Methodology for Using Multi-Temporal Landsat Images to Monitor Urban Growth of Kirkuk Governorate by Tabark Y. Gehad, Nejat Q. Omer, Nada S. Abdulmajeed

“…The Kirkuk Governorate has experienced significant urban growth in recent years, causing various environmental, economic, and social issues. the study aims to monitor the growth of Kirkuk Governorate from 1990-2020 using multi-spectral Landsat images to better understand urban development. …”
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Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification by Yasir Salam Abdulghafoor, Auns Qusai Al-Neami, Ahmed Faeq Hussein

“…More than 70 state-of-the-art articles (from 2019 to 2024) were extensively explored to highlight the different machine learning and deep learning (DL) techniques of different models used for the detection, classification, and prediction of cancerous lung tumors. …”
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Data augmentation-assisted deep learning of hand-drawn partially colored sketches for visual search. by Jamil Ahmad, Khan Muhammad, Sung Wook Baik

“…The proposed method is tested on two large datasets for sketch recognition and sketch-based image retrieval and achieved better classification and retrieval performance than many existing methods.…”
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Do ‘language trees with sampled ancestors’ really support a ‘hybrid model’ for the origin of Indo-European? Thoughts on the most recent attempt at yet another IE phylogeny by Alexei S. Kassian, George Starostin

“…We show that the general quality of the lexical data used as the basis for classification has significantly improved from earlier studies, reflecting a more careful curation process on the part of qualified historical linguists involved in the project; however, there remain serious issues when it comes to marking cognation between different characters, such as failure (in many cases) to distinguish between true cognacy and areal diffusion and the inability to take into account the influence of the so-called derivational drift (independent morphological formations from the same root in languages belonging to different branches). …”
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Handling data sparsity via item metadata embedding into deep collaborative recommender system by Gopal Behera, Neeta Nain

“…Many investigations have been made to tackle some of these issues with the help of matrix factorization (MF) approaches. …”
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Approaches to Interstate Interaction of Circumpolar Countries in the Development of the Arctic by N. I. Didenko, D. F. Skripnuk, N. A. Konakhina

“…The research is based on the using the elements of empirical and theoretical methods for economic reality research.Results: the study presents the development of theoretical approaches to issues of interstate interaction in existing economic schools. …”
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Public Catering Enterprises: Analysis and Prospects of Innovative Development by Larisa A. Mayurnikova, Arkadiy A. Koksharov, Tatyana V. Krapiva, Anna I. Petkovich, Vladislav O. Meshkov

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BoneCLIP-XGBoost: A Multimodal Approach for Bone Fracture Diagnosis by Zhihao Su, Yuhuai Zhou, Jianqun Zhou, Hanhua Cao, Huanping Zhang

“…In response to these issues, we introduce BoneCLIP-XGBoost, a novel diagnostic model that combines the strengths of Vision Transformer (ViT) and ClinicalBERT for feature extraction with the powerful classification capabilities of XGBoost. …”
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Mechanical Characterization and Chemical Identification of Clear Binders for Road Surface Courses by Andrea Grilli, Maurizio Bocci, Amedeo Virgili, Carla Conti

“…However, the selection and classification of clear binders are often based only on color and standard requirements referred to traditional bitumen that do not describe consistently the binder behavior. …”
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Machine learning and artificial intelligence based Diabetes Mellitus detection and self-management: A systematic review by Jyotismita Chaki, S. Thillai Ganesh, S.K Cidham, S. Ananda Theertan

“…Also, three current research issues in the field of DM detection and diagnosis and self-management and personalization are listed. …”
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Myeloid/natural killer cell precursor acute leukaemia. Case report and literature review by V. R. Gorodetsky, N. A. Probatova, N. N. Tupitsyn, A. M. Kovrigina, E. N. Sholokhova, M. A. Frenkel, T. T. Kondratyeva, L. Yu. Grivtsova, E. V. Fleishman, A. I. Pavlovskaya

“…The leukemoid infiltration of liver, acute hepatitis and development of liver cell failure were the distinctive features of the described case. The issues pertaining to differential diagnostics and classification of MNKL are also discussed.…”
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Entry point of machine learning in axial spondyloarthritis by Tiantian Sun, Qing Yu, Yuening Chen, Hongxiao Liu, Xinning Qu

“…Furthermore, the high heterogeneity of axSpA, its complex pathogenesis and the lack of specific drugs means that traditional classification standards and treatment guidelines struggle to meet the demands of personalised treatment. …”
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Deep learning-based strategies for evaluating and enhancing university teaching quality by Ying Gao

“…This study aims to address these issues by leveraging deep learning techniques, specifically Convolutional Neural Networks (CNNs), to accurately assess and enhance the quality of university teaching. …”
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Integration of drone and machine learning technology for predicting power infrastructure faults efficiently by WT Alshaibani, Ibraheem Shayea, Ramazan Caglar, Tareq Babaqi

“…Power transmission and distribution networks frequently face issues, especially in harsh environments, leading to high maintenance costs and the need for uninterrupted electricity. …”
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DEVELOPMENT OF CROWDFUNDING AS AN INNOVATIVE METHOD OF SOCIAL PROJECTS FUNDING by O. O. Zakharkin, L. S. Zakharkina, S. V. Pokhylko, O. S. Kreshchik

“…The meaningful notion of the crowdfunding and its classification features are investigated and specified, its strengths and weaknesses are analyzed. …”
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Sample selection using multi-task autoencoders in federated learning with non-IID data by Emre Ardıç, Yakup Genç

“…However, its performance is often hindered by redundant, malicious, or abnormal samples, leading to model degradation and inefficiency. To overcome these issues, we propose novel sample selection methods for image classification, employing a multi-task autoencoder to estimate sample contributions through loss and feature analysis. …”
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Analysis of Model Merging Methods for Continual Updating of Foundation Models in Distributed Data Settings by Kenta Kubota, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

“…Foundation models have achieved remarkable success across various domains, but still face critical challenges such as limited data availability, high computational requirements, and rapid knowledge obsolescence. To address these issues, we propose a novel framework that integrates model merging with federated learning to enable continual foundation model updates without centralizing sensitive data. …”
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Hybrid-CID: Securing IoT with Mongoose Optimization by S. Merlin Sheeba, R. S. Shaji

“…However, security challenges arise due to the wide range of protocols and computational capabilities in IoT devices. To combat these issues, a novel hybrid optimization-enabled neural network for classification of intrusion data against IoT system (Hybrid-CID) is proposed particularly to identify intrusions in resource-constrained IoT devices. …”
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DHQ-DETR: Distributed and High-Quality Object Query for Enhanced Dense Detection in Remote Sensing by Chenglong Li, Jianwei Zhang, Bihan Huo, Yingjian Xue

“…In this paper, we propose the DHQ-DETR framework, which addresses these issues by modeling bounding box offsets as distributions. …”
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Blockchain Security in Focus: A Comprehensive Investigation Into Threats, Smart Contract Security, Cross-Chain Bridges, and Vulnerabilities Detection Tools and Techniques by Deepa Mishra, Shraddha Phansalkar

“…This paper centralizes on the security vulnerabilities, attacks, and challenges faced by blockchain systems, presenting an exhaustive taxonomical classification of blockchain layered security. It classifies diverse security issues across the different layers of blockchain architecture. …”
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