Improving the Accuracy of Indoor Object Localization in the Internet of Things Using Recurrent Neural Networks (LSTM) in Challenging Environments by Hussein Aqeel Hussein, Mehdi Hamidkhani, Nasseer K. Bachache, Mohammadreza Soltan Aghaei

“…Increased optimization is a positive side-effect of harmonizing sparse autoencoders based on a feature selection process, and deep learning classifiers. …”
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Detection of Sugar Syrups in Honey Using Untargeted Liquid Chromatography–Mass Spectrometry and Chemometrics by Jule Hansen, Christof Kunert, Kurt-Peter Raezke, Stephan Seifert

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Exploring the role of moderators in the effectiveness of digital games for stem education: a systematic review and meta-analysis by Isnanik Juni Fitriyah, Sony Yunior Erlangga, Andik Wahyun Muqoyyidin, Septi Aprilia

“…Digital Games did have a strong positive impact on STEM learning outcomes (SMD = 1.26). …”
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Machine vision model using nail images for non-invasive detection of iron deficiency anemia in university students by Jorge Raul Navarro-Cabrera, Miguel Angel Valles-Coral, María Elena Farro-Roque, Nelly Reátegui-Lozano, Lolita Arévalo-Fasanando

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Educators’ perspective on artificial intelligence: equity, preparedness, and development by John Maurice Gayed

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Express Analysis of the Structural and Electronic Properties of Nanomaterials Using Big Data, Large Language Models and Generative Artificial Intelligence by N. A. Shymanski, A. V. Baglov, Kh. B. Musaev, O. N. Ruzimuradov, L. S. Khoroshko

“…The possibility of using large language models, generative machine learning and big data methods for predictive analysis of the electronic properties of nanostructures based on semiconductor materials is considered, without limiting the generality of this approach for other crystalline materials. …”
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Efficient Text Style Transfer Through Robust Masked Language Model and Iterative Inference by Osama Subhani Khan, Naima Iltaf, Usman Zia, Rabia Latif, Nor Shahida Mohd Jamail

“…We conduct experiments on two real world widely used product reviews sentiment datasets on both polarities, i.e., positive to negative and negative to positive. Comparison with various prompt-based as well as unsupervised learning based methods demonstrate state-of-the-art performance of our approach.…”
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VIOLET: Vectorized Invariance Optimization for Language Embeddings Using Twins by Mikhail E. Ram, G. Manju

“…Unlike conventional contrastive learning methods that rely on large batch sizes and hard negative mining to achieve performance, VIOLET operates exclusively on positive pairs. …”
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WCS-YOLOv8s: an improved YOLOv8s model for target identification and localization throughout the strawberry growth process by Sheng Gao, Sheng Gao, Gongpei Cui, Qiaohua Wang

“…This model proposes a data enhancement strategy based on the Warmup learning rate to stabilize the initial training process. …”
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Sample Inflation Interpolation for Consistency Regularization in Remote Sensing Change Detection by Zuo Jiang, Haobo Chen, Yi Tang

“…This principle underlies consistency regularization-based methods. However, while these methods enhance noise robustness, they also risk overlooking subtle but meaningful changes, leading to information loss and missed detections. …”
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Nonlinear compressive reduced basis approximation for PDE’s by Cohen, Albert, Farhat, Charbel, Maday, Yvon, Somacal, Agustin

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Retrospective cohort study of Helicobacter pylori infection and risk stratification using 6-year UBT data by Yan Chen, Miaojuan Wang, Jianfeng Wang, Jianfeng Wang

“…This study aims to develop a machine learning (ML)-based risk prediction model using 6-year longitudinal Urea Breath Test (UBT) data to identify metabolic alterations associated with chronic H. pylori infection.MethodsA retrospective cohort study was conducted using health examination data from 3,409 individuals between 2016 and 2021. …”
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TSINet: A Semantic and Instance Segmentation Network for 3D Tomato Plant Point Clouds by Shanshan Ma, Xu Lu, Liang Zhang

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Periods of high uncertainty: How fertility intentions in Russia changed during 2022–2023 by Elena Vakulenko, Dmitriy Gorskiy, Valeria Kondrateva, Ilya Trofimenko

“…OBJECTIVE: Our objective is to identify factors that influence decision-making in a low fertility context during a crisis, including both objective characteristics and subjective assessment of the current situation. METHODS: This paper is based on unique survey results, conducted in May 2023 (N = 7,967). …”
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Pedagogical Qualities of Artificial Intelligence-Assisted Teaching: An Exploratory Analysis of a Personal Tutor in a Voluntary Business Higher-Education Course by Nikša Alfirević, Marko Hell, Darko Rendulić

“…There is minimal research concerning the role of custom-trained artificial intelligence (AI) tools in higher education, with a lack of research concerning the pedagogical qualities of an AI-based personal tutor. To fill this literature gap, we examined how a custom GPT personal tutor shapes key teaching and learning qualities. …”
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XRGuard: A Model-Agnostic Approach to Ransomware Detection Using Dynamic Analysis and Explainable AI by M. Adnan Alvi, Zunera Jalil

“…Ransomware remains a persistent and evolving cybersecurity threat, demanding advanced and adaptable detection strategies. Traditional methods often fall short as signature-based systems are easily circumvented by emerging ransomware variants, while techniques like obfuscation and polymorphism add complexity to the detection process. …”
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Prognostic effect of CD74 and development of a radiomic model for predicting CD74 expression in non-small cell lung cancer by Yancheng Wang, Zhen Gao, Meng Li, Meng Li, Zhen Feng, Zhen Feng, Hui Wang, Hui Wang

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Bridging the gap in teacher SEL training: Designing and piloting an online SEL intervention with and for teachers by Sofia Oliveira, Andreia Cardoso, Mariana Oliveira Martins, Magda Sofia Roberto, Ana Margarida Veiga-Simão, Alexandra Marques-Pinto

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Exploring potential methylation markers for ovarian cancer from cervical scraping samples by Ju-Yin Lien, Lu Ann Hii, Po-Hsuan Su, Lin-Yu Chen, Kuo-Chang Wen, Hung-Cheng Lai, Yu-Chao Wang

“…Therefore, this study aimed to develop a methylation-based machine-learning model to stratify patients with ovarian cancer from the cervical scraping samples collected via Pap test. …”
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ACNet: An Attention–Convolution Collaborative Semantic Segmentation Network on Sensor-Derived Datasets for Autonomous Driving by Qiliang Zhang, Kaiwen Hua, Zi Zhang, Yiwei Zhao, Pengpeng Chen

“…Comparative experiments with classical segmentation networks, attention mechanisms, and convolution modules validate the effectiveness of the proposed approach. The proposed method demonstrates outstanding performance in sensor-based semantic segmentation tasks and is well-suited for environmental perception systems in autonomous driving.…”
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