Global positioning system (GPS) collar data shows variations in distribution, ranging area and habitat selection of the African savannah elephant in a semi-arid protected area by Nobert Tafadzwa Mukomberanwa, Phillip Taru, Beaven Utete, Patmore Ngorima

“…Minimum Convex Polygon method was employed to delineate elephant home ranges and the MaxEnt algorithm was used to model their habitat preferences. …”
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Near Field UHF RFID Antenna System Enabling the Tracking of Small Laboratory Animals by Luca Catarinucci, Riccardo Colella, Luca Mainetti, Vincenzo Mighali, Luigi Patrono, Ilaria Sergi, Luciano Tarricone

“…In this work, a novel RFID-based approach enabling an effective localization and tracking of small-sized laboratory animals is proposed. It is mainly based on a UHF Near Field RFID multiantenna system, to be placed under the animals’ cage, and able to rigorously identify the NF RFID tags implanted in laboratory animals (e.g., mice). …”
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A Lightweight Rolling Bearing Fault Diagnosis Method Based on Multiscale Depth-Wise Separable Convolutions and Network Pruning by Qingming Hu, Xinjie Fu, Dandan Sun, Donghui Xu, Yanqi Guan

“…Current deep learning-based approaches for rolling bearing fault diagnosis mainly rely on complex models that require significant hardware storage and computing power. …”
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Hybrid Weighted Random Forests Method for Prediction & Classification of Online Buying Customers by Umesh Kumar Lilhore, Sarita Simaiya, Devendra Prasad, Deepak Kumar Verma

“…A random forest (RF) machine learning method is a widely used classification method. It is mainly based on an ensemble of a single decision tree. …”
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Dual-branch graph Transformer for node classification by Yong Zhang, Jingjing Song, Eric C.C. Tsang, Yingxing Yu

“…As an emerging architecture, graph Transformers (GTs) have demonstrated significant potential in various graph-related tasks. Existing GTs are mainly oriented to graph-level tasks and have proved their advantages, but they do not perform well in node classification tasks. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…It also includes an optimization algorithm, MAOOA, for optimizing the hyper‐parameters of the model. …”
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Artificial neural networking for computational assessment of ternary hybrid nanofluid flow caused by a stretching sheet: implications of machine-learning approach by Imad Khan, M. Waleed Ahmed Khan

“…Researchers are mainly interested in using soft computing artificial intelligence (AI) methods due to their broad applications in analysis, modelling and simulations. …”
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Bytecode-based approach for Ethereum smart contract classification by Dan LIN, Kaixin LIN, Jiajing WU, Zibin ZHENG

“…In recent years, blockchain technology has been widely used and concerned in many fields, including finance, medical care and government affairs.However, due to the immutability of smart contracts and the particularity of the operating environment, various security issues occur frequently.On the one hand, the code security problems of contract developers when writing contracts, on the other hand, there are many high-risk smart contracts in Ethereum, and ordinary users are easily attracted by the high returns provided by high-risk contracts, but they have no way to know the risks of the contracts.However, the research on smart contract security mainly focuses on code security, and there is relatively little research on the identification of contract functions.If the smart contract function can be accurately classified, it will help people better understand the behavior of smart contracts, while ensuring the ecological security of smart contracts and reducing or recovering user losses.Existing smart contract classification methods often rely on the analysis of the source code of smart contracts, but contracts released on Ethereum only mandate the deployment of bytecode, and only a very small number of contracts publish their source code.Therefore, an Ethereum smart contract classification method based on bytecode was proposed.Collect the Ethereum smart contract bytecode and the corresponding category label, and then extract the opcode frequency characteristics and control flow graph characteristics.The characteristic importance is analyzed experimentally to obtain the appropriate graph vector dimension and optimal classification model, and finally the multi-classification task of smart contract in five categories of exchange, finance, gambling, game and high risk is experimentally verified, and the F1 score of the XGBoost classifier reaches 0.913 8.Experimental results show that the algorithm can better complete the classification task of Ethereum smart contracts, and can be applied to the prediction of smart contract categories in reality.…”
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A New Method to Convert the DNA Sequence of Human to a QR Code by Sadoon Abdullah, Zahraa Abdulhamid

“…<br /> QR Codes technique is mainly used to convert and store messages since it has higher and large storage capacity, in addition to that we used, in this paper , the STR (Short Tandem Repeats) DNA sequence. …”
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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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Developing Site-Specific Prescription Maps for Sugarcane Weed Control Using High-Spatial-Resolution Images and Light Detection and Ranging (LiDAR) by Kerin F. Romero, Muditha K. Heenkenda

“…Sugarcane is a perennial grass species mainly for sugar production and one of the significant crops in Costa Rica, where ideal growing conditions support its cultivation. …”
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ETHANOL PRODUCTION FROM COCOYAM (Хanthosoma sagittifolium): APPLICATION OF THERMODYNAMIC-TOPOLOGICAL ANALYSIS by S. Serna-Loaiza, Yu. A. Pisarenko, C. A. Cardona

“…In Colombia, there are not extensive crops of this plant, but it is used for animal feeding mainly. The plant has an aerial part with a high content of protein (leaves) and a tuber with an average starch content about 25% w/w. …”
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Forecasting Air Pollution Contingencies Using Predictive Analytic Techniques by Raul Ramirez-Velarde, Oscar Esquivel-Flores, Gerardo Mejía-Velázquez

“…The proliferation of pollutants affects the world’s population, mainly those who live in large cities. Neurological and cardiovascular dysfunctions have a correlation with air particulate matter concentration, among other chronic diseases. …”
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A dual input dual spliced network with data augmentation for robust modulation recognition in communication countermeasures by Wang Guan

“…The modulation recognition task mainly encompasses two key aspects: the dataset and the network model. …”
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A speed optimization model for connected and autonomous vehicles at expressway tunnel entrance under mixed traffic environment. by Jianrong Cai, Yang Liu, Zhixue Li

“…However, existing speed optimization models mainly focus on urban signal-controlled intersections or expressway weaving zones, neglecting research on speed optimization in expressway tunnel entrances. …”
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Analyzing key users’ behavior trends in volunteer-based networks by Nofar Piterman, Tamar Makov, Michael Fire

“…We introduce two innovative algorithms: the first outlines the evolution of volunteers’ behavior patterns over time, while the second employs machine learning techniques to forecast their future behavior, including whether they will remain active donors or become mainly recipients, and vice-versa. …”
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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…The measurement tools are mainly single machine version， which is difficult to meet the current requirements for improving drilling quality and efficiency. …”
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Startup Drift Compensation of MEMS INS Based on PSO–GRNN Network by Songlai Han, Jingyi Xie, Jing Dong

“…We adopted a correlation analysis to determine the input parameters of the PSO-GRNN model that mainly affect startup drift. In the process of training this model, we used the PSO algorithm to optimize the spread parameter of the PSO-GRNN model. …”
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SHAPING THE STOCK PORTFOLIO BY THE INVESTMENT RATING METHOD by Svyatoslav N. Digo, Aleksandra M. Sokolova

“…Thus securities market needs more effective methods and algorithms of shaping the stock portfolio, as investor’s expectations of getting profits could be met  only in case of professional choice of investment projects. …”
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Research on an Eye Control Method Based on the Fusion of Facial Expression and Gaze Intention Recognition by Xiangyang Sun, Zihan Cai

“…At the same time, the corresponding eye movement behavior discrimination algorithm was combined for each eye movement action to realize the output of eye behavior instructions. …”
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