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Adaptive Multi-strategy Rabbit Optimizer for Large-scale Optimization

Journal of Bionic engineering 2025年第1期22卷 398-416页

作者： Baowei Xiang Yixin Xiang Department of Computing School of Electronic and Information Engineering Taizhou UniversityTaizhou318000China Department of Software Engineering College of Software Nankai UniversityTianjin300350China

As optimization problems continue to grow in complexity,the need for effective metaheuristic algorithms becomes increasingly ***,the challenge lies in identifying the right parameters and strategies for these *** this paper,we introduce the adaptive multi-strategy Rabbit Algorithm(RA).RA is inspired by the social interactions of rabbits,incorporating elements such as exploration,exploitation,and adaptation to address optimization *** employs three distinct subgroups,comprising male,female,and child rabbits,to execute a multi-strategy *** parameters,including distance factor,balance factor,and learning factor,strike a balance between precision and computational *** offer practical recommendations for fine-tuning five essential RA parameters,making them versatile and *** is capable of autonomously selecting adaptive parameter settings and mutation strategies,enabling it to successfully tackle a range of 17 CEC05 benchmark functions with dimensions scaling up to *** results underscore RA’s superior performance in large-scale optimization tasks,surpassing other state-of-the-art metaheuristics in convergence speed,computational precision,and ***,RA has demonstrated its proficiency in solving complicated optimization problems in real-world engineering by completing 10 problems in CEC2020.

关键词： Adaptive parameter Large scale optimization Rabbit algorithm Swarm intelligence engineering optimization

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engineering software Systems for Quantum computing as a Service: A Mapping Study

arXiv

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arXiv 2023年

作者： Ahmad, Aakash Waseem, Muhammad Liang, Peng Fehmideh, Mahdi Khan, Arif Ali Reichelt, David Georg Mikkonen, Tommi School of Computing and Communications Lancaster University Leipzig Leipzig Germany Faculty of Information Technology University of Jyväskylä Jyväskylä Finland School of Computer Science Wuhan University Wuhan China School of Business University of Southern Queensland QLD Australia M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland

Quantum systems have started to emerge as a disruptive technology and enabling platforms-exploiting the principles of quantum mechanics-to achieve quantum supremacy in computing. Academic research, industrial projects (e.g., Amazon Braket), and consortiums like 'Quantum Flagship' are striving to develop practically capable and commercially viable quantum computing (QC) systems and technologies. Quantum computing as a Service (QCaaS) is viewed as a solution attuned to the philosophy of service-orientation that can offer QC resources and platforms, as utility computing, to individuals and organisations who do not own quantum computers. To understand the quantum service development life cycle and pinpoint emerging trends, we used evidence-based software engineering approach to conduct a systematic mapping study (SMS) of research that enables or enhances QCaaS. The SMS process retrieved a total of 55 studies, and based on their qualitative assessment we selected 9 of them to investigate (i) the functional aspects, design models, patterns, programming languages, deployment platforms, and (ii) trends of emerging research on QCaaS. The results indicate three modelling notations and a catalogue of five design patterns to architect QCaaS, whereas Python (native code or frameworks) and Amazon Braket are the predominant solutions to implement and deploy QCaaS solutions. From the quantum software engineering (QSE) perspective, this SMS provides empirically grounded findings that could help derive processes, patterns, and reference architectures to engineer software services for QC. © 2023, CC BY.

关键词： Life cycle

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Partially-hiding functional encryption for degree-2 polynomials with fine-grained access control

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Frontiers of Computer Science 2024年第3期18卷 231-233页

作者： Haifeng QIAN Cheng LIN Qiaohan CHU Jie CHEN Shanghai Key Laboratory of Trustworthy Computing Software Engineering InstituteEast China Normal UniversityShanghai 200062China

1 Introduction Boneh et al.[1]first systematically introduce the concept of Functional Encryption(FE)which overcomes all-or-nothing limitation of traditional public key ***,FE hides a potential problem:even if the secret key is obtained legitimately,once it is released,it can be used *** leads to that the secret key may leak information *** deal with this problem and make FE more practical,Abdalla et al.[2]recently constructed inner-product FE(IPFE)with fine-grained access control achieving strong security guarantees under standard assumptions.

关键词： grain Encryption encryption

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Crowd dynamics analysis and behavior recognition in surveillance videos based on deep learning

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Multimedia Tools and Applications 2024年 1-35页

作者： Ilyas, Anum Bawany, Narmeen Center for Computing Research Department of Computer Science and Software Engineering Jinnah University for Women Karachi Pakistan

Video surveillance is widely adopted across various sectors for purposes such as law enforcement, COVID-19 isolation monitoring, and analyzing crowds for potential threats like flash mobs or violence. The vast amount of data generated daily from surveillance devices holds significant potential but requires effective analysis to extract value. Detecting anomalous crowd behavior, which can lead to chaos and casualties, is particularly challenging in video surveillance due to its labor-intensive nature and susceptibility to errors. To address these challenges, this research contributes in two key areas: first, by creating a diverse and representative video dataset that accurately reflects real-world crowd dynamics across eight different categories;second, by developing a reliable framework, ‘CRAB-NET,’ for automated behavior recognition. Extensive experimentation and evaluation, using Convolutional Long Short-Term Memory networks (ConvLSTM) and Long-Term Recurrent Convolutional Networks (LRCN), validated the effectiveness of the proposed approach in accurately categorizing behaviors observed in surveillance videos. The employed models were able to achieve the accuracy score of 99.46% for celebratory crowd, 99.98% for formal crowd and 96.69% for violent crowd. The demonstrated accuracy of 97.20% for comprehensive dataset achieved by the LRCN underscores its potential to revolutionize crowd behavior analysis. It ensures safer mass gatherings and more effective security interventions. Incorporating AI-powered crowd behavior recognition like ‘CRAB-NET’ into security measures not only safeguards public gatherings but also paves the way for proactive event management and predictive safety strategies. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Shellfish

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Development of Pattern-Based Test Case Catalog to Increase Reuse and Variety in software Testing 4

Development of Pattern-Based Test Case Catalog to Increase R...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Kemal, Alwan Kusumo, Dana Sulistiyo Riskiana, Rosa Reska School of Computing Telkom University Software Engineering Department Bandung Indonesia

ISBN: (纸本)9798331506490

In software development, the quality control process is a critical element that aims to oversee and verify product quality. Poor quality control processes are frequently a key factor in software project failures. software testing is key to identifying defects, but designing an effective test suite requires a huge effort that can affect cost, effectiveness, maintenance time, and development schedules. The Directorate of the Center for Excellence in Information Technology (PUTI) as one of the IT support units within Telkom University, is currently facing the same challenges in managing the BaSO application, which is an application for making official letters online. This application requires further testing to ensure that each function runs properly in various browser and device environments. In this case, the reuse and pattern approach was proposed as a solution, and based on this approach, a test case catalog was created. To assess the design system's impact and effectiveness, an experimental study was conducted for the PUTI QA team to test the BaSO application. The experimental results show that the use of a test case catalog during the test case development process can increase the reusability of test cases, with an average precision value of about 50%. In addition, the obtained test case variation value also increased by 35.5%. The findings highlight the significant impact of using a test case catalog, thus contributing to a more effective software testing process. © 2024 IEEE.

关键词： software quality

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User-Centric Evaluation of Novelty and Explanation Aspects of Recommender Systems in an Indonesia E-commerce Platform Based on Perceived Usefulness 2

User-Centric Evaluation of Novelty and Explanation Aspects o...

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2nd International Conference on software engineering and Information Technology, ICoSEIT 2024

作者： Hasanah, Andi Uswatun Kusumo, Dana Sulistyo Telkom University Bachelor of Software Engineering School of Computing Bandung Indonesia

ISBN: (纸本)9798350317503

In e-commerce, recommender systems have been widely used to help their customers with which item to buy. Keeping recommendations accurate to users has always been the main topic in recommender systems studies. However, the recommendations that are very accurate at times are not the most useful recommendations to users. Among many aspects, novelty is becoming a more common component of evaluation practice, and explanation can play a useful role. On top of that, a few researchers suggested studying recommender systems from a user-centric perspective. This research performed a user-centric evaluation to examine the influence of novelty and explanation on perceived usefulness using a within-subject design approach. During within-subject design, participants were shown two recommendation list designs from each aspect. Put simply, there are four designs in this study, and then later, participants evaluate the design. The results of the user-centric evaluation were analyzed using a wilcoxon test. The outcome from the test showed that there is no significant difference between the two novelty scenarios on perceived usefulness. On the other hand, there are significant differences between the two explanation scenarios on perceived usefulness. The conclusion of this paper is that both novelty scenarios are useful from the user perspective. In sharp contrast, one of two explanation scenarios has better influence on perceived usefulness and is more helpful based on the user's perspective. © 2024 IEEE.

关键词： Recommender systems

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Activation Sparsity Opportunities for Compressing General Large Language Models

Activation Sparsity Opportunities for Compressing General La...

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2024 IEEE International Performance, computing, and Communications Conference, IPCCC 2024

作者： Dhar, Nobel Deng, Bobin Islam, Md Romyull Ahmad Nasif, Kazi Fahim Zhao, Liang Suo, Kun Kennesaw State University College of Computing and Software Engineering United States

ISBN: (纸本)9798350367942

Deploying local AI models, such as Large Language Models (LLMs), to edge devices can substantially enhance devices' independent capabilities, alleviate the server's burden, and lower the response time. Owing to these tremendous potentials, many big tech companies have been actively promoting edge LLM evolution and released several lightweight Small Language Models (SLMs) to bridge this gap. However, SLMs currently only work well on limited real-world applications. We still have huge motivations to deploy more powerful (larger-scale) AI models on edge devices and enhance their smartness level. Unlike the conventional approaches for AI model compression, we investigate from activation sparsity. The activation sparsity method is orthogonal and combinable with existing techniques to maximize compression rate while maintaining great accuracy. According to statistics of open-source LLMs, their Feed-Forward Network (FFN) components typically comprise a large proportion of parameters (around 2/3). This internal feature ensures that our FFN optimizations would have a better chance of achieving effective compression. Moreover, our findings are beneficial to general LLMs and are not restricted to ReLU-based *** work systematically investigates the tradeoff between enforcing activation sparsity and perplexity (accuracy) on state-of-the-art LLMs. Our empirical analysis demonstrates that we can obtain around 50% of main memory and computing reductions for critical FFN components with negligible accuracy degradation. This extra 50% sparsity does not naturally exist in the current LLMs, which require tuning LLMs' activation outputs by injecting zero-enforcing thresholds. To obtain the benefits of activation sparsity, we provide a guideline for the system architect for LLM prediction and prefetching. Moreover, we further verified the predictability of activation patterns in recent LLMs. The success prediction allows the system to prefetch the necessary weights while omitting

关键词： Cache memory

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Committed-programming reductions: formalizations,implications and relations

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Science China(Information Sciences) 2024年第10期67卷 151-171页

作者： Jiang ZHANG Yu YU Dengguo FENG Shuqin FAN Zhenfeng ZHANG State Key Laboratory of Cryptology Department of Computer Science and Engineering Shanghai Jiao Tong University Trusted Computing and Information Assurance Laboratory Institute of SoftwareChinese Academy of Sciences

In this work, we introduce a class of black-box(BB) reductions called committed-programming reduction(CPRed) in the random oracle model(ROM) and obtain the following interesting results:(1) we demonstrate that some well-known schemes, including the full-domain hash(FDH) signature(Eurocrypt1996) and the Boneh-Franklin identity-based encryption(IBE) scheme(Crypto 2001), are provably secure under CPReds;(2) we prove that a CPRed associated with an instance-extraction algorithm implies a reduction in the quantum ROM(QROM). This unifies several recent results, including the security of the Gentry-Peikert-Vaikuntanathan IBE scheme by Zhandry(Crypto 2012) and the key encapsulation mechanism(KEM) variants using the Fujisaki-Okamoto transform by Jiang et al.(Crypto 2018) in the ***, we show that CPReds are incomparable to non-programming reductions(NPReds) and randomly-programming reductions(RPReds) formalized by Fischlin et al.(Asiacrypt 2010).

关键词： provable security random oracle model quantum random oracle model black-box reduction/separation programmability

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Taming diffusion model for exemplar-based image translation

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Computational Visual Media 2024年第6期10卷 1031-1043页

作者： Ma, Hao Yang, Jingyuan Huang, Hui Shenzhen University Visual Computing Research Center College of Computer Science and Software Engineering Shenzhen China (GRID:grid.263488.3) (ISNI:0000 0001 0472 9649)

Exemplar-based image translation involves converting semantic masks into photorealistic images that adopt the style of a given ***,most existing GAN-based translation methods fail to produce photorealistic *** this study,we propose a new diffusion model-based approach for generating high-quality images that are semantically aligned with the input mask and resemble an exemplar in *** proposed method trains a conditional denoising diffusion probabilistic model(DDPM)with a SPADE module to integrate the semantic *** then used a novel contextual loss and auxiliary color loss to guide the optimization process,resulting in images that were visually pleasing and semantically *** demonstrate that our method outperforms state-of-the-art approaches in terms of both visual quality and quantitative metrics.

关键词： exemplar image translation denoising diffusion probabilistic model(DDPM)

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Towards a new Benchmark for Emotion Detection in NLP: A Unifying Framework of Recent Corpora 2

Towards a new Benchmark for Emotion Detection in NLP: A Unif...

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2nd Workshop on Generalisation (Benchmarking) in NLP, GenBench 2024

作者： Koufakou, Anna Nieves, Elijah Peller, John Department of Computing & Software Engineering Florida Gulf Coast University United States

ISBN: (纸本)9798891761827

Emotion recognition in text is a complex and evolving field that has garnered considerable interest. This paper addresses the pressing need to explore and experiment with new corpora annotated with emotions. We identified several corpora presented since 2018. We restricted this study to English single-labeled data. Nevertheless, the datasets vary in source, domain, topic, emotion types, and distributions. As a basis for benchmarking, we conducted emotion detection experiments by finetuning a pretrained model and compared our outcomes with results from the original publications. More importantly, in our efforts to combine existing resources, we created a unified corpus from these diverse datasets and evaluated the impact of training on that corpus versus on the training set for each corpus. Our approach aims to streamline research by offering a unified platform for emotion detection to aid comparisons and benchmarking, addressing a significant gap in the current landscape. Additionally, we present a discussion of related practices and challenges. Our code and dataset information are available at https://***/a-koufakou/ EmoDetect-Unify. We hope this will enable the NLP community to leverage this unified framework towards a new benchmark in emotion detection. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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