Computationally efficient solution for finding the current density on the illuminated and shadow sides of an infinitely thin circular disk by Dmitry K. Ketukh

“…The aim of this paper is to eliminate this disadvantage by forming a computationally efficient algorithmic solution based on the method of moments and allowing numerically to set a smooth approximation of the surface current density on the illuminated and shadow sides of an infinitely thin ideally conducting circular disk. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…This narrative review outlines the current applications and considerations of artificial intelligence (AI) for diagnosis, management, and prognosis in rheumatoid arthritis (RA), axial spondyloarthritis (axSpA), and psoriatic arthritis (PsA). …”
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Survey on Backdoor Attacks on Deep Learning: Current Trends, Categorization, Applications, Research Challenges, and Future Prospects by Muhammad Abdullah Hanif, Nandish Chattopadhyay, Bassem Ouni, Muhammad Shafique

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Increasing pathogenic germline variant diagnosis rates in precision medicine: current best practices and future opportunities by Sonam Dukda, Manoharan Kumar, Andrew Calcino, Ulf Schmitz, Matt A. Field

“…While interpreting genetic variation via standards such as ACMG guidelines is increasingly being recognized as a gold standard approach, the underlying datasets and algorithms recommended are often slow to incorporate additional data types and methodologies. …”
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Exploring the Current Applications and Future Implications of Artificial Intelligence in Public Health Dentistry: A Narrative Review by Tanushri Mahendra Dalvi, Rajeshri Kotwadekar, Shrivardhan R Kalghatgi, Priyanka Paul Madhu, Priyanka Methildeotare

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Right ventricular mechanical support as a bridge to lung transplantation: A literature review of current practices by Michaela Orlitová, Bert Demeulenaere, Dieter Van Beersel, Dirk E. Van Raemdonck, Robin Vos, Laurens J. Ceulemans, Steffen Rex, Laurent Godinas, Tom Verbelen, Arne P. Neyrinck

“…We aim to synthesize current evidence on RVD/RVF assessment and management in BTT patients requiring ECLS, providing a foundation to aid development of standardized clinical algorithms.A scoping literature search across PubMed, Embase, Web of Science, Cochrane Library, and grey literature was performed. …”
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Current Status of Application of Spaceborne GNSS-R Raw Intermediate-Frequency Signal Measurements: Comprehensive Review by Qiulan Wang, Jinwei Bu, Yutong Wang, Donglan Huang, Hui Yang, Xiaoqing Zuo

“…This article provides a comprehensive overview of the current status of the measurement of raw IF signals from spaceborne GNSS-R in multiple application fields. …”
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Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review by Claire R. van Genugten, Claire R. van Genugten, Melissa S. Y. Thong, Melissa S. Y. Thong, Melissa S. Y. Thong, Wouter van Ballegooijen, Wouter van Ballegooijen, Wouter van Ballegooijen, Annet M. Kleiboer, Annet M. Kleiboer, Donna Spruijt-Metz, Arnout C. Smit, Mirjam A. G. Sprangers, Mirjam A. G. Sprangers, Yannik Terhorst, Yannik Terhorst, Heleen Riper, Heleen Riper, Heleen Riper

“…This review evaluates the current state of JITAIs in the field of mental health including their alignment with Nahum-Shani et al.'…”
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A Voting-Based Star Identification Algorithm Using a Partitioned Star Catalog by Xu He, Lei Zhang, Jiawei He, Zhiya Mu, Zhuang Lv, Jun Wang

“…Experimental results indicate an average identification rate of 99.760% and an average identification time of 8.861 milliseconds, exhibiting high robustness against position errors, magnitude errors, and false stars. The proposed algorithm presents a clear advantage over other common star identification methods, meeting the current requirement for star sensors with high star identification speed and a high identification rate.…”
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MULTI-OBJECTIVE OPTIMIZATION DESIGN FOR CUTTING MECHANISM OF ROADHEADER BASED ON IMPROVED GENETIC ALGORITHM by MAO Jun, PAN DeWen, XIE Miao, ZHENG GuangHui

“…This paper takes motion parameters and structure parameters of cutting mechanism for design variables and optimizes multi-objective function of comprehensive performance of cutting mechanism based on the improved genetic algorithm. Optimization results show that cutting dust,quantity of pick consumption,specific density consumption and load fluctuation of roadheader are decreased accordingly and productivity is increased significantly,which effectively improve the whole performance of the machine and accord with development trend of the roadheader in line with the current and future.…”
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Transportation Path Optimization of Modern Logistics Distribution considering Hybrid Tabu Search Algorithm by Jinjin Guo, Huiying Zhang, Guie Sun

“…The optimization of transportation path for distribution vehicles, which is about the mixed tabu search method, can not only reduce the cost but also improve the optimization of the vehicle transportation path. This algorithm first studies the current situation of the logistics distribution vehicle transportation path and then uses the hybrid tabu search method to calculate the vehicle transportation path. …”
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Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

“…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
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FORMAL CONDITIONS OF STEGANOGRAPHIC METHOD’S SUSTAINABILITY TO COMPRESSION ATTACKS AND THEIR IMPLEMENTATION IN NEW STEGANOGRAPHIC ALGORITHM by Kobozeva A.A., Melnik M.A.

“…The algorithm is stable to compression, including low compression rate. …”
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A distributed CRN resource allocation algorithm based on CBR and cooperative Q-learning by Lin XU, Zhijin ZHAO

“…In order to solve the problem of channel and power allocation in distributed cognitive radio networks (CRN),a case-based reasoning (CBR) and cooperative Q-learning algorithm was proposed.In order to optimize the Q initialization of Q-learning algorithm,the current problem and the historical case were matched according to the similarity function,the Q value of the matching case was extracted and normalized as the initial value.Cooperative Q-learning was based on the total reward value,and each agent integrates the Q values of other agents with higher reward values with different weights to gain learning experience to reduce unnecessary exploration.Simulations show that the proposed algorithm can improve the energy efficiency of the cognitive system’s channel and power allocation,and accelerate the convergence speed of the system.…”
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Non-invasive respiratory support paths in hospitalized patients with COVID-19: proposal of an algorithm by J.C. Winck, R. Scala

“…Despite the accumulated data in favor of the use of different Non-invasive Respiratory therapies in COVID-19 related Acute Respiratory Failure, it is not fully understood when start, escalate and de-escalate the best respiratory supportive option for the different timing of the disease. Based on the current published experience with Non-invasive Respiratory therapies in COVID-19 related Acute Respiratory Failure, we propose an algorithm in deciding when to start, when to stop and when to wean different NIRT. …”
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Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer by Xiaorui Zhang, Xingyuan Xu, Hengliang Shi

“…An innovative adaptive Kalman Filtering (KF) algorithm based on innovation covariance is proposed. …”
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From philosophy to algorithms: a commentary on the evolution of human behavior and the role of artificial intelligence by Luca Vascelli

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A distributed CRN resource allocation algorithm based on CBR and cooperative Q-learning by Lin XU, Zhijin ZHAO

“…In order to solve the problem of channel and power allocation in distributed cognitive radio networks (CRN),a case-based reasoning (CBR) and cooperative Q-learning algorithm was proposed.In order to optimize the Q initialization of Q-learning algorithm,the current problem and the historical case were matched according to the similarity function,the Q value of the matching case was extracted and normalized as the initial value.Cooperative Q-learning was based on the total reward value,and each agent integrates the Q values of other agents with higher reward values with different weights to gain learning experience to reduce unnecessary exploration.Simulations show that the proposed algorithm can improve the energy efficiency of the cognitive system’s channel and power allocation,and accelerate the convergence speed of the system.…”
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Reference frame list optimization algorithm in video coding by quality enhancement of the nearest picture by Junyan HUO, Ruipeng QIU, Yanzhuo MA, Fuzheng YANG

“…Interframe prediction is a key module in video coding, which uses the samples in the reference frames to predict those in the current picture, thus helps to represent the complex video by transmitting a small amount of the prediction residual.In lossy video coding, the qualities of reference frames are affected by the quantization distortion, which lead to poor prediction accuracy and performance degradation.Targeted at the low latency video services, a reference frame list optimization algorithm was proposed, which enhanced the quality of the nearest reference frame by a deep learning-based convolutional neural network, and integrated the enhanced reference frame into the reference frame list to improve the accuracy of interframe prediction.Compared with H.265/HEVC reference software HM16.22, the proposed algorithm provides BD-rate savings of 9.06%, 14.92% and 13.19% for Y, Cb and Cr components, respectively.…”
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