Comparative Analysis of Linear Regression and Neural Network Algorithms for Stock Price Prediction by Eldrianto Christian Wibowo, Ariya Dwika Cahyono

“…Although Neural Networks are more flexible in capturing non-linear patterns, Linear Regression demonstrates greater stability under market conditions present in the observed data period.…”
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Non‐Autoregressive Translation Algorithm Based on LLM Knowledge Distillation in English Corpus by Fang Ju, Weihui Wang

“…ABSTRACT Although significant advancements have been made in the quality of machine translation by large‐scale language models, their high computational costs and resource consumption have hindered their widespread adoption in practical applications. …”
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A multi-tiered feature selection model for android malware detection based on Feature discrimination and Information Gain by Parnika Bhat, Kamlesh Dutta

“…These malware detectors classify target applications based on the patterns found in the features present in the Android applications. …”
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Mitigating Data Leakage in a WiFi CSI Benchmark for Human Action Recognition by Domonkos Varga

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Risk level prediction for problematic internet use: A digital health perspective by Youngjung Suh, Jinwon Yoo

“…To improve understanding and detection of PIU, we designed a comprehensive machine learning pipeline that combines detailed preprocessing, feature extraction, modeling, and performance validation strategies. …”
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A Comparative Evaluation of Texture Features for Semantic Segmentation of Breast Histopathological Images by R. Rashmi, Keerthana Prasad, Chethana Babu K. Udupa, V. Shwetha

“…Support Vector Machine and Multi Layer Perceptron algorithms are trained to perform pixelwise classification. …”
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BEYOND TRADITIONAL METRICS: ESG AND FINANCIAL PERFORMANCE IN INNOVATION-DRIVEN SECTORS by ANNALISA FERRARI, FEDERICO CINI, ROSELLA CASTELLANO

“…The dataset comprises a basket of firms listed in the Euro Stoxx 600 index for the period 2016–2021. Employing a Machine Learning approach and SHapley Additive exPlanations (SHAP) values for model interpretability, the study, leveraging covariate analysis, uncovers patterns and reveals how ESG factors contribute to shaping financial outcomes. …”
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A New Approach for the Betterment of Wireless Network Performance Using Bandwidth Degradation and Ad-hoc Relaying by Maryam Monemian, Pejman Khadivi

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Intelligent multi-modeling reveals biological relationships and adaptive phenotypes for dairy cow adaptation to climate change by Robson Mateus Freitas Silveira, Angela Maria de Vasconcelos, Concepta McManus, Luiz Paulo Fávero, Iran José Oliveira da Silva

“…In this study, we develop a systematic methodology with multivariate models and machine learning algorithms to (i) model complex patterns of relationships or multi-phenotypic differences between the thermal environment and thermoregulatory, hormonal, biochemical, hematological and productive responses; and (ii) identify potential associations among biological relationships that may underlie shared and specific phenotypic patterns of adaptive responses. …”
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Music Similarity Detection Through Comparative Imagery Data by Asli Saner, Min Chen

“…We tested the trained model with legally verified data as well as AI-generated music, confirming that the models produced with our approach can detect similarity patterns which are typically associated with music plagiarism. …”
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Intelligent regulation for cryptocurrency anti-money laundering: models, methods, and applications by ZHANG Yifei, YUAN Yong, YANG Dong, WANG Fei-Yue

“…The main models, methods, and application patterns in AML regulatory research were summarized from multiple dimensions, including traditional machine learning, deep learning, ensemble learning, graph analysis, and heuristic approaches. …”
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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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Effective defense against physically embedded backdoor attacks via clustering-based filtering by Mohammed Kutbi

“…Abstract Backdoor attacks pose a severe threat to the integrity of machine learning models, especially in real-world image classification tasks. …”
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The Role of Autophagy and Cell Communication in COPD Progression: Insights from Bioinformatics and scRNA-seq by Kaiqi Ren, Lu Zou, Jingjing Yang, Yuxiu Wang, Lingfeng Min

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An interpretable approach for trustworthy intrusion detection systems against evasion samples by Ngoc Tai Nguyen, Hien Do Hoang, The Duy Phan, Van-Hau Pham

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AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…The use of AI in biomarker discovery improves precision medicine by uncovering biomarker signatures that are essential for early detection and treatment of diseases within vast and diverse datasets. Deep learning and machine learning diagnostics are two examples of AI technologies that are changing the way biomarkers are made by finding patterns in large datasets and making new technologies that make it possible to deliver accurate and effective therapies. …”
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Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 by Thanakrit Yoongsomporn, Alvin Christopher Galang Varquez, Sunkyung Choi, Makoto Okumura, Shinya Hanaoka, Manabu Kanda

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Electricity Demand Prediction by a Transformer-Based Model by Ahmed Mohammed Mahmood, Musaddak Maher Abdul Zahra, Waleed Hamed, Bashar S. Bashar, Alaa Hussein Abdulaal, Taif Alawsi, Ali Hussein Adhab

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Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic–Ischemic Encephalopathy Injury by Leah Twomey, Sergi Gomez, Emanuel Popovici, Andriy Temko

“…This paper proposes a novel workflow for background EEG grading, implementing a blend of Digital Signal Processing (DSP) and Machine-Learning (ML) techniques. First, the EEG signal is transformed into an amplitude and frequency modulated audio spectrogram, which enhances its relevant signal properties. …”
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AP-GRIP evaluation framework for data-driven train delay prediction models: systematic literature review by Tiong Kah Yong, Zhenliang Ma, Carl-William Palmqvist

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