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Opposition-based multi-objective ant colony optimization framework for sustainable retrofitting: time–cost–energy–risk trade-offs

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Asian Journal of Civil engineering 2025年第5期26卷 2223-2239页

作者： Pokkuluri, Kiran Sree Chauhan, Trupti Ravindra Macedo, Víctor Daniel Jiménez Manjunath, T.C. Bharadwaj, Manish Sethi, Krushna Chandra Department of Computer Science and Engineering Shri Vishnu Engineering College for Women Bhimavaram India Department of Design Manipal School of Architecture and Planning Manipal Academic of Higher Education Manipal Karnataka Udupi India Mechanical Engineering Faculty Michoacan University of Saint Nicholas of Hidalgo Morelia Mexico Department of Computer Science and Engineering Rajarajeswari College of Engineering Bengaluru India Department of Management Studies Atal Bihari Vajpayee Indian Institute of Information Technology and Management Gwalior India Civil Engineering Department Centurion University of Technology and Management Gajapati India

The increasing emphasis on sustainable retrofitting of buildings has brought attention to the need for optimizing trade-offs among critical objectives, such as time, cost, energy consumption, and risk. This study proposes an opposition-based multi-objective ant colony optimization (OB-MOACO) framework to address these challenges effectively. The framework incorporates opposition-based learning to enhance solution exploration and convergence in multi-objective optimization problems, specifically tailored for sustainable retrofitting projects. The study develops a time–cost–energy–risk trade-off (TCERT) model with four objectives: minimizing retrofitting time, cost, energy consumption, and risks. The model integrates constraints related to budget, project timelines, and energy efficiency to ensure feasibility and sustainability. A detailed case study of retrofitting a mixed-use building is presented, encompassing 11 aspects such as structural reinforcement, energy efficiency enhancement, and accessibility improvements. Results demonstrate the superiority of OB-MOACO over conventional methods like NSGA-III, MODE, and MOPSO in achieving Pareto-optimal solutions. Key performance metrics, including hypervolume (HV) and inverted generational distance (IGD), highlight the model's efficiency in balancing competing objectives. The study contributes to advancing sustainable retrofitting practices by providing an innovative, cost-effective, and energy-efficient decision-making framework. Implications for practitioners and policymakers are discussed, alongside recommendations for future research. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Multi-objective optimization Opposition-based ant colony optimization Pareto optimization Sustainable retrofitting Time–cost–energy–risk trade-off

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A multiple sensitive attributes data publishing method with guaranteed information utility

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CAAI Transactions on Intelligence technology 2023年第2期8卷 288-296页

作者： Haibin Zhu Tong Yi Songtao Shang Minyong Shi Zhucheng Li Wenqian Shang Department of Computer Science and Mathematics Nipissing UniversityNorth BayOntarioCanada Key Lab of Education Blockchain and Intelligent Technology Ministry of EducationGuangxi Normal UniversityGuilinChina Guangxi Key Lab of Multi‐Source Information Mining and Security Guangxi Normal UniversityGuilinChina School of Computer and Communication Engineering Zhengzhou University of Light IndustryZhengzhouChina School of Computer Science Communication University of ChinaBeijingChina Business College Beijing Union UniversityBeijingChina

Data publishing methods can provide available information for analysis while preserving *** multiple sensitive attributes data publishing,which preserves the relationship between sensitive attributes,may keep many records from being grouped and bring in a high record suppression *** category of multiple sensitive attributes data publishing,which reduces the possibility of record suppression by breaking the relationship between sensitive attributes,cannot provide the sensitive attributes association for ***,the existing multiple sensitive attributes data publishing fails to fully account for the comprehensive information *** acquire a guaranteed information utility,this article defines comprehensive information loss that considers both the suppression of records and the relationship between sensitive attributes.A heuristic method is leveraged to discover the optimal anonymity scheme that has the lowest comprehensive information *** experimental results verify the practice of the proposed data publishing method with multiple sensitive *** proposed method can guarantee information utility when compared with previous ones.

关键词： data analysis data privacy security of data

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Progressive Exploration-Conformal Learning for Sparsely Annotated Object Detection in Aerial Images 38

Progressive Exploration-Conformal Learning for Sparsely Anno...

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38th Conference on Neural information Processing Systems, NeurIPS 2024

作者： Lu, Zihan Wang, Chenxu Xu, Chunyan Zheng, Xiangwei Cui, Zhen PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Shandong Normal University Jinan China

The ability to detect aerial objects with limited annotation is pivotal to the development of real-world aerial intelligence systems. In this work, we focus on a demanding but practical sparsely annotated object detection (SAOD) in aerial images, which encompasses a wider variety of aerial scenes with the same number of annotated objects. Although most existing SAOD methods rely on fixed thresholding to filter pseudo-labels for enhancing detector performance, adapting to aerial objects proves challenging due to the imbalanced probabilities/confidences associated with predicted aerial objects. To address this problem, we propose a novel Progressive Exploration-Conformal Learning (PECL) framework to address the SAOD task, which can adaptively perform the selection of high-quality pseudo-labels in aerial images. Specifically, the pseudo-label exploration can be formulated as a decision-making paradigm by adopting a conformal pseudo-label explorer and a multi-clue selection evaluator. The conformal pseudo-label explorer learns an adaptive policy by maximizing the cumulative reward, which can decide how to select these high-quality candidates by leveraging their essential characteristics and inter-instance contextual information. The multi-clue selection evaluator is designed to evaluate the explorer-guided pseudo-label selections by providing an instructive feedback for policy optimization. Finally, the explored pseudo-labels can be adopted to guide the optimization of aerial object detector in a closed-loop progressive fashion. Comprehensive evaluations on two public datasets demonstrate the superiority of our PECL when compared with other state-of-the-art methods in the sparsely annotated aerial object detection task. The code will be available at: https://***/SAOD-research/PECL. © 2024 Neural information processing systems foundation. All rights reserved.

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Text-to-Speech User Interface for ChatGPT 4

Text-to-Speech User Interface for ChatGPT

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

作者： Suni, Alfa Faridh Utomo, Aryo Baskoro Fathoni, Khoiruddin Mahendra, Budiandra Yusuf Seinsiani, Izzati Gemi Hastawan, Ahmad Fashiha Universitas Negeri Semarang Computer Engineering Semarang Indonesia Universitas Negeri Semarang Electrical Engineering Semarang Indonesia Universitas Negeri Semarang Information Technology Education Semarang Indonesia Universitas Negeri Semarang English Literature Study Program Semarang Indonesia

ISBN: (纸本)9798350378368

The emergence of OpenAI's ChatGPT is paying a lot of attention to Generative AI and its impact on Academic integrity. Generative AI is a system designed to generate content or output such as text, image, audio, simulation, video and code based on their respective training data. ChatGPT itself is in the form of a chatbot where users can communicate with AI through dialogue applications via text. GPT 3 API is the technology behind the ChatGPT. However, interaction via text is not as flexible as dialogue using voice. Therefore, speech-to-text technology is needed to interface between the user and the AI. Chatbot AI powered by GPT3 with the optional voice UI powered by Google Text to Speech clearly benefits accessibility and usability. The output of dialogue between human users and AI can be done through text or sound. This research attempts to implement a Text to Speech and vice versa Speech to Text as a User Interface on a Gen-AI using the GPT 3 API so that it will be more user-friendly and accessible. This research opens many possibilities for human-AI interaction (HAX) in implementing virtual assistants. A seamless dialogue between humans and AI will be our goal in the future. © 2024 IEEE.

关键词： ChatGPT Generative AI Speech to Text Text to Speech

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Enhancing IoT Data Security: Integrating Elliptic Galois Cryptography with Matrix XOR Steganography and Adaptive Firefly Optimization 8

Enhancing IoT Data Security: Integrating Elliptic Galois Cry...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Chinnasamy, P. Ayyasamy, Ramesh Kumar Anuradha, K. Alam, Irfan Nair, Deveendra Menon Narayanan Kiran, Ajmeera Kalasalingam Academy of Research and Education School of Computing Department of Computer Science and Engineering Tamilnadu India Faculty of Information and Communication Technology Kampar Malaysia Telangana India Scai Vit Bhopal University Cyber Security and Digital Forensics Division Kothari Kalan Sehore India Mlr Institute of Technology Department of Computer Science and Engineering Hdyerabad India

ISBN: (纸本)9798350376425

Securing the uninterrupted data flow is crucial in the fast-advancing Internet of Things (IoT) market. This work investigates the incorporation of elliptic Galois cryptography and matrix XOR coding steganography to improve data security. The suggested solution employs the elliptic Galois cryptography protocol to encrypt sensitive data from diverse medical records. The private information is embedded within images through the matrix XOR encoding steganography algorithm. The Adaptive Firefly optimization approach is used to improve the efficiency of utilizing cover blocks for steganography. The effectiveness of the proposed technique is evaluated using various modern approaches. We analyze the efficiency and security of the proposed approach by comparing it with a previous hybrid method employing the New York State Department of Health dataset. The results unequivocally validate that our approach offers enhanced safety in Internet of Things (IoT) applications. © 2024 IEEE.

关键词： Steganography

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3D printed-electrospun PCL/hydroxyapatite/MWCNTs scaffolds for the repair of subchondral bone

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Regenerative Biomaterials 2023年第1期10卷 294-305页

作者： Yanyan Cao Lei Sun Zixian Liu Zhizhong Shen Wendan Jia Peiyi Hou Shengbo Sang College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China

Osteochondral defect caused by trauma or osteoarthritis exhibits a major challenge in clinical treatment with limited symptomatic effects at *** regeneration and remodeling of subchondral bone play a positive effect on cartilage regeneration and further promotes the repair of osteochondral *** use of the strengths of each preparation method,the combination of 3D printing and electrospinning is a promising method for designing and constructing multi-scale scaffolds that mimic the complexity and hierarchical structure of subchondral bone at the microscale and nanoscale,*** this study,the 3D printed-electrospun poly(ɛ-caprolactone)/nano-hydroxyapatites/multi-walled carbon nanotubes(PCL/nHA/MWCNTs)scaffolds were successfully constructed by the combination of electrospinning and layer-by-layer 3D *** resulting dual-scale scaffold consisted of a dense layer of disordered nanospun fibers and a porous microscale 3D scaffold layer to support and promote the ingrowth of subchondral ***,the biomimetic PCL/nHA/MWCNTs scaffolds enhanced cell seeding efficiency and allowed for higher cell-cell interactions that supported the adhesion,proliferation,activity,morphology and subsequently improved the osteogenic differentiation of bone marrow mesenchymal stem cells in ***,this study elucidates that the construction of 3D printed-electrospun PCL/nHA/MWCNTs scaffolds provides an alternative strategy for the regeneration of subchondral bone and lays a foundation for subsequent in vivo studies.

关键词： additive manufacturing 3D printing electrospinning subchondral bone

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Skin Cancer Disease Classification Using Tasnet V2 In Image Classification 2

Skin Cancer Disease Classification Using Tasnet V2 In Image ...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Banu, M.Sheerin Elanangai, V. Chakraborty, Uddyalok Sharmiladevi, D. Ramesh Babu, P. Rajeswari, P. R.M.K. Engineering College Department of Information Technology India St. Peter's Institute of Higher Education and Research Department of Eee Avadi Tamilnadu Chennai India Upl University of Sustainable Technology Department of Computer Engineering Gujarat Ankleshwar India Sona College of Technology Tamilnadu Salem India College of Engineering and Technology Wollega University Department of Computer Science Oromia Region Nekemte Ethiopia R.M.D Engineering College India

ISBN: (纸本)9798350371055

Skin cancer is very common and can be fatal. To improve patient results, it is essential to find the disease early. It can be hard to tell the difference between benign and malignant skin lesions when using standard picture classification methods. The complicated features and intricate patterns that can be seen in dermatoscopic images make it very hard to use the current methods for classifying skin cancer signs. If a diagnosis is delayed or not dealt with properly, the effects can be very bad. The study goal is to make skin cancer classification more accurate with the help of TasNet v2 in order to meet a need that appears in the current methods. This study suggests that TasNet v2, a state-of-the-art deep learning framework, be used to sort skin cancer into different groups. In order to solve the problem of the need for more reliable and advanced diagnostic tools, this would work. The suggested method uses transfer learning on a very large set of labelled dermatoscopic images to teach TasNet v2 how to find signs of skin cancer. The trained model is checked and tried on several different sets of data. Using TasNet v2 unique design, which improves feature extraction, lets the model find smaller details that could be signs of skin cancer. The fact that TasNet v2 was able to do picture classification tasks that were not in its original area of expertise shows how flexible and useful it is. These results make it more likely that a new development will happen that will help doctors make more accurate skin cancer diagnoses. © 2024 IEEE.

关键词： Deep Learning Dermatoscopic Images Image Classification Skin Cancer TasNet v2

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Data Poisoning: Issues, Challenges, and Needs 7

Data Poisoning: Issues, Challenges, and Needs

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7th IET Smart Cities Symposium, SCS 2023

作者： Aljanabi, Mohammad Omran, Alaa Hamza Mijwil, Maad M. Abotaleb, Mostafa El-Kenawy, El-Sayed M. Mohammed, Sahar Yousif Ibrahim, Abdelhameed Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science &Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence. © The Institution of engineering & technology 2023.

关键词： Machine learning

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A Copyright-Preserving and Fair Image Trading SchemeBased on Blockchain

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Tsinghua Science and technology 2023年第5期28卷 849-861页

作者： Feng Yu Jiahui Peng Xianxian Li Chunpei Li Bin Qu School of Computer Science&Engineering Guangxi Normal UniversityGuilin 541004Chinaand with the Key Lab of Education Blockchain and Intelligent TechnologyMinistry of EducationGuangxi Normal UniversityGuilin 541004Chinaand also with Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent ProcessingGuangxi Normal UniversityGuilin 541004China Guangxi Power Grid Materials Co Ltd Nanning 530022China

With the proliferation of the Internet,particularly the rise of social media,digital images have gradually become an important part of life,and trading platforms have emerged for buying and selling ***,traditional image trading service providers may disclose users’private information for ***,many image trading platforms disregard the fairness of a transaction and the issue of copyright protection after an image is *** neglect harms the interests of users and affects their enthusiasm for trading.A secure way to safely transact images is *** proposed a copyright-preserving and fair image trading scheme based on blockchain,which combines amplifying locality-sensitive hashing with searchable symmetric encryption to achieve safe image retrieval on blockchain and ensure the credibility of the image retrieval ***,we use digital fingerprint and watermark technologies to realize the copyright protection of images and use smart contracts to achieve fair transaction *** experimental results show that our scheme can protect image copyrights and realize a fair trading process while ensuring efficiency.

关键词： blockchain copyright-preserving trade fair trade tadors code

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EFFECTS OF CUTTING AND WELDING ON ELECTRIC STEELS' FERROMAGNETIC MATERIAL

EFFECTS OF CUTTING AND WELDING ON ELECTRIC STEELS' FERROMAGN...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Agarhari, Abishek Singh, Thakur Meenu Balaji, N.V. Arul Antran Vijay, S. Borade, Monali Ravindra Department of Computer Science & Engineering Invertis University Uttar Pradesh Bareilly243123 India School of Mechenical Engineering Dev Bhoomi Uttarakhand University Uttarakhand 248007 India Department of Computer Science & Engineering School of Engineering & Technology K. R. Mangalam University Haryana Gurugram122103 India Department of Computer Science Karpagam Academy of Higher Education Coimbatore641021 India Department of Computer Science Engineering Karpagam College of Engineering Coimbatore641032 India AI & Ds Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798350355338

This study examines the crucial function that silicon steels, sometimes referred to as electric steels, serve in electromagnetic applications like transformers and motors. The need of preserving ferromagnetic characteristics for effective energy exchange is emphasized in particular. In order to fill in knowledge gaps about the precise effects of the two processes on these materials, this investigation presents a methodology that emphasizes the significance of careful material selection, thorough recording of the cutting and welding procedures, and an organized method of measurement and *** study recognizes the broad implications for industrial, power distribution, and automotive sectors, where ferromagnetic properties are necessary for electrical equipment to remain reliable. The study attempts to provide understanding of the unique effects of the two processes on electric steels, suggesting mitigating measures via a thorough analysis of the body of current literature. The transparent and reproducible technique presented in this study contributes to our knowledge of how electric steels behave in various contexts. The ultimate goal of the study is to improve production methods and guarantee that electromagnetic gear operates as well it can in our environment of growing electricity. © 2024 IEEE.

关键词： Automotive industry

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