Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network by Zhichao ZHOU, Yi FENG, Xiaohan XIA, Yuyao FENG, Chao CAI, Jiahui QIU, Lihui YANG, Yunxiao WU

“…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes. by Alireza Naghizadeh, Wei-Chung Tsao, Jong Hyun Cho, Hongye Xu, Mohab Mohamed, Dali Li, Wei Xiong, Dimitri Metaxas, Carlos A Ramos, Dongfang Liu

“…Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. …”
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A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing by Jia Zhao, Yan Ding, Gaochao Xu, Liang Hu, Yushuang Dong, Xiaodong Fu

“…We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). …”
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Design and Implementation of Hybrid GA-PSO-Based Harmonic Mitigation Technique for Modified Packed U-Cell Inverters by Hasan Iqbal, Arif Sarwat

“…This paper proposes a hybrid version of the GA-PSO algorithm that exploits the exploratory strengths of GA and the convergence efficiencies of PSO in determining the optimized switching angles for SHM techniques applied to modified five-level and seven-level PUC inverters. …”
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Calculation Methods for the Permeability Coefficient of Concrete Face Rockfill Dam with Cracks by Zhongwen Shi, Zhongru Wu, Chongshi Gu, Bo Chen, Hailong Zhang, Wenzhong Yin, Bangbin Wu

“…This calculation helped simplify the establishment of a finite element model and improve the efficiency of calculating the seepage of dams. …”
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Torsional Stiffness Correction of the Split-Type Triple-Box Steel Box Girder Based on Refined Simulation by Yu Tang, Min Xu, Jie Yue, Shixiong Zheng

“…Then, the beam element is used for conventional modelling of the bridge, and artificial bee colony (ABC) algorithm is adopted for the optimization and correction of structure parameters of the BEM of the girder. …”
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Local pattern aware 3D video swin transformer with masked autoencoding for realtime augmented reality gesture interaction by Suli Wang

“…During data preprocessing, the study uses a synthetic data annotation method to automatically generate 3D gesture images and annotate joint information, significantly improving data annotation efficiency. Using weighted Euclidean distance and structural similarity optimization, the paper proposes an image denoising model based on maximum a posteriori probability that effectively reduces noise interference in gesture image analysis. …”
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Perception Error-resistant Air Combat Maneuvering Decisions Based on Deep Reinforcement Learning by Chengbin TIAN, Hui LI, Xiliang CHEN, Fengguo WU

“…In response to this issue, an algorithm based on Proximal Policy Optimization (PPO) is proposed using features extracted by a Gated Recurrent Unit (GRU). …”
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Few-Shot Intelligent Anti-Jamming Access with Fast Convergence: A GAN-Enhanced Deep Reinforcement Learning Approach by Tianxiao Wang, Yingtao Niu, Zhanyang Zhou

“…Under dynamic jamming and intelligent jamming, the algorithm significantly outperforms the DQN, Proximal Policy Optimization (PPO), and Q-learning (QL) algorithms.…”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…This study proposes a stroke risk classification model using ensemble learning that combines Random Forest and XGBoost algorithms. …”
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A Two-Stage Site Selection and Capacity Determination Method for Energy Storage Power Stations Based on HC-MOPSO by Wangwang BAI, Dezhou YANG, Wanwei LI, Tao WANG, Yaozhong ZHANG

“…The MOPSO algorithm embedded in power flow calculation is designed to solve the model. …”
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Multivariate Load Forecasting of Integrated Energy System Based on CEEMDAN-CSO-LSTM-MTL by WANG Yongli, LIU Zeqiang, DONG Huanran, LI Dexin, CHEN Xin, GUO Lu, WANG Jiarui

“…Based on this，a comprehensive energy system short-term load forecasting model is proposed，which combines complete ensemble empirical mode decomposition with adaptive noise （CEEMDAN），cross optimization algorithm （CSO），long short term memory （LSTM） network，and multi task learning （MTL）. …”
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Design and Implementation of Local Threshold Segmentation Based on FPGA by Shangshang Gao, Yuanyuan Wang, Zhaofeng Chen, Feng Zhou, Rugang Wang, Naihong Guo

“…Finally, the design algorithm is verified by ModelSim simulation software and QT5 software. …”
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Enhancing Consumer Decision-Making in Skincare: Implementation of the VIKOR Method for Product Recommendation Systems by Diah Arifah Prastiningtyas, Greta Septy Purwiantono, Febry Eka Purwiantono, Addin Aditya

“…By demonstrating the efficacy of the VIKOR method, this research paves the way for its future application in various industries, offering a replicable and adaptable model for improving decision processes in consumer goods selection across diverse markets. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Enhancing data quality, refining feature selection, and using advanced modeling techniques are crucial for improving predictive capabilities. …”
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Multiple Interface Parallel Approach of Bioinspired Routing Protocol for Mobile Ad Hoc Networks by L. J. García Villalba, D. Rupérez Cañas, A. L. Sandoval Orozco, T.-H. Kim

“…The simulation results indicate that PAntOR and PAntOR-MI improve performances of AntOR, whilst it is also noticed that PAntOR-MI is the most suitable for highly dynamic environments.…”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…Traditional deep learning (DL) models and decision tree (DT)-based algorithms have been widely employed for this purpose. …”
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Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. …”
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Short-Term Traffic Flow Prediction: A Method of Combined Deep Learnings by Chuanxiang Ren, Chunxu Chai, Changchang Yin, Haowei Ji, Xuezhen Cheng, Ge Gao, Heng Zhang

“…Then, the neuron number, loss function, optimization algorithm, and other parameters of the CDLP model are discussed and set through experiments. …”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…The algorithm innovatively designs three core modules: the AdaptiveVision Network (AVN) backbone for enhanced feature extraction, the Dual-Domain Enhanced Transformer (DDET) module for spatiotemporal-frequency domain collaboration, and the Adaptive Multi-scale Feature Model (AMFM) for improved feature fusion. …”
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