Snoring Sound Recognition Using Multi-Channel Spectrograms by Ziqiang YE, Jianxin PENG, Xiaowen ZHANG, Lijuan SONG

“…This paper proposes a snoring sound detection algorithm using a multi-channel spectrogram and convolutional neural network (CNN). …”
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Dual-stream interactive mechanism with multi-modal hierarchical aggregation transformer for gait recognition by Jinghang Liu, Xiangyuan Xu, Yan Qiu, Chunzhi Wang

“…When processing multimodal data, existing algorithms frequently encounter challenges such as integration difficulties and insufficient fusion due to data heterogeneity across different modalities. …”
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Temporal scalability analysis of spectral remote sensing and Machine Learning-Based models for forest mapping in the tropical region of Nigeria by K. Pawłuszek-Filipiak, D. Włodarczyk, K. Stuchły, F.E. Ikuemonisan

“…To address this challenge, the study recommends prioritizing adaptive modeling strategies. These strategies involve continuously updating and retraining ML-RS models to ensure they remain accurate over different periods, thereby improving the reliability of forest mapping over time. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Modern multi-tiered data storage systems optimize file access by managing data across a hybrid composition of caches and storage tiers while using policies whose decisions can severely impact the storage system’s performance. Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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MRFB-Net: A Novel Attention Pooling Network With Modified Receptive Field Block for Uterine Fibroid Segmentation by Yun Jiang, Xiaokang Ding, Hongmei Zhou

“…The evaluation results demonstrate the accuracy and reliability of the proposed MRFB-Net, as well as its adaptability to different types of medical images. …”
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All-Digital Timing Recovery for Free Space Optical Communication Signals With a Large Dynamic Range and Low OSNR by Yunfeng Gu, Sheng Cui, Changjian Ke, Keji Zhou, Deming Liu

“…For this reason flexible digital coherent receivers (DCR) capable of adapting to different channel conditions have attracted much attention in the FSOC field. …”
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Ranking Assisted Unsupervised Morphological Disambiguation of Turkish by Hayri Volkan Agun, Ozkan Aslan

“…Furthermore, to reduce ambiguity in sentences from different genres with scarce samples, the proposed method is easily adaptable.…”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…Our research introduces a novel multisensor dataset designed to support the creation and evaluation of advanced multisensor fall detection algorithms. …”
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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…To improve multi-scale feature utilization, we designed the Dynamic-Weight-based Quad-Head Detector (DWQH), which dynamically assigns weights to different scales, enabling adaptive fusion and enhancing multi-scale feature representation. …”
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Log-Based Analysis of Creativity in the Context of Computational Thinking by Rotem Israel-Fishelson, Arnon Hershkovitz

“…We took a learning analytics log-based approach to evaluate measures of CT and creativity. We developed a Python algorithm to automatically analyze the logged solutions across four creativity measures. …”
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Reinforcement-Learning-Based Edge Offloading Orchestration in Computing Continuum by Ioana Ramona Martin, Gabriel Ioan Arcas, Tudor Cioara

“…We have chosen the Deep Q-Learning algorithm and adapted it to our workload offloading problem. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

“…However, the single model has poor adaptability to different types of subway stations. Compared with a single model, LightGBM-LSTM model equipped with merits of multiple models, fulfills a better function in forecasting and a better adaptability to different types of urban rail transit stations.…”
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SegMatch: semi-supervised surgical instrument segmentation by Meng Wei, Charlie Budd, Luis C. Garcia-Peraza-Herrera, Reuben Dorent, Miaojing Shi, Tom Vercauteren

“…For binary segmentation tasks, our algorithm was evaluated on the MICCAI Instrument Segmentation Challenge datasets, Robust-MIS 2019 and EndoVis 2017. …”
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Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children by Satrio Agung Wicaksono, Satrio Hadi Wijoyo, Fatmawati Fatmawati, Tri Afirianto, Diva Kurnianingtyas, Mochammad Chandra Saputra

“…Six test scenarios were conducted using different percentages of training data (90%, 80%, 70%, 60%, 50%, and 40%) to evaluate the reliability of the Naïve Bayes method. …”
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“Decision Tree” as a Tool for Analyzing the Psychodiagnostics Data Latent Connections by Elena V. Slavutskaya, Leonid A. Slavutsky

“…The study demonstrated the possibilities of the proposed data processing algorithm for evaluating the latent connections between psychological characteristics and for building the hierarchical structures corresponding to vertical system data analysis. …”
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Energy Management of a 1 MW Photovoltaic Power-to-Electricity and Power-to-Gas for Green Hydrogen Storage Station by Dalila Hidouri, Ines Ben Omrane, Kassmi Khalil, Adnen Cherif

“…Dynamic performance assessments were conducted under different conditions of solar radiation, temperature, and load, demonstrating the system’s adaptability. …”
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Improving Scheduling Efficiency: A Mathematical Approach to Multi-Operation Optimization in MSMEs by Reyner Pérez-Campdesuñer, Alexander Sánchez-Rodríguez, Margarita De Miguel-Guzmán, Gelmar García-Vidal, Rodobaldo Martínez-Vivar

“…A multi-criteria optimization method with weighted aggregation was used, employing either an exhaustive search or a heuristic algorithm with nested loops, in which multiple possible combinations of operational sequences were evaluated, considering several key indicators and their respective weights. …”
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Predicting nosocomial pneumonia of patients with acute brain injury in intensive care unit using machine-learning models by Junchen Pan, Zhen Yue, Jing Ji, Yongping You, Liqing Bi, Yun Liu, Xinglin Xiong, Genying Gu, Ming Chen, Shen Zhang

“…Despite differences in populations and algorithms, the models we constructed demonstrated reliable predictive performance.…”
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Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction by Zhengbiao Hu, Shuangshan Bu, Kai Wang, Qianqian Cao, Huanhuan Zheng, Jie Yang, Shanshan Chen, Yuemeng Wu, Wenkai Ren, Chenlei He

“…In this study, multiple machine learning algorithms were used to develop a non-invasive and improved model for the diagnosis of IgAN. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…Moreover, the research conducts a comparative evaluation of various machine learning models to identify the most effective algorithms for different climatic zones and crop types. …”
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