A narrative review of surgical approaches in cervical degenerative myelopathy and update of the algorithm for decision making by Majid Reza Farrokhi, Seyed Reza Mousavi, Abbas Khosravifarsani, Jaloliddin Mavlonov, Mohammadhadi Amir Shahpari Motlagh, Seyed Bahram Seif, Armin Akbarzadeh

“…Personalized surgical planning is essential to optimize outcomes in CDM management.…”
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Review of Icing Prediction Model and Algorithm for Overhead Transmission Lines Considering Time Cumulative Effects by Chuanqi WANG, Liwen WU, Zhibin DENG, Weifeng DENG, Bin YANG

“…Secondly, the combination and intercrossing mode of support vector machine, hybrid swarm intelligence optimization algorithm, genetic algorithm in the model focus on the identification and modeling of icing process. …”
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A Novel Energy Replenishment Algorithm to Increase the Network Performance of Rechargeable Wireless Sensor Networks by Tariq, Vishwanath Eswarakrishnan, Adil Hussain, Zhu Wei, Muhammad Uzair

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BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…Second, we incorporated a Bidirectional Feature Pyramid Network (BiFPN) on top of the FPN + PAN structure to optimize feature fusion and improve the extraction of small disease regions, thereby enhancing the detection accuracy for small lesion targets. …”
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Novel Node Localization Algorithm Based on Nonlinear Weighting Least Square for Wireless Sensor Networks by Fu Xiao, Mingtan Wu, Haiping Huang, Ruchuan Wang, Sudan Wang

“…This paper presents a new method for wireless sensor network node positioning based on nonlinear weighting least-square algorithm. Regarding ranging equation error-weighted sum as a whole, this method starts with the initial iteration point of stepwise refinement to explore the optimal solution and further reduces the positioning computational complexity by the simplification of the Taylor equation. …”
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A Novel Two-Stage Learning-Based Phase Unwrapping Algorithm via Multimodel Fusion by Chao Yan, Tao Li, Yandong Gao, Shijin Li, Xiang Zhang, Xuefei Zhang, Di Zhang, Huiqin Liu

“…To solve this problem, this paper combines a deep neural network model with the traditional PhU model and proposes a novel two-stage learning-based phase unwrapping (TLPU) algorithm via multimodel fusion. The major advantages of TLPU are as follows: 1) A high-resolution U-Net (HRU-Net) model trained on a dataset constructed according to InSAR interferometric geometry is utilized for the PhU for the first time, which effectively improves the performance of the DLPU. 2) TLPU utilizes the traditional PhU method to optimize the results of DLPU, addressing the issue of weak generalization ability of a single DLPU, while improving accuracy in areas with large-gradient changes. …”
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Frequency minimum inertia calculation of complex power systems based on an improved simulated annealing algorithm by Qiang Zhang, Qi Jia, Tingqi Zhang, Hui Zeng, Chao Wang, Wansong Liu

“…In order to enhance the inertia situational awareness and stability of the power system in the context of the reduction of power system inertia and the challenge of frequency stability due to the high proportion of new energy access, the background and purpose of the study are stated in the introduction; methodologically, based on the frequency response model of the power system, we analyze the time and magnitude of the maximum frequency offset, clarify the factors affecting the frequency stability and construct the mathematical relationship, and then build a model for assessing the minimum inertia of the power system taking into account the virtual inertia of the new energy source. Then, based on the whole process of frequency response, we construct a power system minimum inertia assessment model taking into account the virtual inertia of new energy sources, and introduce an improved simulated annealing algorithm to solve the problem; the results validate the accuracy of the method through the IEEE-14 node model; the discussion section points out that this method provides a feasible solution for the inertia situational awareness of power system, which is helpful for the optimization of the operation, and also proposes that in the future we can take into account more uncertainties to improve the model and algorithm and to enhance the practicability and adaptability of this method. …”
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Vertical Handover Decision Algorithm Using Ants’ Colonies for 4G Heterogeneous Wireless Networks by Imad El Fachtali, Rachid Saadane, Mohammed ElKoutbi

“…The concept is based on QoS aware ant colony built on the vertical handoff mechanism that uses an updated version of ants’ colony optimization decision algorithm (ACOR), the dynamic and static factors such as RSS, the cost of service, bandwidth, the velocity of MT, the power consumption and security, and the module for predicting the traveling distance within an IEEE 802.11 WLAN cell. …”
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Research on the Construction of Crossborder e-Commerce Logistics Service System Based on Machine Learning Algorithms by Jinbo Xu, Shibiao Mu

“…Second, we design a simple calculation example, use Python programming through a simulated shopping environment, give the solution process of the optimal recommendation strategy in the whole process, and prove the feasibility of the algorithm. …”
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Impact of an improved random forest-based financial management model on the effectiveness of corporate sustainability decisions by Jianhui Zhang

“…With the development of the economy, more and more electronic manufacturing enterprises are emerging like mushrooms after rain. These enterprises, while developing, also face financial risks caused by various reasons. …”
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Real‐Time Parameter Identification and State of Charge Estimation of Electric Vehicle Batteries by A. Maheshwari, S. Nageswari, R. Palanisamy, B. Karthikeyan, Mohamed Metwally Mahmoud, Daniel Eutyche Mbadjoun Wapet, Ali M. El‐Rifaie, Ezzeddine Touti, Ahmed I. Omar

“…The fixed forgetting factor RLS (FFRLS) algorithm is implemented with two different forgetting factor (FF) values, while the VFFRLS method utilizes different initial FF values. …”
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DECISION TREE WITH HILL CLIMBING ALGORITHM BASED SPECTRUM HOLE DETECTION IN COGNITIVE RADIO NETWORK by N Suganthi, R Meenakshi, A Sairam, M Parvathi

“…The objective of the DTHC method is to improve detection accuracy while minimizing false alarm rates. The approach integrates a Decision Tree (DT) algorithm for rapid initial classification of Primary User (PU) activity, followed by a Hill Climbing (HC) optimization algorithm that fine-tunes the detection based on a fitness function. …”
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Training multi-layer binary neural networks with random local binary error signals by Luca Colombo, Fabrizio Pittorino, Manuel Roveri

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Minimizing Delay in UAV-Aided Federated Learning for IoT Applications With Straggling Devices by Mudassar Liaq, Waleed Ejaz

“…We formulate an optimization problem to minimize system delay, considering UAV-MEC’s computation power, computation and communication power of IoT devices, and quality of service constraints. …”
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Sum Rate Maximization of Active RIS-Assisted FD-NOMA Systems by Yi Peng, Yang Xiao, Qingqing Yang

“…To address this problem, we propose an alternating optimization algorithm that combines semi-definite relaxation (SDR) and successive convex approximation (SCA) methods. …”
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Solving the Problem of Vehicle Routing Problem With Time Window via Dual Adaptive Genetic Algorithm by Chunge Hua

“…To address the Vehicle Routing Problem with Time Windows (VRPTW), this paper presents a novel Dual Adaptive Genetic Algorithm (DAGA). While numerous metaheuristic algorithms have been proposed to solve VRPTW, most existing approaches either rely on fixed cost functions or incorporate local search heuristics without adaptive control. …”
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YOLOv8A-SD: A Segmentation-Detection Algorithm for Overlooking Scenes in Pig Farms by Yiran Liao, Yipeng Qiu, Bo Liu, Yibin Qin, Yuchao Wang, Zhijun Wu, Lijia Xu, Ao Feng

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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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A Hybrid Algorithm for PMLSM Force Ripple Suppression Based on Mechanism Model and Data Model by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…Experiments show that the hybrid framework effectively compensates the unmodeled disturbance through the data model while maintaining the physical interpretability of the mechanistic model, which provides a new idea for motor performance optimization under complex working conditions.…”
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Automated Design Method Based on Boosting Algorithms for Improving the Radiation Performance of Microstrip Antenna Arrays by Sina Hasibi Taheri, Ali Lalbakhsh, Amirhassan Zareanborji, Slawomir Koziel

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