DETERMINATION OF MELDONIUM, γ-BUTYROBETAINE, AND CARNITINE IN BLOOD PLASMA BY HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY WITH MASS-SELECTIVE DETECTION by P. N. Sorokoumov, E. I. Savelieva, G. V. Karakashev, V. A. Kopeikin, A. S. Radilov

Get full text

Trade-off between gradient measurement efficiency and expressivity in deep quantum neural networks by Koki Chinzei, Shinichiro Yamano, Quoc Hoan Tran, Yasuhiro Endo, Hirotaka Oshima

Get full text

PREMALIGNANT LESIONS AND SYNCHRONOUS GASTRIC CANCER IN PATIENTS WITH LUNG AND HEAD AND NECK CANCER by О. V. Cheremisina, К. Yu. Menshikov, S. G. Afanasyev, M. V. Vusik

Get full text

PERFUSION LUNG SCINTIGRAPHY IN PATIENTS WITH A PULMONARY HYPERTENSION OF A VARIOUS ETIOLOGY by O. A. Arkhipova, T. V. Martynyuk, L. E. Samoilenko, V. B. Sergienko, I. Ye. Chazova

Get full text

Real-Time Analysis of Basketball Sports Data Based on Deep Learning by Peng Yao

“…The second part is the analysis and research of the action recognition algorithm based on the convolution of the space-time graph. …”
Get full text

Golay Coded Sequences in Synthetic Aperture Imaging Systems by Ihor TROTS, Yuriy TASINKEVYCH, Andrzej NOWICKI, Marcin LEWANDOWSKI

Get full text

Illustration image style transfer method design based on improved cyclic consistent adversarial network. by Xiaojun Wang, Jing Jiang

“…With the change of peak signal-to-noise ratio, the accuracy of the research algorithm has been greater than 95.00%. Practical application found that the color of the image obtained by the research method is more gorgeous and the line features are more obvious. …”
Get full text

BIMLP Model Based on Deep Learning for Predicting Electrical Load Demand by Somayeh Talebzadeh, Reza Radfar, Abbas Toloei Ashlaghi

“…To address this challenge, this research proposes a novel hybrid machine-learning approach for predicting electricity demand. …”
Get full text

An Enhanced Shuffle Attention with Context Decoupling Head with Wise IoU Loss for SAR Ship Detection by Yunshan Tang, Yue Zhang, Jiarong Xiao, Yue Cao, Zhongjun Yu

Get full text

Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

Get full text

Detection of external defects on potatoes by hyperspectral imaging technology and image processing method by Su Wenhao, Liu Guishan, He Jianguo, Wang Songlei, He Xiaoguang, Wang Wei, Wu Longguo

“…The traditional classification method has low efficiency and poor objectivity, costs big labor intensity, and is difficult to identify shortcomings through it.In order to realize the accurate and fast classification of potatoes in the process of actual processing, various potatoes with external defects were detected in spectral region of 400 - 1 000 nm using hyperspectral image technology, and an online nondestructive testing method was established by principal component analysis of characteristic wavelengths and image subtraction algorithm.Six defective potato types (mechanical damage, hole, scab, surface bruise, sprout, green skin, normal) and one qualified potato type were used as the research objects in this study, and their hyperspectral images were obtained, respectively. …”
Get full text

A statistical method for high-throughput emergence rate calculation for soybean breeding plots based on field phenotypic characteristics by Yan Sun, Mengqi Li, Meiling Liu, Jingyi Zhang, Yingli Cao, Xue Ao

“…In this study, UAV (Unmanned Aerial Vehicle)-scale data combined with ground measurement data were used as the research object to explore the feasibility of improving the throughput, efficiency, and accuracy of breeding screening under intensive soybean planting. …”
Get full text

Evaluation of Soil Moisture Retrievals from a Portable L-Band Microwave Radiometer by Runze Zhang, Abhi Nayak, Derek Houtz, Adam Watts, Elahe Soltanaghai, Mohamad Alipour

Get full text

Exploiting compressed sensing and polynomial-based progressive secret image sharing for visually secure image selection encryption with authentication by Zhihua Gan, Shiping Song, Lin Zhou, Daojun Han, Jiangyu Fu, Xiuli Chai

Get full text

Implementasi Algoritma Mickey 2.0 untuk Mengamankan Komunikasi Data pada Perangkat Bluetooth Low Energy by Amelia Dwi Rochani, Ari Kusyanti, Fariz Andri Bakhtiar

“…In this research, Mickey 2.0 algorithm is used for encryption. …”
Get full text

Spatially optimized allocation of water and land resources based on multi-dimensional coupling of water quantity, quality, efficiency, carbon, food, and ecology by Yingbin Wang, Haiqing Wang, Jiaxin Sun, Peng Qi, Wenguang Zhang, Guangxin Zhang

“…The research on optimizing agricultural water and land resources is significant for improving resource utilization efficiency, ensuring food security, protecting the ecological environment, and promoting sustainable economic development. …”
Get full text

Formation of a heterogeneous group of UAVS with a reasonable number of false and real drones by Volodymyr Prymirenko, Andrii Demianiuk, Roman Shevtsov, Serhii Bazilo, Andrey Pilipenko, Mykola Vovchanskyi

“…The subject of scientific research is the joint use of false and real unmanned aerial vehicles (UAVs) as part of a heterogeneous group of UAVs to perform military tasks. …”
Get full text

Lightweight Encryption Technique to Enhance Medical Image Security on Internet of Medical Things Applications by Mohammad Kamrul Hasan, Shayla Islam, Rossilawati Sulaiman, Sheroz Khan, Aisha-Hassan Abdalla Hashim, Shabana Habib, Mohammad Islam, Saleh Alyahya, Musse Mohamed Ahmed, Samar Kamil, Md Arif Hassan

“…The importance of image security in the field of medical imaging is challenging. Several research works have been conducted to secure medical healthcare images. …”
Get full text

Utilizing machine learning and bioinformatics analysis to identify drought stress responsive genes in wheat (Triticum aestivum L.) by Jiabei He, Jiabei He, Baoyue Cui, Baoyue Cui, Pingzeng Liu, Pingzeng Liu, Xianyong Meng, Xianyong Meng, Jun Yan, Jun Yan

“…Among the various machine learning models, the random forest algorithm performed best in identifying drought stress-responsive genes. …”
Get full text

Enhancing landslide susceptibility modelling through a novel non-landslide sampling method and ensemble learning technique by Chao Zhou, Yue Wang, Ying Cao, Ramesh P. Singh, Bayes Ahmed, Mahdi Motagh, Yang Wang, Ling Chen, Guangchao Tan, Shanshan Li

Get full text