Energy-efficiency maximization scheme for data collection in wireless power communication networks by Haijiang GE, Zhanwei YU, Kaikai CHI

“…WPCN composed of multiple RF energy sources and sinks was studied.The energy efficiency of data collection were maximized by jointly optimizing the transmission power of energy sources,the time allocation of wireless energy transfer and the time allocation of nodes’ data transmission.Specifically,the energy efficiency maximization problem was modeled firstly.Then,the optimal value of transmitted power was obtained,and the monotonicity of energy-efficiency function and the convexity of throughput function were further deduced.Finally,based on these properties,an efficient algorithm which combines golden-section search and bisection search was designed to get the optimal solution quickly.The simulation results show that the proposed optimal algorithm can significantly improve the energy efficiency compared with the baseline scheme.…”
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Verification of the method for classifying the technical state of a turboshaft engine fuel regulator in the space of operational process parameters under factory test conditions by Ihor Ohanian, Sergiy Yepifanov

“…Recommendations for further improvement of the method include using expert systems and developing effective model identification algorithms. …”
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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…The combination of the indole fragment, which demonstrates activity due to its aromatic structure, with the 1,2,4-triazole nucleus, which is characterised by chemical stability and the ability to form hydrogen bonds, creates a promising basis for the development of new therapeutic agents with improved properties. The active implementation of various modifications of indole and 1,2,4-triazole frameworks is aimed at optimizing the pharmacokinetic and pharmacodynamic characteristics of medicinal products. …”
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Re-Estimating GEDI Ground Elevation Using Deep Learning: Impacts on Canopy Height and Aboveground Biomass by Rei Mitsuhashi, Yoshito Sawada, Ken Tsutsui, Hidetake Hirayama, Tadashi Imai, Taishi Sumita, Koji Kajiwara, Yoshiaki Honda

“…Optimizing models for each region could further enhance accuracy. …”
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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Experimental results demonstrate that the proposed model can rapidly and accurately detect small infrared targets in bio-inspired compound eye image sequences, outperforming other comparative algorithms.…”
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A Novel Nonlinear Adaptive Control Method for Longitudinal Speed Control for Four-Independent-Wheel Autonomous Vehicles by Jinhua Zhang, Zhenghao Chen, Jinshi Yu

“…Based on the design of the upper controller, an innovative optimized longitudinal force distribution strategy and the construction of a tire reverse longitudinal slip model are proposed, followed by the design of a fuzzy PID controller as the lower slip ratio controller to achieve precise whole-vehicle longitudinal speed tracking and improve overall control performance. …”
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Advances in the application of nomograms for patients with gastric cancer associated with peritoneal metastasis by Shiyang Jin, Zeshen Wang, Qiancheng Wang, Zhenglong Li, Xirui Liu, Kuan Wang

“…For instance, Ji et al. constructed a nomogram integrating PCI, preoperative tumor markers, and peritoneal metastasis duration, achieving an area under the ROC curve (AUC) of 0.985 for overall survival prediction. Imaging-based models leverage CT radiomics and deep learning algorithms to detect occult PM, with Huang et al.’s deep learning model attaining an AUC of 0.900. …”
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Analyzing Method of the Absorption Capability of New Energy in Distribution Network with Consideration of Regional Self-discipline and Absorption Quality by Yan CHEN, Wei JIN, Wenbin WANG, Huibin LI, Shengfeng HAN, Kai JIA

“…Firstly, the strategy for implementing the self-discipline operation of the distribution network was unveiled, and the performance indices of self-discipline operation capability were created. Then, the optimal allocation model for the new energy absorption capability of the distribution network was constructed, and the operation behavior model of the distribution network satisfying self-discipline constraints was built based on energy storage, flexible load, and network reconstruction, and solved by the genetic algorithm. …”
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Mapping County-Level Rice Planting Areas by Joint Use of High-Resolution Optical and Time Series SAR Imagery by Jia Xu, Haojie Wang, Lin Qiu, Hui Wang, Yang Mu

“…Subsequently, the long short-term memory (LSTM)-based temporal classification model was utilized to acquire rice cultivation information at parcel scale using time-series Sentinel-1 SAR data. …”
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer’s disease by Jingyuan Liu, Xiaojie Yu, Hidenao Fukuyama, Toshiya Murai, Jinglong Wu, Qi Li, Zhilin Zhang

“…Addressing this obstacle is crucial for improving diagnostic accuracy and optimizing treatment strategies for those affected by AD. …”
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Secondary System Fault Detection Method Based on Association Rules and Reconstruction Error by Yang WANG, Weidong MA, Jiming LIU, Boshi WANG, Kai YAO, Wei HAN, Juan YU

“…Finally, the ensemble learning model is optimized to improve the accuracy of secondary equipment anomaly warning. …”
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Performance of M-QAM MIMO PNC Based on MRC and ZR Techniques by Alaa A. Yassin, Ebtihal H. G. Yousif, Rashid A. Saeed, Hashim Elshafie, Abdullah Alenizi, Hesham Alhumyani

“…Maximum Ratio Combining (MRC) and Zero-Forcing (ZF) for the receive/transmit diversity techniques are used at the relay node to reduce multi-user interference. The system model is based on denoise-and-forward (DNF) relaying along with the Latin Square (LS) mapping algorithm at the relay node and square M-ary Quadrature Amplitude Modulation (M-QAM) at all nodes. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…Thus, preserving features that carry the most relevant information at each scale is crucial for improving counting precision. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…This method centered on the initial meter gas production index and integrated multiple machine-learning algorithms. The results showed that: 1） The Beggs & Bill model and Gray model exhibited poor applicability for predicting the bottom-hole flowing pressure of deep CBM wells, while the single-phase gas model demonstrated reduced overall error as water production declined. …”
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Emergency evacuation planning in natural disasters under diverse population and fleet characteristics by Evangelia Baou, Vasilis P. Koutras, Vasileios Zeimpekis, Ioannis Minis

“…Design/methodology/approach – The problem is formulated using a mixed integer linear programming model and solved using a heuristic algorithm. The authors analyze the selected heuristic with respect to key parameters and use it to address theoretical and practical case studies. …”
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A novel hybrid nonlinear control of four switch buck-boost converter feeding constant power load in fuel cell-based DC microgrid by Hafiz Mian Muhammad Adil, Hassan Abbas Khan

“…Controller parameters are optimized using the slime mould algorithm, minimizing the integral time absolute error (ITAE) to address both transient and steady-state behavior. …”
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Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. …”
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Dynamic Pricing Strategy for Data Product Through Deep Reinforcement Learning by Junxin Shen, Yashi Wang, Fanghao Xiao

“…First, the dynamic pricing problem for data products is modeled as a Markov Decision Process (MDP). Then, a dynamic pricing algorithm based on the Deep Q-learning algorithm is designed, incorporating an annealing mechanism to optimize the exploration strategy. …”
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A Review of Research on Flight Delay Propagation: Current Situation and Prospect by N. Li, H. G. Yao

“…At the same time, researchers also need to constantly explore and optimize algorithms to overcome their current limitations and further improve the reliability of predictions.…”
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Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…This paper proposes a hybrid control and monitoring framework designed to enhance turning operations by integrating artificial neural networks (ANNs) for predictive modeling and adaptive recalibration. The system leverages machine learning (ML) to improve machining efficiency, tool longevity, and energy consumption optimization. …”
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