The Detection and Classification of Grape Leaf Diseases with an Improved Hybrid Model Based on Feature Engineering and AI by Fatih Atesoglu, Harun Bingol

“…The most well-known convolutional neural network (CNN) architectures, texture-based Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG) methods, Neighborhood Component Analysis (NCA), feature reduction methods, and machine learning (ML) techniques are the methods used in this article. …”
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Extinction Risk Assessment and Conservation of the Pachypodium Under Climate Change by Yu Chen, Qisong Wan, Shenglan Du, Hillary Otieno Otieno, Haingotiana Johary Andrianjatovo, Maxwell Njoroge Njenga, Yuvenalis Morara Mbuni, Neng Wei, Jitao Li, Shengwei Wang

“…Pachypodium, a genus endemic to South Africa and Madagascar, exhibits strong habitat specificity, yet the impacts of climate change on its distribution patterns remain not fully understood. This study employs the Biomod2 package in R to predict changes in the distribution patterns of 20 Pachypodium species under climate change scenarios (SSP2‐4.5 and SSP5‐8.5). …”
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A systematic literature review on the role of artificial intelligence in citizen science by Germain Abdul-Rahman, Andrej Zwitter, Noman Haleem

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Design of Intrusion Detection and Response Mechanism for Power Grid SCADA Based on Improved LSTM and FNN by Yu Huang, Liangyuan Su

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TRANSFORMATIONAL PROCESSES IN RESOURCE-RICH COUNTRIES: FROM NATURAL RESOURCES TO INNOVATION AND TECHNOLOGY-BASED ECONOMY by Ihor Hurnyak, Anna Hrytsyshyn, Nataliya Kuzenko, Liana Moskalyk, Olga Tsapko-Piddubna, Lidiya Yemelyanova

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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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MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

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Non‐Autoregressive Translation Algorithm Based on LLM Knowledge Distillation in English Corpus by Fang Ju, Weihui Wang

“…Initially, we conducted a thorough analysis of the English corpus to identify prevalent language patterns and structures. Following this, we developed a knowledge distillation approach that transfers the translation expertise of a large teacher model to a smaller student model, thereby achieving increased translation accuracy and efficiency. …”
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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

“…In particular, we identified key predictive features such as physiological indicators, physical activity, sleep quality, and Internet usage patterns, and clearly elucidated the differences in the positive or negative impact of these key features on PIU detection at different severity levels. …”
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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

“…Various textures such as Filter Banks, Gray Level Co-occurrence matrix and Local Binary Patterns are studied along with colour features for semantic segmentation of nuclei from histopathological images. …”
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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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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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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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Effective defense against physically embedded backdoor attacks via clustering-based filtering by Mohammed Kutbi

“…In such attacks, adversaries embed malicious behaviors triggered by specific patterns in the training data, causing models to misclassify whenever the trigger is present. …”
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