Development of Automatic Balancing Application forFashion Company Using Artificial Intelligence by May Alrasheed, Mohamed Jmali, Thouraya Hamdi

“…It focuses on utilising ant colony algorithms for optimal balancing. The results show the significance of these algorithms in attaining optimal balancing in production systems. …”
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SafeTrack: Secure Tracking Protocol for Mobile Sensor Nodes in Unstable Wireless Sensor Networks by Ali Adnan Al-Khazraji, Fatimah Abdulridha Rashid

“…It also incorporates an Adaptive Routing Algorithm (ARA) and an Energy Optimization Module (EOM) to enable both efficient resource utilization and resilience to changes in dynamic network conditions. …”
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Machine learning approach for prediction of safe mud window based on geochemical drilling log data by Hongchen Cai, Yunliang Yu, Yingchun Liu, Xiangwei Gao

“…Traditional geomechanical methods for SMW determination face challenges in handling complex, nonlinear relationships within drilling datasets.PurposeThis study aims to develop robust machine learning (ML) models to predict two key SMW parameters—Mud Pressure below shear failure (MWsf) and tensile failure (MWtf)—using geochemical drilling log data from Middle Eastern carbonate reservoirs.MethodsHybrid ML models combining Least Squares Support Vector Machine (LSSVM) and Multilayer Perceptron (MLP) with optimization algorithms (Gray Wolf Optimization, GWO; Grasshopper Optimization Algorithm, GOA) were trained on 2,820 data points from three wells. …”
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Land Use Transition and Regional Development Patterns Under Shared Socioeconomic Pathways: Evidence from Prefecture-Level Cities in China by Xiaodong Zhang, Mingjie Yang, Rui Guo, Yaolong Li, Fanglei Zhong

“…These findings provide empirical evidence for optimizing land allocation policies during China’s economic transition.…”
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Impact of rainy season on approach trajectories in high-altitude airport terminal maneuvering area: a clustering analysis by Jianxiong Chen, Jingtao Wang, Fan Li, Lin Zou

“…After data preprocessing, a clustering algorithm was used to identify trajectory patterns and detect outlier trajectories. …”
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Performance Analysis of Three-Phase Interleaved Buck-Boost Converter in Wind Energy Maximum Power Point Tracking by Muhammad Qasim Nawaz Sciences, Wei Jiang Sciences, Aimal Khan Sciences

“…The system responds accurately to wind speed changes, ensuring optimal energy extraction across various operational conditions. …”
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Game-based resource allocation in heterogeneous downlink CR-NOMA network without subchannel sharing by Deepa Das, Rajendra Kumar Khadanga, Deepak Kumar Rout, Md. Minarul Islam, Taha Selim Ustun

“…We frame this joint optimization of SU cluster formation and power allocation as a cooperative multi-armed bandit game. …”
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Laser-induced Breakdown Spectroscopy Based on Pre-classification Strategy for Quantitative Analysis of Rock Samples by Weiheng KONG, Lingwei ZENG, Yu RAO, Sha CHEN, Xu WANG, Yanting YANG, Yixiang DUAN, Qingwen FAN

“…Different element quantitative models were constructed for each rock type. The kNN algorithm was selected using cross-validation to determine the optimal k value, and the key punishment parameter C and RBF width parameter γ of the SVM algorithm were determined using a grid search method. …”
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Simplified Model Predictive for Controlling Circulating and Output Currents of a Modular Multilevel Converter by Abolfazl Sheybanifar, Seyed Masoud Barakati

“…In addition, a bilinear mathematical model of the MMC is derived and discretized to predict the states of the MMC for one step ahead. A sorting algorithm is used to retain the balancing capacitor voltage in each SM, while the cost function guarantees the regulation of the output current, and MMC circulating current. …”
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Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…One of the challenges in this field is using optimal datasets and classification models that meet real-time applications on low-end hardware devices. …”
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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

“…In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. Moreover， to solve the problem of low far-field ranging accuracy， multiple magnetic steering data mining algorithms such as support vector machine （SVM）， decision tree （DT）， multilayer perceptron （MLP） and convolutional neural network （CNN） were built and compared， indicating that the robustness and generalization of the multilayer perceptron algorithm is the best. …”
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Energy Optimisation in Aquaponics—Integrating Renewable Source and Water as Energy Buffer for Sustainable Food Production by Abdul Aziz Channa, Kamran Munir, Mark Hansen, Muhammad Fahim Tariq

“…However, the high energy costs associated with maintaining optimal water conditions remain a critical factor in ensuring its long‐term viability. …”
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Estimation of Current RMS for DC Link Capacitor of S-PMSM Drive System by ZHANG Zhigang, CHANG Jiamian, ZHANG Pengcheng

“…The proposed technique simplifies the tedious calculation process of traditional algorithms and guarantees high calculation accuracy, providing guidance for optimizing the selection of DC link capacitors and the design of life monitoring controllers. …”
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Domain generalization for image classification based on simplified self ensemble learning. by Zhenkai Qin, Xinlu Guo, Jun Li, Yue Chen

“…Specifically, we frame the problem as an optimization process with the objective of minimizing a weighted loss function that balances cross-domain discrepancies and sample complexity. …”
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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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Deep Reinforcement Learning Based Transferable EMS for Hybrid Electric Trains by Yogesh Wankhede, Sheetal Rana, Faruk Kazi

“…To this end, an energy management strategy [EMS] has been developed that optimizes the distribution of energy to reduce the amount of hydrogen required to power the train. …”
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Urban Land-use Features Mapping from LiDAR and Remote Sensing Images using Visual Transformer Network Model by Q. Yuan

“…LiDAR has relatively accurate three-dimensional spatial information, while remote sensing image has rich spectral information. …”
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Sentiment Analysis of Public Satisfaction with the 'INFO BMKG' Application using Naive Bayes, SVM, and KNN by Natasya Aditiya, Pratomo Setiaji, Supriyono Supriyono

“…Thus, Naive Bayes is shown to be the most optimal for sentiment analysis in this study, whereas KNN and SVM showed certain limitations, particularly in efficiency and classification accuracy.…”
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Renal failure in patients with hematological malignancies (literature review) by E. G. Gromova

“…The main reasons for the renal failure development in hematological cancer patients and syndromes that prevent adequate antitumor therapy are considered. Diagnostic algorithm optimization and supportive intensive care of acute renal failure is the key to the successful application of highly effective modern protocols of drug anticancer treatment.A special group is represented by patients suffering from monoclonal gammopathies with acute renal injury and hyperproduction of immunoglobulins free light chains. …”
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Memory consolidation from a reinforcement learning perspective by Jong Won Lee, Min Whan Jung, Min Whan Jung

“…We suggest that memory consolidation might be viewed as a process of deriving optimal strategies based on simulations derived from limited experiences, rather than merely strengthening incidental memories. …”
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