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African Bison Optimization Algorithm:A New Bio-Inspired Optimizer with engineering Applications

computers, Materials & Continua 2024年第10期81卷 603-623页

作者： Jian Zhao Kang Wang Jiacun Wang Xiwang Guo Liang Qi School of Science University of Science and Technology LiaoningAnshan114051China Team of Artificial Intelligence Theory and Application University of Science and Technology LiaoningAnshan114051China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Information and Control Engineering College Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China

This paper introduces the African Bison Optimization(ABO)algorithm,which is based on biological *** is inspired by the survival behaviors of the African bison,including foraging,bathing,jousting,mating,and *** foraging behavior prompts the bison to seek a richer food source for *** bison find a food source,they stick around for a while by bathing *** jousting behavior makes bison stand out in the population,then the winner gets the chance to produce offspring in the mating *** eliminating behavior causes the old or injured bison to be weeded out from the herd,thus maintaining the excellent *** above behaviors are translated into ABO by mathematical *** assess the reliability and performance of ABO,it is evaluated on a diverse set of 23 benchmark functions and applied to solve five practical engineering problems with *** findings from the simulation demonstrate that ABO exhibits superior and more competitive performance by effectively managing the trade-off between exploration and exploitation when compared with the other nine popular metaheuristics algorithms.

关键词： Optimization metaheuristics African bison optimization engineering problems

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Balancing Efficiency with Equality: Auction Design with Group Fairness Concerns 27

Balancing Efficiency with Equality: Auction Design with Grou...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Jia, Fengjuan Zhang, Mengxiao Liu, Jiamou Khoussainov, Bakh School of Computer Science and Engineering University of Electronic Science and Technology of China China School of Computer Science The University of Auckland New Zealand

ISBN: (纸本)9781643685489

The issue of fairness in AI arises from discriminatory practices in applications like job recommendations and risk assessments, emphasising the need for algorithms that do not discriminate based on group *** concern is also pertinent to auctions, commonly used for resource allocation, which necessitate fairness *** study examines auctions with groups distinguished by specific attributes, seeking to (1) define a fairness notion that ensures equitable treatment for all, (2) identify mechanisms that adhere to this fairness while preserving incentive compatibility, and (3) explore the balance between fairness and seller’s *** introduce two fairness notions-group fairness and individual fairness-and propose two corresponding auction mechanisms: the Group Probability Mechanism, which meets group fairness and incentive criteria, and the Group Score Mechanism, which also encompasses individual *** experiments, we validate these mechanisms’ effectiveness in promoting fairness and examine their implications for seller revenue. © 2024 The Authors.

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Developing microwave-induced thermoacoustic tomography:System,application,and reconstruction

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Journal of Electronic science and technology 2023年第4期21卷 1-19页

作者： Shuang-Li Liu Wan-Ting Peng Xiao-Zhang Zhu Jian Song Xin Shang Hua Zhang Zhi-Qin Zhao School of Information Engineering Southwest University of Science and TechnologyMianyang621010China School of Electronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China Yunnan Key Laboratory of Computer Technologies Application Kunming University of Science and TechnologyKunming650500China

A microwave-induced thermoacoustic imaging(MITAT)system is a non-destructive physical medical imaging method that combines the advantages of the high contrast of microwave imaging and the high resolution of ultrasound *** uses the microwave as the excitation source and ultrasound as the information *** different kinds of biological tissue absorb electromagnetic energy,it results in localized temperature *** thermal expansion will induce ultrasonic signals(i.e.,thermoacoustic signals),known as the thermoacoustic *** microwave absorption image of the sample can be reconstructed by algorithm *** MITAT contrast depends on different dielectric parameters of different kinds of *** introduce the developed system and its *** addition,the challenges and prospects of MITAT for further development are discussed.

关键词： Application Microwave-induced thermoacoustic tomography(MITAT) Reconstruction System

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Meta-Mechanisms for Combinatorial Auctions over Social Networks 27

Meta-Mechanisms for Combinatorial Auctions over Social Netwo...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Fang, Yuan Zhang, Mengxiao Liu, Jiamou Khoussainov, Bakh School of Computer Science and Engineering University of Electronic Science and Technology of China China School of Computer Science The University of Auckland New Zealand

ISBN: (纸本)9781643685489

Recently there has been a large amount of research designing mechanisms for auction scenarios where the bidders are connected in a social network. Different from the existing studies in this field that focus on specific auction scenarios e.g. single-unit auction and multi-unit auction, this paper considers the following question: is it possible to design a scheme that, given a classical auction scenario and a mechanism M˜ suited for it, produces a mechanism in the network setting that preserves the key properties of M˜? To answer this question, we design meta-mechanisms that provide a uniform way of transforming mechanisms from classical models to mechanisms over networks and prove that the desirable properties are preserved by our meta-mechanisms. Our meta-mechanisms provide solutions to combinatorial auction scenarios in the network setting: (1) combinatorial auction with single-minded buyers and (2) combinatorial auction with general monotone valuation. To the best of our knowledge, this is the first work that designs combinatorial auctions over a social network. © 2024 The Authors.

关键词： Social networking (online)

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The Future of Work: Robotic Process Automation and its Role in Shaping Tomorrow’s Business Landscape

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SN computer science 2025年第2期6卷 1-19页

作者： Bhardwaj, Vivek Yadav, Shveta Kaur, Navjeet Anand, Darpan School of Computer Science and Engineering Manipal University Jaipur Jaipur India School of Computer Science and Engineering Lovely Professional University Punjab Phagwara India Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab Mohali India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India

In the new era of automation, Robotic Process Automation (RPA) has emerged as a powerful suite of tools for automating mundane, repetitive, rule-based, and structured tasks using software bots without disrupting existing infrastructure. Due to its significant potential, RPA has garnered considerable attention in the business world, being both easier and cheaper to implement while enhancing efficiency and productivity. This study begins by examining the characteristics of an RPA system and suitability of processes for RPA. This study delves into the role and impact of RPA in modern businesses, highlighting its transformative potential. It also explores the latest trends in RPA research, providing insights into cutting-edge developments and innovative applications. Furthermore, the paper addresses the challenges faced in implementing RPA and offers strategies for overcoming these obstacles, aiming to enhance the efficiency and effectiveness of RPA deployments in various business contexts. Lastly, RPA software bots were developed to quickly and accurately extract data from various invoices. The results show that, when implemented correctly, an RPA system is both easy to deploy and scalable, while maintaining high accuracy. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Artificial intelligence Business processes Intelligent automation Robotic process automation (RPA) Software bots

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Translation English to Punjabi: A Concise Review of Significant Approaches

Translation English to Punjabi: A Concise Review of Signific...

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2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Srivastava, Muskan Malik, Nishchay Gupta, Adarshita Chhabra, Megha Khepra, Shaveta Abidi, Ali Imam Sharda University School Of Engineering & Technology Department Of Computer Science & Engineering Greater Noida India Amrita School Of Engineering Department Of Computer Science & Engineering Bangalore India

ISBN: (纸本)9798350306446

Over the years, Machine Translation in English to Punjabi has seen significant advancements. The study emphasizes Punjabi's unique linguistic complexities, which pose challenges for accurate and contextually relevant translations. Recognizing the importance of overcoming these obstacles, the paper investigates various pre-processing methodologies within neural-based and statistical-based Machine Translation systems. It examines the methods to improve translation accuracy, addressing issues such as morphological complexity, syntactic variations, and a lack of parallel corpora. Effective pre-processing techniques are highlighted as a critical step toward improving machine translation performance for Punjabi. Ultimately, by capitalizing on existing advancements, this study highlights practical implications and potential areas for improvement, focusing on the end-user experience. © 2024 IEEE.

关键词： Machine translation

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Gaining Technological Autonomy and Social-emotional Support: A Case Study of How and Why Chinese Older Adults Engage with a Semi-acquaintance Online Community

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Proceedings of the ACM on Human-computer Interaction 2024年第CSCW2期8卷 1-35页

作者： Qian, Zhigu Fu, Jiaojiao Zhou, Yangfan School of Computer Science Fudan University Shanghai Key Laboratory of Intelligent Information Processing Shanghai China School of Information Science and Engineering East China University of Science and Technology Shanghai China

Older adults are often underserved and marginalized in technology engagement due to their reluctance and the barriers they face in adopting and engaging with mainstream technology. However, Pinxiaoquan, a social feature of an e-commerce platform in China, has gained a large number of older users. This work investigates how and why Chinese older adults use Pinxiaoquan, aiming to unveil the underlying logic and inspire technology-inclusive design for older adults. To this end, we conducted a mixed-methods qualitative study over two years, which included online observation, and semi-interview. We found that Pinxiaoquan’s success among Chinese older adults is mainly due to its ability to inspire technological autonomy and provide social-emotional support. Rather than simply lowering technical barriers or asking them to seek assistance outside the platform, Pinxiaoquan builds a semi-acquaintance online community based on location and social ties that allows older adults to realize technical support mutually. Pinxiaoquan also fulfills their social-emotional needs, such as free online expression, memory creation and preservation, relationship expansion and maintenance, and a sense of value. Our research contributes to the HCI community by highlighting the importance of improving older adults’ technology autonomy following their specific social and cultural background and social-emotional needs. This work also provides unique insights and implications for building inclusive technology for the growing aging population. © 2024 Copyright held by the owner/author(s).

关键词： Marketplaces

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DialTest-EA: An Enhanced Fuzzing Approach With Energy Adjustment for Dialogue Systems via Metamorphic Testing

DialTest-EA: An Enhanced Fuzzing Approach With Energy Adjust...

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作者： Chen, Haibo Chen, Jinfu Wu, Yucheng Cai, Saihua Ahmad, Bilal Huang, Rubing Wang, Shengran Zhang, Chi School of Computer Science and Communication Engineering Jiangsu Key Laboratory of Security Technology Industrial Cyberspace Jiangsu University Zhenjiang China School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology China

Deep neural networks (DNNs) possess potent feature learning capability, enabling them to comprehend natural language, which strongly support developing dialogue systems. However, dialogue systems usually perform incorrect behaviours in some corner cases, which may cause misunderstanding or economic loss. To test and debug dialogue systems, a popular fuzzing framework by metamorphic testing with Gini impurity guidance is proposed, namely, DialTest. However, DialTest treats all seeds (the initial test inputs to generate the mutated test inputs) equally during the fuzzing process and does not differentiate seeds, resulting in a certain limitation to its incorrect behaviour detection capability. In this paper, we propose to enhance the DialTest by applying a lightweight energy adjustment strategy called DialTest with Energy Adjustment (DialTest-EA). DialTest-EA employs the ant colony optimization algorithm (ACO) to adjust the mutation energy of each seed adaptively, ensuring that potential seeds have more opportunities to generate subsequent test inputs. To evaluate the effectiveness of the proposed DialTest-EA, we conduct a series of comparisons with the original DialTest and random mutation strategy. The experimental results show that the proposed DialTest-EA outperforms the compared methods both in the intent detection and slot filling tasks. Compared with the original DialTest, the intent detection accuracy of generated test cases by the proposed method is reduced by more than 14%, and the slot filling accuracy is reduced by more than 8%. © 2024 John Wiley & Sons Ltd.

关键词： Ant colony optimization

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Microgrids with day-ahead energy forecasting for efficient energy management in smart grids: hybrid CS-RERNN

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Australian Journal of Electrical and Electronics engineering 2024年第3期21卷 213-227页

作者： Shirley, C.P. Pattar, Jagannath Kavitha Rani, P. Saini, Sumit Ranga, Jarabala Elangovan, D. Venkatakrishna Reddy, Ch. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Madanapalle Institute of Technology & Science Madanapalle India Department of M.Tech Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Electrical Engineering School of Engineering & Technology Central University of Haryana Mahendergarh India Detartment of Electrical and Electronics Engineering Ramachandra College of Engineering Eluru India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Electrical and Electronics Engineering Chaitanya Bharathi institute of technology Hyderabad India

By integrating smart grid technology with home energy management systems, households can monitor and optimise their energy consumption. This allows for more efficient use of energy resources, reducing waste and lowering energy bills. In this manuscript, a hybrid approach is proposed for smart grid home energy management with microgrids and day-ahead energy forecasts. The proposed control approach combines the Circle Search (CS) algorithm and Recalling-Enhanced Recurrent Neural Network (RERNN). Commonly it is named as CS-RERNN technique. The novelty of this paper is to optimise energy consumption and production within microgrids, thereby contributing to the overall efficiency of the smart grid system. The proposed method is used to reduce the electricity cost, peak-to-average ratio (PAR), and maximising consumer comfort. Energy management is performed based on the CS algorithm. A smart home connected to the external power grid (PG) is managed by the proposed method. Here, load demand is predicted by using RERNN. By then, the performance of the proposed method is implemented in MATLAB platform. The proposed method shows a high efficiency of 96%, and 22 $ of low electricity bill cost compared with other existing methods such as Particle swarm optimisation (PSO), Cuckoo search algorithm (CSA, and Border collie Optimisation (BCO). ©, Engineers Australia.

关键词： Energy utilization

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Design an optimization based ensemble machine learning framework for detecting rice leaf diseases

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Multimedia Tools and Applications 2024年第36期83卷 84401-84424页

作者： Rajasekhar, Veeramreddy Arulselvi, Gnanasekaran Babu, K. Suresh Department of Computer Science Engineering Annamalai University Tamilnadu Chidambaram India Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University Tamil Nadu Chidambaram India International School of Technology and Sciences for Women East Gonagudem Rajanagaram A.P Rajamahendravaram India

The agriculture industry is currently dealing with serious issues with rice plants as a result of illnesses that decrease the quantity and output of the harvest. Numerous fungi and bacteria diseases harm plants that affect the growth of yield. So identification of the detection of crop diseases is essential for enhancing the productivity of crops. Many techniques have been developed to improve disease detection in crops but there are still some issues such as noise, time consumption, delay, poor segmentation, and less accuracy. To overcome these issues, this paper, designed a Spider Monkey-based Random Forest (SMbRF) model for accurate detection and classification of rice leaf diseases and the designed model was implemented in the Python system. The main aim is to develop an optimization-based random forest technique for accurate prediction of rice leaf disease by exact segmentation. Initially, preprocessing is performed to enhance the data quality and remove errors. Furthermore, separate the lesions using mean shift image segmentation and extract the shape and color features to improve the detection results of the developed model. As well, spider monkey fitness is updated in the RF classification layer for accurate classification of diseases and improves accuracy with less execution time. The experiment results show the reliability and efficiency of the designed model, it attains better performance in accuracy, sensitivity, specificity, and precision. The designed model attained 99.29% accuracy, 99.52% sensitivity, 98.76% precision, and 99% specificity proving the scalability of the designed model. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Machine learning

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