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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Behavior Trees and State Machines in Robotics Applications

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IEEE Transactions on Software engineering 2023年第9期49卷 4243-4267页

作者： Ghzouli, Razan Berger, Thorsten Johnsen, Einar Broch Wasowski, Andrzej Dragule, Swaib Chalmers University of Technology Department of Computer Science and Engineering Gothenburg40530 Sweden Ruhr University Bochum Faculty of Computer Science Bochum44801 Germany Chalmers University of Gothenburg Department of Computer Science and Engineering Gothenburg40530 Sweden University of Oslo Department of Informatics Oslo0316 Norway IT University of Copenhagen Software Development Group Copenhagen2300 Denmark

Autonomous robots combine skills to form increasingly complex behaviors, called missions. While skills are often programmed at a relatively low abstraction level, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. State machines have been the go-to language to model behavior for decades, but recently, behavior trees have gained attention among roboticists. Originally designed to model autonomous actors in computer games, behavior trees offer an extensible tree-based representation of missions and are claimed to support modular design and code reuse. Although several implementations of behavior trees are in use, little is known about their usage and scope in the real world. How do concepts offered by behavior trees relate to traditional languages, such as state machines? How are concepts in behavior trees and state machines used in actual applications? This paper is a study of the key language concepts in behavior trees as realized in domain-specific languages (DSLs), internal and external DSLs offered as libraries, and their use in open-source robotic applications supported by the Robot Operating System (ROS). We analyze behavior-tree DSLs and compare them to the standard language for behavior models in robotics: state machines. We identify DSLs for both behavior-modeling languages, and we analyze five in-depth. We mine open-source repositories for robotic applications that use the analyzed DSLs and analyze their usage. We identify similarities between behavior trees and state machines in terms of language design and the concepts offered to accommodate the needs of the robotics domain. We observed that the usage of behavior-tree DSLs in open-source projects is increasing rapidly. We observed similar usage patterns at model structure and at code reuse in the behavior-tree and state-machine models within the mined open-source projects. We contribute all extracted models as a dataset, hoping to inspire the commu

关键词： Modeling languages

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Internal Validity Index for Fuzzy Clustering Based on Relative Uncertainty

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computers, Materials & Continua 2022年第8期72卷 2909-2926页

作者： Refik Tanju Sirmen Burak Berk Üstündag Graduate School of Science Engineering&Technology Istanbul Technical UniversityIstanbul34469Turkey Faculty of Computer&Informatics Istanbul Technical UniversityIstanbul34469Turkey

Unsupervised clustering and clustering validity are used as essential instruments of data *** clustering being realized under uncertainty,validity indices do not deliver any quantitative evaluation of the uncertainties in the suggested ***,validity measures may be biased towards the underlying clustering ***,neglecting a confidence requirement may result in *** the absence of an error estimate or a confidence parameter,probable clustering errors are forwarded to the later stages of the ***,having an uncertainty margin of the projected labeling can be very fruitful for many applications such as machine ***,the validity issue was approached through estimation of the uncertainty and a novel low complexity index proposed for fuzzy *** involves only uni-dimensional membership weights,regardless of the data dimension,stipulates no specific distribution,and is independent of the underlying similarity *** tests and comparisons returned that it can reliably estimate the optimum number of partitions under different data distributions,besides behaving more robust to over ***,in the comparative correlation analysis between true clustering error rates and some known internal validity indices,the suggested index exhibited the highest strong *** relationship has been also proven stable through additional statistical acceptance *** the provided relative uncertainty measure can be used as a probable error estimate in the clustering as ***,it is the only method known that can exclusively identify data points in dubiety and is adjustable according to the required confidence level.

关键词： Machine learning data science clustering validity fuzzy clustering uncertainty intelligent systems data analytics

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Exploring the dynamics of creative tourism:A tourist-centric perspective to achieve economic sustainable development

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Journal of Mountain Science 2025年第1期22卷 278-295页

作者： ZOU Fuxia Atefeh AHMADI DEHRASHID Mehmet AKIF CIFCI Emrah ARSLAN Nina KHALIGHI College of Tourism and Aviation Management Hunan Women's UniversityChangsha 410004China Faculty of Natural Resources Department of ClimatologyUniversity of KurdistanSanandaj ***Iran Member of Department of Zrebar Lake Economic-social Research Kurdistan Studies InstituteUniversity of KurdistanSanandaj ***Iran Department of Computer Engineering Bandirma Onyedi Eylul UniversityBalikesir 10200Türkiye Engineering and Informatics Department Klaipėdos ValstybinėKolegija/Higher Education InstitutionKlaipeda 92294Lithuania Engineering and Informatics Department KTO KaratayKonya 42020Türkiye Department of Urban Planning and Design Faculty of Art and ArchitectureUniversity of KurdistanSanandaj ***Iran

Creative tourism is a dynamic and innovative approach to tourism,which points out the importance of people's active participation and their immersion in such *** a vernacular context,it should attract people(local and tourists)attention to accomplish its main *** its rich cultural and natural assets,Kurdistan province faces several challenges that impact its tourism *** achieve that,the study uses quantitative approach to thoroughly analyze and evaluate the components of creative tourism in this *** research focuses on tourists who visited the province's ten towns during the spring and summer of *** collection utilized a Likert-scale questionnaire ranging from"very good"to"very poor".The study employed a semistructured questionnaire developed through qualitative interviews alongside a researcher-made questionnaire validated by experts from the University of *** qualitative questionnaire achieved a high-reliability score of 93%using Cronbach's alpha ***-depth interviews and literary research were conducted to identify creative tourism components and indicators,informing the development of a quantitative *** analysis was performed using SPSS 20 and AMOS software to scrutinize the survey findings,providing insights into enhancing creative tourism strategies in Kurdistan *** results reveal the varying significance of these dimensions,with the cultural dimension identified as the most crucial(factor loading:0.95),followed by the social(0.92),economic(0.88),and managerial/political dimensions(0.83).The study highlights the importance of cultural planning,community engagement,and infrastructural support in fostering creative ***,it explores the impact of creative industries,such as music and arts rooted in Kurdish culture,on tourism *** diversification and spatialphysical considerations are critical factors in enhancing Kurdistan's appeal as a creative

关键词： Creative tourism Tourism development Local and regional development Structural equation Iran

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Machine Learning-Based Calibration Approaches for Single-Beam and Multiple-Beam Distance Sensors

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IEEE Sensors Journal 2024年第1期24卷 975-983页

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Biernacki, Piotr Ziebinski, Adam National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice44-100 Poland Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice44-100 Poland

Sensors are the foundation to facilitate smart cities, smart grids, and smart transportation, and distance sensors are especially important for sensing the environment and gathering information. Researchers have developed various methods to calibrate distance sensors;however, they mainly focus on using external information for calibration, which is inefficient and computationally expensive. To alleviate the above problems, we propose machine learning (ML)-based calibration approaches for distance sensors. We develop two calibration mechanisms, where the naive mechanism directly predicts the true distance, while the residual mechanism predicts the residual for calibration. The conventional ML regression algorithms are then adopted to predict the true distance or calibration residual. Experimental results show that the designed residual calibration mechanism outperforms the naive mechanism by reducing the root mean square error (RMSE) by 92.2% and mean absolute error (MAE) by 93.3% in the fitting task. In prediction, the proposed 2-D-residual mechanism achieves an improvement of 78.6% and 65.7% compared to the state-of-the-art method. The experimental results show the effectiveness and generalization of the proposed ML-based calibration method, especially for the 2-D mechanism, which achieves the highest robustness in all fitting and prediction tasks. © 2001-2012 IEEE.

关键词： Calibration

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MobileDNN: Leveraging the Potential of Hybrid MobileNetV2-DNN for Advanced Image Analysis

MobileDNN: Leveraging the Potential of Hybrid MobileNetV2-DN...

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2024 International Conference on Science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Ogundokun, Roseline Oluwaseun Maskeliunas, Rytis Damasevicius, Robertas Adebiyi, Marion Olubunmi Landmark University Department of Computer Science Omu Aran Nigeria Kaunas University of Technology Department of Multimedia Engineering Lithuania Kaunas University of Technology Faculty of Informatics Kaunas Lithuania

ISBN: (纸本)9798350358155

computer vision systems designed for posture recognition could offer valuable solutions in the healthcare sector, improving healthy ageing and supporting elderly individuals in their daily routines. One area of interest is the automatic detection of falls, which has garnered attention from computer vision and pattern recognition communities. While many existing methods rely on wearable sensors, which demonstrate high accuracy in fall detection, some individuals may be reluctant to wear such devices. Consequently, alternative approaches, such as vision-based techniques, have been developed. The proposed method utilizes a vision-based system that employs a convolutional neural network (CNN) to recognize and categorize various postures (e.g., sitting, lying, standing) in each frame, if available. This approach begins by detecting the person in the frame, applying background subtraction for human body shape extraction, and associating each daily activity with the extracted shape. The proposed model achieved an accuracy of 93.75%, which shows an outstanding performance over existing models. Subsequently, it estimates bounding boxes encompassing the predicted person's body shape. Overall, the proposed technique shows promising results for indoor monitoring systems. © 2024 IEEE.

关键词： Convolutional neural networks

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Neutrosophic Model for Evaluation Healthcare Security Criteria for Powerful and Lightweight Secure Storage System in Cloud-Based E-Healthcare Services

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Neutrosophic Sets and Systems 2023年 58卷 367-378页

作者： El-Douh, Ahmed A. Lu, SongFeng Abdelhafeez, Ahmed Ali, Ahmed M. Aziz, Alber S. School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Faculty of Information Systems and Computer Science October 6th University Giza12585 Egypt Faculty of Computers and Informatics Zagazig University Sharqiyah Zagazig44519 Egypt

Large data volumes make manually keeping and preserving health records for future reference problematic. Most unusual is the coronavirus epidemic's overcrowding of hospitals. The Secure Pattern Electronic Healthcare Records (SPEHR) scheme provides a powerful and lightweight secure storage system for cloud-based E-healthcare services that meets remote healthcare security criteria. So we proposed a neutrosophic model with a multi-criterion decision-making (MCDM) method for the analysis and evaluation of these criteria. The neutrosophic model is used to deal with vague and uncertain data. Then we integrated the neutrosophic model with the AHP method to rank and compute the weights of the criteria. Offering stakeholders a secure interface and avoiding unwanted access to cloud-stored data mitigates E-healthcare risks. The key derivation ensures end-to-end data. ciphering to prevent unauthorized use (KDF). This work provides robust security solutions for various environments. This work can meet security needs for people and secure-communicating organizations. We found the data privacy is the best criterion. © (2023). All Rights Reserved.

关键词： Access control

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One-Shot Verification for Paper Certificates in Public Service System

One-Shot Verification for Paper Certificates in Public Servi...

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2024 International Conference on Information Technology Systems and Innovation, ICITSI 2024

作者： Aditama, Raditya Maulana, Maulvi Ziadinda Harisman, M. Rifki Virziadeili Hariyanto, Agus Susanto, Teguh T. D Universitas Indonesia Faculty of Computer Science Depok Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Universitas Kristen Teknologi Solo Department of Informatics Engineering Surakarta City Indonesia Universitas Negeri Jakarta Department of Educational Management Jakarta Indonesia

ISBN: (纸本)9798331511470

Even if an explosive number of proposals and prototype systems of blockchain based certificates and verification have been suggested and implemented since 2015, still in the public service areas paper certificates are prevalent. Because of advancement of color duplication and editing tools obtainable at almost no price in the internet, paper certificates are easily forged and modified. For the reason, the verification technology of the paper certificates needs need regressive research and can provide abundant research opportunities. In this research, various research suggestions and technical implementation are reviewed and a new system, called 'one-shot' verification is briefly described. The one-shot verification captures the image and QR code of the printed certificates with mobile devices before sending them to block-chained server. The block-chained server decides whether the printed certificates are tampered or not, with the OCR content by comparing hash value with hash value of the original content. The image OCR of the paper was trained with more than 1,700 images using YOLOv8. In the testing with preprocessing, the technology showed 96% accuracy. © 2024 IEEE.

关键词： Blockchain

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Drone-Based Public Surveillance Using 3D Point Clouds and Neuro-Fuzzy Classifier

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computers, Materials & Continua 2025年第3期82卷 4759-4776页

作者： Yawar Abbas Aisha Ahmed Alarfaj Ebtisam Abdullah Alabdulqader Asaad Algarni Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Science and Engineering College of InformaticsKorea UniversitySeoul02841Republic of Korea Cognitive Systems Lab University of BremenBremen28359Germany

Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot ***,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera *** research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)*** first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale *** YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further *** joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are *** features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity ***-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing *** particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.

关键词： Activity recognition geodesic distance pattern recognition neuro fuzzy classifier

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Performance Evaluation of Raspberry Pi Pico for Internet of Things and Its Analysis 4

Performance Evaluation of Raspberry Pi Pico for Internet of ...

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4th International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2024

作者： Adi, Puput Dani Prasetyo Kristiyanto, Arip Sopandi, Ajang Nirmala, Irma Tahir, Muhlis Wijaya, Etistika Yuni Department of Telecommunication Bandung Indonesia Faculty of Computer Sciences Pamulang University Department of Information System Indonesia University of Muhammadiyah Department of Informatics Engineering Tangerang Indonesia Tanjungpura University Department of Computer Systems West Borneo Pontianak Indonesia Trunojoyo University Madura Department of Informatics Education Indonesia

ISBN: (纸本)9798350378368

The massive development of the Internet of Things to date continues to develop a lot of small devices that are integrated such as the Wireless Sensor Network, several experts have conducted research using simulation and practice of WSN, one of the powerful embedded system hardware is the Raspberry Pi Pico, which is a small-sized Raspberry Pi such as Mini Arduino or Micro Arduino. The purpose of developing research in the field of Embedded Systems is to strive in terms of power consumption and dynamism in research, which can be placed on drones and also in various research ideas such as medical for patient comfort. Raspberry Pi RP2040 microcontroller uses an ARM Cortex-M0+ dual-core processor, Raspberry Pi Pico works on a voltage of 1.8 - 5.5 V DC, and can be handled with a 3.7 V DC battery. With its small dimensions, Raspberry Pi pico can be applied to various applicative research. © 2024 IEEE.

关键词： ARM processors

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