Development of a microwave low-pass filter based on a microstrip line projection mode by A. D. Yarlykov, O. A. Demin

“…Sections of microstrip lines having finite length are widely used to develop integrated circuits and microwave devices for various purposes, such as power dividers, directional couplers, attenuators, and filters. …”
Get full text

Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

“…The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. …”
Get full text

Path Algebra-Driven Classification Solution to Realize User-Centric Performance-Oriented Virtual Network Embeddings by Stelios Prekas, Panagiotis A. Karkazis, Panagiotis Trakadas

“…Traditional solutions like the shortest path algorithm and mono-constraint methodologies are inadequate to handle customized user-defined performance parameters and effectively classify physical resources according to these intricate demands. …”
Get full text

Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…This study proposes a systematic framework, termed VMD-RUN-Seq2Seq-Attention, for noise reduction, outlier detection, and wind speed prediction by integrating Variational Mode Decomposition (VMD), the Runge–Kutta optimization algorithm (RUN), and a Sequence-to-Sequence model with an Attention mechanism (Seq2Seq-Attention). …”
Get full text

Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…An Improved Particle Swarm Optimization (IPSO) algorithm was used to optimize this model, forming the IPSO-CNN-BiGRU-Attention hybrid model. …”
Get full text

Sensor‐Guided Smart Irrigation for Tomato Production: Comparing Low and Optimum Soil Moisture in Greenhouse Environments by Ibrahim Dirlik, Ferhat Uğurlar, Cengiz Kaya

“…Future research should explore the integration of advanced sensors, machine learning algorithms, and predictive models to further optimize irrigation strategies, with an emphasis on scalability and environmental impact. …”
Get full text

Hybrid Machine Learning-Based Fault-Tolerant Sensor Data Fusion and Anomaly Detection for Fire Risk Mitigation in IIoT Environment by Jayameena Desikan, Sushil Kumar Singh, A. Jayanthiladevi, Shashi Bhushan, Vinay Rishiwal, Manish Kumar

“…The proposed approach also deploys machine learning algorithms to dynamically adjust probabilistic models based on real-time sensor reliability, thereby improving prediction accuracy even in the presence of unreliable sensor data. …”
Get full text

Diurnal Variations of Infrared Land Surface Emissivity in the Taklimakan Desert: An Observational Analysis by Yufen Ma, Kang Zeng, Ailiyaer Aihaiti, Junjian Liu, Zonghui Liu, Ali Mamtimin

“…This study’s field observations of Light Source Efficiency (LSE) in the Taklamakan Desert have unveiled significant daily average variations across different wavelengths, with LSE values ranging from 0.827 at 9.1 μm to a peak of 0.969 at 12.1 μm, and notably, a substantial daily variation (DV) of Δε = 0.080 in the 14.3 μm band. …”
Get full text

Construction and validation of a nomogram for predicting 3-month outcome in elderly patients with nonvalvular atrial fibrillation-induced acute ischemic stroke by Yang Yang, Xiaohong Zhang

“…The nomogram also showed excellent calibration and clinical applicability, as confirmed by calibration curve analysis and DCA.ConclusionStroke history, NIHSS score, HbA1c, D-dimer, NLR, and LAD are independent risk factors for poor outcomes in elderly patients with NVAF-AIS. The nomogram, integrating these factors, provides intuitive, individualized predictions for the risk of poor outcomes, aiding in the selection of treatment options for these patients.…”
Get full text

Histogram Filter with Smoothing Parameter Setting by A. V. Ausiannikau, V. M. Kozel

“…The histogram filter is an easy-to-implement tool that can be easily integrated into any open distribution law identification (recognition) algorithm…”
Get full text

Informing Disaster Recovery Through Predictive Relocation Modeling by Chao He, Da Hu

“…This study explores the use of machine learning algorithms to improve the prediction of household relocation in the aftermath of disasters. …”
Get full text

Machine learning models for reinjury risk prediction using cardiopulmonary exercise testing (CPET) data: optimizing athlete recovery by Arezoo Abasi, Ahmad Nazari, Azar Moezy, Seyed Ali Fatemi Aghda

“…Machine learning (ML) algorithms offer promising capabilities in uncovering complex patterns within this data, allowing for more accurate injury risk assessment. …”
Get full text

Digital transformation of modern corporation management tools: the current state and development paths by V. A. Laptev, S. Yu. Chucha, D. R. Feyzrakhmanova

“…The authors distinguish three types of digital corporate governance: remote management (exercised by human individuals), smart management (based on algorithms designed by human engineers), and artificial intelligence (AI) management (that does not require human involvement). …”
Get full text

Predicting p53 Status in IDH‐Mutant Gliomas Using MRI‐Based Radiomic Model by Jiamin Li, Zhihong Lan, Xiao Zhang, Xiaoyun Liang, Hanwei Chen, Xiangrong Yu

Get full text

Sensor-Based Yield Prediction in Durum Wheat Under Semi-Arid Conditions Using Machine Learning Across Zadoks Growth Stages by Süreyya Betül Rufaioğlu, Ali Volkan Bilgili, Erdinç Savaşlı, İrfan Özberk, Salih Aydemir, Amjad Mohamed Ismael, Yunus Kaya, João P. Matos-Carvalho

“…In the same model, RMSE and MAE values were calculated as 0.49 and 0.37, respectively. …”
Get full text

Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model by Tingting Hu, Liheng Zhao, Xueling Zhao, Lin He, Xiaoli Zhong, Zhe Yin, Junjie Chen, Yanting Han, Ka Li

“…Abstract Objective The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery. …”
Get full text

Huffman coding-based data reduction and quadristego logic for secure image steganography by Irsyad Fikriansyah Ramadhan, Ntivuguruzwa Jean De La Croix, Tohari Ahmad, Andre Uzamurengera

“…To address these challenges, this study proposes a novel steganographic algorithm integrating two key innovations: (1) Enhancement of stego image quality via stego image’s segmentation into four images, reducing concentration-induced distortions, and (2) optimization of data embedding through Huffman coding through a lossless compression minimizing the embedding-induced distortions while maximizing payload capacity. …”
Get full text

Long-Term Monitoring of Coastal Water Quality Using Sentinel-2 Satellite Images and Google Earth Engine: The Case Study Izmir and Erdek Bays by O. Y. Altuntas, M. Saygi, I. Colkesen

“…The Coast 2 Regional CoastColor (C2RCC) algorithm was applied to retrieve Chl-a and TSM values. …”
Get full text

Model-Free Adaptive Control of an Active Half-Vehicle-Seat System Coupled with a Nonlinear Energy Sink Inerter (NESI) by Yuanyuan Zhang, Chunling Ren, Haodong Meng, Yong Wang

“…In order to reduce vehicle vibration and improve vehicle ride comfort and handling stability, a nonlinear energy sink inerter (NESI) is designed by combing an inerter and nonlinear energy sink (NES) for use in the seat suspension and vehicle suspension for the half-vehicle-seat (HVS) system; furthermore, a model-free adaptive control (MFAC) method based on the genetic algorithm is proposed to enhance the dynamic performance of the passive HVS system. …”
Get full text

Performance prediction of radio frequency based negative ion source using fusion neural network model by Yu Gu, Chundong Hu, Yang Li, Yuwen Yang, Yahong Xie, Qinglong Cui, Yuanzhe Zhao

“…Notably, the theoretical foundations and associated algorithms of the model are not limited to this ion source. …”
Get full text