Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study by Marlika Marceau, Sevan Dulgarian, Jacob Cambre, Pamela M Garabedian, Mary G Amato, Diane L Seger, Lynn A Volk, Gretchen Purcell Jackson, David W Bates, Ronen Rozenblum, Ania Syrowatka

“…ConclusionsParticipants favored integration to improve usability and optimize workplace efficiency by reducing the amount of time spent seeking answers to their medication- and disease-related questions. …”
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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…Next, Star Blocks from the StarNet framework are employed to optimize the C3k2 module in the Neck stage, thereby improving the localization accuracy of deep features without increasing network complexity. …”
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Statistical and Machine Learning Classification Approaches to Predicting and Controlling Peak Temperatures During Friction Stir Welding (FSW) of Al-6061-T6 Alloys by Assad Anis, Muhammad Shakaib, Muhammad Sohail Hanif

“…Some simulations showed temperatures exceeding the material’s melting point, indicating the need for improved thermal control. This was achieved by using three machine learning (ML) algorithms, i.e., Logistic Regression, k-Nearest Neighbors (k-NN), and Naive Bayes. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

“…This study employed multiple machine learning models to perform risk prediction and result exploration for first-trimester Down syndrome in East Asian populations, aiming to identify an optimal risk prediction model that will enhance future predictions of Down syndrome risk and improve the efficiency of the screening process.Patients and Methods: This study collected data from the Down syndrome screening database at Taipei Chang Gung Memorial Hospital from May 1, 2018, to February 29, 2024. …”
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Molecular biomarkers in salivary diagnostic materials: Point-of-Care solutions — PoC-Diagnostics and -Testing by Ziyad S. Haidar

“…Addressing these challenges requires continued research into improving assay sensitivity, data integration, and cost-effectiveness. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Through comprehensive evaluation using both synthetic and real-world traces from deep learning training workloads, our method demonstrates substantial improvements over state-of-the-art algorithms: achieving up to 45.1% reduction in average I/O latency, 32.5% improvement in throughput for critical applications, and 28.8% reduction in storage costs. …”
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PSO Tuned Super-Twisting Sliding Mode Controller for Trajectory Tracking Control of an Articulated Robot by Zewdalem Abebaw Ayinalem, Abrham Tadesse Kassie

“…Numerical simulations revealed that the tracking error and root mean square error (RMSE) improvements were approximately 18.33%, 16.66%, and 14.29% for PSO–STSMC compared to STSMC, and 79.50%, 78.04%, and 25.0% compared to PSO–SMC for each of the three joints under ideal conditions, respectively. …”
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An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology by Ismail Gassoumi, Lamjed Touil, Bouraoui Ouni, Abdellatif Mtibaa

“…Optimization for power is one of the most important design objectives in modern digital image processing applications. …”
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Synthesis of a reversible quantum Vedic multiplier on IBM quantum computers by Mojtaba Noorallahzadeh, Mohammad Mosleh

“…Abstract Quantum computers provide considerable potential to enhance computing technology, anticipated to surpass conventional computers by resolving intricate challenges that existing systems cannot tackle. They use quantum algorithms for improved performance and depend on reversible computations based on quantum physics and linear algebra. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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Skip-Connected CNN Exploiting BNN Surrogate for Antenna Modelling by Yubo Tian, Jinlong Sun, Zhiwei Zhu

“…The combination of evolutionary algorithms with full-wave electromagnetic (EM) simulation software is an effective method for antenna optimal design. …”
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Artificial intelligence tools for engagement prediction in neuromotor disorder patients during rehabilitation by Simone Costantini, Anna Falivene, Mattia Chiappini, Giorgia Malerba, Carla Dei, Silvia Bellazzecca, Fabio A. Storm, Giuseppe Andreoni, Emilia Ambrosini, Emilia Biffi

“…Results The study found that combining HRV and EDA features into a comprehensive dataset improved the synergistic representation of engagement compared to unimodal datasets. …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…This study introduces a machine learning-based framework for predicting vegetation flow resistance, incorporating nine ML methods, including SVM, XGBoost, and BP. To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
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Special Issue on Contemporary Research Studies in Operations Research, Business Analytics, and Business Intelligence by Viswanath Kumar Ganesan, S. Vinodh, Malolan Sundararaman, M. Vimala Rani, M. Mathirajan

“…Optimization Algorithms: Developing efficient algorithms to solve linear fractional transshipment problem with multi-objective linear fractional functions. 4. …”
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Fish Detection Using Deep Learning by Suxia Cui, Yu Zhou, Yonghui Wang, Lujun Zhai

“…Authors of this article have learned the necessity of platform upgrade from a previous AUV design project, and would like to share the experience of one task extension in the area of fish detection. Because most of the embedded systems have been improved by fast growing computing and sensing technologies, which makes them possible to incorporate more and more complicated algorithms. …”
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Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

“…Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou, Xiaoming Qin

“…Nowadays, spatio-temporal series prediction algorithms are emerging, but their prediction accuracy requires improvement. …”
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A neighborhood search-based heuristic for the dynamic vehicle routing problem by Wilton Gustavo Gomes da Costa, Ricardo Santos, Willy Alves de Oliveira Soler, Bianca de Almeida Dantas

“…The DSNR achieved improvements of 15% to 17% in terms of distance and final delivery costs.…”
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A Secure Data Collection Method Based on Deep Reinforcement Learning and Lightweight Authentication by Yunlong Wang, Jie Zhang, Guangjie Han, Dugui Chen

“…To address such challenges, we propose a lightweight chain authentication protocol for scalable IoT environments (LCAP-SIoT), which uses Physical Unclonable Functions (PUFs) and distributed authentication to secure communications, and a secure data collection algorithm, named LS-QMIX, which fuses the LCAP-SIoT and Q-learning Mixer (QMIX) algorithm to optimize the path planning and cooperation efficiency of the multi-UAV system. …”
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