Zenith Tropospheric Delay Forecasting in the European Region Using the Informer–Long Short-Term Memory Networks Hybrid Prediction Model by Zhengdao Yuan, Xu Lin, Yashi Xu, Jie Zhao, Nage Du, Xiaolong Cai, Mengkui Li

“…This model employs a parallel ensemble learning strategy that combines the strengths of both the Informer and LSTM networks to extract features from ZTD data. …”
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Rancang Bangun Alat Pengenal Finger Vein Menggunakan Raspberry Pi dengan Metode Convolutional Neural Network (CNN) by Barlian Henryranu Prasetio, Jevandika, Dahnial Syauqy

“…This research uses a Raspberry Pi 4-based system with the help of IR LEDs and webcams for the acquisition process of finger blood vessel image data, which is expected to be able to carry out the Finger Vein recognition process faster, and the use of the proven Convolutional Neural Network method to produce better accuracy with the Deep Learning process. Of the 30 data used as system testers alongside embedded software and hardware, the accuracy reached 96.66%. …”
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Perancangan Desain Antarmuka Pengguna Aplikasi Pertunjukan dan Pembelajaran Kesenian Tradisional Menggunakan Pendekatan Human-Centered Design by Winda Putri Hapsari, Hanifah Muslimah Az-zahra, Prima Zulvarina

“…The existence of the "Cultural Theater" application is expected to penetrate the boundaries of space and time for someone who wants to learn and enjoy the Topeng Malangan. …”
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A comprehensive analysis of molecular characteristics of hot and cold tumor of gastric cancer by Chenxi Lv, Tianwei Chen, Jiangtao Li, Yuqiang Shan, Hong Zhou

“…Subsequently, 101 machine learning algorithm combinations were employed to construct a prognostic model based on the identified gene modules. …”
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Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications by Wan D. Bae, Shayma Alkobaisi, Matthew Horak, Siddheshwari Bankar, Sartaj Bhuvaji, Sungroul Kim, Choon-Sik Park

“…With their ability to find solutions among complex relationships of variables, machine learning (ML) techniques are becoming more applicable to various fields, including health risk prediction. …”
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Participation in a pre-registration student interprofessional education (IPE) society: influence on subsequent professional practice by Christine Hirsch, Emily Audet, Emily Audet, Ekrahh Dawood, Freya Beardmore, Nafeesa Hussain, Wing Chi Wong, Robert J. Barry, Sharon Buckley

“…Resulting themes were reviewed for relevance to the University of Birmingham (UK) IPE Framework, which uses the competency domains of the Canadian Interprofessional Health Collaborative Competency Framework as the required learning outcomes for IPE at Birmingham.ResultsEight interviews with former KASE members were conducted between November 2022 and March 2023. …”
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Effects of a social participation-focused virtual reality intervention for community-dwelling stroke survivors with physical disabilities: a randomised controlled trial protocol by Janita Pak Chun Chau, Suzanne Hoi Shan Lo, Vivian Wing Yan Lee, Kai Chow Choi, Alexander Yuk Lun Lau, David R Thompson, Eddie Chi Fai Kwok

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A Mitochondria‐Related Signature in Diffuse Large B‐Cell Lymphoma: Prognosis, Immune and Therapeutic Features by Zhen‐Zhong Zhou, Jia‐Chen Lu, Song‐Bin Guo, Xiao‐Peng Tian, Hai‐Long Li, Hui Zhou, Wei‐Juan Huang

“…Conclusions We established a novel prognostic mitochondria‐related signature by machine learning algorithm, which also demonstrated outstanding predictive value in tumor microenvironment and responses to therapies.…”
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Pengaruh Prediksi Missing Value pada Klasifikasi Decision Tree C4.5 by Aji Seto Arifianto, Kursita Dewi Safitri, Khafidurrohman Agustianto, I Gede Wiryawan

“…Abstract The supervised learning approach to data classification requires a complete dataset. …”
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Analisis Sentimen Wacana Pemindahan Ibu Kota Indonesia Menggunakan Algoritma Support Vector Machine (SVM) by Primandani Arsi, Retno Waluyo

“…Dalam penerapan analisis sentimen menggunakan metode machine learning terdapat beberapa metode yang sering digunakan. …”
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Six Sigma Approach to Developing a Microgrid Station for Research and Teaching by Gabriel Nasser Doyle de Doile, Miguel Castilla, Pedro Paulo Balestrassi, Antonio Carlos Zambroni de Souza, Jaume Miret

“…The conclusion of this paper highlights the benefits of using the DFSS conceptual methodology to develop a microgrid station for research and teaching, such as adaptation to educational needs; enhancement of the learning experience; refutation of experimental errors; cost-effective, flexible, and modular design; collaborative learning environment; data-driven teaching; and continuous improvement. …”
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Annual change in the distribution and landscape health of mangrove ecosystems in China from 2016 to 2023 with Sentinel imagery by Yuchao Sun, Mingzhen Ye, Bin Ai, Zhenlin Lai, Jun Zhao, Zhuokai Jian, Xinyan Qi

“…The integration of remote sensing data and deep learning models enables precise identification of mangroves. …”
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HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…We address the limitations of classical machine learning models in processing the intrinsic linkage relationships of high-dimensional data. …”
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Seleksi Fitur dengan Particle Swarm Optimization pada Klasifikasi Penyakit Parkinson Menggunakan XGBoost by Deni Kurnia, Muhammad Itqan Mazdadi, Dwi Kartini, Radityo Adi Nugroho, Friska Abadi

“…Saat ini diagnosa dapat dilakukan menggunakan machine learning dengan memanfaatkan rekaman suara pasien. …”
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Hierarchical Recognition for Urban Villages Fusing Multiview Feature Information by Zhenkang Wang, Nan Xia, Song Hua, Jiale Liang, Xiankai Ji, Ziyu Wang, Jiechen Wang

“…The spectral, textural, and structural features were extracted from Google RSI by machine-learning classifiers for each segmented block. The deep-learning method was applied to SVI to capture the architectural feature at each viewpoint. …”
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Deteksi Objek menggunakan Dashboard Camera untuk Sistem Peringatan Pencegah Kecelakaan pada Mobil by Raymond Sutjiadi, Timothy John Pattiasina

“…This application was developed using Object Detection Method in Tensorflow Open Source Machine Learning Library. The research stage was started from problem analysis, literature study to search comparison from previous research, also software development and finalized with testing to measure system performance. …”
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Radiomics analysis of thoracic vertebral bone marrow microenvironment changes before bone metastasis of breast cancer based on chest CT by Hao-Nan Zhu, Yi-Fan Guo, YingMin Lin, Zhi-Chao Sun, Xi Zhu, YuanZhe Li

“…Radiomic features were extracted from the bone marrow of thoracic vertebrae on non-contrast chest CT scans. Multiple machine learning algorithms were utilized to construct various radiomics models for predicting the risk of bone metastasis, and the model with optimal performance was integrated with clinical features to develop a nomogram. …”
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AI-Driven Plant Health Assessment: A Comparative Analysis of Inception V3, ResNet-50 and ViT with SHAP for Accurate Disease Identification in Taro by Valeria Maeda-Gutiérrez, Juan José Oropeza-Valdez, Luis C. Reveles-Gómez, Cristian Padron-Manrique, Osbaldo Resendis-Antonio, Luis Octavio Solís-Sánchez, Hector A. Guerrero-Osuna, Carlos Alberto Olvera Olvera

“…The novelty of this work lies in the first-ever integration of SHapley Additive exPlanations (SHAP) with deep learning architectures to enhance model interpretability while providing a comprehensive comparison of state-of-the-art methods for this underexplored crop. …”
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Priority effects, nutrition and milk glycan-metabolic potential drive Bifidobacterium longum subspecies dynamics in the infant gut microbiome by Nicholas Pucci, Joanne Ujčič-Voortman, Arnoud P. Verhoeff, Daniel R. Mende

“…We further implemented machine learning tools to identify significant features associated with B. longum subspecies abundance. …”
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Implementasi Self Organizing Maps untuk Pengelompokan Kabupaten/Kota Berdasarkan Indeks Pembangunan Manusia by Dwi Marisa Midyanti, Syamsul Bahri

“…Hasil penelitian ini menunjukkan bahwa, dengan menggunakan learning rate 0.001, maksimum iterasi 1100, dihasilkan sejumlah 4 cluster dengan nilai Silhouette Coefficients sebesar 0.331611 untuk penambahan variabel kepadatan penduduk, 0.290092 untuk penambahan variabel jumlah guru dan murid, 0.298582 untuk penambahan variabel jumlah pengangguran , dan 0.273734 untuk adanya penambahan variabel kepadatan penduduk, jumlah guru dan murid, dan jumlah pengangguran. …”
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