Hybrid Machine Learning for IoT-Enabled Smart Buildings by Robert-Alexandru Craciun, Simona Iuliana Caramihai, Ștefan Mocanu, Radu Nicolae Pietraru, Mihnea Alexandru Moisescu

“…This paper presents an intrusion detection system (IDS) leveraging a hybrid machine learning approach aimed at enhancing the security of IoT devices at the edge, specifically for those utilizing the TCP/IP protocol. …”
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Hypothetical learning trajectory on cylinder with Bloom's taxonomy perspective by Hamida Izatul Jannah, Mohammad Faizal Amir

“…Addressing this gap, the present study aims to develop and evaluate a Hypothetical Learning Trajectory (HLT) grounded in Bloom’s taxonomy to enhance students' understanding of cylinders. …”
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Measuring Airtightness of High-Rise Buildings (Lessons Learned) by Stefanie Rolfsmeier, Emanuel Mairinger, Johannes Neubig, Thomas Gayer

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Review of learning materials of an ecology course at Universitas Terbuka by Yuni Tri Hewindati, Sri Kurniati Handayani, Aminudin Zuhairi, Raflen Aril Gerungan

“…Purpose – This article presented the results of studies that examined the appropriateness of the content, readability of printed learning materials and the effectiveness of external resources in ecology course offered at Universitas Terbuka. …”
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3D Model Classification Based on Contrastive Learning by QU Zhongshui, LIU Shan, GAO Yuan, DING Bo

“…At present, 3D model classification has been a research hotspot. …”
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Predicting the Performance of Students Using Deep Ensemble Learning by Bo Tang, Senlin Li, Changhua Zhao

“…The proposed method presents a new feature-ranking mechanism based on existing approaches. …”
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Estimation of Battery SoC using Reinforcement Learning by Mortabit Idriss, Rachid Aziz, Errifai Nidale, Boudmane Bilal

“…Our findings suggest that adaptive learning frameworks present a promising direction for the development of power management technologies for electric mobility solutions.…”
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Deep Learning for Traffic Scene Understanding: A Review by Parya Dolatyabi, Jacob Regan, Mahdi Khodayar

“…This review paper presents an in-depth analysis of deep learning (DL) models applied to traffic scene understanding, a key aspect of modern intelligent transportation systems. …”
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Representation Learning for Place Recognition Using MIMO Radar by Prashant Kumar Rai, Nataliya Strokina, Reza Ghabcheloo

“…Traditional radar perception often rely on point clouds derived from radar heatmap using CFAR filtering, which can result in the loss of valuable information, especially weaker signals crucial for accurate perception. To address this, we present a novel approach for representation learning directly from pre-CFAR heatmaps, specifically for place recognition using a high-resolution MIMO radar sensor. …”
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THE USE OF SOCIAL MEDIA FOR LEARNING ENGLISH: STUDENTS PERSPECTIVE by Muetia Safitri, Atik Yuliyani, Farida Hamid, Aminah Suriaman

“…However, to use social media effectively, itâs important to know studentâs perception as reference for teacher in using social media. Thus the present study was conducted to explore high-school studentsâ perception of social media use for English learning. 83 students of one private Senior High School in Depok, Indonesia, were involved in this study. …”
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Investigating the Adoption of Metaverse-Based Immersive Learning in TESOL by Saja Wardat, Mohammed Akour

“…A J48 decision tree validated by machine learning was able to predict 91.22% of IUM with good accuracy. …”
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ROBOT NAVIGATION IN INDOOR ENVIRONMENT THROUGH SELF LEARNING by Chandan Kalita, Kishore Kashyap, Mirzanur Rahman, Satyajit Sarma, Parvez Aziz Boruah

“…This data is then utilized to train a Machine Learning model, specifically based on Deep Reinforcement Learning techniques. …”
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Machine learning unravels the mysteries of glioma typing and treatment by Ying Dang, Youhu Chen, Jie Chen, Guoqiang Yuan, Yawen Pan

“…Gliomas, which are complex primary malignant brain tumors known for their heterogeneous and invasive nature, present substantial challenges for both treatment and prognosis. …”
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Deep learning enhanced quantum holography with undetected photons by Weiru Fan, Gewei Qian, Yutong Wang, Chen-Ran Xu, Ziyang Chen, Xun Liu, Wei Li, Xu Liu, Feng Liu, Xingqi Xu, Da-Wei Wang, Vladislav V. Yakovlev

“…In this report, we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms, resulting in vastly reduced noise and distortion, alongside a notable enhancement in spatial resolution. …”
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Machine Learning-Enabled Attacks on Anti-Phishing Blacklists by Wenhao Li, Shams Ul Arfeen Laghari, Selvakumar Manickam, Yung-Wey Chong, Binyong Li

“…Using real-world data and employing machine learning techniques, the Random Forest (RF) classifier emerged as the most effective among all tested supervised classifiers, achieving 100% accuracy in distinguishing APEs from regular users and enabling attackers to bypass blacklist detection. …”
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Learning spatial‐frequency interaction for generalizable deepfake detection by Tianbo Zhai, Kaiyin Lu, Jiajun Li, Yukai Wang, Wenjie Zhang, Peipeng Yu, Zhihua Xia

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Deep learning for predicting myopia severity classification method by WangMeiYu Xing, XiaoNa Li, JingShu Ni, YuanZhi Zhang, ZhongSheng Li, Yong Liu, YiKun Wang, Yao Huang

“…To improve the efficiency of myopia screening, this paper proposes a deep learning model, X-ENet, which combines the advantages of depthwise separable convolution and dynamic convolution to classify different severities of myopia. …”
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Synthesis and characterization of machine learning designed TADF molecules by Weimei Shi, Yan Li, Ziying Zhang, Zheng Tan, Shiqing Yang

“…In this study, we present a novel approach to the development of thermally activated delayed fluorescence (TADF) molecules with potentials for organic light-emitting diode (OLED) applications, leveraging machine learning (ML) algorithms to guide the materials design process. …”
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Cowpea leaf disease identification using deep learning by Rajesh Kannan Megalingam, Gowtham Gopakumar Menon, Swathi Binoj, Deepika Asandi Sai, Akhil Revi Kunnambath, Sakthiprasad Kuttankulangara Manoharan

“…Understanding the specific types of diseases present in a crop facilitates early detection and helps implement control measures. …”
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Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care by Rahul Kumar, Kyle Sporn, Akshay Khanna, Phani Paladugu, Chirag Gowda, Alex Ngo, Ram Jagadeesan, Nasif Zaman, Alireza Tavakkoli

“…Musculoskeletal tumors present a diagnostic challenge due to their rarity, histological diversity, and overlapping imaging features. …”
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