Advancements in Parkinson’s Disease Diagnosis: A Comprehensive Survey on Biomarker Integration and Machine Learning by Ruchira Pratihar, Ravi Sankar

“…This comprehensive review explores the advancements in machine learning algorithms in the diagnosis of Parkinson’s disease (PD) utilizing different biomarkers. …”
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The Cultural Value Validity of Digital Media Art Based on Deep Learning Network Model by Yuan Ruan

“…The enhancement of features and the suppression of irrelevant features realize the evaluation of artistic and cultural value. The experimental results show that, compared with mainstream neural network models and traditional classification algorithms, the proposed algorithm has higher classification accuracy and higher recognition and classification efficiency.…”
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Identifying the mitochondrial ribosomal protein MRPL13 as an oncogenic RBP that promotes proliferation, migration, and anti-apoptotic effects in esophageal cancer cells by Yaxi Song, Hui Wang, Shiyao Li, Weili Tao, Chunqing Li, Bin Wang, Caifeng Gong

“…XCell, QUANRISEQ, MCPcounter, EPIC, CIBERSORT, ssGSEA and Estimate algorithm were used to evaluate the abundance of various components of the immune microenvironment. …”
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Interaction between Viscoelastic Composite Beams and Vehicles by a Decoupled Method and Its Application in Engineering by Xia Zhang, Enli Chen, Wei Jiang, Guoqing Wang, Ali Wu

“…Thus, this paper presents a decoupled method named the separation reconstruction algorithm. To theoretically verify whether the separate construction (SR) algorithm is consistent with the direct coupling (DC) algorithm, two dynamic system models of a Bernoulli–Euler composite beam under a moving vehicle are established, which correspond to the two algorithms. …”
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Bioinspired Load Balancing in Large-Scale WSNs Using Pheromone Signalling by Ipek Caliskanelli, James Harbin, Leandro Soares Indrusiak, Paul Mitchell, Fiona Polack, David Chesmore

“…We explore the performance consequences of the pheromone-based load balancing approach using (1) a system-level simulator, (2) deployment of real sensor testbeds to provide a competitive analysis of these evaluation methodologies. The effectiveness of the proposed algorithm is evaluated with different scenario parameters and the required performance evaluation techniques are investigated on case studies based on sound sensors.…”
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MATHEMATICAL MODEL AND DELAY TIME OF REFLECTED SIGNAL IN SYNTHETIC APERTURE SONAR by S. R. Heister, T. T. Tran

“…The evaluation results of the delay time, the phase shift and the Doppler frequency for the different points of seabed surface are represented.…”
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YOLOv7-DWS: tea bud recognition and detection network in multi-density environment via improved YOLOv7 by Xiaoming Wang, Xiaoming Wang, Zhenlong Wu, Guannan Xiao, Guannan Xiao, Chongyang Han, Cheng Fang

“…Secondly, a new loss function WiseIoU is proposed for the loss function in YOLOv7, which improves the accuracy of the model. Finally, we evaluate different attention mechanisms to enhance the model’s focus on key features.Results and discussionThe experimental results show that the improved YOLOv7 algorithm has significantly improved over the original algorithm in all evaluation indexes, especially in the RTea(+6.2%) and mAP@0.5 (+7.7%). …”
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Correction Processing Method and Application of Induction Logging Tool in Highly Deviated Wells by LIU Jiacheng

“…Based on the influence of borehole invasion and the actual measurement signal processing algorithm, the resistivity curves of different detection depth can be obtained by projecting the processing actual logging data from vertical well to deviated-well. …”
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Parallel Simulation Multi-Sample Task Scheduling Approach Based on Deep Reinforcement Learning in Cloud Computing Environment by Yuhao Xiao, Yping Yao, Feng Zhu

“…Complex scenario analysis and evaluation simulations often involve multiple sets of simulation applications with different combinations of parameters, thus resulting in high computing power consumption, which is one of the factors that limits the efficiency of multi-sample parallel simulations. …”
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Research on incremental deployment mechanism of network modality for polymorphic network environment by Jiong LI, Yuxiang HU, Pengshuai CUI, Le TIAN, Yongji DONG

“…Polymorphic networks support diverse network requirements and can coexist, evolve, and change on a unified physical or logical infrastructure in the form of network modality.They can maximize the innovation vitality of network technology driven by new applications.The evolution and development of modality require the incremental deployment of modality to meet the needs of convenience and privacy protection in the multi-user deployment process.However, the deployment of current network functions still uses the one-by-one deployment method, resulting in high complexity of the deployment of new modality, and mutual exposure of processing logic between different users.To address these issues, an incremental deployment mechanism for polymorphic network environments was proposed.Firstly, an incremental deployment mechanism for network modality was designed.Then, the incremental deployment of modality was abstracted as a graph merging problem based on this mechanism, and an adjacency list-based merge parsing graph algorithm was designed.The simulation results indicate that the proposed mechanism can achieve fast and correct merging of network modality, support incremental modality deployment, and greatly reduce the application deployment and service provision threshold of new network systems.…”
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Research on incremental deployment mechanism of network modality for polymorphic network environment by Jiong LI, Yuxiang HU, Pengshuai CUI, Le TIAN, Yongji DONG

“…Polymorphic networks support diverse network requirements and can coexist, evolve, and change on a unified physical or logical infrastructure in the form of network modality.They can maximize the innovation vitality of network technology driven by new applications.The evolution and development of modality require the incremental deployment of modality to meet the needs of convenience and privacy protection in the multi-user deployment process.However, the deployment of current network functions still uses the one-by-one deployment method, resulting in high complexity of the deployment of new modality, and mutual exposure of processing logic between different users.To address these issues, an incremental deployment mechanism for polymorphic network environments was proposed.Firstly, an incremental deployment mechanism for network modality was designed.Then, the incremental deployment of modality was abstracted as a graph merging problem based on this mechanism, and an adjacency list-based merge parsing graph algorithm was designed.The simulation results indicate that the proposed mechanism can achieve fast and correct merging of network modality, support incremental modality deployment, and greatly reduce the application deployment and service provision threshold of new network systems.…”
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Energy Storage Configuration Optimization of a Wind–Solar–Thermal Complementary Energy System, Considering Source-Load Uncertainty by Guangxiu Yu, Ping Zhou, Zhenzhong Zhao, Yiheng Liang, Weijun Wang

“…Then, wind and solar output, as well as loads, are treated as fuzzy variables based on fuzzy chance constraints, and uncertainty constraints are transformed using clear equivalence class processing to establish a bi-level optimization model that considers uncertainties. A differential evolution algorithm and CPLEX are used for solving the upper and lower levels, respectively. …”
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Predictive modeling of hydrogen production and methane conversion from biomass-derived methane using machine learning and optimisation techniques by Adegboyega Bolu Ehinmowo, Bright Ikechukwu Nwaneri, Joseph Oluwatobi Olaide

“…In this study, the integration of various machine learning algorithms with Bayesian optimisation, firefly algorithm, Levenberg-Marquardt, and differential evolution techniques were investigated for hydrogen production via thermocatalytic methane decomposition. …”
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An amalgamated load shifting cum curtailing policy with smart charging of PHEV for economic operation of microgrid system by Bishwajit Dey, Srikant Misra, Arnab Pal, Fausto Pedro Garcia Marquez

“…This strategy utilizes technologies that connect vehicles to the grid and vice versa. The differential evolution (DE) algorithm was used as an optimization tool for the study. …”
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Stiffness Regulation of Cable-Driven Redundant Manipulators Through Combined Optimization of Configuration and Cable Tension by Zhuo Liang, Pengkun Quan, Shichun Di

“…Motion-level and tension-level factors are introduced as control variables into the respective optimization models, enabling effective manipulation of configuration and tension solutions for stiffness regulation. An improved differential evolution algorithm is employed to generate adjustable configuration solutions based on motion-level factors, while a modified gradient projection method is adopted to derive adjustable cable tension solutions based on tension-level factors. …”
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A New Approach for Automatic Search for Families of Optimal Undirected Double-Loop Networks by Emilia A. Monakhova, Oleg G. Monakhov, Edward R. Rzaev, Aleksandr A. Amerikanov, Mikhail Y. Romashikhin, Aleksandr Y. Romanov

“…After applying the integration of differential evolution methods, exhaustive local search, and a new search algorithm (based on the division of graph description polynomials) to the analysis of the generated dataset, we found a large amount of new (distinct from all previously known) families of optimal double-loop networks with generators of linear or quadratic types. …”
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A Hybrid CT-DEWCA-Based Energy-Efficient Routing Protocol for Data and Storage Nodes in Underwater Acoustic Sensor Networks by Imran Khan, Muhammad Rauf, Atif Jamil

“…This research proposes an energy-aware deployment approach and introduces the Controlled Transmission enhanced by hybrid model scheme with Differential Evolution, Whale Optimization, and Chaotic Adaptation (CT-DEWCA) for relay selection. …”
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Physics-Informed Neural Network for Load Margin Assessment of Power Systems with Optimal Phasor Measurement Unit Placement by Murilo Eduardo Casteroba Bento

“…The IEEE 68-bus system and the Brazilian interconnected power system were chosen as the test systems to perform the case studies and evaluations. Three different metaheuristics called the Hiking Optimization Algorithm, Artificial Protozoa Optimizer, and Particle Swarm Optimization were applied and evaluated in the test system. …”
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Cultivation Method Analysis for Teachers’ Teaching Ability Driven by Artificial Intelligence Technology by Yanfang Chen, Shasha Xu

“…First, this work researches and improves the teaching ability training strategies of college teachers driven by artificial intelligence from different levels. Second, this work proposes a neural network (IPSO-BP) for evaluating the teaching ability of college teachers via artificial intelligence technology. …”
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Sparse Array Mutual Coupling Reduction by C. Larmour, N. Buchanan, V. Fusco, M. Ali Babar Abbasi

“…The paper conducts a comprehensive comparison of multiple array design optimisation techniques, including genetic algorithm, covariance matrix adaptation evolution strategy, particle swarm optimisation, trust-region framework, Nelder-Mead simplex algorithm, interpolated Quasi-Newton, and classic Powell. …”
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