Myriad of Traumatic Oral Soft Tissue Pathologies: A 12-Year Histopathological Experience by Madhur Sharma, Anjali Narwal, Gopikrishnan Vijayakumar, Mala Kamboj, Anju Devi

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Detecting Online Sexism: Integrating Sentiment Analysis with Contextual Language Models by Faiza Belbachir, Thomas Roustan, Assia Soukane

“…Nevertheless, detecting and preventing sexism on social networks remains a critical issue. Recent studies have leveraged language models such as transformers, known for their ability to capture the semantic nuances of textual data. …”
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A hybrid blockchain-based solution for secure sharing of electronic medical record data by Gang Han, Yan Ma, Zhongliang Zhang, Yuxin Wang

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The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

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Treatment Strategies for Distal Clavicle Fractures: A Narrative Review by Yue L, Huang C, Zhang J, Wang Z, Wang S, Sun H

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ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application by Rajib Kumar Halder, Mohammed Nasir Uddin, Md. Ashraf Uddin, Sunil Aryal, Sajeeb Saha, Rakib Hossen, Sabbir Ahmed, Mohammad Abu Tareq Rony, Mosammat Farida Akter

“…Chronic kidney diseases (CKDs) are a significant public health issue with potential for severe complications such as hypertension, anemia, and renal failure. …”
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Data-Driven Control Design for Complex Systems: Theory, Challenges, and Novel Applications by Chandar Kumar, Muhammad Sabih, Shubash Kumar, Zahid Ali, Ahmed Muddassir Khan

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The Application of Evidence Theory in Supplier Evaluation by WANG Guang-ze, YANG Gui-zhi, HU Nan-nan, ZHAO Li-hua

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Recent landscape research in Hungary by Péter Csorba, Dénes Lóczy, Gábor Mezosi

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Geospatial dataset on deforestation and urban sprawl in Dhaka, Bangladesh: A resource for environmental analysisMendeley Data by Md. Fahad Khan, Md. Rakibul Islam, Shanto Kumar Basak, Ahmed Imtiaz, Abhijit Bhowmik, Dip Nandi, Mashiour Rahman, Debajyoti Karmaker

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G&G Attack: General and Geometry-Aware Adversarial Attack on the Point Cloud by Geng Chen, Zhiwen Zhang, Yuanxi Peng, Chunchao Li, Teng Li

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Enhancing credit card fraud detection: highly imbalanced data case by Dalia Breskuvienė, Gintautas Dzemyda

“…This paper emphasizes the main issues in fraud detection and suggests a novel feature selection method called FID-SOM (feature selection for imbalanced data using SOM). …”
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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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Evaluation of Water Extraction Indices Using Landsat Satellite Images (Case Study: Gamasiab River of Kermanshah) by sayyad asghari, roholah jalilyan, noshin pirozineghad, aghil madadi, milad yadeghari

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Adversarial example defense algorithm for MNIST based on image reconstruction by Zhongyuan QIN, Zhaoxiang HE, Tao LI, Liquan CHEN

“…With the popularization of deep learning, more and more attention has been paid to its security issues.The adversarial sample is to add a small disturbance to the original image, which can cause the deep learning model to misclassify the image, which seriously affects the performance of deep learning technology.To address this challenge, the attack form and harm of the existing adversarial samples were analyzed.An adversarial examples defense method based on image reconstruction was proposed to effectively detect adversarial examples.The defense method used MNIST as the test data set.The core idea was image reconstruction, including central variance minimization and image quilting optimization.The central variance minimization was only processed for the central area of the image.The image quilting optimization incorporated the overlapping area into the patch block selection.Considered and took half the size of the patch as the overlap area.Using FGSM, BIM, DeepFool and C＆amp;W attack methods to generate adversarial samples to test the defense performance of the two methods, and compare with the existing three image reconstruction defense methods (cropping and scaling, bit depth compression and JPEG compression).The experimental results show that the central variance minimization and image quilting optimization algorithms proposed have a satisfied defense effect against the attacks of existing common adversarial samples.Image quilting optimization achieves over 75% classification accuracy for samples generated by the four attack algorithms, and the defense effect of minimizing central variance is around 70%.The three image reconstruction algorithms used for comparison have unstable defense effects on different attack algorithms, and the overall classification accuracy rate is less than 60%.The central variance minimization and image quilting optimization proposed achieve the purpose of effectively defending against adversarial samples.The experiments illustrate the defense effect of the proposed defense algorithm in different adversarial sample attack algorithms.The comparison between the reconstruction algorithm and the algorithm shows that the proposed scheme has good defense performance.…”
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A Deep Learning Approach to Unveil Types of Mental Illness by Analyzing Social Media Posts by Rajashree Dash, Spandan Udgata, Rupesh K. Mohapatra, Vishanka Dash, Ashrita Das

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Historical habitat mapping from black-and-white aerial photography: A proof of concept for post World War II Switzerland by Nica Huber, Matthias Bürgi, Christian Ginzler, Birgit Eben, Andri Baltensweiler, Bronwyn Price

“…Yet, map predictions sometimes varied substantially, indicating that the sampling strategies address different classification issues. Hence, we conclude that combining different sampling strategies for training data collection has the potential to improve the mapping, particularly in the case of multi-class classifications.…”
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Dynamic clustering of genomics cohorts beyond race, ethnicity—and ancestry by Hussein Mohsen, Kim Blenman, Prashant S. Emani, Quaid Morris, Jian Carrot-Zhang, Lajos Pusztai

“…For early modern classification systems, data collection was also considerably arbitrary and limited. …”
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Advanced genetic algorithm (GA)-independent component analysis (ICA) ensemble model for predicting trapped humans through hybrid dimensionality reduction by Enoch Adama Jiya, Ilesanmi B. Oluwafemi

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An Early Detection of Asthma Using BOMLA Detector by Md. Abdul Awal, Md. Shahadat Hossain, Kumar Debjit, Nafiz Ahmed, Rajan Dev Nath, G. M. Monsur Habib, Md. Salauddin Khan, Md. Akhtarul Islam, M. A. Parvez Mahmud

“…ADASYN algorithm has also been employed in the BOMLA detector to eradicate the issues created due to the imbalanced dataset. It has even been attempted to delineate how the ADASYN algorithm affects the classification performance. …”
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