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10th International Conference on Civil Engineering, ICCE2023

作者： Naumov, V. Bilokon, A. Sokolov, I. Plakhtii, Ye. Nesevrya, P. Department of Organization and Management in Construction Prydniprovska State Academy of Civil Engineering and Architecture 24-а Architect Oleg Petrov St. Dnipro Ukraine Department of Construction Technologies Prydniprovska State Academy of Civil Engineering and Architecture 24-а Architect Oleg Petrov St. Dnipro Ukraine Department of Computer Science Information Technologies and Applied Mathematics Prydniprovska State Academy of Civil Engineering and Architecture 24-а Architect Oleg Petrov St. Dnipro Ukraine

ISBN: (纸本)9789819743544

This investigation develops an innovative dismantling methodology for industrial facilities impacted by a 2022 missile strike, aiming to restore operations with minimal interruption. The purpose of the research is to establish a rapid and secure dismantling process that integrates seamlessly with ongoing industrial activities, ensuring safety and efficiency. It focuses on the damaged workshop facilities, analyzing the affected structures and utilities to inform emergency dismantling and recovery efforts. Advanced technologies, including specialized excavator attachments and carts, are introduced for precise dismantling, maintaining the integrity of adjacent structures. Our findings illustrate the efficacy of integrating advanced dismantling technologies within active industrial settings, significantly enhancing operational safety and efficiency. The successful application of these methodologies not only aids in the rapid recovery of damaged facilities but also sets a new benchmark for emergency industrial operations. Object of Research: The primary focus is on the damaged industrial workshop facilities, specifically examining the structures, utilities, and operational frameworks affected by the missile strike. This includes the physical site, the technological layout, and the existing industrial processes within the context of emergency dismantling and restoration efforts. © The Author(s) 2024.

关键词： Restoration

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An Object-Based Detection of Splicing Forgery using Color Illumination Inconsistencies 12

An Object-Based Detection of Splicing Forgery using Color Il...

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12th International Conference on Computing Communication and Networking technologies, ICCCNT 2021

作者： Sekhar, P.N.R.L. Chandra Shankar, T.N. Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP Guntur India Department of Computer Scienceand Engineering Gandhi Institute of Technology and Management Visakhapatnam AP India

ISBN: (纸本)9781728185958

This digital imaging era has become ingrained in people to share images and videos with their loved ones via social networking sites. On the other hand, photo editing software innovation allows anyone to easily and quickly modify multimedia content. As a result, people have become accustomed to alter digital content for the sake of amusement or to attract the attention of others. As a result, Digital Image Forensics emerges to provide trustworthiness to the content shared via the internet. This paper proposes efficient tampering detection and localization method for detecting splicing attacks using color illumination inconsistencies. First, the image's color illuminant features extract using the grayness index in rg-chromaticity space. The color illuminants of each color channel are then combined with a logistic regression model to reveal tampered objects in the image. The experimental results show that the proposed method outperforms the state-of-the-art. © 2021 IEEE.

关键词： Color

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A Netnographic-Based Semantic Analysis of Tweet Contents for Stress management

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computers, Materials & Continua 2022年第1期70卷 1845-1856页

作者： Jari Jussila Eman Alkhammash Norah Saleh Alghamdi Prashanth Madhala Mohammad Ayoub Khan HAMK Smart Research Unit Häme University of Applied SciencesHämeenlinna13100Finland Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Computer and Information Sciences Princess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Faculty of Management and Business Tampere UniversityTampere33720Finland College of Computing and Information Technologies University of BishaBisha67714Saudi Arabia

Social media platforms provide new value for markets and research *** article explores the use of social media data to enhance customer value *** case study involves a company that develops wearable Internet of Things(IoT)devices and services for stress *** and semantic annotation for recognizing and categorizing the context of tweets are conducted to gain a better understanding of users’stress management *** aim is to analyze the tweets about stress management practices and to identify the context from the ***,we map the tweets on pleasure and arousal to elicit customer *** analyzed a case study of a marketing strategy on the Twitter *** in the marketing campaign shared photos and texts about their stress management *** learning techniques were used to evaluate and estimate the emotions and contexts of the tweets posted by the campaign *** computational semantic analysis of the tweets was compared to the text analysis of the *** content analysis of only tweet images resulted in 96%accuracy in detecting tweet context,while that of the textual content of tweets yielded an accuracy of 91%.Semantic tagging by Ontotext was able to detect correct tweet context with an accuracy of 50%.

关键词： Social media stress semantic analysis Twitter context recognition

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Digitalisation and Green Strategies: A Systematic Review of the Textile, Apparel and Fashion Industries

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Circular Economy and Sustainability 2025年 1-53页

作者： Orisadare, Emmanuel Ayo Achukwu, Okechukwu Emmanuel Ogunyemi, Abiodun Afolayan Adedeji, Deborah Oluwayemisi Diyaolu, Idowu Jamiu Ugwu, Eunice Ifenyinwa Oluwatope, Ayodeji Oludola Bakare, Kudirat Oyebisi Awoyelu, Iyabo Olukemi Department of Information and Communication Technology University of Ilesa Osun State Ilesa Nigeria School of Computing Engineering and Technology Sir Ian Wood Building Robert Gordon University Garthdee Road Aberdeen AB10 7GJ United Kingdom School of Digital Technologies Tallinn University Narva mnt 29 Tallinn 10120 Estonia Department of Clothing and Textile Design Faculty of Sciences University of Ilesa Ilesa Nigeria Department of Family Nutrition and Consumer Sciences Obafemi Awolowo University Osun State Ile-Ife Nigeria Department of Home Economics and Hospitality Management Education Faculty of Vocational and Technical Education University of Nigeria Enugu State Nsukka Nigeria Department of Computer Science and Engineering Obafemi Awolowo University Osun State Ile-Ife Nigeria

The textile, apparel, and fashion (TAF) industries are vital to national economies, providing employment and fostering global economic development. On the other hand, TAF industries contribute to approximately 20% of global pollution. The rise of Industry 4.0 (I4.0) technologies—including the Internet of Things (IoT), Artificial Intelligence (AI), and robotics—aims to enhance production efficiency and resource management. However, this transition brings several challenges, such as potential disruptions from automation, concerns regarding energy efficiency, and escalating sustainability demands. In response, Industry 5.0 (I5.0) emphasises the integration of human-centric and sustainable practices, encouraging collaboration between humans and machines. While some existing studies highlight the potential of these technologies as enablers of the circular economy (CE), they often fall short of comprehensively linking these technologies to specific operational and strategic elements of CE. Furthermore, they do not sufficiently address how these digital tools fit within a broader sustainability framework in the context of CE principles. This review study aims to explore how digital transformation through I4.0 and I5.0 technologies can enhance circular economy practices in the TAF industries while alleviating the environmental and social challenges associated with industrial growth. The study examined 42 peer-reviewed studies from 2013 to 2023, employing a descriptive and theoretical literature review methodology to analyse the strategies, impacts, and challenges of digitalisation and green transition in the TAF industries. Findings reveal a significant disparity between firms in the Global North, which focus on technology advancement, and those in the Global South, facing implementation barriers. The study advocates for an approach that contextualises the integration of I4.0 and I5.0 technologies, ensuring that sustainable production practices align with regional needs. ©

关键词： Circular economy Digital transformation Green strategies Industry 4.0 Industry 5.0 Textile, apparel and fashion industries

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Compared to The Threshold Dependent Segmentation Technique, Normal Type Lung Cancer Identification in CT Images Utilizing Structural Flood Segmentation Process to Enhance Efficiency

Compared to The Threshold Dependent Segmentation Technique, ...

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Advance Computing and Innovative technologies in Engineering (ICACITE), International Conference on

作者： Ashok Kumar Yadav Sneha Kashyap Sachin S. Pund Hayder Mahmood Salman R. S. Ernest Ravindran G. V. Sriramakrishnan Department of Computer Applications Galgotias University India Department of Computer Science ARKA JAIN University India Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Computer Science Department Al-Turath Universiy College Iraq Department of ECE Koneru Lakshmaiah Education Foundation India Computer Science and Engineering Mohan Babu University Tirupati India

Image segments are a method for analyzing digital pictures that divides one piece of the image with sufficient details to match other image data.. The aim of lung tumor detection in the input figure is to identify the affected images as malignant based on the existence of a tumor. The use of a morphological watershed transforms for segmenting benign type lung tumour affected regions in CT images is suggested in this study. The proposed work is compared to threshold dependent segmentation, another image segmentation technique, with a sample size of 30 for each group. Mean Squared Error (MSE) and Universal Index Quality Measure (UIQI) parameters are used to evaluate the output of an image segmentation algorithm. Better segmentation is indicated by high MSE and UIQI values. The image thresholding and the cutoff transformation, in that order, provide the average MSE rates, mean MSE values, and means. The effectiveness of the stream is tracked the decision is made through descriptive statistics employing a picking area T-test and actual results.

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Ensuring Web Application Quality: The Role of Software Testing as a Form of Quality Assurance

Ensuring Web Application Quality: The Role of Software Testi...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Maneesh Vilash Deshpande Priyanka Ambar Soitkar Diwakar Ramanuj Tripathi Sudhir Balwant Agarmore Department of Computer Science Tai Golwalkar Mahavidyalaya Ramtek Nagpur Department of Computer Science Dr. Ambedkar College Nagpur S.S. Maniar College of Computer & Management RTMNU Nagpur Faculty of Science & Technology School of Allied Science Datta Meghe Institute of Higher Education & Research Wardha

Software quality is a precise characteristic that identifies the characteristics that every software should have. Quality is the primary determinant of the success or failure of a software project and a software-related company. Software quality has been the subject of several studies. To produce high-quality software, organizations involved in the software industry adhere to requirements set out by Capability Maturity Model Integration. Software Quality Assurance, Software Quality Plans, and Software Quality Control are the three key levels that make up quality. Therefore, in this research, we'll talk about the concepts and quality standards that are applied to software projects in the Bangalore software industry, as well as how these standards are monitored and maintained. We will examine how many software companies use the CMMI guidelines while producing software in this research. How many companies evaluate the quality of their initiatives, and how many are meeting international standards. The discoveries exhibit that specific organizations in Bangalore are utilizing software quality assurance strategies.

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Healthcare Assistance to COVID-19 Patient using Internet of Things (IoT) Enabled technologies

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Materials Today: Proceedings 2023年 80卷 3777-3781页

作者： Mukati, Naveen Namdev, Neha Dilip, R. Hemalatha, N. Dhiman, Viney Sahu, Bharti Department of Electronics and Communication Engineering Prestige Institute of Engineering Management and Research Indore India Department of Electronics and Instrumentation Engineering Shri Govindram Seksaria Institute of Technology and Science Indore India Acharya Institute of Technology Department of Mechatronics Engineering Bengaluru India Chennai India Postgraduate Institute of Medical Education and Research Chandigarh India Department of Computer Engineering Dr. D.Y. Patil Institute of Technology Pune18 Pimpri India

The IoT can lead to disruptive healthcare innovation. Research articles on IoT in healthcare and COVID-19 pandemics are thus researched in order to discover the potential of this technology. This literature-based research may help professionals to explore solutions to associated issues and battle the COVID-19 epidemic. Using a process diagram, IoT's significant accomplishments were briefly evaluated. Then seven critical IoT technologies that look useful in healthcare during the COVID-19 Pandemic are identified and illustrated. Finally, in the COVID-19 Pandemic, potential fundamental IoT applications were identified for the medical industry with a short explanation. The present predicament has opened up a fresh avenue to creativity in our everyday lives. The Internet of Things is an up-and-coming technology that enhances and gives better solutions in the medical area, such as appropriate medical record-keeping, sample, device integration, and cause of sickness. IoT's sensor-based technology gives a remarkable ability to lower the danger of intervention in challenging circumstances and is helpful for the pandemic type COVID-19. In the sphere of medicine, IoT's emphasis is on helping to treat diverse COVID-19 situations accurately. It facilitates the work of the surgeon by reducing risks and enhancing overall performance. Using this technology, physicians may readily identify changes in the COVID-19′s vital parameters. These information-based services provide new prospects for healthcare as they advance towards the ideal technique for an information system to adapt world-class outcomes by improving hospital treatment systems. Medical students may now be better taught and led in the future for the identification of sickness. Proper use of IoT may assist handle several medical difficulties such as speed, affordability, and complexity appropriately. It may simply be adapted to track patients' calorific intake and therapy with COVID-19 asthma, diabetes, and arthritis. In C

关键词： COVID-19

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Cerebral and muscle tissue oxygenation during exercise in healthy adults: A systematic review

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Journal of Sport and Health science 2024年第4期13卷 459-471,F0003页

作者： Diego Orcioli-Silva Victor Spiandor Beretta Paulo Cezar Rocha Santos Felipe Marroni Rasteiro Anita Brum Marostegan Rodrigo Vitorio Claudio Alexandre Gobatto Fulvia Barros Manchado-Gobatto Laboratory of Applied Sport Physiology(LAFAE) School of Applied Sciences(FCA)University of Campinas(UNICAMP)Limeira 13484-350Brazil Posture and Gait Studies Laboratory(LEPLO) Institute of BiosciencesSao Paulo State University(UNESP)Rio Claro 13506-900Brazil Physical Education Department School of Technology and SciencesSao Paulo State University(UNESP)Presidente Prudente 19060-900Brazil Department of Computer Science&Applied Mathematics Weizmann Institute of ScienceRehovot 7610001Israel Center of Advanced Technologies in Rehabilitation Sheba Medical CenterRamat Gan 5265601Israel Department of Sport Exercise and RehabilitationNorthumbria UniversityNewcastle upon Tyne NE18STUK

Background:Near-infrared spectroscopy(NIRS)technology has allowed for the measurement of cerebral and skeletal muscle oxygenation simultaneously during *** this technology has been growing and is now successfully used in laboratory and sports settings,this systematic review aimed to synthesize the evidence and enhance an integrative understanding of bloodﬂow adjustments and oxygen(O_(2))changes(i.e.,the balance between O_(2) delivery and O_(2) consumption)within the cerebral and muscle systems during ***:A systematic review was conducted using PubMed,Embase,Scopus,and Web of science databases to search for relevant studies that simultaneously investigated cerebral and muscle hemodynamic changes using the near-infrared spectroscopy system during *** review considered manuscripts written in English and available before February 9,*** step of screening involved evaluation by 2 inde-pendent authors,with disagreements resolved by a third *** Joanna Briggs Institute Critical Appraisal Checklist was used to assess the methodological quality of the ***:Twenty studies were included,of which 80%had good methodological quality,and involved 290 young or middle-aged *** types of exercises were used to assess cerebral and muscle hemodynamic changes,such as cycling(n=11),treadmill(n=1),knee extension(n=5),isometric contraction of biceps brachii(n=3),and duet swim routines(n=1).The cerebral hemodynamics anal-ysis was focused on the frontal cortex(n=20),while in the muscle,the analysis involved vastus lateralis(n=18),gastrocnemius(n=3),biceps brachii(n=5),deltoid(n=1),and intercostal muscle(n=1).Overall,muscle deoxygenation increases during exercise,reaching a plateau in voluntary exhaustion,while in the brain,oxyhemoglobin concentration increases with exercise intensity,reaching a plateau or declining at the exhaustion ***:Muscle and cerebral oxygenation respond differently to exercise,with muscle

关键词： Near-infrared spectroscopy Hemodynamic Blood flow Brain Muscle metabolism

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Lung Cancer Prediction from CT Images and using Deep Learning Techniques 2

Lung Cancer Prediction from CT Images and using Deep Learnin...

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2nd International Conference on Trends in Electrical, Electronics and computer Engineering, TEECCON 2023

作者： Mamatha, Botla Rashmi, D. Tiwari, Kanchan S. Sikrant, Poornima A Jovith, A Arokiaraj Reddy, Pundru Chandra Shaker Geethanjali College of Engineering and Technology Computer Science and Engineering Hyderabad India CMR Institute of Technology Department of Information Science and Engineering Bengaluru India Electronics and Telecommunications MES Wadia College of Engineering Pune Maharasta India Sri Ramachandra Institute of Higher Education and Research Sri Ramachandra Faculty of Management Sciences Tamilnadu Chennai India Networking and Commun. College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur India Lovely Professional University School of Computer Science and Engineering Phagwara Punjab India

ISBN: (纸本)9798350339949

Cellular proliferation in the lung tissues is a hallmark of lung cancer. Lung cancer is particularly dangerous since the lungs are responsible for both breathing in oxygen and exhaling carbon dioxide-two of the body's most vital functions. The application of deep-learning (DL) for the identification of lymph node involvement on histopathology slides has gained a lot of attention due to the potential impact it could have on patient diagnosis and therapy. Recognition accuracy, precision, sensitivity, F-Score, specificity, etc., are all significantly lower with the current approach. Convolution-Neural-Network (CNN), CNN Gradient-Descent (CNN GD), VGG-16, VGG-19, and Resnet-50 are just few of the deep learning algorithms that exhibit improved performance in the metrics with the proposed methodology. CT scan pictures and histopathology images are used to evaluate the suggested method. When histopathological tissues are analyzed, the results demonstrate that detection accuracy improves. © 2023 IEEE.

关键词： computerized tomography

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An Explainable AI Model for Student Engagement in Tablet Learning

An Explainable AI Model for Student Engagement in Tablet Lea...

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IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Akshay Mohan Merin Mathew K. Malavika Georg Gutjahr Radhika Menon Prema Nedungadi Centre for Research in Analytics Technologies and Education Amrita Vishwa Vidhyapeetham Kollam India Department of Mathematics Amrita Vishwa Vidhyapeetham Kollam India Centre for Research in Analytics Technologies and Education & Dept. of Computer Science Amrita Vishwa Vidhyapeetham Kollam India

ISBN: (数字)9798350381689

ISBN: (纸本)9798350381696

This study examines the effectiveness of tabletintegrated teaching and learning in rural India using artificial intelligence (AI) models. Academic motivation was assessed using the Instructional Materials Motivation Survey (IMMS) in the afterschool programs of seven centers located in Tamil Nadu, Uttar Pradesh, Telangana, and Karnataka. The survey is based on the ARCS model for motivation, which postulates that the traits of academic motivation include Attention, Relevance, Confidence, and Satisfaction. The main research question is which of these components contributes the most to the successful participation of a student in the tablet-integrated teaching program, where participation is measured by tablet usage by the students. Our research utilized the AI model XGBoost to examine the trait of academic motivation to make predictions about the students’ participation in the program. The SHAP (SHapley Additive exPlanations) algorithm enables the interpretation of the impact of traits on predictions, which is visually depicted using Waterfall and Beeswarm plots. These graphic explanations allow us to interpret the model's prediction. In that way, the explainable AI model helps to understand methods to improve confidence in students and to relate the connection between the relevance of any technologyintegrated academic intervention program and student attendance.

关键词： Surveys Graphics Analytical models Explainable AI education Learning (artificial intelligence) Predictive models

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