Comprehensive Approach to Developing Baseline Reference Ranges for Platelet Function by Olga B. Gordeeva, Maria S. Karaseva, Vasily A. Lastovka, Nato D. Vashakmadze, Margarita A. Soloshenko, Gregory V. Revunenkov, Kirill A. Valyalov, Viktor V. Altunin

“…The results of further research may contribute in the development of the algorithm for controlling antiplatelet therapy in patients with contraindications or with genetically determined low sensitivity to thrombocyte aggregation inhibitors based on acetylsalicylic acid.…”
Get full text

Interpretable machine learning approaches to assess the compressive strength of metakaolin blended sustainable cement mortar by Naseer Muhammad Khan, Liqiang Ma, Waleed Bin Inqiad, Muhammad Saud Khan, Imtiaz Iqbal, Muhammad Zaka Emad, Saad S. Alarifi

“…However, MEP and GEP algorithms expressed their output in the form of empirical equations which other black-box algorithms couldn’t produce. …”
Get full text

Joint Resource Scheduling of the Time Slot, Power, and Main Lobe Direction in Directional UAV Ad Hoc Networks: A Multi-Agent Deep Reinforcement Learning Approach by Shijie Liang, Haitao Zhao, Li Zhou, Zhe Wang, Kuo Cao, Junfang Wang

“…The simulation results show that the proposed attention mechanism-based MADRL algorithm enhances the performance of the MADRL algorithm by 22.17%. …”
Get full text

Classical simulability of constant-depth linear-optical circuits with noise by Changhun Oh

“…In this work, we investigate the complexity of shallow-depth linear-optical circuits under the effects of photon loss and partial distinguishability. By establishing a correspondence between a linear-optical circuit and a bipartite graph, we show that the effects of photon loss and partial distinguishability are equivalent to removing the corresponding vertices. …”
Get full text

An Improved Kernel Based Extreme Learning Machine for Robot Execution Failures by Bin Li, Xuewen Rong, Yibin Li

“…For improving the prediction accuracy of robot execution failures, this paper proposes a novel KELM learning algorithm using the particle swarm optimization approach to optimize the parameters of kernel functions of neural networks, which is called the AKELM learning algorithm. …”
Get full text

Design of hybridly-connected hybrid precoding in millimeter-wave massive MIMO system by Hongyu ZHAO, Hongyan YAO

“…In order to improve the spectral efficiency of hybridly-connected hybrid precoding,the optimal hybrid precoding matrix under the ideal conditions was firstly obtained by using the principle of successive interference cancellation (SIC).Secondly,the optimal hybrid precoding matrix was decomposed into the digital precoding matrix and the analog precoding matrix by using the gradient descent theory.Finally,considering the constant modulus constraint condition of the analog precoding matrix,the digital and analog precoding matrices were optimized by using the alternating minimization method aim to maximize the spectral efficiency.Due to the hybridly-connected structure,the proposed hybrid precoding design algorithm is significantly superior to the partially-connected and fully-connected hybrid precoding in terms of the system energy efficiency.Meanwhile,the algorithm does not increase any hardware complexity and only increases a small amount of computation of the hybridly-connected hybrid precoding.Computer simulation results exhibit that the proposed algorithm can improve the system spectral efficiency of the hybridly-connected hybrid precoding,and the upgrade of spectral efficiency is more significant especially in the conditions that the number of radio frequency (RF) links is greater than the number of data streams.Since the sub-blocks are not necessary to satisfy orthogonality conditions,the proposed algorithm is more suitable for practical application than the existing hybridly-connected hybrid precoding.…”
Get full text

A proximal policy optimization based deep reinforcement learning framework for tracking control of a flexible robotic manipulator by Joshi Kumar V, Vinodh Kumar Elumalai

“…This paper puts forward a policy feedback based deep reinforcement learning (DRL) control scheme for a partially observable system by leveraging the potentials of proximal policy optimization (PPO) algorithm and convolutional neural network (CNN). …”
Get full text

Predicting brain age for veterans with traumatic brain injuries and healthy controls: an exploratory analysis by John P. Coetzee, John P. Coetzee, Xiaojian Kang, Xiaojian Kang, Victoria Liou-Johnson, Victoria Liou-Johnson, Victoria Liou-Johnson, Ines Luttenbacher, Srija Seenivasan, Elika Eshghi, Daya Grewal, Siddhi Shah, Frank Hillary, Emily L. Dennis, Emily L. Dennis, Maheen M. Adamson, Maheen M. Adamson, Maheen M. Adamson

“…This may be driven by underlying biological changes resulting from the injury. Machine learning algorithms can use structural MRIs to give a predicted brain age (pBA). …”
Get full text

Principles of effective out-patient diagnostics of diffuse liver diseases by Komova A. G., M. V. Mayevskaya, V. T. Ivashkin

“…Abnormal liver functional tests were revealed in 30,6% of industrial city inhabitants — in 1461 of 4768 cases (232 patients were excluded from the study due to partial data loss), significantly more frequently in men in comparison to women, i.e. 49,7 and 25,5% respectively (p<0,001). …”
Get full text

Analysis of imaging differences between high-resolution CT and digital radiography chest films in pneumoconiosis screening by Lijuan LIU, Fenghong WANG

“…The HRCT review showed that, dispersively distributed micro nodule shadows and/or short-thread shape thin shadows in the lung in four patients, the rest two patients' HRCT images showed multiple localized pleural thickening and partial calcification and multiple nodules like pleural uplift thickening. …”
Get full text

Wideband Beam-Steering Flat Dielectric Lens Antenna for 5G Communications by Zahra Rahimian Omam, Saeideh Shad, Bahram Khalichi, Hani Mehrpouyan, Mohsen Khalily, Ahmed A. Kishk

“…A compact cylindrical-shaped flat dielectric lens (FDL) antenna, partially sandwiched within a parallel-plate waveguide (PPW), is presented. …”
Get full text

Spatio-Temporal Generalization of VIS-NIR-SWIR Spectral Models for Nitrogen Prediction in Sugarcane Leaves by Carlos Augusto Alves Cardoso Silva, Rodnei Rizzo, Marcelo Andrade da Silva, Matheus Luís Caron, Peterson Ricardo Fiorio

“…From the hyperspectral data, clustering analysis was performed to identify the patterns between the spectral bands for each region where the spectral readings were made, using the Partitioning Around Medoids (PAM) algorithm. Then, the LNC values were used to generate spectral models using Partial Least Squares Regression (PLSR). …”
Get full text

Combining UAV Multispectral Imaging and PROSAIL Model to Estimate LAI of Potato at Plot Scale by Shuang Li, Yongxin Lin, Ping Zhu, Liping Jin, Chunsong Bian, Jiangang Liu

“…Secondly, the hybrid models combining LUTs generated by PROSAIL and two machine learning algorithms (random forest (RF), Partial Least Squares Regression (PLSR)) are built to estimate potato LAI. …”
Get full text

Simultaneous Determination of Caffeine and Taurine in Energy Drinks by FT-MIR Spectroscopy Coupled with Multivariate Analysis by Marcela González-Vázquez, Ofelia Gabriela Meza-Márquez, Tzayhri Gallardo-Velázquez, Guillermo Osorio-Revilla, José Luis Velázquez Hernández, Maylet Hernández-Martínez

“…The best prediction model was obtained with the partial least squares (PLS1) algorithm; for taurine, the following values were obtained: determination coefficient of calibration (Rc2) = 0.9999, standard error of calibration (SEC) = 0.15, determination coefficient of validation (Rv2) = 0.9997, and standard error of prediction (SEP) = 0.16; for caffeine, Rc2 = 0.9999, SEC = 0.26, Rv2 = 0.9999, and SEP = 0.32. …”
Get full text

Network analysis of chronic disease among middle-aged and older adults in China: a nationwide survey by Chen Chen, Chen Chen, Hongfeng Wu, Likun Yang, Ke Kan, Xinping Zhang, Su Zhang, Rufu Jia, Xian Li

“…The IsingFit model was used to build the chronic disease co-morbidity network, where nodes represented diseases and edges reflected conditionally independent partial correlations. Community detection identified groups of closely related diseases using the Louvain algorithm. …”
Get full text

Development and Validation of Subchannel Analysis Program for LMR Based on FEM by ZHU Xinyang, CHEN Ronghua, WANG Jinshun, TIAN Jiahao, QIU Suizheng, SU Guanghui, TIAN Wenxi

“…To solve the coupled nonlinear partial differential equations, the Jacobians-Free Newton-Krylov (JFNK) algorithm was used. …”
Get full text

Design and simulation of a 5 KW solar-powered hybrid electric vehicle charging station with a ANN–Kalman filter MPPT and MPC-based inverter control for reduced THD by Youness Hakam, Hajar Ahessab, Ahmed Gaga, Mohamed Tabaa, Benachir El Hadadi

“…By integrating a Kalman filter with Artificial Neural Networks (ANN) for Maximum Power Point Tracking (MPPT), the system optimizes energy capture from photovoltaic (PV) panels, even in severe weather conditions and partial shading. Unlike traditional MPPT methods, which face challenges with multiple peaks in the Power–Voltage (P–V) curve, the hybrid algorithm enhances tracking accuracy, reduces errors, and cuts tracking time by up to 99.93%. …”
Get full text

Are Electromyography Data a Fingerprint for Patients with Cerebral Palsy (CP)? by Mehrdad Davoudi, Firooz Salami, Robert Reisig, Dimitrios A. Patikas, Nicholas A. Beckmann, Katharina S. Gather, Sebastian I. Wolf

“…DMC is a measure that can potentially serve as a partial predictor of outcomes, particularly in patients with poor pre-operative gait. …”
Get full text

Heat transfer in magneto-hybrid nanofluids with viscous and joule dissipation: a successive over relaxation analysis by Kamel Guedri, Aftab Ahmed Faridi, Shakeela Iqbal, Kashif Ali, Wasim Jamshed, Bandar M. Fadhl, Syed M. Hussain

“…Mathematical model of the problem is simulated through successive over-relaxation (SOR) methodology to obtain the numerical solutions of the governing nonlinear partial differential equations. The results are compared with existing literature to validate our numerical algorithm. …”
Get full text

Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars by Xing Wu, JiaCheng Liu, WeiChao Sun, Yang Liu, Joseph Michalski, Wei Tan, XiaoRong Qin, YongLiao Zou

“…We established a quantitative spectral model by combining the genetic algorithm and partial least squares regression (GA-PLSR) to predict the chemical properties (SiO2, Al2O3, Fe2O3) and index of laterization (IOL). …”
Get full text