High-Performance Thin PTFE-Ni Metamaterial Absorber for Ultra-Broadband Applications by Camilla C. Moro Carmo, Ursula C. Resende, Silvia C. Albuquerque, Mauricio D. Almeida

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Small Defects Detection of Galvanized Strip Steel via Schatten-<i>p</i> Norm-Based Low-Rank Tensor Decomposition by Shiyang Zhou, Xuguo Yan, Huaiguang Liu, Caiyun Gong

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Optimization and analysis of interior permanent magnet drive motor with unequal thickness magnetic poles for electric vehicle by Shilun MA, Yongyi WU, Changwei LI, Keqi CHEN

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Classification of Precipitation Types and Investigation of Their Physical Characteristics Using Three-Dimensional S-Band Dual-Polarization Radar Data by Choeng-Lyong Lee, Wonbae Bang, Chia-Lun Tsai, GyuWon Lee

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Application of Image Processing Technology in Aerobics Injury Diagnosis by Duo Zhang, Yan Tian

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An implementation of smoothed particle hydrodynamic methods for fluids problems by Nguyen Hoai Son, Nguyen Duy Hung

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Impact of bridging the gap between Artificial Intelligence and nanomedicine in healthcare by Divyam Mishra, Bhavishya Chaturvedi, Vishal Soni, Dhairya Valecha, Megha Goel, Jamilur R. Ansari

“…Furthermore, this study investigates the application of AI in predicting nanomedicine interactions with biological systems, aiming to establish AI-enabled platforms for personalized nanomedicine therapies. …”
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Diurnal distribution of phytoplankton in large shallow lakes based on time series clustering by Yanhong Chen, Haibin Cai, Yiqing Gong, Kun Lu, Jingqiao Mao, Weiyu Chen, Kang Wang, Huan Gao, Mingming Tian

“…However, short-term changes in phytoplankton distributions are often overlooked, leading to underestimations in predictions and difficulties in lake management. Considering that potential information from abundant automatic monitoring datasets has not been fully explored, we developed an automated recognition method to identify diurnal variations in phytoplankton via time series clustering. …”
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Combination of Remote Sensing and Artificial Intelligence in Fruit Growing: Progress, Challenges, and Potential Applications by Danielle Elis Garcia Furuya, Édson Luis Bolfe, Taya Cristo Parreiras, Jayme Garcia Arnal Barbedo, Thiago Teixeira Santos, Luciano Gebler

“…With the advancement of technologies, mapping fruits using remote sensing and machine learning (ML) and deep learning (DL) techniques has become an essential tool to optimize production, monitor crop health, and predict harvests with greater accuracy. This study was developed in four main stages. …”
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Artificial intelligence-driven modeling of biodiesel production from fats, oils, and grease (FOG) with process optimization via particle swarm optimization by Badril Azhar, Muhammad Ikhsan Taipabu, Cries Avian, Karthickeyan Viswanathan, Wei Wu, Raymond Lau

“…A ML model evaluation, using various algorithms, identify XGBoost, Extra Trees, Gradient Boosting, LGBM, and Random Forest demonstrate the best performer for predicting process parameters, achieving an R2 value of nearly to 1. …”
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Research on the WSN Node Localization Based on TOA by Qing-hui Wang, Ting-ting Lu, Meng-long Liu, Li-feng Wei

“…Simulation results show that the proposed algorithm renders satisfactory performance in terms of average delay reduction from end to end, packet loss rate, and routing overhead. …”
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Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis by Dominik Takács, Ambrus Zelei

“…The IPG CarMaker uses a multibody vehicle model and a learning algorithm for the virtual driver. The goal is to discover the behavior of the learning algorithm from the point of view of reliability and convergence. …”
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Identification of biomarkers for the diagnosis of type 2 diabetes mellitus with metabolic associated fatty liver disease by bioinformatics analysis and experimental validation by Guiling Wu, Guiling Wu, Sihui Wu, Sihui Wu, Tian Xiong, Tian Xiong, Tian Xiong, You Yao, You Yao, Yu Qiu, Yu Qiu, Yu Qiu, Liheng Meng, Cuihong Chen, Xi Yang, Xi Yang, Xi Yang, Xinghuan Liang, Yingfen Qin

“…Immune dysregulation was observed in MAFLD, with TNFRSF1A and SERPINB2 strongly linked to immune regulation.ConclusionThe sensitivity and accuracy in diagnosing and predicting T2DM-associated MAFLD can be greatly improved using SERPINB2 and TNFRSF1A. …”
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Method of unknown protocol classification based on autoencoder by Chunxiang GU, Weisen WU, Ya’nan SHI, Guangsong LI

“…Aiming at the problem that a large number of unknown protocols exist in the Internet,which makes it very difficult to manage and maintain the network security,a classification and identification method of unknown protocols was proposed.Combined with the autoencoder technology and the improved K-means clustering technology,the unknown protocol was classified and identified for the network traffic.The autoencoder was used to reduce dimensionality and select features of network traffic,clustering technology was used to classify the dimensionality reduction data unsupervised,and finally unsupervised recognition and classification of network traffic were realized.Experimental results show that the classification effect is better than the traditional K-means,DBSCAN,GMM algorithm,and has higher efficiency.…”
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A Non-Invasive and Highly Accurate Multi-Wavelength Light Near-Infrared Glucose Sensor Using A Multilevel Metric Learning–Back Propagation Network by Yuwei Chen, Chenxi Li, Bo Gao, Huangrong Xu, Weixing Yu

“…Finally, the optimized data were utilized as the BP network input to predict blood glucose concentrations. The predicted results showed that the factor analysis algorithm had the best performance in our HMML-BP network and that all the predicted glucose values fell into region A, with a mean absolute relative difference of 9.98%, meeting the requirements of daily glucose monitoring. …”
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Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma by Xiang Xiong, Wen Liu, Chuan Yao

“…Immune cell infiltration and Tumor Mutational Burden (TMB) analyses were carried out using the CIBERSORT and maftools algorithms. Finally, the “oncoPredict” package was employed to predict immunotherapy sensitivity and to further forecast potential anti-tumor immune drugs. qPCR was used for experimental verification.ResultsWe identified 155 alkaliptosis-related lncRNAs and determined that 5 of these lncRNAs serve as independent prognostic factors. …”
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Impact of climate change on the potential global prevalence of Macrophomina phaseolina (Tassi) Goid. under several climatological scenarios by Peter F. Farag, Dalal Hussien M. Alkhalifah, Shimaa K. Ali, Aya I. Tagyan, Wael N. Hozzein

“…Maximum Entropy (MaxEnt) model was used to predict the spatial distribution of this fungus throughout the world while algorithms of DIVA-GIS were chosen to confirm the predicted model.ResultsBased on the Jackknife test, minimum temperature of coldest month (bio_6) represented the most effective bioclimatological parameter to fungus distribution with a 52.5% contribution. …”
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Efficiently Learning an Encoder That Classifies Token Replacements and Masked Permuted Network-Based BIGRU Attention Classifier for Enhancing Sentiment Classification of Scientific... by Muhammad Inaam Ul Haq, Khalid Mahmood, Qianmu Li, Ashok Kumar Das, Sachin Shetty, Majid Hussain

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Calculation Method for Load Capacity of Urban Rail Transit Station considering Cascading Failure by Jiajun Huang, Feng Zhou, Mengru Xi

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High precision DOA estimation of microphone array for shipboard teleconferencing by Liu Yuji, Tong Feng, Chen Dongsheng, Lu Rongfu, Feng Wanjian

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