Gyroscope-Based Smartphone Model Identification via WaveNet and EfficientNetV2 Ensemble by Erkan Kiymik, Ali Emre Ozturk

“…Leveraging the Google Smartphone Decimeter Challenge 2023–2024 dataset, which provides real-world gyroscope data from multiple smartphones mounted identically on vehicles during various driving tests, the challenging task of distinguishing between smartphone models under nearly identical motion conditions is addressed. …”
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EPPTA: Efficient partially observable reinforcement learning agent for penetration testing applications by Zegang Li, Qian Zhang, Guangwen Yang

“…However, real‐world pen‐testing tasks often involve incomplete knowledge of the target network system. …”
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Compressive sampling–based ultrasonic computerized tomography technique for damage detection in concrete-filled steel tube in a bridge by Binbin Li, Bo Liu, Fan Xu, Yang Liu, Wentao Wang, Tao Yang

“…The results indicate that the improved ultrasonic computerized tomography technique in compressive sampling framework has a great potential for rapid damage detection, which is a game-changing technique for accurate and cost-efficient damage detection in real-world applications.…”
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A Novel Approach for Model Interpretability and Domain Aware Fine-Tuning in AdaBoost by Raj Joseph Kiran, J. Sanil, S. Asharaf

“…Abstract The success of machine learning in real-world use cases has increased its demand in mission-critical applications such as autonomous vehicles, healthcare and medical diagnosis, aviation and flight safety, natural disaster prediction, early warning systems, etc. …”
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Unveiling the content of frontal feedback in challenging object recognition by Nastaran Darjani, Jalaledin Noroozi, Mohammad-Reza A. Dehaqani

“…Object recognition under challenging real-world conditions, including partial occlusion, remains an enduring focus of investigation in cognitive visual neuroscience. …”
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Generating context-specific sports training plans by combining generative adversarial networks. by Juquan Tan, Jingwen Chen

“…Existing machine learning (ML) and rule-based approaches cannot dynamically generate context-specific training programs, reducing their applicability in real-world scenarios. This study aims to develop a Generative Adversarial Network (GAN)- based framework to create context-specific training plans by integrating numeric attributes (e.g., age, heart rate) and motion features from video data. …”
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IALight: Importance-Aware Multi-Agent Reinforcement Learning for Arterial Traffic Cooperative Control by Lu WEI, Xiaoyan ZHANG, Lijun FAN, Lei GAO, Jian YANG

“…To enhance practicality and safety for real-world applications, we adopt a green duration optimisation strategy under a cyclic fixed phase sequence. …”
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Connecting electronic health records to a biomedical knowledge graph to link clinical phenotypes and molecular endotypes in atopic dermatitis by Francesca Frau, Paul Loustalot, Margaux Törnqvist, Nina Temam, Jean Cupe, Martin Montmerle, Franck Augé

“…Since biomedical knowledge graphs (BKGs) are limited to the integration of prior knowledge data and do not integrate real-world data (RWD) that would allow for the incorporation of patient level information, we propose a first step towards using RWD, BKGs and graph machine learning (ML) to enable a fully integrated precision medicine strategy. …”
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A Channel Attention-Driven Optimized CNN for Efficient Early Detection of Plant Diseases in Resource Constrained Environment by Sana Parez, Naqqash Dilshad, Jong Weon Lee

“…We evaluated the proposed method on four datasets: the benchmark plant village (PV), the data repository of leaf images (DRLIs), the newly curated plant composite (PC) dataset, and the BARI Sunflower (BARI-Sun) dataset, which includes diverse and challenging real-world images. The results show that the proposed performs comparably to state-of-the-art methods in terms of accuracy, false positive rate (FPR), model size, and runtime, highlighting its potential for real-world applications.…”
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A Novel Synthetic Minority Oversampling Technique for Multiclass Imbalance Problems by Jiao Wang, Norhashidah Awang

“…Multi-class imbalanced datasets present significant challenges in many real-world classification tasks, where certain classes are severely underrepresented. …”
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OVERCOMING SPEECH BARRIERS AT UNIVERSITY FOREIGN LANGUAGE CLASSES by Alla Durdas, Nataliia Furmanchuk, Anna Bondar, Olena Samar

“…The article highlights the importance of adapting teaching methods to students’ needs, focusing on real-world application of a foreign language like professional communication. …”

Real-Time Control System for Model Railway Based on SIMIS W Interlocking System by Dávid Macko, Ľubomír Hrmo, Jozef Hrbček, Peter Nagy

“…The system effectively replicates real-world signalling conditions with compatibility with existing protocols. …”
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Design and Implementation of a Reconfigurable Test Environment for Network Measurement Tools Based on a Control and Management Framework by Fatih Abut, Mehmet Kızıldağ

“…To be applicable to real-world networks, a realistic evaluation of network measurement tools requires the conditions of the test network to be as similar as possible to the networks in which they are later deployed. …”
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A Multiswarm Intelligence Algorithm for Expensive Bound Constrained Optimization Problems by Wali Khan Mashwani, Ruqayya Haider, Samir Brahim Belhaouari

“…Constrained optimization plays an important role in many decision-making problems and various real-world applications. In the last two decades, various evolutionary algorithms (EAs) were developed and still are developing under the umbrella of evolutionary computation. …”
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Modelling and Simulation of Distributed UAV Swarm Cooperative Planning and Perception by Haifeng Ling, Hongchuan Luo, Haisong Chen, Linyuan Bai, Tao Zhu, Yanjun Wang

“…The applicability of the proposed platform is verified by simulations with the real-world application. The simulation results demonstrate that the proposed system is viable.…”
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Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model by Amir Miraki, Pekka Parviainen, Reza Arghandeh

“…Through extensive evaluation on two real-world datasets focused on renewable energy and electricity demand, we demonstrate that our approach achieves state-of-the-art performance in probabilistic energy time series forecasting tasks. …”
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Achieving Equity via Transfer Learning With Fairness Optimization by Xiaoyang Wang, Chia-Hsuan Chang, Christopher C. Yang

“…Machine learning algorithms are increasingly used in real-world decision-making systems, raising concerns about potential biases and unfairness. …”
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Obscene beasts: the stage behind the scenes in A Midsummer Night’s Dream by Mathilde La Cassagnère

“…Mimesis, the art of imitating the real world on the stage, is all the more difficult if this real world consists of a beast—a wild, dangerous, supposedly “obscene” animal in the Latin sense: literally off-stage. …”
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Maximum Butterfly Generators Search in Bipartite Networks by Jianrong Huang, Guangyao Pang, Fei Hao

“…Bipartite graphs are widely used for modelling various real-world scenarios characterized with binary relations, such as, scholarly articles recommendation with author-paper relations, and product recommendation with user-product relations. …”
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Development of a multiaxial fatigue damage parameter and life prediction methodology for non-proportional loading by Sandip Suman, Alan Kallmeye, John Smith

“…Most of the prior studies on the prediction of fatigue lives have been limited to uniaxial loading cases, whereas real world loading scenarios are often multiaxial, and the prediction of fatigue life based upon uniaxial fatigue properties may lead to inaccurate results. …”
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