Novel metrics and LSH algorithms for unsupervised, real-time anomaly detection in multi-aspect data streams by Samira Khodabandehlou, Alireza Hashemi Golpayegani

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Multi-Scenario Remote Sensing Image Forgery Detection Based on Transformer and Model Fusion by Jinmiao Zhao, Zelin Shi, Chuang Yu, Yunpeng Liu

“…Finally, to promote network optimization, on the one hand, we explore multiple loss functions and select label smooth loss, which can reduce the model’s excessive dependence on training data. …”
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German Language Teachers and Dyslexic Students by Danuta Grzesiak-Witek, Urszula Niekra, Paweł Witek

“…Symptoms of specific foreign language learning difficulties include, for example, poor development of linguistic functions, difficulties in differentiating sounds and finding sounds in words, problems with dividing words into syllables or distinguishing similar-sounding words, difficulties in assimilating grammatical and spelling rules. …”
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KAN-Based Tool Wear Modeling with Adaptive Complexity and Symbolic Interpretability in CNC Turning Processes by Zhongyuan Che, Chong Peng, Jikun Wang, Rui Zhang, Chi Wang, Xinyu Sun

“…However, traditional physics-based models lack adaptability, while machine learning approaches are often limited by poor interpretability. …”
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Enhanced HoVerNet Optimization for Precise Nuclei Segmentation in Diffuse Large B-Cell Lymphoma by Gei Ki Tang, Chee Chin Lim, Faezahtul Arbaeyah Hussain, Qi Wei Oung, Aidy Irman Yajid, Sumayyah Mohammad Azmi, Yen Fook Chong

“…This study aims to evaluate the performance of HoVerNet, a deep learning model, for nuclei segmentation and classification in CMYC-stained whole slide images and to assess its integration into a user-friendly diagnostic tool. …”
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A 3D Clinical Face Phenotype Space of Genetic Syndromes Using a Triplet-Based Singular Geometric Autoencoder by Soha S. Mahdi, Eduarda Caldeira, Harold Matthews, Michiel Vanneste, Nele Nauwelaers, Meng Yuan, Giorgos Bouritsas, Gareth S. Baynam, Peter Hammond, Richard Spritz, Ophir D. Klein, Michael Bronstein, Benedikt Hallgrimsson, Hilde Peeters, Peter Claes

“…In this paper, a triplet loss-based autoencoder developed by geometric deep learning (GDL) is trained using multi-task learning, which combines supervised and unsupervised learning approaches. …”
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PA-Win2: In Silico-Based Discovery of a Novel Peptide with Dual Antibacterial and Anti-Biofilm Activity by Jin Wook Oh, Min Kyoung Shin, Hye-Ran Park, Sejun Kim, Byungjo Lee, Jung Sun Yoo, Won-Jae Chi, Jung-Suk Sung

“…<b>Conclusions:</b> These findings suggest PA-Win2 as a promising drug candidate against ARB and demonstrate the potential of in silico methods in discovering functional peptides from biological data.…”
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GNNs and ensemble models enhance the prediction of new sRNA-mRNA interactions in unseen conditions by Shani Cohen, Lior Rokach, Isana Veksler-Lublinsky

“…Abstract Bacterial small RNAs (sRNAs) are pivotal in post-transcriptional regulation, affecting functions like virulence, metabolism, and gene expression by binding specific mRNA targets. …”
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Dynamics of educational activity of students under the influence of digitalisation by D. Yu. Narkhov, E. N. Narkhova, D. V. Shkurin

“…The fixation of qualitative changes in educational activity in non-standard conditions, along with the development of a theoretical basis for the digital educational community of students, is necessary for making qualified managerial decisions.The aim of the present research was to identify the factors and dynamics of students as a digital educational community in the context of self-isolation and online learning.Methodology and research methods. This study is based on the use of specific approaches to industry-specific sociological knowledge (youth and education): community, system, structural-functional, institutional, temporal, thesaurus, network, panoramic (pedagogical science). …”
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基于数字图像比色法的食用油酸价检测研究Determination of acid value of edible oil by digital image colorimetry-based method by 李跃凡1，马改琴1，王媛媛1，张帆2，于修烛1LI Yuefan1, MA Gaiqin1, WANG Yuanyuan1, ZHANG Fan2, YU Xiuzhu1

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Stimulus, expectations, desires and response strategies:The building blocks of nonlinear interaction dynamics by Dimitrios S. Dendrinos

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Domain Adaptation via Low Rank and Class Discriminative Representation for Autism Spectrum Disorder Identification: A Multi-Site fMRI Study by Xingdan Liu, Jiacheng Wu, Wenqi Li, Qian Liu, Lixia Tian, Huifang Huang

“…In addition, we locate some meaningful biomarkers: Most of the top important biomarkers are inter-network resting-state functional connectivities (RSFCs). The proposed LRCDR method can effectively improve the identification of ASD, and has great potential as a clinical diagnostic tool.…”
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Grid-search method for short-term over long-term average parameter tuning: an application to Stromboli explosion quakes by Andrea Di Benedetto, Andrea Di Benedetto, Anna Figlioli, Anna Figlioli, Antonino D’Alessandro, Giosue’ Lo Bosco, Giosue’ Lo Bosco

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Tracking Control of CSTRs Based on Improved OU Noise and the TD3 Algorithm by Hongyan Shi, Xiaofei Wu, Guogang Wang

“…Furthermore, a well-designed reward function and optimized hyperparameters enable the agent to efficiently learn the optimal control policy, achieving high-precision tracking control of the CSTRs system. …”
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Exploring quantum control landscape and solution space complexity through optimization algorithms and dimensionality reduction by Haftu W. Fentaw, Steve Campbell, Simon Caton

“…Evaluations of traditional control techniques and machine learning algorithms reveal that Genetic Algorithms (GA) outperform Stochastic Gradient Descent (SGD), while Q-learning (QL) shows great promise compared to Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO). …”
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MoSViT: a lightweight vision transformer framework for efficient disease detection via precision attention mechanism by Yuanqi Chen, Aiping Wang, Ziyang Liu, Jie Yue, Enxu Zhang, Fei Li, Ning Zhang

“…This study introduces MoSViT, an innovative classification model leveraging advanced machine learning and computer vision technologies. Built on the MobileViT V2 framework, MoSViT integrates the CLA focus mechanism, DRB module, MoSViT Block, and the LeakyRelu6 activation function to enhance feature extraction accuracy while reducing computational complexity. …”
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Joint Optimization in Underwater Image Enhancement: A Training Framework Integrating Pixel-Level and Physical-Channel Techniques by Ozan Demir, Metin Aktas, Ender M. Eksioglu

“…We also propose to use the joint loss function for both Image-to-Image Module and Physics-Informed Module to enforce the joint optimization for better underwater image enhancement performance. …”
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Analysis of Parameterized Quantum Circuits: On the Connection Between Expressibility and Types of Quantum Gates by Yu Liu, Kazuya Kaneko, Kentaro Baba, Jumpei Koyama, Koichi Kimura, Naoyuki Takeda

“…In the context of variational-quantum-algorithm-based quantum machine learning (QML), a QML model composed of a highly expressible PQC and a sufficient number of qubits is theoretically capable of approximating any arbitrary continuous function. …”
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Adaptation of the REINVENT neural network architecture to generate potential HIV-1 entry inhibitors by D. A. Varabyeu, A. D. Karpenko, A. V. Tuzikov, A. M. Andrianov

“…To accelerate the learning of the neural network in the modified version of the REINVENT model, the AutoDock-Vina-GPU-2.1 docking program was used, and to clarify the results of its work, the procedure for revaluing the affinity of compounds to the target using the RFScore-4 evaluation function was used.Results. …”
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Improved ADRC With ILC Control of a CCD-Based Tracking Loop for Fast Steering Mirror System by Quanrui Dong, Yongkai Liu, Yuliang Zhang, Shijie Gao, Tao Chen

“…First, based on the open-loop frequency response results of the system, we can approximately confirm the system transfer function and prepare for the design of the controller. …”
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