MODEL PEMBELAJARAN KONTEKSTUAL PADA MATA PELAJARAN PAI DI SMP AL-AZHAR BANJAR PATROMAN by M. Badrut Tamam

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TSALATS MARAHIL LI TATHWIR TA'LIM AL-LUGHAH AL-ARABIYYAH FI INDONESIA by Muhajir Muhajir

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The Student’s Understanding and Response Towards Case Study Method in Arabic Language Research l Istijabatu wa Mafhum al-Thalabah fi Manhaj Dirasah al-Halah fi Bahts al-Lughah al-‘... by Ubaid Ridlo, Kojin Kojin, Kisno Umbar

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Taṭbīqu Ṭorīqotu al Musyābahah Fīy Ta’allumi al Mufrodāt al ‘Arobiyyah Liṭṭullābi al Indonisiyyin by Idrus Muchsin Bin Agil, Hasyim Amrullah Hasyim Amrullah, Miftachul Taubah Miftachul Taubah

Subjects: “…musyabahah method…”
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Comparative Study of Problem-Based Learning and Traditional Teaching Methods on Medical Students’ Outcomes in Pediatrics Clerkships by Ba H, Xu L, Gu Y, Li Y, Jiang X, Li X, Li S

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Dual feature-based and example-based explanation methods by Andrei Konstantinov, Boris Kozlov, Stanislav Kirpichenko, Lev Utkin, Vladimir Muliukha

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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…Although traffic encryption is employed to protect the privacy of IoT devices, attackers can still leverage Machine Learning (ML) and Deep Learning (DL) techniques to classify device types by analyzing packet characteristics, such as size and timing. …”
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Review of Fault Detection and Diagnosis Methods in Power Plants: Algorithms, Architectures, and Trends by Camelia Adela Maican, Cristina Floriana Pană, Daniela Maria Pătrașcu-Pană, Virginia Maria Rădulescu

“…The analysis reveals a significant transition from traditional statistical methods to machine learning (ML) and deep learning (DL) models, with over 70% of recent studies employing AI-driven approaches. …”
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Understanding the Role of Diversity in Ensemble-Based AutoML Methods for Classification Tasks by Salomey Osei, Andres R. Masegosa, Antonio D. Masegosa

“…Ensemble-based Automated Machine Learning (AutoML) methods have gained prominence for their ability to combine diverse machine learning models, achieving superior generalization performance. …”
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Identification of varietal and geographical origin of wines using artificial intelligence methods by Alexan Khalafyan, Zaual Temerdashev, Aleksey Abakumov, Evgeniy Gipich

“…The purpose of this study was to build models for identifying the varietal and geographical origin of wines using machine learning methods based on the mineral composition of 426 wine samples. …”
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Comparative Study on Rail Damage Recognition Methods Based on Machine Vision by Wanlin Gao, Riqin Geng, Hao Wu

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A Comprehensive Analysis of Data Augmentation Methods for Speech Emotion Recognition by Umut Avci

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Research Progress on Data-Driven Industrial Fault Diagnosis Methods by Liang Lei, Weibin Li, Shiwei Zhang, Changyuan Wu, Hongxiang Yu

“…Finally, the paper looks ahead to the future development of data-driven fault diagnosis methods, pointing out that data quality, interpretability of deep learning, and edge-based large models are important research directions that urgently require breakthroughs.…”
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Inversion Methods of Soil Hydraulic Parameters Based on Hyperspectral Characteristics by WU Yanmei, ZHU Han, LI Ji, LI Zixin, HE Jianliang, LIN Kairong, ZHUANG Luwen, DONG Chunyu

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Detecting Malicious .NET Executables Using Extracted Methods Names by Hamdan Thabit, Rami Ahmad, Ahmad Abdullah, Abedallah Zaid Abualkishik, Ali A. Alwan

“…As a result, there remains a significant knowledge gap regarding the development of effective detection methods tailored to .NET malware. This work introduces a novel framework for detecting malicious .NET executables using statically extracted method names. …”
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Quantum granular-ball generation methods and their application in KNN classification by Suzhen Yuan, Xiaojiang Tian, Wenping Lin, Shuyin Xia, Jeremiah D. Deng

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A Survey on Computational Methods in Drug Discovery for Neurodegenerative Diseases by Caterina Vicidomini, Francesco Fontanella, Tiziana D’Alessandro, Giovanni N. Roviello

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Algorithms and Methods for Individual Source Camera Identification: A Survey by Jaroslaw Bernacki, Rafal Scherer

“…This paper presents a comprehensive review of the existing methods and algorithms used for this purpose. It discusses approaches based on matrix noise analysis, including methods utilizing sensor pattern noise, photo response non-uniformity, statistical methods, aberrations analysis, as well as modern techniques based on deep neural networks and machine learning. …”
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Seismic fault identification method based on CBAM-TransUNet by Xin WANG, Wei ZHANG, Tongjun CHEN, Ao ZHANG, Dang ZHAO

“…Detection and identification of faults are crucial in the process of coal exploration and mining, and the traditional manual method of fault interpretation can no longer meet the needs of actual production, and the deep learning-based seismic fault interpretation method performs better in the field of fault segmentation. …”
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Extraction and discrimination of tobacco leaf shape based on landmark method by ZHONG Peige, ZHOU Yeying, ZHANG Yan, SHI Yi, GUO Yan, LI Baoguo, MA Yuntao

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