An Efficient and Fast Model Reduced Kernel KNN for Human Activity Recognition by Zongying Liu, Shaoxi Li, Jiangling Hao, Jingfeng Hu, Mingyang Pan

“…Many classic machine learning algorithms, such as artificial neural network, feed forward neural network, K-nearest neighbors, and support vector machine, achieve good performance for detecting human activity. …”
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Random features and polynomial rules by Fabián Aguirre-López, Silvio Franz, Mauro Pastore

“…Random features models play a distinguished role in the theory of deep learning, describing the behavior of neural networks close to their infinite-width limit. In this work, we present a thorough analysis of the generalization performance of random features models for generic supervised learning problems with Gaussian data. …”
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Non-intrusive load monitoring based on time-enhanced multidimensional feature visualization by Tie Chen, Yimin Yuan, Jiaqi Gao, Shinan Guo, Pingping Yang

“…By adding a time axis to the V–I trajectory, it integrates the rate of change in voltage and current, power factor, and third harmonic to form a three-dimensional spatiotemporal color V–I trajectory, addressing the gap in dynamic characteristics. The ECA-ResNet34 network model is used for load identification, avoiding the problems of network degradation and training difficulties caused by the excessive depth of traditional convolutional neural networks (CNN), and achieving efficient monitoring of household loads. …”
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Estimation of the structural changes of employment at the regional labour markets by N.V.

“…Problems of structural changes in the sphere of employment at the regional level in the context of innovative changes require detailed research and become especially relevant, because especially the growth of the educational level of the population of the regions provides opportunities for the realization of their educational potential. …”
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Calculation and Analysis of Specific Losses of Active Power in Overhead Power Lines due to Corona in View of Climatic Data by D. A. Sekatski, N. A. Papkova

“…In the USSR (Union of Soviet Socialist Republics), based on field tests and experimental data, recommendations were developed for accounting for losses of electric energy due to corona and interference in overhead lines, the average values of which were given in the relevant instruction for the regulation and justification of the norm of electricity consumption for its transmission over electric networks. …”
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Advanced Assessment of Oxidative Stress and Inflammation in Military Personnel: Development of a Novel IIRPM Score Using Artificial Intelligence by Florina-Diana Mihai, Emil-Tiberius Trasca, Patricia-Mihaela Radulescu, Razvan Mercut, Elena-Irina Caluianu, Eleonora Daniela Ciupeanu-Calugaru, Dan Marian Calafeteanu, Georgiana-Andreea Marinescu, Suzana Danoiu, Dumitru Radulescu

“…Extended exposure to extreme conditions can cause oxidative stress and systemic inflammation, potentially affecting performance. To address this problem, we developed an innovative diagnostic tool, the Post-Mission Integrated Risk Index (IIRPM), which integrates hematologic markers with key clinical variables. …”
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Understanding the ancient classic and famous prescriptions via the property of Chinese materia medica by Dan Qin, Dan Qin, He Zhang, Bin Du, Hui Wang, Ligang Liu, Yun Wang

“…We formulated the backward process as a constrained combinatorial optimization problem to rebuild ACFPs from their PCCMMs. We evaluated the performance of PCCMM in reconstructing ACFPs using the Jaccard similarity coefficient. …”
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Multi-label semantic segmentation of magnetic resonance images of the prostate gland by Mark Locherer, Christopher Bonenberger, Wolfgang Ertel, Boris Hadaschik, Kristina Stumm, Markus Schneider, Jan Philipp Radtke

“…Especially freely available labeled prostate magnetic resonance imaging data is rare. With regard to this problem, we show a method to combine two existing small datasets to form a bigger one. …”
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Active Compliance Control System for Intelligent Inspection Robot in Power Room by Ning Guan, Pei Zhang

“…In order to solve the problems of blind spot and time-consuming and laborious monitoring in manual inspection of power information and communication rooms, a kind of active compliant control system for intelligent inspection robots of power information and communication rooms is proposed. …”
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Scheduling framework based on reinforcement learning in online-offline colocated cloud environment by Ling MA, Qiliang FAN, Ting XU, Guanchen GUO, Shenglin ZHANG, Yongqian SUN, Yuzhi ZHANG

“…Some reinforcement learning-based scheduling algorithms for cloud computing platforms barely considered one scenario or ignored the resource constraints of jobs and treated all machines as the same type, which caused low resource utilization or insufficient scheduling efficiency.To address the scheduling problems in online-offline colocated cloud environment, a framework named JobFusion was proposed.Firstly, an efficient resource partitioning scheme was built in the cloud computing platform supporting virtualization technology by integrating the hierarchical clustering method with connectivity constraints.Secondly, a graph convolutional neural network was utilized to embed the attributes of elastic dimension with various constraints and the jobs with various numbers, to capture the critical path information of workflow.Finally, existing high-performance reinforcement learning methods were integrated for scheduling jobs.According to the results of evaluation experiments, JobFusion improves the resource utilization by 39.86% and reduces the average job completion time by up to 64.36% compared with baselines.…”
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Research and Application of a Multitarget Detection Algorithm Based on Improved YOLOv8 for Indoor Objects by Yanzhen Wang, Wei Wang, Xiaolong Zhou, Xubin Dong, Jianyong Li, Qi Zhao, Xinyu Yang, Yao Wang

“…First, the GAM global attention mechanism is embedded in the backbone network of YOLOv8 to improve the sensitivity of the backbone network to the important feature information and reduce the attention to the irrelevant features, and it is determined that the GAM global attention mechanism will be embedded in the backbone network of YOLOv8 after comparing and analyzing the GAM with the attention mechanisms of CBAM, SE, and ECA; second, at the neck layer, the original PAN-FPN network structure is replaced with the BiFPN structure at the neck layer to realize bidirectional cross-scale connectivity and weighted feature fusion. …”
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Voice recognition enhancement by genetic algorithm by Mohamed Salah Salhi, Ali Hamdan Alenezi

“…The results show that the proposed approach achieves an average recognition rate of over 95 %.…”
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RFCS-YOLO: Target Detection Algorithm in Adverse Weather Conditions via Receptive Field Enhancement and Cross-Scale Fusion by Gang Liu, Yingzheng Huang, Shuguang Yan, Enxiang Hou

“…It addresses challenges like complex backgrounds and problems of missing and mis-detecting traffic targets in bad weather. …”
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Underground personnel recognition based on low-light enhancement of infrared and visible light image fusion by NAN Jingjing, PAN Hongguang, JIANG Ze, ZHANG Libin, ZHANG Huipeng

“…Finally, texture-contrast enhancement networks performed feature-level fusion, enhancing overall visual perception in terms of texture and contrast. …”
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Research and Experiment on a Chickweed Identification Model Based on Improved YOLOv5s by Hong Yu, Jie Zhao, Xiaobo Xi, Yongbo Li, Ying Zhao

“…Currently, multi-layer deep convolutional networks are mostly used for field weed recognition to extract and identify target features. …”
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Research on Breast Cancer Detection Methods Based on ODMV-MulDyHead-YOLO by Yanhong Zhang, Pei Li, Yihua Lan, Xiao Jia, Yingjie Lv

“…Second, a lightweight backbone network, MobileNetV2-ODConv, is used to improve the ability of the network to extract features of lumps in breast X-ray images while reducing the number of parameters and floating-point operations. …”
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Renewable Energy Consumption Strategies for Electric Vehicle Aggregators Based on a Two-Layer Game by Xiu Ji, Mingge Li, Zheyu Yue, Haifeng Zhang, Yizhu Wang

“…For the complexity of large-scale scheduling, this paper introduces the A2C (Advantage Actor-Critic) reinforcement learning algorithm, which combines the value network and the strategy network synergistically to optimize the real-time scheduling process. …”
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Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture by Zheng Huang, Xiuhua Zhang, Hongsen Wang, Huajie Wei, Yi Zhang, Guihong Zhou

“…Aiming at the problems of low precision, slow speed and difficult detection of small target pear fruit in a real environment, this paper designs a pear fruit detection model in a natural environment based on a lightweight Transformer architecture based on the RT-DETR model. …”
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Detect material volume by fusing heterogeneous camera target detection and depth estimation information by Wei Tian, Xuecong Cheng, Yipeng Zhang, Huazhi Lin

“…Experiments show that the average accuracy of this method is 92.9%.…”
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Wearable IoT (w-IoT) artificial intelligence (AI) solution for sustainable smart-healthcare by Gurdeep Singh

“…This study will cover all stages of design science methodology, guidelines for w-IoT healthcare solution development, by presenting experimental prototype towards pipeline implementation to address healthcare needs, alleviating previously prevalent Body Area Networks (BANs) solutions precision with advancing w-IoT smart technologies or Wireless Body Sensor Networks (WBSNs).…”
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