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Boosted Spider Wasp Optimizer for High-dimensional Feature Selection

Journal of Bionic Engineering 2024年第5期21卷 2424-2459页

作者： Elfadil A.Mohamed Malik Sh.Braik Mohammed Azmi Al-Betar Mohammed A.Awadallah Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman University346AjmanUnited Arab Emirates Department of Computer Science Al-Balqa Applied UniversityAl-Salt19117Jordan Department of Information Technology Al-Balqa Applied UniversityIrbid21510Jordan Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial Intelligence Research Center(AIRC) Ajman University346AjmanUnited Arab Emirates

With the increasing dimensionality of the data,High-dimensional Feature Selection(HFS)becomes an increasingly dif-ficult *** is not simple to find the best subset of features due to the breadth of the search space and the intricacy of the interactions between *** of the Feature Selection(FS)approaches now in use for these problems perform sig-nificantly less well when faced with such intricate situations involving high-dimensional search *** is demonstrated that meta-heuristic algorithms can provide sub-optimal results in an acceptable amount of *** paper presents a new binary Boosted version of the Spider Wasp Optimizer(BSWO)called Binary Boosted SWO(BBSWO),which combines a number of successful and promising strategies,in order to deal with *** shortcomings of the original BSWO,including early convergence,settling into local optimums,limited exploration and exploitation,and lack of population diversity,were addressed by the proposal of this new variant of *** concept of chaos optimization is introduced in BSWO,where initialization is consistently produced by utilizing the properties of sine chaos mapping.A new convergence parameter was then incorporated into BSWO to achieve a promising balance between exploration and *** exploration mechanisms were then applied in conjunction with several exploitation strategies to effectively enrich the search process of BSWO within the search ***,quantum-based optimization was added to enhance the diversity of the search agents in *** proposed BBSWO not only offers the most suitable subset of features located,but it also lessens the data's redundancy *** was evaluated using the k-Nearest Neighbor(k-NN)classifier on 23 HFS problems from the biomedical domain taken from the UCI *** results were compared with those of traditional BSWO and other well-known meta-heuristics-based *** findings indicate that,in comparison to other competing techn

关键词： High-dimensional features SWO algorithm Feature selection Optimization Machine learning

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Mathematical Problem Solving in Arabic: Assessing Large Language Models 6

Mathematical Problem Solving in Arabic: Assessing Large Lang...

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6th International Conference on AI in Computational Linguistics, ACLing 2024

作者： Mahgoub, Abeer Khoriba, Ghada Elsabry, Elhassan Anas NLP Research Group Center for Informatics Science School of Information Technology and Computer Science Nile University Giza Egypt

This paper comprehensively evaluates the efficacy of different large language models (LLMs) in addressing mathematical challenges expressed in natural languages, mainly focusing on low-resource languages like Arabic. The main challenge of this problem is that despite the considerable size and impressive problem-solving capabilities of these models, they still require enhancements to achieve satisfactory performance for mathematical problem-solving. An LLM must be trained or fine-tuned extensively in understanding and solving mathematical problems articulated in natural language contexts. This is further complicated by the scarcity of high-quality, annotated datasets in low-resource languages. To overcome this problem, we introduce a method for generating synthetic data to address the challenge of data scarcity in Arabic. This approach includes using LLMs to create high-quality, synthetic mathematical problem datasets that can be used to augment the training process. We propose the Synthetic Data Augmentation (SDA) framework, an advanced variant of traditional data augmentation techniques explicitly tailored for mathematical problem-solving in low-resource languages. Experimental studies reveal that using synthetic data significantly improves the performance of LLMs in solving mathematical problems in Arabic. This study contributes to the field of natural language processing and provides insights into the potential of synthetic data generation to enhance LLM performance in low-resource languages. © 2024 Elsevier B.V.. All rights reserved.

关键词： Data assimilation

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Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

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computers, Materials & Continua 2024年第9期80卷 4475-4496页

作者： Xiwang Guo Liangbo Zhou Zhiwei Zhang Liang Qi Jiacun Wang Shujin Qin Jinrui Cao College of Information and Control Engineering Liaoning Petrochemical UniversityFushun113000China Department of Computer Science and Technology Shandong University of Science and TechnologyQingdao266590China Department of Computer Science and Software Engineering Monmouth UniversityWest Long BranchNJ 07764USA Research Center of the Economic and Social Development of Henan East Provincial Joint Shangqiu Normal UniversityShangqiu476000China Department of Computer Science New Jersey City UniversityJersey CityNJ 07305USA

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle *** on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is *** enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular *** established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,*** a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

关键词： Parallel disassembly line balancing problem multi-product multiskilled workers discrete chemical reaction optimization algorithm

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Model-Knowledge Mutual Reinforcement for Few-Shot Cellular Network Fault Diagnosis

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IEEE Transactions on Cognitive Communications and Networking 2024年第3期11卷 1-1页

作者： Liu, Chengyong Zhu, Kun Li, Jianpeng Zhang, Yang Niyato, Dusit Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing211106 China Nanyang Technological University College of Computing and Data Science Singapore Singapore

Data-driven cellular network fault diagnosis faces the great challenge of lacking sufficient high-quality labeled data from real networks. Also, how to exploit existing domain knowledge to aid the diagnosis in an efficient manner needs to be addressed. To obtain a high-performance diagnosis system based on a coarse dataset and knowledge base, we propose a Robust Belief Weighting Framework (RBWF) based on abductive learning and belief rule structure for the few-shot fault diagnosis. Our method is mainly innovative in three parts: our framework can obtain weights from insufficient knowledge base to effectively revise pseudo-labels to enhance classifier model performance. Meanwhile, our framework can make the coarse knowledge base more comprehensive by taking advantage of the revised pseudo-labels obtained from enhanced classifiers. To further improve performance, we also design Pattern Extraction (PET) to learn local information from unlabeled data and apply the Synthetic Minority Oversampling Technique (SMOTE) to generate new samples of the minority class. Experimental results illustrate the effectiveness and stability of the proposed framework using the cellular networks data. Furthermore, the PET and SMOTE enhance the diagnostic performance of the minority class. © 2024IEEE.

关键词： Zero-shot learning

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RC structural system control subjected to earthquakes and TMD

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Structural Engineering and Mechanics 2024年第2期89卷 213-223页

作者： Shao, Jenchung Noor, M. Nasir Ken, P. Chang, Chuho Wang, R. College of Electrical Engineering and Computer Science National Kaohsiung University of Science and Technology Taiwan College of Maritime National Kaohsiung University of Science and Technology Taiwan Information and Research Center of China 1/9 Road: 2 Block: D Section: 15 Dhaka1216 Bangladesh

This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory. Copyright © 2024 Techno-Press, Ltd.

关键词： Fuzzy control

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Challenges and future directions of secure federated learning:a survey

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Frontiers of computer science 2022年第5期16卷 173-180页

作者： Kaiyue ZHANG Xuan SONG Chenhan ZHANG Shui YU Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Faculty of Engineering and Information Technology University of Technology SydneySydney 2007Australia SUSTech-UTokyo Joint Research Center on Super Smart City Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China

Federated learning came into being with the increasing concern of privacy security,as people’s sensitive information is being exposed under the era of big *** is an algorithm that does not collect users’raw data,but aggregates model parameters from each client and therefore protects user’s ***,due to the inherent distributed nature of federated learning,it is more vulnerable under attacks since users may upload malicious data to break down the federated learning *** addition,some recent studies have shown that attackers can recover information merely from ***,there is still lots of room to improve the current federated learning *** this survey,we give a brief review of the state-of-the-art federated learning techniques and detailedly discuss the improvement of federated *** open issues and existing solutions in federated learning are *** also point out the future research directions of federated learning.

关键词： federated learning privacy protection security

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of computer science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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Object Counting Using a Refinement Network

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Tsinghua science and technology 2022年第5期27卷 869-879页

作者： Lehan Sun Junjie Ma Liping Jing School of Science Beijing Jiaotong UniversityBeijing 100044China Department of Computer Science and Technology and Beijing National Research Center for Information Science and Technology(BNRist)Tsinghua UniversityBeijing 100084China School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China

To address the scale variance and uneven distribution of objects in scenarios of object-counting tasks,an algorithm called Refinement Network(RefNet) is *** proposed top-down scheme sequentially aggregates multiscale features,which are laterally connected with low-level *** by a multiresolution density regression loss,a set of intermediate-density maps are estimated on each scale in a multiscale feature pyramid,and the detailed information of the density map is gradually added through coarse-to-fine granular refinement progress to predict the final density *** evaluate our RefNet on three crowd-counting benchmark datasets,namely,ShanghaiTech,UCFC0,and UCSD,and our method achieves competitive performances on the mean absolute error and root mean squared error compared to the state-of-the-art *** further extend our RefNet to cell counting,illustrating its effectiveness on relative counting tasks.

关键词： object counting Refinement Network(RefNet) scale variation uneven distribution

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Key Agreement and Management Scheme Based on Blockchain for 5G-Enabled Vehicular Networks

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China Communications 2025年第3期22卷 270-287页

作者： Wang Zhihua Wang Shuaibo Wang Haofan Li Jiaze Yao Yizhe Wang Yongjian Yang Xiaolong School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China School of Cyber Science and Engineering Zhengzhou UniversityZhengzhou 449001China Lab of National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029China

5G technology has endowed mobile communication terminals with features such as ultrawideband access,low latency,and high reliability transmission,which can complete the network access and interconnection of a large number of devices,thus realizing richer application scenarios and constructing 5G-enabled vehicular ***,due to the vulnerability of wireless communication,vehicle privacy and communication security have become the key problems to be solved in vehicular ***,the large-scale communication in the vehicular networks also makes the higher communication efficiency an inevitable *** order to achieve efficient and secure communication while protecting vehicle privacy,this paper proposes a lightweight key agreement and key update scheme for 5G vehicular networks based on ***,the key agreement is accomplished using certificateless public key cryptography,and based on the aggregate signature and the cooperation between the vehicle and the trusted authority,an efficient key updating method is proposed,which reduces the overhead and protects the privacy of the vehicle while ensuring the communication ***,by introducing blockchain and using smart contracts to load the vehicle public key table for key management,this meets the requirements of vehicle traceability and can dynamically track and revoke misbehaving ***,the formal security proof under the eck security model and the informal security analysis is conducted,it turns out that our scheme is more secure than other authentication schemes in the vehicular *** analysis shows that our scheme has lower overhead than existing schemes in terms of communication and computation.

关键词： blockchain certificateless public key cryptography 5G vehicular networks key agreement key management

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Semantic and secure search over encrypted outsourcing cloud based on BERT

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Frontiers of computer science 2022年第2期16卷 152-159页

作者： Zhangjie FU Yan WANG Xingming SUN Xiaosong ZHANG Engineering Research Center of Digital Forensice Ministry of EducationNanjing University of Information Science and TechnologyNanjing 210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 210044China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Searchable encryption provides an effective way for data security and privacy in cloud *** can retrieve encrypted data in the cloud under the premise of protecting their own data security and ***,most of the current content-based retrieval schemes do not contain enough semantic information of the article and cannot fully reflect the semantic information of the *** this paper,we propose two secure and semantic retrieval schemes based on BERT(bidirectional encoder representations from transformers)named SSRB-1,*** training the documents with BERT,the keyword vector is generated to contain more semantic information of the documents,which improves the accuracy of retrieval and makes the retrieval result more consistent with the user’s ***,through testing on real data sets,it is shown that both of our solutions are feasible and effective.

关键词： cloud computing semantic search BERT model searchable encryption

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