Human activity recognition system based on low-cost IoT chip ESP32 by Chao HU, Bangyan LU, Yanbing YANG, Zhe CHEN, Lei ZHANG, Liangyin CHEN

“…Human activity recognition widely exists in applications such as sports management and activity classification.The current human activity recognition applications are mainly divided into three types: camera-based, wearable device-based, and Wi-Fi awareness-based.Among them, the camera-based human activity recognition application has the risk of privacy leakage, and the wearable device-based human activity recognition application has problems such as short battery life and poor accuracy.Human activity recognition based on Wi-Fi sensing generally uses Wi-Fi network cards or software-defined radio devices to identify the rules of channel state information changes, so as to infer user activity.It does not have the problems of privacy leakage and short battery life.But Wi-Fi network cards need to rely on computers and software-defined radio platforms are expensive, which greatly limit the application scenarios of Wi-Fi sensing.Aiming at the above problems, a human activity recognition system based on the low-cost IoT chip ESP32 was proposed.Specifically, the Hampel filter and Gaussian filter were used to preprocess the channel state information obtained by ESP32.Then, the principal component analysis and discrete wavelet transform were utilized to reduce the dimension of the data.Finally, the K-nearest neighbor (KNN) algorithm was applied to classify data.The experimental results show that the system can achieve a recognition accuracy which close to the current mainstream Wi-Fi perception system (Intel 5300 network card) when only two ESP32 nodes are deployed, and the average accuracy rate for the six activities is 98.6%.…”
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Low illumination image enhancement algorithm of CycleGAN coal mine based on attention mechanism and Dilated convolution by Yuanbin WANG, Yaru GUO, Jia LIU, Xu WANG, Bingchao WU, Meng LIU

“…It is difficult to make paired low-light image data sets for model training. To solve these problems, a low illumination image enhancement algorithm based on CycleGAN is proposed. …”
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Prediction of Traffic Flow considering Electric Vehicle Market Share and Random Charging by Yunjuan Yan, Weixiong Zha, Jungang Shi, Liping Yan

“…This paper mainly studies the multiclass stochastic user equilibrium problem considering the market share of battery electric vehicles (BEVs) and random charging behavior (RCB) in a mixed transport network containing electric vehicles and gasoline vehicles (GVs). …”
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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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A combined data assimilation and deep learning approach for continuous spatio-temporal SWE reconstruction from sparse ground tracks by Matteo Guidicelli, Kristoffer Aalstad, Désirée Treichler, Nadine Salzmann

“…A feedforward neural network (FNN) is then used for spatial propagation of the daily mean and standard deviation of the updated SWE ensemble members obtained from the IES. …”
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Design and Performance Verification of Deep Learning-Based River Flood Prediction System Design and Digital Twin-Based Its Application by Heesang Eom, Younghun Kim, Jongho Paik

“…This paper presents a digital twin-based river management and flood prediction system designed for hydrological environments, including volcanic geology. To address the problems of rapid runoff and complex terrain, a deep learning-based hybrid model is proposed that integrates a Convolutional Neural Network (CNN) for spatial feature extraction and a Recurrent Neural Network (RNN) with Long Short-Term Memory (LSTM) units for temporal sequence modeling. …”
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UAV spatiotemporal crowdsourcing resource allocation based on deep reinforcement learning by Yaxi LIU, Xulong LI, Jiahao HUO, Wei HUANGFU

“…This approach aims to minimize the average AoI across the network while also reducing the energy consumption of IoT devices. …”
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Converting Hydraulic Resistance Energy of the System into Electricity by A. A. Sahakyan, D. A. Butko

“…In relation to such a system, the problems of converting the energy of local artificial hydraulic resistance into electricity are investigated.Materials and Methods. …”
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AS-Faster-RCNN: An Improved Object Detection Algorithm for Airport Scene Based on Faster R-CNN by Zhige He, Yuanqing He

“…To overcome these problems, we design an object detection method for airport scene named AS-Faster-RCNN. …”
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Research on Railway Passenger Volume Forecast Based on the Spline Interpolation and IPSO-Gradient Difference Acceleration Rule by Dingyuan Fan, Fei Yang, Jinghao Ji, Zexi Zhang

“…In comparison with the BP neural network, Holt exponential smoothing, simple averaging, and conventional redifference approaches, the IPSO-redifference acceleration method achieves a superior prediction performance, and the absolute values of the forecast error are reduced by 3.320%, 1.518%, 2.419%, and 0.602%.…”
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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

“…To address the above problems, this paper proposes a lightweight YOLOv8n-SOI algorithm for tire defect detection. …”
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Sticky Trap-Embedded Machine Vision for Tea Pest Monitoring: A Cross-Domain Transfer Learning Framework Addressing Few-Shot Small Target Detection by Kunhong Li, Yi Li, Xuan Wen, Jingsha Shi, Linsi Yang, Yuyang Xiao, Xiaosong Lu, Jiong Mu

“…With sufficient samples in the language character domain, transfer learning can effectively enhance the tiny and complex feature extraction capabilities of deep networks in the pest domain and mitigate the few-shot learning problem in tea pest detection. …”
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Three-Dimensional Human Model-Guided View Morphing for Clothed Gait Silhouettes by Mohamad Ammar Alsherfawi Aljazaerly, Chi Xu, Shuqiong Wu, Xiang Li, Yasushi Yagi

“…., the SMPL) to train the deformation estimation network to account for clothing and accessories in the final output. …”
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Prediction analysis and control strategies on coupling coordination between low-carbon transportation and high-quality economic development in the backward U-shaped bend metropolit... by Wang Wei, Mo Yuan-rui, Guan Lei, Gong Liang

“…The CCDs of these 15 cities have shown a growth trend, with the average CCD projected to reach the stage of barely coordinated development（0.554）by 2030. (3) Four key indicators，which include the share of non-fossil energy consumption, highway network density, air passenger traffic per 10,000 people and high-speed rail mileage per 10,000 people, have significant positive driving effects on the development of LCT. …”
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Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…This study employed the Informer model to forecast drought and conducted a comparative analysis with Autoregressive Integrated Moving Average (ARIMA), long short-term memory (LSTM), and Convolutional Neural Network (CNN) models. …”
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Multi-UAV path planning considering multiple energy consumptions via an improved bee foraging learning particle swarm optimization algorithm by Yuanhang Qi, Haoran Jiang, Gewen Huang, Liang Yang, Fujie Wang, Yunjian Xu

“…Abstract With the advancement of unmanned aerial vehicle (UAV) technology, UAVs, such as multi-rotor drones, have found widespread application in wireless sensor networks. In scenarios where multiple UAVs collaborate to gather sensor data from the field, it is essential to establish a path planning model that incorporates an accurate energy consumption model for these UAVs. …”
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Indicators of the psycho-emotional status of adolescents khakassia with different online behavior by L. S. Evert, N. Yu. Grishkevich, Yu. R. Kostyuchenko, S. A. Bakhshieva

“…Excessive use of the Internet in adolescents is often accompanied by a violation of their psychoemotional state, often in combination with other comorbid psychosomatic disorders and a high risk of their transformation into chronic types of pathology, which indicates the relevance of this problem. The purpose of the study is to conduct a comparative analysis of the features of psycho-emotional characteristics of teenagers in Khakassia with different online behavior. …”
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Economic burden of hepatitis B patients and its influencing factors in China: a systematic review by Mengxia Yan, Huanhuan Ye, Ying Chen, Huajie Jin, Han Zhong, Bobo Pan, Youqin Dai, Bin Wu

“…Abstract Background & aim Hepatitis B is globally recognized as a major public health problem that imposes a huge economic burden on society. …”
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Trends and spatial distribution of Human African Trypanosomiasis (HAT), Uganda, 2005 – 2015: A descriptive analysis of surveillance data by Susan Kizito, Charles W. Wamboga, Edridah Muheki Tukahebwa, Abbass Kakembo, Lilian Bulage, Alex Riolexus Ario

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Is cold ironing (onshore power supply, or alternative maritime power, or shore-to-ship power): a viable solution for reducing greenhouse gas emissions in ports? EU / Greek ports pe... by Emmanouil Nikolaidis, Marina Maniati

“…<p>Adaptation to climate change has led Institutional bodies to work relentlessly to find solutions to this progressing problem. European Union has been diligently formulating a comprehensive institutional framework aimed at addressing maritime transport’s environmental impact and fostering sustainable practices. …”
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