Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…The optimized model was integrated with structure-based virtual screening via molecular docking to prioritize repurposing candidate compounds. …”
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Distinguishing novel coronavirus influenza A virus pneumonia with CT radiomics and clinical features by Lianyu Sui, Huan Meng, Jianing Wang, Wei Yang, Lulu Yang, Xudan Chen, Liyong Zhuo, Lihong Xing, Yu Zhang, Jingjing Cui, Xiaoping Yin

“…After incorporating clinical features, the clinical model’s discriminatory and predictive efficacy further improved in testing sets (AUC, 0.669 vs. 0.820, P = 0.002). …”
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Notice of Violation of IEEE Publication Principles: Dynamic Embedding and Scheduling of Service Function Chains for Future SDN/NFV-Enabled Networks by Haotong Cao, Hongbo Zhu, Longxiang Yang

“…The dynamic embedding and scheduling algorithm has flexible network function placement and improves the underlying resource utilization. …”
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Intelligent Assessment of Personal Credit Risk Based on Machine Learning by Chuansheng Wang, Hang Yu

“…Then, the XGBoost algorithm is used to evaluate the credit risk level of customers, and the traditional Sparrow Search Algorithm is improved by using Tent chaotic mapping, sine and cosine search, reverse learning, and Cauchy mutation strategy to improve the optimization performance of algorithm parameters. …”
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Active micro-vibration isolation system for adaptive vibration suppression tests using piezoelectric stack actuator by Zhiyuan Gao, Lei Zhang, Tongxin Xu, Xiaojin Zhu

“…System identification is conducted using an improved particle swarm optimization method, specifically the Hybrid PSO-Jaya algorithm, which sequentially integrates the PSO algorithm with the Jaya algorithm. …”
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铰链四杆刚体导引机构综合的区间逃逸粒子群算法 by 易建, 何兵, 车林仙

“…The length of the bars is regarded as the restrict condition to obtain the unconstrained optimization model for rigid-body guidance approximate kinematc synthesis of hinged 4-bar linkages and this optimal problem is solved by means of the particle swarm optimization （PSO） algorithm. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…The results reveal the following: (1) NTU and EER levels steadily improved from 2004 to 2022, although coordination between cities still requires enhancement; (2) CCD exhibited a temporal pattern of “progressive escalation and continuous optimization,” and a spatial pattern of “dual-core leadership and regional diffusion,” with most cities shifting from NTU-lagged to synchronized development; (3) environmental regulations (MAR) and fixed asset investment (FIX) emerged as the most influential CCD drivers, and significant nonlinear interactions were observed, particularly those involving population size (HUM); (4) CCD drivers exhibited complex spatiotemporal heterogeneity, characterized by “stage dominance—marginal variation—spatial mismatch.” …”
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Network access and spectrum allocation in next-generation multi-heterogeneous networks by Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang

“…By preprocessing of objective function, constraint simplification, and standardization, the complex spectrum allocation problem is transformed into a standard form of the 01 programming problem, and the solution is obtained by an improved Hungarian algorithm. Second, an intelligent optimization algorithm named improved non-dominated sorting genetic algorithm II is proposed, which combines the interference constraints of the primary network and the service quality requirements of the secondary users into the objective value evaluation of non-dominated sorting, and corrects the chromosomes that do not meet the constraints. …”
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Comparison of Support Vector Machine-Based Techniques for Detection of Bearing Faults by Lijun Wang, Shengfei Ji, Nanyang Ji

“…The global optimization and high computational efficiency of SFLA are applied to the SVM model. …”
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A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

“…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Faster RCNN and Yolov8 were used to compare the performance of object detection, and the loss function and accuracy curve before and after model improvement were compared. The results show that compared to mainstream single detection algorithms, DR-YOLOM multi task detection algorithm has better comprehensive detection ability, and this algorithm can ensure high target recognition accuracy, segmentation accuracy, and appropriate inference speed with a small number of parameters. …”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

“…To tackle the challenge of designing an improved diabetes classification algorithm that is more accurate, random oversampling and hyper‐tuning parameter techniques have been used in this study. …”
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An adaptive video stream transmission control method for wireless heterogeneous networks based on A3C by Zhiqiang LUO, Wei WANG, Xiaorong ZHU

“…The adaptive bit rate (ABR) algorithm has become the focus research in video transmission.However,due to the characteristics of 5G wireless heterogeneous networks,such as large fluctuation of channel bandwidth and obvious differences between different networks,the adaptive video stream transmission with multi-terminal cooperation was faced with great challenges.An adaptive video stream transmission control method based on deep reinforcement learning was proposed.First of all,a video stream dynamic programming model was established to jointly optimize the transmission rate and diversion strategy.Since the solution of this optimization problem depended on accurate channel estimation,dynamically changing channel state was difficult to achieve.Therefore,the dynamic programming problem was improved to reinforcement learning task,and the A3C algorithm was used to dynamically determine the video bit rate and diversion strategy.Finally,the simulation was carried out according to the measured network data,and compared with the traditional optimization method,the method proposed better improved the user QoE.…”
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Privacy-preserving federated learning framework with dynamic weight aggregation by Zuobin YING, Yichen FANG, Yiwen ZHANG

“…There are two problems with the privacy-preserving federal learning framework under an unreliable central server.① A fixed weight, typically the size of each participant’s dataset, is used when aggregating distributed learning models on the central server.However, different participants have non-independent and homogeneously distributed data, then setting fixed aggregation weights would prevent the global model from achieving optimal utility.② Existing frameworks are built on the assumption that the central server is honest, and do not consider the problem of data privacy leakage of participants due to the untrustworthiness of the central server.To address the above issues, based on the popular DP-FedAvg algorithm, a privacy-preserving federated learning DP-DFL algorithm for dynamic weight aggregation under a non-trusted central server was proposed which set a dynamic model aggregation weight.The proposed algorithm learned the model aggregation weight in federated learning directly from the data of different participants, and thus it is applicable to non-independent homogeneously distributed data environment.In addition, the privacy of model parameters was protected using noise in the local model privacy protection phase, which satisfied the untrustworthy central server setting and thus reduced the risk of privacy leakage in the upload of model parameters from local participants.Experiments on dataset CIFAR-10 demonstrate that the DP-DFL algorithm not only provides local privacy guarantees, but also achieves higher accuracy rates with an average accuracy improvement of 2.09% compared to the DP-FedAvg algorithm models.…”
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Reliability Prediction for Computer Numerical Control Machine Servo Systems Based on an IPSO-Based RBF Neural Network by Zheng Jiang, GuangJian Wang, ZuGuang Huang, Ye He, RuiJuan Xue

“…A novel reliability prediction model based on radial basis function (RBF) neural network optimized by improved particle swarm optimization (IPSO) was proposed. …”
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Exploration of Energy-Saving Chilling Landscape Design Based on Algo for Group Intelligence by Zhuo Li

“…The experimental results show that the algo for group intelligence outperforms another algorithm in terms of solving ability to the extent that the average optimization ability is improved by 13.45%, so the algo for group intelligence demonstrates its superior ability to take into account both local and global search. …”
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An Advanced Recomposition-Based Displaying Technique: Maximizing Image Reconstruction for Virtual Museum Applications by Jingjie Zhao, Xin Shi, Olga Yezhova, Qinchuan Zhan, Xijing Zhang

“…These methods, combined with a multi-layer aggregation algorithm that encodes deep feature representations in a Gaussian Mixture Model (GMM), enable seamless scene reconstruction with improved precision. …”
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MAT-FHE: arbitrary dimension matrix multiplication scheme for floating point over fully homomorphic encryption by Yatao Yang, Zhaofu Li, Yucheng Ding, Man Hu

“…Abstract Matrix operation is one of the most basic and practical operations in statistical analysis and machine learning. …”
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Intelligent tuning method for service scheduling in electric power communication networks based on operational risk and QoS guarantee. by Yang Yu, YueLin Jiang, Zeng Dou, Li Cong, Wei Huang, Qiang Zhang, Yang Hu, YanJun Bi

“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…When compared with mainstream object recognition algorithms such as SSD, Faster RCNN, and various YOLO versions, the optimized model shows its superiority. …”
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