Targeted Interventional Therapies for the Management of Postamputation Pain: A Comprehensive Review by Dunja Savicevic, Jovana Grupkovic, Uros Dabetic, Dejan Aleksandric, Nikola Bogosavljevic, Uros Novakovic, Ljubica Spasic, Slavisa Zagorac

“…Nevertheless, further research is required to standardize clinical algorithms, optimize therapeutic decision-making and improve long-term outcomes and quality of life for individuals with PAP.…”
Get full text

Micro hole drilling and multi criteria optimization of soda lime glass via ultrasonic assisted rotary electrochemical discharge drilling by Sahil Grover, Viveksheel Rajput, Sanjay Kumar Mangal, Sarbjit Singh, Sandeep Singh, Shubham Sharma, Ehab El Sayed Massoud, Dražan Kozak, Jasmina Lozanovic

“…Machine learning-based algorithms are also used to predict the responses using Random Forest and Gradient Boost approaches. …”
Get full text

Multi-Robot exploration for coal mine rescue based on the extension of undirected graph by Linna ZHOU, Tihao WU, Xinli HUANG, Chunyu YANG, Xin ZHANG

“…Therefore, in response to the complex post-disaster downhole environment, a multi-robot autonomous exploration method based on the extended undirected graph is proposed, aiming at studying the collaborative search and rescue of a multi-robot autonomous exploration system to further improve rescue efficiency. …”
Get full text

Improvement of the technique applied to preserve species and varieties of <i>Fragaria</i> L. in the field genebank at Krymsk Experiment Breeding Station of VIR by V. N. Podorozhniy, N. A. Piyanina

Get full text

Estimation of elbow flexion torque using equilibrium optimizer on feature selection of NMES MMG signals and hyperparameter tuning of random forest regression by Raphael Uwamahoro, Raphael Uwamahoro, Kenneth Sundaraj, Farah Shahnaz Feroz

“…The performance of the GLEO-coupled with the RFR model was compared with the standard Equilibrium Optimizer (EO) and other state-of-the-art algorithms in physical and physiological function estimation using biological signals.ResultsExperimental results showed that selected features and tuned hyperparameters demonstrated a significant improvement in root mean square error (RMSE), coefficient of determination (R2) and slope with values improving from 0.1330 to 0.1174, 0.7228 to 0.7853 and 0.6946 to 0.7414, respectively for the test dataset. …”
Get full text

Combining miRNA concentrations and optimized machine-learning techniques: An effort for the tomato storage quality assessment in the agriculture 4.0 framework by Seyed Mohammad Samadi, Keyvan Asefpour Vakilian, Seyed Mohamad Javidan

“…However, the RF, with hyperparameters optimized by the genetic algorithm, was able to improve the R2 values of the prediction of storage temperature and period to 0.96 and 0.89. …”
Get full text

A two-stage robust optimization model for emergency service facilities location-allocation problem under demand uncertainty and sustainable development by Hongyan Li, Dongmei Yu, Yiming Zhang, Yifei Yuan

“…Abstract Under the backdrop of frequent emergencies, the rational layout of emergency service facilities (ESF) and the effective allocation of emergency supplies have emerged as crucial in determining the timeliness of post-disaster response. By adequately accounting for potential uncertainties and carrying out comprehensive pre-planning, the robustness of location-allocation decisions can be significantly improved. …”
Get full text

A lithium-ion batteries SOH estimation method based on extracting new features during the constant voltage charging stage and improving BPNN. by Yanhua Xian, Mingyang Li, Jiayin Huang

Get full text

Inversion of snow geophysical parameters using the VHR PAZ X-band dual polarimetric SAR data: first known experiments in the Himalayan region by Hemant Singh, Divyesh Varade

“…In this study, we proposed an improved algorithm for SD inversion, instead of relying on a single in-situ snow density value, we incorporated a range of snow densities (0.15 to 0.27 g/cm3), optimizing the axial ratio between 1.13 and 1.17. …”
Get full text

Optimizing intelligent reflecting surface assisted visible light communication networks under blockage and practical constraints using TLBO for IoT applications by Vipul Dixit, Ajit Kumar, Nishant Sharan, Shikha Pandey, Atul Kumar, Ram Sewak Singh

“…Additionally, detailed convergence analysis demonstrates that TLBO performs better than Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in terms of convergence speed, higher fitness value and lower sensitivity to initial conditions, making it most suitable for real-time IRS-VLC based IoT applications.…”
Get full text

A multi-task genetic programming approach for online multi-objective container placement in heterogeneous cluster by Ruochen Liu, Haoyuan Lv, Ping Yang, Rongfang Wang

“…MOCP-MTGP can automatically generate multiple groups of allocation rules from historical workload patterns and different cluster states, and capture the similarities between all online tasks to guide the transfer of general knowledge during optimization. Comprehensive experiments show that the proposed algorithm can improve the resource utilization of clusters, reduce the number of physical machines, and effectively meet resource constraints and high availability requirements.…”
Get full text

A modified particle swarm optimization-based adaptive maximum power point tracking approach for proton exchange membrane fuel cells by Bhukya Laxman, Ramesh Gugulothu, Surender Reddy Salkuti

“…Additionally, the proposed approach showed improvements in power efficiency by 2.47 %, 2.87 %, and 13.58 % for the Jaya algorithm. demonstrating effective MPPT tracking under different operating conditions and perturbations. …”
Get full text

On the Performance of Downlink Channel Estimation‐Based Cell‐Free Massive MIMO Systems Under Correlated Rician Fading Channels by Jiarui Li, Yao Zhang, Fengjiao Gan, Na Liu, Longxiang Yang, Hongbo Zhu

Get full text

Re-Supplying Autonomous Mobile Parcel Lockers in Last-Mile Distribution by Sajjad Hedayati, Mostafa Setak, Tom Van Woensel, Emrah Demir

“…The CSA algorithm incorporates the K-means clustering method with specialized operators rooted in an extensive neighborhood search, aiming to improve the effectiveness of solution discovery. …”
Get full text

Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

Get full text

A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…The validation experimental results agree well with the GRA-TOPSIS-RFR-optimized outcomes. This research provides valuable insights into optimizing the micro-milling process of titanium components, ultimately contributing to improved quality, performance, and service life across various aerospace applications.…”
Get full text

Optimizing Security of Radio Frequency Identification Systems in Assistive Devices: A Novel Unidirectional Systolic Design for Dickson-Based Field Multiplier by Atef Ibrahim, Fayez Gebali

Get full text

New chemometrics-assisted spectrophotometric methods for simultaneous determination of co-formulated drugs montelukast, rupatadine, and desloratadine in their different dosage comb... by Marco M. Z. Sharkawi, Nehal F. Farid, Moataz H. Hassan, Said A. Hassan

“…The proposed approaches, partial least squares-1 (PLS-1) and artificial neural network (ANN), were optimized using genetic algorithm (GA) to select the most influential wavelengths, enhancing model performance. …”
Get full text

The Robust Steiner Team Orienteering Problem with Decreasing Priorities under budgeted uncertainty by Lucas Assunção, Andréa Cynthia Santos

“…Post-disaster relief operations have gained attention over the past decade, focusing on enhancing resilience in labor and social environments. …”
Get full text

Weak Fault Detection for Rolling Bearings in Varying Working Conditions through the Second-Order Stochastic Resonance Method with Barrier Height Optimization by Huaitao Shi, Yangyang Li, Peng Zhou, Shenghao Tong, Liang Guo, Baicheng Li

“…In this paper, an underdamped second-order adaptive general variable-scale stochastic resonance (USAGVSR) method with potential well parameters’ optimization is put forward. For input signals with different fault frequencies, the potential well parameters related to the barrier height are figured out and optimized through the ant colony algorithm. …”
Get full text