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Highly-Accurate Robot Calibration Based on Plane Constraint via Integrating Square-Root Cubature Kalman filter and Levenberg-Marquardt Algorithm 19

Highly-Accurate Robot Calibration Based on Plane Constraint ...

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19th IEEE International Conference on Networking, Sensing and Control, ICNSC 2022

作者： Chen, Tinghui Li, Shuai Wu, Hao Chongqing University of Posts and Telecommunications Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing School University of Chinese Academy of Sciences School of Computer Science and Technology Chongqing China Swansea University Faculty of Science and Engineering Swansea United Kingdom Zienkiewicz Centre for Computational Engineering Swansea United Kingdom College of Computer and Information Science Southwest University Chongqing China

ISBN: (纸本)9781665472432

In the field of modern industrial manufacturing, industrial robots are indispensable intelligent automatic mechanical equipment for advanced industrial production. However, due to long-term mechanical wear and structural deformation, the absolute positioning accuracy is low, which greatly hinders the development of the manufacturing industry. Calibrating the kinematic parameters of the robot is an effective way to address it. However, the main measuring equipment such as laser trackers and coordinate measuring machines are expensive and need special personnel to operate. Additionally, in the measurement process, due to the influence of extensive environmental factors, measurement noises are generated affecting the calibration accuracy of the robot. Based on these, we have done the following work: a) developing a robot calibration method based on plane constraint to simplify measurement steps;b) employing square-root culture Kalman filter (SCKF) algorithm for reducing the influence of measurement noises;c) proposing a novel algorithm for identifying kinematic parameters based on SCKF algorithm and Levenberg-Marquardt (LM) algorithm to achieve the high calibration accuracy;d) adopting the dial indicator as the measuring equipment for slashing costs. Enough experiments verify the effectiveness of the proposed calibration algorithm and experimental platform. © 2022 IEEE.

关键词： Industrial robots

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Automation 5.0: The Key to Systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Colour Characterization and Detection of Dry Chinese Sausage Casing Twist using Colour Image Analysis 5

Colour Characterization and Detection of Dry Chinese Sausage...

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5th International Conference on Electronic Design, ICED 2020

作者： Lam, CheeYuen Ehkan, Phaklen Jungjit, Suwimol Research Cluster School of Computer and Communication Engineering Universiti Malaysia Perlis Perlis Arau Malaysia Department of Computer and Information Technology Faculty of Science Thaksin University Phatthalung Thailand

Chinese sausage is traditional air-dry sausage that loved by the Chinese community around the globe. This sausage can be served alone after steam cook or cook with other ingredients to create other tasty Chinese delicacies. However, a manual hand cutting process is required to cut out the sausage linking twist during the sausage's packaging phase. This hand cutting process is tedious, time consuming and danger to workers. This study has proposed two types of sausage casing twist detector using image processing technique based on HSL and RGB colour characteristic and a set of blob detection technique to detect sausage casing twist blob on the output image. Hue, green-blue and red-blue colour characteristics are found being significant to represent the sausage casing twist in the sample images and used in the proposed algorithms. The RGB based algorithm is capable to produce a low noise image with SNR of 3.73dB as compared to Hue-based detector at-8.89dB which unsuccessful to remove shadow and object outlining of the output image. The proposed blob detection algorithm is able to detect 73.02% of the blob in hue-based image while 94.18% in RGB based image. The false detection rate in hue-based image has reached 333.33% compared to 12.17 % in RGB based image. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Color

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Investigations on Cyber Security Vulnerability using Distribution Analysis

Investigations on Cyber Security Vulnerability using Distrib...

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IEEE Students' Conference on Electrical, Electronics and computer Science (SCEECS)

作者： Leo John Baptist Andrews Annamalai Alagappan D Sarathkumar M. Fathima Sampath Kumar Venkatachary R Rajeshkanna Raymon Antony Raj Department of Information Technology Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Network and Infrastructure Management Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Electrical and Electronics Engineering Kongu Engineering College Erode District Tamilnadu India Department of Computer Science and Business Systems Sri Krishna College of Engineering and Technology Coimbatore Tamilnadu India Grant Thornton Gaborone Botswana Department of EEE Thamirabarani Engineering College Tirunelveli Tamil Nadu India

Internet communication is used as a mode of engagement by businesses, organizations, and even nations in a variety of contexts. As a result, both the quantity of data produced and the importance of the information that can be derived from it are growing. Multiple safeguards are required in order to ensure that the accessibility, integrity, and confidentiality of company information and assets are maintained. When it comes to protecting the privacy of a company and its reputation, adopting countermeasures and minimizing the damage caused by irreversible cyberattacks are both very crucial. It is possible to utilize both active and passive attack tactics, as well as social engineering tests, to evaluate the weaknesses of a corporation’s cyber security. The identification and ranking of vulnerabilities both play an active part in the process of raising the level of corporate awareness, as well as closing shortfalls and enhancing measures. In this investigation, ethics committee reports and confidentiality agreements were followed in order to do a cyber security vulnerability assessment on seven separate organizations. These organizations represented the governmental sector, the corporate sector, and the civil society. In order to evaluate the effectiveness of the firms' cyber security infrastructures, security scans such as port, web, application-based system and network penetration tests, distributed denial of service attacks, and social engineering were carried out. The Common Vulnerability Scoring System (CVSS) was used in order to change the base score of each institution and to identify the vulnerabilities that were present. Enterprise Networks, Cyber Security Analysis, Cyber Attacks, Penetration, and Vulnerability are some of the Keywords that can be found in this article.

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Bidirectional Gate Recurrent Unit Neural Network for Recognizing Face Touching Activities using Smartwatch Sensors 25

Bidirectional Gate Recurrent Unit Neural Network for Recogni...

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25th International computer Science and engineering Conference, ICSEC 2021

作者： Mekruksavanich, Sakorn Jantawong, Ponnipa Hnoohom, Narit Jitpattanakul, Anuchit School of Information and Communication Technology University of Phayao Department of Computer Engineering Phayao Thailand Mahidol University Faculty of Engineering Image Information and Intelligence Laboratory Department of Computer Engineering Nakorn Pathom Thailand King Mongkut's University of Technology North Bangkok Intelligent and Nonlinear Dynamic Innovations Research Center Faculty of Applied Science Department of Mathematics Bangkok Thailand

ISBN: (纸本)9781665411974

Globally, the COVID-19 pandemic has caused dev-Astation and continues to do so even a year after its first outbreak. Behavioral modifications could help to mitigate a mechanism for acquiring and spreading illnesses. Using wearable devices such as smartwatches to recognize face contact has the opportunity to decrease face touching and, therefore, the spread of respiratory disease through fomite transmission. The purpose of this paper is to demonstrate how we can utilize accelerometer data from wristwatch sensors to identify face touching actions using deep learning techniques. We proposed the BiGRU deep learning model for the high-performance recognition of hand-To-face actions. The Face Touching dataset is used as a benchmark for evaluating the recognition accuracy of deep learning networks, including our network model. The experimental findings indicate that the BiGRU surpasses other baseline deep learning models regarding accuracy (98.56%) and F1-score (98.56%). © 2021 IEEE.

关键词： Accelerometers

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Statistical Investigation of Scientific Journals Impact Factors in Relation to Benford's Law

Statistical Investigation of Scientific Journals Impact Fact...

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Novel Intelligent and Leading Emerging Sciences Conference (NILES)

作者： Marwa A. Sorour Yassmine A. Marey Islam Tharwat Abdel Halim Mohamed Mahran Kasem School of Information Technology and Computer Science Nile University Giza Egypt Research office Nile University Giza Egypt Faculty of Engineering Alexandria University Egypt School of Engineering and Applied Science Nile University Giza Egypt

ISBN: (数字)9798350378511

ISBN: (纸本)9798350378528

Benford's law (BL) has been used as a tool for the detection of possible data manipulation in datasets. The statistics of the first digit(s) of the observed values are compared to a set of expected values given by BL, and violations signal possible data anomalies. Though this method is first used for economical purposes, it has been recently used in bibliometric statistical analyses. The method provides alert that records may have certain unusual trends. In the present work, we investigate the impact factor statistics for 24 years starting from 1997 up to 2021, for open access and subscribed journals. We study conformity to BL using the basic first digit(s) violation test and the mantissa arc test, besides using the relative size factor test. Results show that open access journals adhere to Benford's Law more closely than subscribed journals.

关键词： Open Access Statistical analysis Bibliometrics Coherence Market research Fraud

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Systematic Literature Review Langchain Proposed

Systematic Literature Review Langchain Proposed

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International Electronics Symposium (IES)

作者： Rakha Asyrofi Mutia Rahmi Dewi Muhammad Irfan Lutfhi Prasetyo Wibowo Faculty of Marine Science and Engineering Universitas Hangtuah Surabaya Indonesia Department of Computer Science and Information Engineering National Central University Taiwan Faculty of Engineering Universitas Negeri Yogyakarta Yogyakarta Indonesia Graduate Institute of Network Learning Technology National Central University Taiwan Department of Information Technology Politeknik Negeri Padang Padang Indonesia Department of Informatics and Computer Engineering Politeknik Elektronika Negeri Surabaya Surabaya Indonesia

While systematic literature reviews are frequently carried out within software engineering research, performing them in a rigorous and reproducible manner can be difficult. This paper proposes some new methods for evaluating and validating systematic literature reviews. Our approach consists of several steps, such as: Selecting a set of relevant scientific papers to analyze, Developing a list of questions and criteria to evaluate each literature review, and Determining what types of functionality and performance should be evaluated. We tested our method by having multiple experts evaluate the literature reviews based on our questions and criteria. We measured the similarity in scores between each expert to determine the reliability of the evaluations. The average similarity index between experts was 0.58 to 0.83, indicating a reasonable level of agreement in their assessments. This shows our evaluation method can produce fairly consistent results, even when different experts are involved. The relatively high level of agreement is notable considering each expert brings their perspectives and opinions in analyzing literature reviews. By providing concrete questions, criteria, and evaluation methods, we aimed to guide the experts toward more uniform evaluations. In summary, we developed and tested a new approach for evaluating and validating systematic literature reviews in software engineering. By assessing reliability via interrater agreement, we showed that consistent and reproducible results are possible using our evaluation framework and methodology. Our methods could help researchers gain more insight into what makes for an effective and high-quality literature review.

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Improved mayfly optimization algorithm by adaptive random opposition-based learning 6

Improved mayfly optimization algorithm by adaptive random op...

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6th International Conference on Mechatronics and Intelligent Robotics, ICMIR 2022

作者： Zhang, Hengqi Lin, Yong Qian, Qian Pan, Jiawen Feng, Yong Fu, Yunfa Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming Yunnan650500 China Yunnan Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Kunming Yunnan650500 China Library and Archives Yunnan Communications Vocational and Technical College Kunming Yunnan650500 China

ISBN: (纸本)9781510656635

An adaptive random reverse learning mayfly algorithm is proposed to overcome the shortcomings of mayfly optimization. Specifically, hyperbolic tangent function is used as adaptive curve to flexibly optimize the personal experience and social experience coefficients of the algorithm, so that the algorithm can better balance the global and local search capabilities through the evolutionary iterations. In addition, on the basis of elite mayfly in each generation, random reverse learning mechanism is used to expand population diversity and speed up algorithm convergency. The calculation results of several test functions show that the algorithm presented has good convergence accuracy and improved algorithm performance. © 2022 SPIE.

关键词： Hyperbolic functions

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Smart Crop Protection Against Animal Encroachment using Deep Learning

Smart Crop Protection Against Animal Encroachment using Deep...

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Intelligent engineering and Management (ICIEM), International Conference on

作者： Rishi Sanjaykumar Patel Dhrumi Devendra Amin Sachin Patel Mrugendrasinh Rahevar Chirag Patel Amit Nayak Department of Information Technology Faculty of Technology and Engineering (FTE) Devang Patel Institute of Advance Technology and Research (DEPSTAR) Charotar University of Science and Technology U & PU Patel Department of Computer Engineering Faculty of Technology and Engineering (FTE) Chandubhai S. Patel Institute of Advance Technology and Research (CSPIT) Charotar University of Science and Technology Faculty of Technology and Engineering (FTE) Devang Patel Institute of Advance Technology and Research (DEPSTAR) Charotar University of Science and Technology

In today's world, agriculture faces numerous challenges, one of which is animal intrusion that poses a threat to crop yields and food security. However, with the help of IoT and DL techniques, farmers can now tackle this challenge effectively. By using devices such as LED, Buzzer, Pi Camera, and ESP8266 Wireless Fidelity module, farmers can execute a machine algorithm that is capable of identifying animals and alerting them when they are approaching their fields. The success of this technique lies in the use of Convolutional neural networks that are based on a region and one-shot detection algorithms, both of which use machine learning methods to categorize animals and identify objects in photos. While both techniques are critical, the location-based convolutional neural network is outperformed by the Single Shot Detection approach. This is because it is faster and more accurate. To ensure that farmers receive timely information, the Twilio API-interfaced program provides them with the relevant information they need to take action in their fields. With this system in place, farmers can now safeguard their crops and improve their profits, ultimately contributing to food security.

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VMD-Inspired Bidirectional LSTM for Anomaly Detection of Hyperspectral Images 3

VMD-Inspired Bidirectional LSTM for Anomaly Detection of Hyp...

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3rd International Conference on Geology, Mapping and Remote Sensing, ICGMRS 2022

作者： He, Zhi Xiao, Man He, Dan Lou, Anjun Li, Xinyuan School of Geography and Planning Guangzhou510275 China National Key Laboratory of Science and Technology on Automatic Target Recognition China Sun Yat-sen University School of Geography and Planning Guangzhou510275 China School of Computer and Information Dongguan City College Dongguan511700 China Macau University of Science and Technology School of Computer Science and Engineering Faculty of Innovation Engineering China

ISBN: (数字)9781665485951

ISBN: (纸本)9781665485951

Anomaly detection plays an essential role in hyperspectral remote sensing. Various widespread detectors, such as ReedXiaoli (RX), sparse representation, or deep learning-based methods, have been developed by using the original spectral or spatial-spectral features. However, most of the existing methods cannot adaptively extract spatial-spectral information by integrating traditional and deep learning methods. In this paper, we propose a variational mode decomposition (VMD)-inspired bidirectional long short-term memory (termed as VbiLSTM) for anomaly detection of hyperspectral images (HSI). The VbiLSTM consists of three main modules, i.e., noise reduction module, intrinsic feature extraction module, and anomaly detection module. First, wavelet transform is performed on the original HSI datasets to reduce the noise. Second, VMD-guided biLSTM is proposed for intrinsic feature extraction of the denoised image. Finally, a one-class support vector machine (OCSVM) is adopted for anomaly detection by feeding the extracted features and the final detection results are an ensemble of detection results over all the features. Experiments performed on two HSI datasets demonstrate that the VbiLSTM achieves superior detection results compared with current state-of-the-art methods. © 2022 IEEE.

关键词： Variational mode decomposition

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