Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…However, satellite-derived AOD datasets frequently suffer from missing values due to factors such as cloud cover, algorithmic limitations, and various atmospheric conditions. …”
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Selection of a Complex of Informative Features for Assessing the Internal Characteristics of Eggs for Consumption by Toncho Kolev, Mariya Georgieva-Nikolova, Miglena Kazakova, Danail Bonchev, Hristo Lukanov, Zlatin Zlatev

“…This paper concerns the methods and algorithms developed for tracking changes in the internal characteristics of eggs during storage that emphasize rapid and simple classification and satisfactory regression accuracy, considering technological requirements. …”
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Shared pathogenic mechanisms linking obesity and idiopathic pulmonary fibrosis revealed by bioinformatics and in vivo validation by Linjie Chen, Haojie Chen, Zinan Chen, Kunyi Zhang, Hongsen Zhang, Jiahe Xu, Tongsheng Chen

“…Functional enrichment (GO/KEGG), protein-protein interaction (PPI) networks, and machine learning algorithms were applied to screen hub genes, validated by ROC curves. …”
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Two-step consensus clustering approach to immune cell infiltration: An integrated exploration and validation of prognostic and immune implications in sarcomas by Ao-Yu Li, Jie Bu, Hui-Ni Xiao, Zi-Yue Zhao, Jia-Lin Zhang, Bin Yu, Hui Li, Jin-Ping Li, Tao Xiao

“…Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithms were applied to decipher the immune cell infiltration landscape and TME profiles of sarcomas. …”
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CONCEPT OF FINANCIAL FLOW MANAGEMENT OF ENTERPRISE CORPORATE SECURITY SYSTEM by Olena Sergienko, Nataliia Volosnikova, Natalia Reshetniak, Maryna Mashchenko, Valeria Baranova

“…It is proved the topicality and relevance of algorithms implementation for finding and analyzing performance indicators and decision-making criteria, which form the basis of the decision-making system for effective management of industrial enterprises’ resource potential, including financial, in conditions of factors instability and significant changes in the micro and macroeconomic environment. …”
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An Automated Image-Based Dietary Assessment System for Mediterranean Foods by Fotios S. Konstantakopoulos, Eleni I. Georga, Dimitrios I. Fotiadis

“…The proposed volume estimation subsystem uses stereo vision techniques and algorithms, and needs the input of two food images to reconstruct the point cloud of the food and to compute its quantity. …”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…This research presents an innovative approach to enhance altitude estimation accuracy for UAVs weighing under 2 kg without cameras, utilizing advanced AI Deep Learning algorithms. The primary novelty of this study lies in its unique integration of unsupervised and supervised learning techniques. …”
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Non-Destructive Monitoring of External Quality of Date Palm Fruit (<i>Phoenix dactylifera</i> L.) During Frozen Storage Using Digital Camera and Flatbed Scanner by Younes Noutfia, Ewa Ropelewska, Zbigniew Jóźwiak, Krzysztof Rutkowski

“…Then, extracted features were used as inputs for pre-established algorithms–groups within WEKA 3.9 software to classify frozen date fruit samples after 0, 2, 4, and 6 months of storage. …”
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YOLOv10n-Based Defect Detection in Power Insulators: Attention Enhancement and Feature Fusion Optimization by Zhihao Wei, Yan Wei

“…The experimental results show that the mAP@50 of the improved model reaches 94.2%, which is 2.4% higher than that of the baseline model YOLOv10n, and better than the mainstream algorithms such as YOLOv5 (93.1%) and YOLOv8n (93.2%).…”
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Ambulatory electrocardiographic monitoring in patients with Fabry disease: study design and cohort characterization by E. V. Kotelnikova, V. N. Senchikhin, T. P. Lipchanskaya

“…For effective management of FD, additional multicenter studies are required to develop algorithms for making tactical decisions in the process of cardiac monitoring, taking into account the characteristics of the cardiovascular manifestations of this disease. …”
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Screening biomarkers related to cholesterol metabolism in osteoarthritis based on transcriptomics by ChenDeng Lao, Wei Wei, JianWen Cheng, ShiJie Liao, XiaoLin Luo, Qian Huang, HengZhen Huang, JinMin Zhao

“…Three machine learning algorithms identified ATF3, CHKA, CLU, CTNNB1, and FASN as potential biomarkers. …”
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Limited Performance of Machine Learning Models Developed Based on Demographic and Laboratory Data Obtained Before Primary Treatment to Predict Coronary Aneurysms by Mi-Jin Kim, Gi-Beom Kim, Dongha Yang, Yeon-Jin Jang, Jeong-Jin Yu

“…Various supervised machine learning algorithms were applied to develop a model for predicting CAA. …”
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Priorities of ensuring hygiene and occupational safety of medical personnel and the resilience of healthcare facilities in emergency situations by R. P. Brukhno, O. P. Yavorovskyi, Yu. M. Skaletskyi, T. O. Zinchenko

“…There is an urgent need to develop clear response algorithms for healthcare facilities to cope with emergency situations that could influence them. …”
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A Multi-Branch Convolution and Dynamic Weighting Method for Bearing Fault Diagnosis Based on Acoustic–Vibration Information Fusion by Xianming Sun, Yuhang Yang, Changzheng Chen, Miao Tian, Shengnan Du, Zhengqi Wang

“…Experimental results demonstrate that our method significantly outperforms other algorithms in terms of convergence speed and final performance. …”
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A Method for Recognizing Dead Sea Bass Based on Improved YOLOv8n by Lizhen Zhang, Chong Xu, Sai Jiang, Mengxiang Zhu, Di Wu

“…Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. …”
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A novel smart baby cradle system utilizing IoT sensors and machine learning for optimized parental care by Kunal Chandnani, Suryakant Tripathy, Ashutosh Krishna Parbhakar, Kshitij Takiar, Urvi Singhal, P. Sasikumar, S. Maheswari

“…Microcontrollers like Raspberry Pi and NodeMCU use intelligent machine-learning algorithms to process the collected data and trigger adaptive responses. …”
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The applicability and challenges of black carbon sensors in monitoring networks by J. T. Elomaa, K. Luoma, K. Luoma, S. D. Harni, A. Virkkula, H. Timonen, T. Petäjä

“…To reduce the effect of changing <span class="inline-formula"><i>T</i></span> and RH, more robust environmentally controlled boxes should be developed, or correction algorithms, such as environmental compensation, should be applied.…”
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Unveiling tumor-infiltrating immune cell-driven immune-mediated drug resistance in clear cell renal cell carcinoma: prognostic insights and therapeutic strategies by Jifeng Yang, Yixuan Xing, Jiusong Luan, Wenbo Yang, Xin Zhang, Yanhua Tian, Haisong Zhang

“…Methods Integrative analyses of transcriptomic and single-cell RNA sequencing data from multiple cohorts were employed to characterize immune and metabolic landscapes in ccRCC. Machine learning algorithms were utilized to identify key TIIC-related RNAs (TIIC-RNAs) associated with prognosis and therapeutic response. …”
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Optimising management against dynamic threats: A spatially explicit approach based on integer programming by José Salgado‐Rojas, Virgilio Hermoso, Eduardo Álvarez‐Miranda

“…Employing a Warm‐start algorithmic strategy ensures rapid generation of feasible solutions, enhancing the model's practical applicability and scalability. …”
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Development and validation of an interpretable machine learning model for predicting left atrial thrombus or spontaneous echo contrast in non-valvular atrial fibrillation patients. by Chaoqun Huang, Shangzhi Shu, Miaomiao Zhou, Zhenming Sun, Shuyan Li

“…A retrospective study of 1,222 NVAF patients was conducted. Nine ML algorithms combined with demographic, clinical, and laboratory data were applied to develop prediction models for LAT/SEC in NVAF patients. …”
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