Advanced 5G Channel Estimation in mmWave MIMO Systems: Leveraging Compressive Sensing for Enhanced Performance by Zaid Albataineh, Mohammad Al Bataineh, Khaled Farouq Hayajneh, Raed Al Athamneh

“…In this paper, we propose an enhanced adaptive channel estimation technique that leverages compressive sensing (CS) principles to effectively mitigate pilot overhead while maintaining high estimation accuracy. The proposed approach combines compressive sampling matching pursuit (CoSaMP) and sparsity adaptive matching pursuit (SAMP) algorithms, augmented by a novel iterative reweighting strategy and adaptive thresholding mechanism. …”
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HammingVis: A visual analytics approach for understanding erroneous outcomes of quantum computing in hamming space by Jieyi Chen, Zhen Wen, Li Zheng, Jiaying Lu, Hui Lu, Yiwen Ren, Wei Chen

“…One highlights the overall structure of errors, while the other focuses on the impact of errors within important subspaces. …”
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Improving triage performance in emergency departments using machine learning and natural language processing: a systematic review by Bruno Matos Porto

“…Results Sixty studies covering 57 ML algorithms were included. Logistic Regression (LR) was the most used model, while eXtreme Gradient Boosting (XGBoost), decision tree-based algorithms with Gradient Boosting (GB), and Deep Neural Networks (DNNs) showed superior performance. …”
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Reinforcement Learning With Selective Exploration for Interference Management in mmWave Networks by Son Dinh-van, van-Linh Nguyen, Berna Bulut Cebecioglu, Antonino Masaracchia, Matthew D. Higgins

“…Numerical results demonstrate that selective exploration improves per-user spectral efficiency by up to 22.5% compared to scenarios without it. Additionally, our algorithms significantly outperform existing methods by 50% in terms of per-user spectral effciency and achieve 90% of the per-user spectral efficiency of the exhaustive search approach while requiring only 0.1% of its computational runtime.…”
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Refining CT image analysis: Exploring adaptive fusion in U-nets for enhanced brain tissue segmentation. by Bang-Chuan Chen, Chung-Yi Shen, Jyh-Wen Chai, Ren-Hung Hwang, Wei-Chuan Chiang, Chi-Hsiang Chou, Wei-Min Liu

“…However, Deep-Learning (DL) algorithms often generate false alarms (FA) beyond the cerebral region.…”
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A Comprehensive Survey on Machine and Deep Learning for Optical Communications by Mohammad Ali Amirabadi, S. Alireza Nezamalhosseini, Mohammad Hossein Kahaei, Lawrence R. Chen

“…Many algorithms have yet to be fully deployed in practical settings, underscoring the emerging nature of this research area. …”
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AI-powered blockchain technology in industry 4.0, a review by Mohsen Soori, Roza Dastres, Behrooz Arezoo

“…Artificial Intelligence (AI) algorithms can be employed to enhance the security of the blockchain networks in the era of industry 4.0. …”
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Building trust for traffic flow forecasting components in intelligent transportation systems via interpretable ensemble learning by Jishun Ou, Jingyuan Li, Chen Wang, Yun Wang, Qinghui Nie

“…However, most existing studies have concentrated on developing advanced algorithms or models to attain state-of-the-art forecasting accuracy. …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…Their effectiveness is limited by the attacks being controlled by the center, the limited data transmission capacity and also the viruses' ability to operate under-the-roof while using the mobile nodes which helps them move covertly. …”
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Automated Detection of Recent Mud Extrusions Using UAV Imagery and Deep Learning: A Comparative Analysis of Traditional and CNN-Based Approaches by M. Guastella, M. Guastella, A. Pisciotta, R. Martorana, A. D’Alessandro

“…Traditional algorithms rely on handcrafted features, while CNNs learn hierarchical representations directly from raw data. …”
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Discovering User Sentiment Patterns in Libraries with a Hybrid Machine Learning and Lexicon-Based Approach by Dini Nurmalasari, Dini Hidayatul Qudsi, Nessa Chairani, Heri R Yuliantoro

“…The high accuracy and effectiveness of the employed algorithms highlight the potential of this methodology for libraries. …”
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A new dataset for measuring the performance of blood vessel segmentation methods under distribution shifts. by Matheus Viana da Silva, Natália de Carvalho Santos, Julie Ouellette, Baptiste Lacoste, Cesar H Comin

“…Creating a dataset for training supervised machine learning algorithms can be a demanding task. This is especially true for blood vessel segmentation since one or more specialists are usually required for image annotation, and creating ground truth labels for just a single image can take up to several hours. …”
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Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review by Jade Basem, Racheed Mani, Scott Sun, Kevin Gilotra, Neda Dianati-Maleki, Reza Dashti

“…In the focus of cryptogenic strokes, there is promising research elucidating likely underlying cardiac causes and thus, improved treatment options and secondary stroke prevention. While many algorithms still require a larger knowledge base or manual algorithmic training, AI/ML in neurocardiology has the potential to provide more comprehensive healthcare treatment, increase access to equitable healthcare, and improve patient outcomes. …”
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Method for designing specialized computing systems on the basis of hardware and software cooptimization by I. E. Tarasov, P. N. Sovietov, D. V. Lulyava, N. A. Duksin

“…This is due to the specifics of the algorithms for placing and routing components of digital devices, which are not capable of optimizing solutions in a strict mathematical sense in an acceptable time. …”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…The success of developing effective detection algorithms is dependent on the availability of comprehensive datasets that integrate data from multiple synchronized sensors. …”
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Survival Prediction in Brain Metastasis Patients Treated with Stereotactic Radiosurgery: A Hybrid Machine Learning Approach by Tuğçe Öznacar, İpek Pınar Aral, Hatice Yağmur Zengin, Yılmaz Tezcan

“…The goal was to compare the performance of multiple algorithms and identify the most effective model for clinical use. …”
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Monitoring Pine Wilt Disease Using High-Resolution Satellite Remote Sensing at the Single-Tree Scale with Integrated Self-Attention by Wenhao Lv, Junhao Zhao, Jixia Huang

“…The use of self-attention algorithms enables models to extract more precise morphological features of discolored pine trees, enhancing user accuracy while potentially reducing production accuracy.…”
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Intraoperative Course of Left Ventricular Diastolic Strain in Surgical Valve Replacement for Severe Aortic Valve Stenosis by Katharina Seuthe, Eva Gerwin, Parwis Rahmanian, Bernd W. Böttiger, Deepak Borde, Jakob Labus

“…LV relaxation and filling improved during the intraoperative course of AVR as measured by diastolic strain, while most conventional grading algorithms were not able to detect these alterations.…”
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Single target tracking in high-resolution satellite videos: a comprehensive review by Xin Huang, Ding Wang, Qiqi Zhu, Ying Zheng, Qingfeng Guan

“…To the best of our knowledge, while some review work has been proposed for satellite videos object tracking, it has primarily concentrated on new datasets or has simply applied target tracking algorithms designed for ordinary videos directly to satellite videos for review. …”
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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…Single-objective optimisation focuses on optimising a single objective, while multi-objective optimisation considers multiple conflicting objectives. …”
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