Topic adversarial neural network for cross-topic cyberbullying detection by Shufeng Xiong, Wenzhuo Liu, Bingkun Wang, Yinchao Che, Lei Shi

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Enhancing skin lesion classification: a CNN approach with human baseline comparison by Deep Ajabani, Zaffar Ahmed Shaikh, Amr Yousef, Karar Ali, Marwan A. Albahar

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eFC-Evolving Fuzzy Classifier with Incremental Clustering Algorithm Based on Samples Mean Value by Emmanuel Tavares, Gray Farias Moita, Alisson Marques Silva

“…The center of the clusters is adjusted based on the mean value of the attributes. The eFC model was evaluated and compared with state-of-the-art evolving fuzzy systems on 8 randomly selected data streams from the UCI and Kaggle repositories. …”
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Unveiling the impact of the SMARTCLAP project on habilitation by Matthew Bonello, Nathalie Buhagiar, Philip Farrugia, Joseph Mercieca

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Definition of an 802.11 Interface Management Process in a Proposed System for Transmission Capacity Enhancement in Wireless Mesh Networks by Christian Köbel, Walter Baluja García, Joachim Habermann

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From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation by Seok Joo Chae, Seolah Shin, Kangmin Lee, Seunggyu Lee, Jae Kyoung Kim

“…However, incorporating spatial heterogeneity considerably increases computational time. To address this, we explored various stochastic quasi-steady-state approximations (QSSAs) that simplify the model and reduce simulation time. …”
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A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems by Xilin Zhao, Zhenyu Lin, Bo Fu, Yang Yang, Jimin Ma

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A Comparative Study of Backward Euler and Adams-Moulton Methods for Lotka-Volterra Prey-Predator Model by Nadia Sajidah Mohd Sobree, Nurizatul Syarfinas Ahmad Bakhtiar, Nur Fatihah Fauzi, Nur Izzati Khairudin, Huda Zuhrah Ab Halim

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On the Power Dissipation of Embedded Memory Blocks Used to Implement Logic in Field-Programmable Gate Arrays by Scott Y. L. Chin, Clarence S. P. Lee, Steven J. E. Wilton

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AromaCanvas: A wearable olfactory display for Chinese painting appreciation and learning in virtual reality by Tao Lin, Quanhao Gan, Fuxi Ouyang, Yiming Luo, Yushan Pan, Yushi Li, Shaoyu Cai

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ASATM: Automated security assistant of threat models in intelligent transportation systems by Mohammad Ali Ramazanzadeh, Behnam Barzegar, Homayun Motameni

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Design of the Urban Lighting Control System Based on Optical Multisensor Technology and the GM Model by Weili Wu, Xiang Tang

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Photovoltaic panel defect detection algorithm based on infrared imaging and improved YOLOv8 by Jingdong Wang, Zhu Cheng

“…To address the challenges of high missed detection rates, complex backgrounds, unclear defect features, and uneven difficulty levels in target detection during the industrial process of photovoltaic panel defect detection, this article proposes an infrared detection method based on computer vision, with enhancements built upon the YOLOv8 model. …”
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An Analysis of the Severity of Alcohol Use Disorder Based on Electroencephalography Using Unsupervised Machine Learning by Kaloso M. Tlotleng, Rodrigo S. Jamisola

“…This study can be useful in creating an automatic AUD severity level detection tool for alcoholics to aid in early intervention and supplement evaluations by mental health professionals.…”
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TARGE: large language model-powered explainable hate speech detection by Muhammad Haseeb Hashir, Memoona, Sung Won Kim

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Deep learning in time series forecasting with transformer models and RNNs by Rogerio Pereira dos Santos, João P. Matos-Carvalho, Valderi R. Q. Leithardt

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Neurocognitive factors of new drone Pilots: Identifying candidates with expert potential by Miguel A. Ramallo-Luna, Sara Gonzalez-Torre, Álvaro Rodríguez-Mora, Gabriel G. de la Torre

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Machine learning for predicting Plasmodium liver stage development in vitro using microscopy imaging by Corin F. Otesteanu, Reto Caldelari, Volker Heussler, Raphael Sznitman

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AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

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CurriMAE: curriculum learning based masked autoencoders for multi-labeled pediatric thoracic disease classification by Taeyoung Yoon, Daesung Kang

“…However, determining the optimal masking ratio requires extensive experimentation, resulting in significant computational overhead. To address this challenge, we propose CurriMAE, a curriculum-based training approach that progressively increases the masking ratio during pretraining to balance task complexity and computational efficiency. …”
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