K-Nearest Neighbors for Anomaly Detection and Predictive Maintenance in Water Pumping Systems by João Pablo Santos da Silva, André Laurindo Maitelli

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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

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Medium-sized protein language models perform well at transfer learning on realistic datasets by Luiz C. Vieira, Morgan L. Handojo, Claus O. Wilke

“…While larger models, such as the 15 billion parameter model ESM-2, promise to capture more complex patterns in sequence space, they also present practical challenges due to their high dimensionality and high computational cost. …”
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Research on a Multi-Dimensional Information Fusion Mechanical Wear Fault-Diagnosis Algorithm Based on Data Regeneration by Qifan Zhou, Bosong Chai, Kunwen Ran, Yingqing Guo, Shan Zhou, Wangyu Wu, Kun Wang, Yao Ni

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Integrating hybrid bald eagle crow search algorithm and deep learning for enhanced malicious node detection in secure distributed systems by Feras Mohammed Al-Matarneh

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Interfacial adhesion between dissimilar thermoplastics fabricated via material extrusion-based multi-material additive manufacturing by Felix Richter, Dazhong Wu

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Age- and Post-Based Complex Analyses of Heart Rate Variability in Young Male Handball Players for Potential Prevention of Overload-induced Injuries by Zita Petrovszki, Olivér Czimbalmos, Vera Gal, Gabor Korosi, Edit Nagy, Rita Mikulan, Gyongyi Horvath

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Drone Detection Using YOLOv5 With GhostNet Backbone and Adaptive Fourier Neural Operator (AFNO 2D) by K. Kavin Akash, Uma Kuppusamy

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Design and Validation of a Multi-Epitope mRNA Vaccine Construct Against Human Monkeypox Virus (hMPXV) by Annotating Protein of Intracellular Mature Virus (IMV) Form of hMPXV by Mohammad Asrar Izhari, Siraj B. Alharthi, Raed A. Alharbi, Ahmad H. A. Almontasheri, Wael A. Alghamdi, Abdulmajeed Abdulghani A. Sindi, Ahmad Abdulmajed Salem, Ali Mahzari, Fahad Alghamdi, Ahmed R. A. Gosady

“…<b>Results</b>: The MPXV-2-Beta vaccine constructs, of the six initially designed constructs, was identified as the most promising candidate, signifying nonallergenic profile and nontoxic features, with a predicted antigenicity score (PAS) = 0.7202, 407 residues, a molecular weight of 43,102.1 Da, pI of 9.2, and favorable stability parameters (AI: 65.65, GRAVY: −0.597, I-i: 25.92). …”
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GPPK4PCM: pest classification model integrating growth period prior knowledge by Jianhua Zheng, Junde Lu, Yusha Fu, Ruolin Zhao, Jinfang Liu, Zhaoxi Luo, Zhijie Luo

“…The model is composed of three sub-modules where: i) A deep learning network first identifies the growth periods of pests, and this prior knowledge is then used to guide the text encoder of the CLIP pre-trained model in generating period-specific textual features. ii) A parallel deep learning network extracts visual features from pest images. iii) An efficient low-rank multimodal fusion module integrates textual and visual features through parameter-optimized tensor decomposition, significantly improving classification accuracy across pest developmental phases. …”
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Tier-based strict locality and the typology of agreement by Kenneth Hanson

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Predicting object size from hand kinematics: a temporal perspective. by Caterina Ansuini, Andrea Cavallo, Atesh Koul, Marco Jacono, Yuan Yang, Cristina Becchio

“…Interestingly, some kinematics features exhibited a higher ability to discriminate the target size than others did. …”
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Evaluation of the precision and accuracy in the classification of breast histopathology images using the MobileNetV3 model by Kenneth DeVoe, Gary Takahashi, Ebrahim Tarshizi, Allan Sacker

“…In comparison with previous efforts, using older and larger convolutional network architectures with feature extraction pre-processing, our work highlights that modern, resource-efficient architectures can classify histopathological images with accuracy that at least matches that of previous efforts, without the need for labor-intensive feature extraction protocols. …”
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SSDFusion: A Semantic Segmentation Driven Framework for Infrared and Visible Image Fusion by Qishen Lv, Rui Yang, Chengmin Zhang, Shuaihui Liu, Xinyan Fan, Zihao Luo

“…SSDFusion also exhibits excellent performance in terms of computational efficiency and parameter count. Furthermore, we have also verified the good generalization ability of SSDFusion on the RoadScene and M3FD datasets.…”
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GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…This process significantly reduces modeling complexity and improves computational efficiency. We propose different modeling strategies tailored to the dynamics of various subsequences. …”
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Evaluation criteria of centralization options in the architecture of multicomputer systems with traps and baits by Antonina Kashtalian, Sergii Lysenko, Anatoliy Sachenko, Bohdan Savenko, Oleg Savenko, Andrii Nicheporuk

“…But the specifics of the tasks of systems for detecting malicious software and computer attacks require such an organization of systems that it is difficult for attackers to understand their behavior. …”
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Unveiling smart contract vulnerabilities: Toward profiling smart contract vulnerabilities using enhanced genetic algorithm and generating benchmark dataset by Sepideh HajiHosseinKhani, Arash Habibi Lashkari, Ali Mizani Oskui

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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…The online resource SwissADME has been used to analyse the physicochemical properties and pharmacokinetic parameters of the studied compounds. The molecular docking method, based on computational algorithms, has been used to predict and study interactions, including the identification of potential binding sites, estimation of energy parameters and spatial configuration of molecules. …”
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CSCA-YOLOv8: A lightweight network model for evaluating drought resistance in mung bean. by Dongshan Jiang, Jinyang Liu, Haomiao Zhang, Wenxiang Liang, Ziqiu Luo, Wenlong An, Shicong Li, Xin Chen, Xingxing Yuan, Shangbing Gao

“…The final experimental results show that compared with the YOLOv8s baseline model, the number of parameters of our proposed algorithm is reduced by 24%, the floating point number is reduced by 35%, and the accuracy is improved by 2.52%, which supports the deployment on embedded edge devices with limited computing power. …”
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Construction of an LNG Carrier Port State Control Inspection Knowledge Graph by a Dynamic Knowledge Distillation Method by Langxiong Gan, Qihao Yang, Yi Xu, Qiongyao Mao, Chengyong Liu

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