Diagnosis of Pain Deception Using Minnesota Multiphasic Personality Inventory-2 Based on XGBoost Machine Learning Algorithm: A Single-Blinded Randomized Controlled Trial by Hyewon Chung, Kihwan Nam, Subin Lee, Ami Woo, Joongbaek Kim, Eunhye Park, Hosik Moon

“…For analyzing the MMPI-2, the XGBoost ML algorithm was applied. <i>Results</i>: Of a total of 96 participants, 50 and 46 were assigned to the ND group and the D group, respectively. …”
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A Recursive Optimization Approach for Buffer Allocation in Large Production Lines by Lei Li, Menggao Dong, Jian Zhou

“…Two different recursive algorithms are developed and their performance is demonstrated by comparing them with a gradient search algorithm. …”
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PSO-FDM (Particle Swarm Optimization-Finite Difference Method)-Based Simulation Model of Temperature and Velocity of Full-Scale Continuous Annealing Furnace by Yang Liu, Qiang Guo, Tieheng Yuan, Yingrui Han, Chao Liu, Wenquan Sun

“…To improve the prediction accuracy for different strip sizes, the PSO optimization algorithm was employed to determine the optimal heat transfer coefficient for each strip size. …”
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Food Cooking Process Modeling With Neural Networks by Javier Fananas-Anaya, Gonzalo Lopez-Nicolas, Carlos Sagues, Sergio Llorente

“…Specifically, we propose a Nonlinear AutoRegressive with eXogenous inputs Neural Network (NARX-NN). The main novelty is that we define a novel training algorithm adapted to the modeling of real-time dynamical systems, allowing a NARX-NN with a simple structure to obtain a negligible error compared to the results of the original FEM model. …”
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Charging path optimization in mobile wireless rechargeable sensor networks by Quanlong NIU, Riheng JIA, Minglu LI

“…The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wireless sensor networks, which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers’ deployment or mobile chargers’ charging path for static sensor nodes with fixed sensor node positions, ignoring the scenario with mobile sensor nodes.Thus, design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes, to maximize the charging utility within a finite time horizon, that is, the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then, based on the constructed directed acyclic graph using discretization method, a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by layer-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility .…”
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Charging path optimization in mobile wireless rechargeable sensor networks by Quanlong NIU, Riheng JIA, Minglu LI

“…The wireless power transfer technique is promising in solving the energy bottleneck of sensor nodes in wireless sensor networks, which can thus prolong the network lifetime or even maintain sustainable network operations.Most existing works focused on optimizing the static chargers’ deployment or mobile chargers’ charging path for static sensor nodes with fixed sensor node positions, ignoring the scenario with mobile sensor nodes.Thus, design and optimize the charging path of a mobile charger was studied for dynamic wireless sensor networks with mobile sensor nodes, to maximize the charging utility within a finite time horizon, that is, the charger can encounter as more sensor nodes as possible in a limited time and charge them.Notice that the mobile charger may stop to simultaneously charge multiple nodes within its charging range during its charging tour.The proposed charging path optimization problem was proven to be an APX-hard problem.Then, based on the constructed directed acyclic graph using discretization method, a layer-wise pruning algorithm based on the backtracking method was proposed.The proposed algorithm took the solution generated by the greedy algorithm as the benchmark and searched the optimal charging path under a fixed time division by layer-wise pruning.Simulation results show that the proposed algorithm can effectively improve the charging utility .…”
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Machine Learning Algorithm-Aided Determination of Predictors of Mortality from Diabetic Foot Sepsis at a Regional Hospital in South Africa During the COVID-19 Pandemic by Carlos Matsinhe, Shingirai Brenda Kagodora, Tshifhiwa Mukheli, Tshepo Polly Mokoena, William Khabe Malebati, Maeyane Stephens Moeng, Thifhelimbilu Emmanuel Luvhengo

“…Supervised machine learning algorithms were used to compare their ability to predict mortality due to diabetic foot sepsis. …”
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To Be competitive or not to be competitive: How performance goals shape human-AI and human-human collaboration by Spatola Nicolas

“…These results demonstrate how setting goals may influence the preference to rely on algorithmic or human assistance and particularly how performance goal contexts catalyze a situation in which participants are more prone to rely on algorithms compared to peer recommendation. …”
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Method of Achieving the Goal on a Graph Model with Two Quality Criteria by S. V. Chebakov, L. V. Serebryanaya

“…Initially, all vertices are open, but their states may change in the process of problem solving. The search for a solution is limited by a given time. …”
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Improving the classification of a nanocomposite using nanoparticles based on a meta-analysis study, recurrent neural network and recurrent neural network Monte-Carlo algorithms by Rania Loukil, Wejden Gazehi, Mongi Besbes

“…The primary objective is to identify the optimal algorithm using software information and leading to better classification methodology. …”
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A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network by Patwary et al.

“…As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm, to detect malicious nodes in an OBS network. …”
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MODEL OF ORGANIZATION OF KIDNEY CANCER EARLY DIAGNOSIS by V. G. Moreva, G. N. Alekseeva, P. F. Kiku, L. I. Gurina, K. M. Sabirova, V. N. Rasskazova

“…The model included a population questionnaire to identify risk factors and algorithm of patient routing («roadmap») with suspected kidney cancer for in-depth examination and treatment. …”
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University proceedings. Volga region. Technical sciences by Yu.V. Dubenko, E.E. Dyshkant, V.A. Demidov

“…During operation, situations may arise that require prompt modification of the MAS architecture (changes in environmental parameters, malfunctions, and failures of agents). …”

Adjustable robust optimization with decision‐dependent uncertainty for power system problems: A review by Tao Tan, Meng Yang, Rui Xie, Yuji Cao, Yue Chen

“…Next, we summarize the state‐of‐the‐art solution algorithms for RO with DDU, such as variants of the column‐and‐constraint generation (C&CG) algorithm, variants of Benders decomposition, and multiparametric programming. …”
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Hierarchical Event-Triggered Online Charging Management of Time-Varying Network of Electric Vehicles Based on Cooperative Game Theory by Maryam Amirabad Farahani, Mohammad Haeri

“…A cyber-attack or communication failure may cause a problem in the connection between the aggregators and their information exchange. …”
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An Improved Dynamic Matrix Control Algorithm and Its Application in Cold Helium Temperature Control of a Modular High-Temperature Gas-Cooled Reactor (mHTGR) by Zhendong Wu, Zhe Dong, Jilan Zhang

“…The improved algorithm is applied to cold helium temperature control of the modular High-Temperature Gas-Cooled Reactor (mHTGR). …”
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Optimization of Vehicles Routing Problem using GA For AL-Rasheed municipality, Baghdad, Iraq by zainab talib, Muayed Al-Huseiny

“…If waste is not disposed of properly, environmental problems such as air pollution and groundwater contamination may occur. This problem raises the alarm for the need for specialized solutions for averting potential calamities that might occur throughout the world. …”
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Virtual care for prostate cancer survivorship: protocol for an evaluation of a nurse-led algorithm-enhanced virtual clinic implemented at five cancer centres across Canada by Antonio Finelli, Ricardo Rendon, Joseph A Cafazzo, Robert Hamilton, Alejando Berlin, Jacqueline L Bender, Denise Bryant-Lukosius, Quynh Pham, Jason Hearn, Ian Brown, Andrew H Feifer, Geoffrey Gotto

“…Despite the promise of the Ned Clinic, the model remains limited by its dependence on oncology specialists, lack of an autonomous triage algorithm, and has only been implemented among PCa survivors living in Ontario.Methods and analysis Our programme of research comprises two main research objectives: (1) to evaluate the process and cost of implementing and sustaining five nurse-led virtual PCa survivorship clinics in three provinces across Canada and identify barriers and facilitators to implementation success and (2) to assess the impact of these virtual clinics on implementation and effectiveness outcomes of enrolled PCa survivors. …”
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Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
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The effects of nursing care package implementation on pressure injuries prevention in the intensive care unit by Sevda Önen, Özlem Doğu

“…Abstract Aim The study was aimed to evaluate the effect of the care package prepared in accordance with the algorithm in the intensive care unit on the prevention of pressure injuries. …”
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