetic Algorithm (GA) as an efficient meta-heuristic method is proposed to solve such a hard problem. Finally, a number of test problems are solved to show the efficiency of the proposed GA and the related computational results are compared with the results obtained by the use of an optimization tool.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48440309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
人工智能技术学报(英文)Pub Date : 2021-09-14DOI: 10.37965/jait.2021.0013
S. Mondal, Patricio L. C. Marquez, M. Tokhi
{"title":"Analysis of Mechanical Adhesion Climbing Robot Design for Wind Tower Inspection","authors":"S. Mondal, Patricio L. C. Marquez, M. Tokhi","doi":"10.37965/jait.2021.0013","DOIUrl":"https://doi.org/10.37965/jait.2021.0013","url":null,"abstract":"Mmaintenance of wind turbine farms is a huge task, with associated significant risks and potential hazard to the safety and wellbeing of people who are responsible for carrying the tower inspection tasks. Periodic inspections are required for wind turbine tower to ensure that the wind turbines are in full working order, with no signs of potential failure. Therefore, the development of an automated wind tower inspection system has been very crucial for the overall performance of the renewable wind power generation industry. In order to determine the life span of the tower, an investigation of robot design is discussed in this paper. It presents how a mechanical spring-loaded climbing robot can be designed and constructed to climb and rotate 360° around the tower. An adjustable circular shape robot is designed that allows the device to fit in different diameters of the wind generator tower. The rotational module is designed to allow the wheels to rotate and be able to go in a circular motion. The design further incorporates a suspension that allows the robot to go through any obstacle. This paper also presents afiniteelement spring stress analysis and Simulink control system model to find the optimal parameters that are required for the wind tower climbing robot.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49366728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}