Machine learning based compact MIMO antenna array for 38 GHz millimeter wave application with robust isolation and high efficiency performance by Md. Ashraful Haque, Md. Sharif Ahammed, Soeung Socheatra, Redwan A. Ananta, Md. Jamal Hossain Nirob, Narinderjit Singh Sawaran Singh, Noorlindawaty Md. Jizat, Saeed Alsowail, Samir Salem Al-Bawri

“…An advanced design system (ADS) is utilized to compare the return loss because of CST to create a model like the suggested MPA. The next step is extensive data sampling using CST MWS simulation, followed by applying supervised regression ML techniques. …”
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Higuchi fractal dimension and deep learning on near-infrared spectroscopy for determination of free fatty acid (FFA) content in oil palm fruit by Muhammad Achirul Nanda, Kharistya Amaru, S. Rosalinda, Inna Novianty, Walidatush Sholihah, Gema Parasti Mindara, Anifatul Faricha, Tusan Park

“…This technique comprised the use of Higuchi fractal dimension (HFD) and deep learning to process NIR spectra as a new chemometric analysis. …”
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Type 2 Diabetes Detection With Light CNN From Single Raw PPG Wave by Serena Zanelli, Mounim A. El Yacoubi, Magid Hallab, Mehdi Ammi

“…However, most of these studies require feature extraction and/or several pre-processing steps. Over the past few years, the advent of deep learning has significantly impacted the analysis of biomedical signals. …”
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An explainable-by-design end-to-end AI framework based on prototypical part learning for lesion detection and classification in Digital Breast Tomosynthesis images by Andrea Berti, Camilla Scapicchio, Chiara Iacconi, Charlotte Marguerite Lucille Trombadori, Maria Evelina Fantacci, Alessandra Retico, Sara Colantonio

“…The proposed AI system marks a significant step forward in the timely and accurate analysis of DBT scans, with potential implications for improving early breast cancer detection and patient outcomes.…”
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A Forecasting Method for COVID-19 Epidemic Trends Using VMD and TSMixer-BiKSA Network by Yuhong Li, Guihong Bi, Taonan Tong, Shirui Li

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BAHGRF3: Human gait recognition in the indoor environment using deep learning features fusion assisted framework and posterior probability moth flame optimisation by Muhammad Abrar Ahmad Khan, Muhammad Attique Khan, Ateeq Ur Rehman, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Deepak Gupta, Saima Ahmed Rahin, Yudong Zhang

“…In the first step, the video frames are resized and fine‐tuned by two pre‐trained lightweight DL models, EfficientNetB0 and MobileNetV2. …”
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Automated Assessment of Quality of Jupyter Notebooks Using Artificial Intelligence and Big Code by Priti Oli, Rabin Banjade, Lasang Jimba Tamang, Vasile Rus

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Artificial intelligence in retinal image analysis for hypertensive retinopathy diagnosis: a comprehensive review and perspective by Rajendra Kankrale, Manesh Kokare

“…Overall, the integration of AI into RIA represents a considerable step forward in the early identification and treatment of HR, offering substantial benefits to both healthcare providers and patients.…”
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مادة العربية وتطويرها ببرنامج التعلم التفاعلي لترقية قدرة الطلبة على مهارة الاستماع by azwir azwir, Ikramul Fajri, Furqan Furqan

“…The result, after going through the required steps of conducting developmental research, indicated that the interactive learning program had an effective impact on improving students’ ability to listen since the result from the experts’ questionnaire was 84% and (the test) was greater than the result of the table (table) or 2.04 > 23. 66>2,75. …”
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DESIGNING SPEAKING MATERIAL FOR ENGLISH CONVERSATION CLUB (ECC) STUDENTS OF SMAN 2 KOTA PEKALONGAN by Muhammad Ivan Fauzi

“…The objectives of this study are: 1) to identify the target and learning needs of English Conversation Club students in learning English and 2) to design English learning materials for English Conversation Club in SMAN 2 Kota Pekalongan. …”
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From Camera Image to Active Target Tracking: Modelling, Encoding and Metrical Analysis for Unmanned Underwater Vehicles by Samuel Appleby, Giacomo Bergami, Gary Ushaw

“…We propose SWiMM_2.0, coupling a Unity simulation modelling of a BLUEROV UUV with a DRL backend. A pre-processing step exploits a state-of-the-art CMVAE, reducing dimensionality while minimising data loss. …”
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Evaluation of the Effectiveness of the UNet Model with Different Backbones in the Semantic Segmentation of Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Julieta Raquel Hernandez Vidales

“…Timely identification of crop conditions is relevant for informed decision-making in precision agriculture. The initial step in determining the conditions that crops require involves isolating the components that constitute them, including the leaves and fruits of the plants. …”
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Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation by James G. C. Ball, Katerina Petrova, David A. Coomes, Seth Flaxman

“…New computer vision technologies based on deep learning can be applied to the increasing volume of Earth observation data to generate novel insights and make predictions with unprecedented accuracy. …”
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Memory-like states created by the first ethanol experience are encoded into the Drosophila mushroom body learning and memory circuitry in an ethanol-specific manner. by Caleb Larnerd, Maria Nolazco, Ashley Valdez, Vanessa Sanchez, Fred W Wolf

“…It is unknown if these ethanol memory-like states are also encoded by the canonical learning and memory circuitry that is centered on the mushroom bodies. …”
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Robust prediction of chlorophyll-A from nitrogen and phosphorus content in Philippine and global lakes using fine-tuned, explainable machine learning by Karl Ezra Pilario, Eric Jan Escober, Aurelio de los Reyes V, Maria Pythias Espino

“…This paper presents a methodology using 8 popular machine learning (ML) models for estimating Chl-a concentration from nutrient content in lakes. …”
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Learning Al-Qur'an Hadith Using Study Tours to Improve Religious Moderation Attitudes and Socio-Cultural Literacy of Madrasah Aliyah Students by Zarkasi, Syamsul Ma’arif, Abdul Djamil, Ihsan, M. Afief Mundzir, Alfina Wildatul Fitriyah, Mochamad Tholib Khoiril Waro, Abdullah Hanapi

“… Purpose – This research aims to analyze how learning steps using study tours can improve the religious moderation and socio-cultural literacy of Madrasah Aliyah students. …”
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A Study on the Level of New Quality Productive Forces and Influencing Factors in China's Coastal Areas Based on TOPSIS-Integrated Learning Model by DAI Shanyu, CHE Bin

“…Firstly, this paper applies the entropy-weighted TOPSIS model to measure the development level of new quality productive forces in coastal provinces; secondly, the measurement results are used as the a priori sample pairs of the integrated learning model for training and testing. In addition, this paper introduces the SHAP model for visual analysis to reveal the degree of influence of each indicator on the new quality productive forces. …”
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Evaluating organic carbon in living and dead trees using GLCM features and explainable machine learning: insights from Italian national forest by Mehdi Fasihi, Alex Falcon, Giorgio Alberti, Luca Cadez, Francesca Giannetti, Antonio Tomao, Giuseppe Serra

“…The methodology is structured into five key steps. First, we extract Gray-Level Co-occurrence Matrix (GLCM) texture features from LiDAR-derived canopy height models to quantify spatial heterogeneity in forest structure. …”
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From prediction to practice: mitigating bias and data shift in machine-learning models for chemotherapy-induced organ dysfunction across unseen cancers by Heather Shaw, Pinkie Chambers, Matthew Watson, Luke Steventon, James Harmsworth King, Angelo Ercia, Noura Al Moubayed

“…Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. …”
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Nurturing humanism and professionalism in a clinical setting: A multicenter study to develop a framework for a learning module for clinical students. by Rita Mustika, Anyta Pinasthika, Nadia Greviana, Eti Poncorini Pamungkasari, Annang Giri Moelyo, Rahma Tsania Zhuhra

“…Meaningful integrated learning experiences, patient exposure, and reflection serve as the cornerstones of teaching-learning strategies while considering longitudinally explicit assessments.…”
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