Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…In treatment planning, AI could improve approaches by optimizing surgical resection, radiotherapy regimen, and chemotherapy protocols. …”
Get full text

Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. …”
Get full text

Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

“…This study employed multiple machine learning models to perform risk prediction and result exploration for first-trimester Down syndrome in East Asian populations, aiming to identify an optimal risk prediction model that will enhance future predictions of Down syndrome risk and improve the efficiency of the screening process.Patients and Methods: This study collected data from the Down syndrome screening database at Taipei Chang Gung Memorial Hospital from May 1, 2018, to February 29, 2024. …”
Get full text

A Minimal Path-Based Method for Computing Multistate Network Reliability by Xiu-Zhen Xu, Yi-Feng Niu, Can He

“…Most of modern technological networks that can perform their tasks with various distinctive levels of efficiency are multistate networks, and reliability is a fundamental attribute for their safe operation and optimal improvement. …”
Get full text

Mechanism for data recovery as a result of data corruption, infection and/or unauthorized modification by L. V. Cherkesova, V. A. Savelyev, E. A. Revyakina, A. R. Polulyakh, M. A. Sementsov

“…To develop the software module, a reversible incremental backup algorithm was chosen as the most suitable for the developed algorithm and more convenient to use.Conclusion. …”
Get full text

PSO Tuned Super-Twisting Sliding Mode Controller for Trajectory Tracking Control of an Articulated Robot by Zewdalem Abebaw Ayinalem, Abrham Tadesse Kassie

“…Numerical simulations revealed that the tracking error and root mean square error (RMSE) improvements were approximately 18.33%, 16.66%, and 14.29% for PSO–STSMC compared to STSMC, and 79.50%, 78.04%, and 25.0% compared to PSO–SMC for each of the three joints under ideal conditions, respectively. …”
Get full text

An AIoT-Based Automated Farming Irrigation System for Farmers in Limpopo Province by Relebogile Langa, Michael Nthabiseng Moeti, Thabiso Maubane

“…A machine learning precipitation prediction algorithm optimizes water usage. The paper also describes a system with multiple sensors that detect soil parameters, and automatically irrigate land based on soil moisture by switching the motor on/off. …”
Get full text

Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…This study introduces a machine learning-based framework for predicting vegetation flow resistance, incorporating nine ML methods, including SVM, XGBoost, and BP. To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
Get full text

Estimation of Current RMS for DC Link Capacitor of S-PMSM Drive System by ZHANG Zhigang, CHANG Jiamian, ZHANG Pengcheng

“…The Cotes method eliminates numerous integration calculations, thus improving calculation accuracy. The proposed technique simplifies the tedious calculation process of traditional algorithms and guarantees high calculation accuracy, providing guidance for optimizing the selection of DC link capacitors and the design of life monitoring controllers. …”
Get full text

An Efficient Design of DCT Approximation Based on Quantum Dot Cellular Automata (QCA) Technology by Ismail Gassoumi, Lamjed Touil, Bouraoui Ouni, Abdellatif Mtibaa

“…Optimization for power is one of the most important design objectives in modern digital image processing applications. …”
Get full text

A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou, Xiaoming Qin

“…Nowadays, spatio-temporal series prediction algorithms are emerging, but their prediction accuracy requires improvement. …”
Get full text

Development of a Conditional Generative Adversarial Network Model for Television Spectrum Radio Environment Mapping by Oluwatobi Emmanuel Dare, Kennedy Okokpujie, Emmanuel Adetiba, Olabode Idowu-Bismark, Abdultaofeek Abayomi, Raymond Jules Kala, Emmanuel Owolabi, Udeme Christopher Ukpong

“…The model performance was evaluated using mean square error (MSE) and mean absolute error (MAE). 12 different experiments were carried out varying the training parameters of the CGAN architecture to obtain an optimal model. The achieved root mean square error (RMSE) is 0.1145dBm and MAE is 0.0820dBm, which shows the deviation between the ground truth and the generated REM. …”
Get full text

Edge-Fog Computing-Based Blockchain for Networked Microgrid Frequency Support by Ying-Yi Hong, Francisco I. Alano, Yih-der Lee, Chia-Yu Han

“…The parameters and hyperparameters of the LSTM-MFPC are optimized using the Bayesian Adaptive Direct Search (BADS) algorithm. …”
Get full text

Intracardiac abscess in the clinical course of infective endocarditis complicated by acute heart failure by Собіров Барно Бобір огли

“…Objective: to determine the optimal diagnostic and treatment algorithm for patients with infective endocarditis complicated by acute heart failure (AHF) and intracardiac abscess. …”
Get full text

Intelligent Data Reduction for IoT: A Context-Driven Framework by Laercio Pioli, Douglas D. J. De Macedo, Daniel G. Costa, Mario A. R. Dantas

“…With these predictions based on existing datasets, a selector algorithm module is adopted to identify the most suitable data reduction approach for specific IoT applications. …”
Get full text

Research on Urban Traffic Signal Control Systems Based on Cyber Physical Systems by Li-li Zhang, Qi Zhao, Li Wang, Ling-yu Zhang

“…Finally, considering China, the system designs a general control strategy API to separate data from control strategy. Most of the popular communication protocols between signal controllers and detectors are private protocols. …”
Get full text

DS-AdaptNet: An Efficient Retinal Vessel Segmentation Framework With Adaptive Enhancement and Depthwise Separable Convolutions by Shuting Chen, Chengxi Hong, Hong Jia

“…Second, we develop a Context-Aware Adaptive Threshold Optimization (CA-ATO) algorithm that dynamically determines optimal thresholds by integrating multi-scale contextual information and uncertainty estimates, substantially improving boundary delineation accuracy and fine structure preservation. …”
Get full text

Deep Mining on the Formation Cycle Features for Concurrent SOH Estimation and RUL Prognostication in Lithium-Ion Batteries by Dongchen Yang, Weilin He, Xin He

“…Models that integrate all formation-related data yielded the lowest root mean square error (RMSE) of 2.928% for capacity estimation and 16 cycles for RUL prediction, highlighting the significant role of surface-level physical features in improving accuracy. …”
Get full text

Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors. by Montaser Abdelsattar, Mohamed A Ismeil, Karim Menoufi, Ahmed AbdelMoety, Ahmed Emad-Eldeen

“…Preprocessing techniques, including feature scaling and parameter tuning, improved model performance by enhancing data consistency and optimizing hyperparameters. …”
Get full text

A New Approach to ORB Acceleration Using a Modern Low-Power Microcontroller by Jorge Aráez, Santiago Real, Alvaro Araujo

“…This work also allows for future optimizations that will improve the results of this paper.…”
Get full text