Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…In terms of intelligent control, deep reinforcement learning is used to optimize irrigation decision-making, and adaptive algorithms are combined to improve the flexibility of agricultural equipment scheduling. …”
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Low power IoT device communication through hybrid AES-RSA encryption in MRA mode by Qiang Chang, Tianqi Ma, Wenzhong Yang

“…The improved AES algorithm transitions from a single-threaded encryption and decryption process to a three-threaded design, reducing the ten-round operation to seven rounds to enhance both speed and energy efficiency. …”
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Inverse Kinematics of a 7-Degree-of-Freedom Robotic Arm Based on Deep Reinforcement Learning and Damped Least Squares by Shusheng Yu, Gongquan Tan

“…In this paper, we propose a novel solution to the inverse kinematics problem by combining Proximal Policy Optimization (PPO) with the Damped Least Squares (DLS) method, forming the Multistep PPO-DLS Inverse Kinematics (MPDIK) algorithm. …”
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Numerical Investigation on Influential Factors for Quality of Smooth Blasting in Rock Tunnels by Baoping Zou, Zhipeng Xu, Jianxiu Wang, Zhanyou Luo, Lisheng Hu

“…As prerequisite for the evaluation of the blasting quality, effective identification of the influential factors affecting smooth blasting usually plays a significant role in the improvement of smooth blasting design. Compared to the expensive and time-consuming experiments including physical modelling and field tests, numerical modelling, as a cost-efficient approach, offers an attractive alternative to investigate the influential factors in terms of weight, which might be more applicable and reliable for the optimization of smooth blasting parameters. …”
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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…Experimental results comparing three variants of the Predictive Torque Control (one vector, three vector and modulated) show improvements in torque and flux ripple and improvements of current THD up to 30% over classic Modulated Predictive Torque Control implementation with reduced or similar computational cost. …”
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A lightweight lattice-based group signcryption authentication scheme for Internet of things by XU Chuan, AI Xinghao, WANG Shanshan, ZHAO Guofeng, HAN Zhenzhen

“…In the key generation stage, the improved trapdoor diagonal matrix was designed to optimize the original image sampling algorithm required for key generation and reduce the overall time required for generating a large number of keys. …”
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Two-stage resilience enhancement method for integrated electricity-gas systems through linepack and mobile compressors by Chao Qin, Yongxue Wang, Shuaihu Ye

“…The progressive hedging algorithm is employed to further improve the solution efficiency. …”
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Robust fuzzy dynamic integrated environmental-economic-social scheduling considering demand response and user’s satisfaction with electricity under multiple uncertainties by Hong Zhang, Qianwei Xi, Lei Chen, Yong Min, Xiongxiong Fan, Wenjin Fang, Nan Tian, Fei Xu

“…Taking the lowest comprehensive operation cost as the economic objective, the smallest emissions of CO2 and atmospheric pollutants as environmental objective and the largest user’s comprehensive satisfaction with electricity as the social objective, based on the robust fuzzy theory, the multi-objective uncertainty optimal scheduling model is constructed, which is transformed into deterministic model and then solved by intelligent optimization algorithm. …”
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Comprehensive Evaluation and Trade‐Off of Top‐Level Requirements for BWB UAVs by Xinshi Suo, Zhouwei Fan, Yundong Guo, Tengzhou Xu

“…The optimal design improves the competitiveness of the top‐level requirements by 46.8% compared to the baseline design, validating the feasibility of the proposed method.…”
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Shoulder–Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration by Siyu Zong, Wei Li, Dawen Sun, Zhuoda Jia, Zhengwei Yue

“…To address the precision challenges in upper-limb joint motion prediction, this study proposes a novel artificial neural network (COANN) enhanced by the Cheetah Optimization Algorithm (COA). The model integrates surface electromyography (sEMG) signals with joint angle data through multi-source information fusion, effectively resolving the local optima issue in neural network training and improving the accuracy limitations of single sEMG predictions. …”
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Fingerprint Classification Based on Multilayer Extreme Learning Machines by Axel Quinteros, David Zabala-Blanco

“…In this study, we introduce, for the first time, the use of a multilayer extreme learning machine (M-ELM) for fingerprint classification, aiming to improve training efficiency. A comparative analysis is conducted with CNNs and unbalanced extreme learning machines (W-ELMs), as these represent the most influential methodologies in the literature. …”
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Multimodal Control by Variable-Structure Neural Network Modeling for Coagulant Dosing in Water Purification Process by Jun Zhang, Da-Yong Luo

“…In this paper, combined with rule base, through the PCA method, an improved multimodal variable-structure random-vector neural network algorithm (MM-P-VSRVNN) is proposed for coagulant dosing, which is a key production process in water purification process. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…The model incorporates a neuron model with internal dynamics, including adaptive thresholds and inter-neuron feedback, into the reservoir structure. A Bayesian Optimization algorithm was employed for the selection of hyperparameters. …”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…These findings, supported by the FLOW-AF trial, underscore the usefulness of clinical outcome-based machine learning to improve the efficacy of algorithm based medical diagnostics.…”
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Unsupervised fake news detection on social media using hybrid Gaussian Mixture Model. by Sajida Perveen, Muhammad Shahbaz, Sami S Albouq, Khlood Shinan, Hanan E Alhazmi, Fatmah Alanazi, M Usman Ashraf, Rehan Ashraf

“…In particular, it also proposes a novel hybrid method that leverages the Gaussian Mixture Model (GMM) in conjunction with the Group Counseling Optimizer (GCO), a metaheuristic optimization algorithm, to identify the optimal number of clusters for the detection of fake news. …”
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HUMAN-ORIENTED QUALITY MANAGEMENT SYSTEM OF ENTERPRISE: CONTROL OF NON-CONFORMING PRODUCT AND UTILIZATION by Vyacheslav Feoktistovich Bezyazychny, Maria Evgenyevna Ilyina

“…The presented model algorithm reflects all possible action variants directed on the improvement and the most effective use of non-conforming product. …”
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PRIMARY CARE: HOW TO INCREASE PHYSICAL ACTIVITY IN YOUR PATIENTS by A. L. Slobodyanyuk, I. A. Кrylova, V. I. Kupaev

“…Increasing the reserves of the cardiorespiratory system of the body, physical activity improves the quality of life of patients and reduces the cost of medical care.To effectively combat sedentary lifestyle, it is necessary to adequately motivate patients that can be achieved through routine counseling to enhance physical activity. …”
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Advanced Load Balancing Based on Network Flow Approach in LTE-A Heterogeneous Network by Shucong Jia, Wenyu Li, Xiang Zhang, Yu Liu, Xinyu Gu

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Radioembolization for neuroendocrine tumors: procedure, application and clinical outcomes by Li Shen Ho, Tarik Baetens, Marnix G E H Lam, Arthur J A T Braat

“…Patient management should be tailored on an individual level to optimize outcomes. The incidence of complications is rare (<1%), with radiation-induced liver disease being the most concerning. …”
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