Analysis of clinical nurse educators’ mentoring feedback on new nurse journals at a tertiary hospital in South Korea: utilizing text network analysis by Shinhye Ahn, Hye Won Jeong

“…Results The keyword “attitude” had the highest frequency (726), emphasizing the clinical importance of fostering positive attitudes among new nurses. The keyword network had average centrality measures of degree (.15), closeness (.43), and betweenness (.05). …”
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Melt Density Monitoring of Extruder Extrusion Process Based on Multi-source Data Fusion and Convolutional Long Short-term Memory Neural Network by Binbin ZHANG, Zhuyun CHEN, Fei ZHANG, Gang JIN

“…Conclusions The proposed approach facilitates accurate and timely monitoring of melt density during polymer extrusion and represents a significant advancement in polymer processing monitoring by harnessing the power of multi-source data fusion and advanced neural network techniques. This enables manufacturers to make informed decisions in real time, enhancing product consistency, minimizing defects, and optimizing process parameters for improved productivity and cost-effectiveness.…”
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Ecofriendly Extraction of Polyphenols from <i>Ampelopsis grossedentata</i> Leaves Coupled with Response Surface Methodology and Artificial Neural Network–Genetic Algorithm by Xubo Huang, Chen Li, Yanbin Wang, Jinrong Jiang, Weizhi Wu, Shifeng Wang, Ming Lin, Liang He

“…This study aimed to optimize a novel deep eutectic solvents (DESs)-assisted extraction process for polyphenols in the leaves of <i>Ampelopsis grossedentata</i> (AGPL) with response surface methodology (RSM) and a genetic algorithm–artificial neural network (GA-ANN). …”
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Deep learning and wavelet packet transform for fault diagnosis in double circuit transmission lines by Ziad M. Ali, Ehab M. Esmail

“…Compared with other hybrid approaches integrating WPT with artificial neural networks (ANNs) and adaptive-network-based fuzzy inference systems (ANFIS), the proposed method achieves superior precision, with an average error of only 0.03%. …”
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Minimizing Delay and Power Consumption at the Edge by Erol Gelenbe

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Reduction of Energy Consumption in Mobile Cloud Computing by ‎Classification of Demands and Executing in Different Data Centers by H. Yeganeh, A. Salahi, M. A Pourmina

“…We derived a penalty function for cost and then by using Lyapunov optimization theorem; we designed an algorithm to minimize the average cost of energy consumption based on the online information in MCC. …”
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Prediction of Urban Construction Land Carbon Effects (UCLCE) Using BP Neural Network Model: A Case Study of Changxing, Zhejiang Province, China by Qinghua Liao, Xiaoping Zhang, Zixuan Cui, Xunxi Yin

“…The results demonstrate that the BP neural network model effectively predicts the different types of UCLCE, with an average error rate of 30.10%. (1) The total effect and intensity effect exhibit different trends in the study area, and a carbon effect table for different types of UCL is established. (2) The spatial distribution characteristics of UCLCE reveal a distinct reverse-L pattern (“┙”-shaped layout) with positive spatial correlation (Moran’s I = 0.11, <i>p</i> < 0.001). (3) The model’s core practical value lies in enabling forward-looking assessment of carbon effects in urban planning schemes and precise quantification of emissions reduction benefits. …”
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Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles by Wangbin Luo, Xiang Wang, Fang Han, Zhiguo Zhou, Junyu Cai, Lin Zeng, Hong Chen, Jiawei Chen, Xuehua Zhou

“…In response to the above problems, this paper proposes a long and short memory network-proximal strategy optimization (LSTM-PPO) intelligent obstacle avoidance algorithm for non-particle models in non-ideal environments, and designs a corresponding deep reinforcement learning training environment. …”
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The Modeling and Application of Dynamic Lane Assignment in Urban Areas: A Case Study of Vukovar Street in Zagreb, Croatia by Miroslav Vujić, Luka Dedić, Mijo Majstorović

“…Traffic congestion in urban areas presents significant challenges to mobility, road safety, and the overall quality of the urban traffic network. This study presents a simulation-based modeling framework for dynamic lane assignment (DLA) systems designed to optimize traffic flow on Vukovar Street in Zagreb, Croatia, which is an urban corridor where the existing infrastructure fails to meet capacity demands during peak morning and afternoon hours. …”
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Vehicle routing problem in waste collection: a case study in Son Tra, Da Nang by Le Hoang Son, Truong Nguyen Song Ha, Nguyen Ngoc Phuong, Phan Bao An

“…This study investigates the application of network analysis to optimize solid waste collection routes in Son Tra District, Da Nang City. …”
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DCOOL: Dynamic computation offloading and resource allocation for LEO satellite-assisted edge computing in a ground-space integrated framework by Jeonghwan Kim, Jeongho Kwak

“…To this end, this paper introduces a dynamic computation offloading and resource allocation framework in the LEO satellite MEC architecture. Using Lyapunov optimization, we propose an efficient DCOOL algorithm to minimize average power consumption and propagation delay constrained by queue stability. …”
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Enhancing drought prediction through machine learning: advanced techniques combining phenotypic and agrometeorological data by Efrem Yohannes Obsie, Yongguo Liu

“…The experimental results showed that the proposed GOA-optimized RF model achieved an average accuracy of 98.75 %, outperforming the unimodal model by 5.75 %. …”
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SB‐YOLO‐V8: A Multilayered Deep Learning Approach for Real‐Time Human Detection by Prince Alvin Kwabena Ansah, Justice Kwame Appati, Ebenezer Owusu, Edward Kwadwo Boahen, Prince Boakye‐Sekyerehene, Abdullai Dwumfour

“…To address this issue, we propose SB‐YOLO‐V8 (Scene‐Based—You Only Look Once—Version 8), an optimized YOLO‐based convolutional neural network (CNN) designed specifically for real‐time human detection, not just limited to citrus farms but applicable to various agricultural and urban environments. …”
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Energy efficient inter-cluster multi-hop communication routing protocol for wireless sensor network based on centralized energy efficient clustering routing protocol by Makda Fekadie Tewelgne, Samuel Asferaw Demilew, Dagne Walle Girmaw

“…To minimize power consumption and maximize network lifetimes, this study integrates Multi-Hop communication into the Centralized Energy Efficient Clustering Routing Protocol to determine the optimal path for inter-cluster multi-hop communication between a source (cluster head) and a destination (base station). …”
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A Novel Traffic Scheduling Algorithm for Multi-CQF Using Mixed Integer Programming and Variable Neighborhood Search Genetic Algorithm in Time-Sensitive Networking by Cheng Wang, Zhiquan Lin, Yuhao Zhao, Fen Hu, Zhan Huan

“…Comparing with other existing schemes, computer simulation reveals that MIP reduces delay by approximately 13% on average in small-traffic TSN networks, while the VNS-GA achieves an average delay reduction of 7% in large-traffic ones.…”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
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Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images by Jietao Chen, Weijie Chen, Qianjian Xing, Feng Yu

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Improving TerraClimate hydroclimatic data accuracy with XGBoost for regions with sparse gauge networks: A case study of the Meknes plateau and the Middle Atlas Causse, Morocco by Hammoud Yassine, Allali Youssef, Saadane Abderrahim

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Perbandingan Arsitektur Convolutional Neural Network Pada Klasifikasi Pneumonia, COVID-19, Lung Opacity, dan Normal Menggunakan Citra Sinar-X Thoraks by Agung Wahyu Setiawan

“…The highest performance was obtained using ResNet50v1 and Adam optimizer with the average value of training, validation, and testing accuracy of 92.22 ± 0.25 %. …”
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Predictive and Explainable Artificial Intelligence for Weight Loss After Sleeve Gastrectomy: Insights from Wide and Deep Learning with Medical Image and Non-Image Data by Jaechan Park, Sungsoo Park, Kwang-Sig Lee, Yeongkeun Kwon

“…Here, the WAD model combined a convolutional neural network (CNN) for image data and a linear layer for non-image data (EMR). …”
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