IMPLEMENTATION OF K-MEDOIDS AND K-PROTOTYPES CLUSTERING FOR EARLY DETECTION OF HYPERTENSION DISEASE by Hardianti Hafid, Selvi Annisa

“…The clustering results show K-Medoids' superiority in grouping data with higher Silhouette Coefficient values ​​compared to K-Prototypes. Overall, the K-Medoids and K-Prototypes algorithms can detect early hypertension risk by dividing patients into different risk groups. …”
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DLTM: a deep learning method for tearing mode simulation and prediction by Zhipeng Chang, Baofeng Gao, Ruijie Yin, Xiaofei Zhao

“…Through appropriate training strategies and network structures, we can enhance simulation accuracy and prediction reliability, offering faster and more reliable results compared to traditional methods. The goal of this research is to explore the feasibility of developing a surrogate model for tearing mode prediction that can be applied in complex experimental environments.…”
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Variational Autoencoder Based Anomaly Detection in Large-Scale Energy Storage Power Stations by Tuo Ji, Pinghu Xu, Dongliang Guo, Lei Sun, Kangji Ma, Yanan Wang, Xuebing Han

“…Experimental results demonstrate that the VAE-based model is capable of effectively detecting abnormal data segments and outliers in electricity power real-world data. Compared to classical machine learning algorithms such as Isolation Forest and Support Vector Machine, the detection performance of the VAE-based model demonstrates superiority, indicating its practical value and research significance.…”
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Validating the recording of exacerbations of asthma in electronic health records: a systematic review protocol by Jennifer K Quint, Elizabeth Moore, Zakariah Z Gassasse

“…However, previous studies found significant heterogeneity in the algorithms used to define asthma exacerbations. Validating definitions of asthma exacerbations in EHR will lead to more robust and comparable evidence in future research.Methods and analysis Medline and Embase will be searched for the key concepts relating to asthma exacerbations, EHR and validation. …”
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IoT BotScan: Ultra-Lightweight AI Defense Against Botnet Threats by Sapna Sadhwani, Urvi Kavan Modi, Raja Muthalagu, Pranav M. Pawar, Alavikunhu Panthakkan, Wathiq Mansoor

“…This research study examines the effectiveness of Deep Learning (DL) and Machine Learning (ML) algorithms in identifying BotNet attacks within network infrastructures. …”
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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…This research explored a novel multimodal approach for disease management in cauliflower crops. …”
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Feasibility, Advantages, and Limitations of Machine Learning for Identifying Spilled Oil in Offshore Conditions by Seong-Il Kang, Cheol Huh, Choong-Ki Kim, Meang-Ik Cho, Hyuek-Jin Choi

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Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma by Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry

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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Early diagnosis and efficient categorization of plant diseases are of utmost importance to support agricultural production and profitability. Besides, this research aims to investigate the feasibility that employs data mining framework together with optimization algorithms as approaches towards plant diseases identification and categorization systems. …”
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Decoding bacterial methylomes in four public health-relevant microbial species: nanopore sequencing enables reproducible analysis of DNA modifications by Valentina Galeone, Johanna Dabernig-Heinz, Mara Lohde, Christian Brandt, Christian Kohler, Gabriel E. Wagner, Martin Hölzer

“…Recent advancements in real-time Nanopore sequencing and basecalling algorithms have enabled the direct detection of modified bases from raw signal data, eliminating the need for bisulfite treatment of DNA. …”
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How spatial resolution mediates canopy spectral diversity as a proxy for marsh plant diversity by Yi Fu, Yunlong Yao, Lei Wang, Huaihu Yi, Yuanqi Shan

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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

“…In this study, we propose a new approach for constructing real-time icing grid fields using 1339 online terminal monitoring datasets provided by the China Southern Power Grid Research Institute Co., Ltd. (CSPGRI) during the winter of 2023. …”
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Multi-model ensemble machine learning-based downscaling and projection of GRACE data reveals groundwater decline in Saudi Arabia throughout the 21st century by Arfan Arshad, Muhammad Shafeeque, Thanh Nhan Duc Tran, Ali Mirchi, Zaichen Xiang, Cenlin He, Amir AghaKouchak, Jessica Besnier, Md Masudur Rahman

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Design of a Communication Device of Infrared Thermal Imaging Target Recognition and Tracking System by Le Zhang, Jinsong Wang, Zhiyong An

“…This paper designs a communication device architecture for an infrared thermal imaging target recognition and tracking system and optimizes and compares different target recognition and tracking algorithms. …”
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Multi-crop plant counting and geolocation using a YOLO-Powered GUI System by Renato Herrig Furlanetto, Nathan Schawn Boyd, Ana Claudia Buzanini

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Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…The results of this research show that relevant information can be effectively extracted from Finnish medical reports using classification algorithms with default parameter values. …”
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Least to Most Range (LMR): A Novel Consistent Weighting Multicriteria Method Applied to Green Supplier Selection by Vinicius Moretti, Everton L. Melo, Joao Carlos Colmenero

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Proteomic and metabolomic profiles of plasma-derived Extracellular Vesicles differentiate melanoma patients from healthy controls by SM Bollard, J Howard, C Casalou, BS Kelly, K O'Donnell, G Fenn, J O'Reilly, R Milling, M Shields, M Wilson, A Ajaykumar, K Triana, K Wynne, DJ Tobin, PA Kelly, A McCann, SM Potter

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A lightweight deep-learning model for parasite egg detection in microscopy images by Wenbin Xu, Qiang Zhai, Jizhong Liu, Xingyu Xu, Jing Hua

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Vehicle Painting Robot Path Planning Using Hierarchical Optimization by Yuya Nagai, Hiromitsu Nakamura, Narito Shinmachi, Yuta Higashizono, Satoshi Ono

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