FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…Compared to state-of-the-art RGB-IR object detection algorithms, our method strikes a better balance between detection accuracy and computational efficiency while exhibiting strong robustness across diverse detection scenarios.…”
Get full text

Myocardial revascularization in diabetic patients presenting with critical limbischemia by Ivan Ivanovich Dedov, Victor Yur'evich Kalashnikov, Konstantin Vladimirovich Melkozerov

“…Macroangiopathy continues to bethe predominant complication while coronary heart disease is the main cause of mortality.This paper considers clinical features of diabetic patientswith coronary heart disease and critical limb ischemia; various aspects of optimal drug therapy, preoperative examination and diagnostics precedingvascular non-cardiac surgery; preoperative risk assessment; indications for coronary angiography and myocardial revascularization. …”
Get full text

Machine learning approaches for predicting frailty base on multimorbidities in US adults using NHANES data (1999–2018) by Teng Li, Xueke Li, Haoran XU, Yanyan Wang, Jingyu Ren, Shixiang Jing, Zichen Jin, Gang chen, Youyou Zhai, Zeyu Wu, Ge Zhang, Yuying Wang

“…We used areas under the receiver operating characteristic curve (AUC) and area under the precision-recall curve (AU-PRC) to evaluate six algorithms, select the optimal model, and test the discrimination and consistency of the optimal model. …”
Get full text

A Stochastic-Variational Model for Soft Mumford-Shah Segmentation by Jianhong (Jackie) Shen

“…In contemporary image and vision analysis, stochastic approaches demonstrate great flexibility in representing and modeling complex phenomena, while variational-PDE methods gain enormous computational advantages over Monte Carlo or other stochastic algorithms. …”
Get full text

Trajectory Tracking Nonlinear Hybrid Control of Automated Guided Vehicles by Antonio Sánchez-Rodríguez, Eduardo Bayona, J. Enrique Sierra-García, Matilde Santos

“…The stability of the controller is demonstrated for any differentiable trajectory. When a PID optimized with genetic algorithms is compared with the proposed controller for several trajectories, the LPC outperforms it in all cases.…”
Get full text

Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. …”
Get full text

Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems by Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

“…Diabetes is a global health challenge, and while current treatments offer relief, they often fall short in achieving optimal control and long-term outcomes. …”
Get full text

Decentralized Energy Swapping for Sustainable Wireless Sensor Networks Using Blockchain Technology by Umar Draz, Tariq Ali, Sana Yasin, Mohammad Hijji, Muhammad Ayaz, EL-Hadi M. Aggoune

“…The system is built using NS-3 to simulate node behavior, energy usage, and network dynamics, while Python manages the blockchain architecture, cryptographic security, and trading algorithms. …”
Get full text

AI powered blockchain framework for predictive temperature control in smart homes using wireless sensor networks and time shifted analysis by Cong Feng, Ahmed Kateb Jumaah Al-Nussairi, Mustafa Habeeb Chyad, Narinderjit Singh Sawaran Singh, Jianyong Yu, Amirfarhad Farhadi

“…Abstract In the context of smart homes, efficiently managing temperature control while optimizing energy consumption and ensuring data security remains a significant challenge. …”
Get full text

Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis by Ali Nabavi, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Farimah Safari

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
Get full text

Machine Learning Modeling of Foam Concrete Performance: Predicting Mechanical Strength and Thermal Conductivity from Material Compositions by Leifa Li, Wangwen Sun, Askar Ayti, Wangping Chen, Zhuangzhuang Liu, Lauren Y. Gómez-Zamorano

“…The analysis revealed that the water-to-cement ratio (W/C) and cement content were the most influential factors for mechanical properties, while density and the coarse-to-fine aggregate ratio (Cag/Fag) had the greatest impact on thermal conductivity. …”
Get full text

Water-Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP-Hard Problems by Fernando Rubio, Ismael Rodríguez

“…Many water-based optimization metaheuristics have been introduced during the last decade, both for combinatorial and for continuous optimization. …”
Get full text

About designing a planned education system in an existing corporate infrastructure by D. T. Gedenidze, A. V. Sinitsyn

“…Despite the availability of solutions for corporate training on the market, developing your own system is still the optimal solution for a large company, allowing you to satisfy all the needs of employees and managers in managing corporate training, as well as the most optimal way to integrate the system into the existing over many years, the company’s technological infrastructure, while avoiding the involvement of thirdparty specialists.…”
Get full text

Energy-Efficiency Maximization in Backscatter Communication-Based Non-Orthogonal Multiple Access System: Dinkelbach and Successive Convex Approximation Approaches by Dingjia Lin, Tianqi Wang, Kaidi Wang, Zhiguo Ding

“…Two algorithms, Dinkelbach based on penalty semidefinite relaxation (SDR) and successive convex approximation (SCA), are proposed as high-performance and low-complexity solutions, respectively. …”
Get full text

Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…IoT-connected bins transmit data to a central server, which uses blockchain to ensure secure, transparent data storage. AI algorithms, including machine learning (ML) and deep learning (DL), classify waste in real-time, optimizing waste collection and recycling. …”
Get full text

Resource allocation mechanism in the TWDM-PON and C-RAN joint architecture with hybrid energy supply by Ruyan WANG, Ningning XU

“…Aiming at the problems of low resource utilization rate,high energy consumption and poor user service quality in the existing virtualized Cloud Radio Access Network,an energy-aware virtualized resource allocation mechanism with hybrid energy supply was proposed.According to the energy sources and energy consumption of different network devices,energy arrival and energy consumption models were established.Furthermore,under the premise of guaranteeing the quality of user services,considering proportional fairness and energy consumption optimization,distributed algorithms based on asynchronous update were used to allocate resources and harvested energy for different types of virtual cloud radio access networks and user virtual base stations to effectively improve the energy efficiency of network.The simulation results show that the proposed resource allocation mechanism can reduce energy consumption while effectively reducing the latency and improving the throughput.…”
Get full text

Group twirling and noise tailoring for multiqubit controlled phase gates by Guoding Liu, Ziyi Xie, Zitai Xu, Xiongfeng Ma

“…Specifically, for multiqubit controlled phase gates, which are essential in quantum algorithms and directly implementable in practice, we determine optimal twirling groups within the realm of classically replaceable unitary operations. …”
Get full text

A stacked ensemble machine learning model for the prediction of pentavalent 3 vaccination dropout in East Africa by Meron Asmamaw Alemayehu, Shimels Derso Kebede, Agmasie Damtew Walle, Daniel Niguse Mamo, Ermias Bekele Enyew, Jibril Bashir Adem

“…While RF and GLM meta-learners were also evaluated, they were outperformed by the XGBoost meta-learner. …”
Get full text

Contrast-enhanced ultrasound radiomics model for predicting axillary lymph node metastasis and prognosis in breast cancer: a multicenter study by Shi Yu Li, Yue Ming Li, Yong Qi Fang, Zhi Ying Jin, Jun Kang Li, Xiao Meng Zou, Si Si Huang, Rui Lan Niu, Nai Qing Fu, Yu Hong Shao, Xuan Tong Gong, Mao Ran Li, Wei Wang, Zhi Li Wang

“…LASSO regression was employed to select radiomic features (RFs), while eight machine learning algorithms were utilized to construct radiomic models based on US, CDFI, and CEUS. …”
Get full text

Biobjective Scheduling for Joint Parallel Machines with Sequence-Dependent Setup by Taking Pareto-Based Approach by Wichai Srisuruk, Kanchala Sudtachat, Paramate Horkaew

“…The resultant manufacturing plans obtained by these algorithms are thoroughly assessed and discussed.…”
Get full text