A Quantitative Risk Evaluation Model for Network Security Based on Body Temperature by Y. P. Jiang, C. C. Cao, X. Mei, H. Guo

“…This paper proposed a quantitative risk evaluation model for network security based on body temperature (QREM-BT), which refers to the mechanism of biological immune system and the imbalance of immune system which can result in body temperature changes, firstly, through the r-contiguous bits nonconstant matching rate algorithm to improve the detection quality of detector and reduce missing rate or false detection rate. …”
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Advanced AI-driven detection of interproximal caries in bitewing radiographs using YOLOv8 by Mahsa Bayati, Berhrouz Alizadeh Savareh, Hojjat Ahmadinejad, Farzaneh Mosavat

“…Thus, the present study aimed to develop a deep learning-based AI model using the YOLOv8 algorithm for improving interproximal caries detection in bitewing radiographs. …”
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Design and evaluation of screening and self-care (mobile) application for oral and dental problems and emergencies by Sedighe Sadat Hashemikamangar, Aidin Sooratgar, Mina Khayamzadeh, Shayan Momeni, Ali Asghar Safaei, Behnaz Behniafar

“…Introdution: Although oral and dental diseases may occur in unexpected or even emergency conditions, but some of the diagnosis and treatments can be algorithmically done following some guidelines. The development and implementation of a system that provides users with a record of history and a proposal of required actions can be not only efficiently practical, but also virtually simple. …”
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A Mathematical Model for the Analysis of the Pressure Transient Response of Fluid Flow in Fractal Reservoir by Jin-Zhou Zhao, Cui-Cui Sheng, Yong-Ming Li, Shun-Chu Li

“…Type curves of the wellbore pressure and pressure derivative are plotted and analyzed in real domain using the Stehfest numerical invention algorithm. The SCMS and type curves can interpret intuitively transient pressure response of fractal spherical flow reservoir. …”
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Machine learning-assisted design of Ti–V–Nb–Mo refractory high-entropy alloys with higher ductility and specific yield strength by Yan Li, Junjie Gong, Shilong Liang, Wei Wu, Yongxin Wang, Zheng Chen

“…The combination of the aforementioned dataset with the solid solution strengthening (SSH) model and the D (γs/γusf) parameter enabled the construction of a highly accurate strength-ductility prediction model for the alloys through the use of an XGBoost algorithm. The model was employed to predict the compositions of two novel RHEAs and their mechanical properties were verified by experiments. …”
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Dynamic Analysis of <i>Spartina alterniflora</i> in Yellow River Delta Based on U-Net Model and Zhuhai-1 Satellite by Huiying Li, Guoli Cui, Haojie Liu, Qi Wang, Sheng Zhao, Xiao Huang, Rong Zhang, Mingming Jia, Dehua Mao, Hao Yu, Zongming Wang, Zhiyong Lv

“…The U-Net model, coupled with the Relief-F algorithm, achieved a superior extraction accuracy (Kappa > 0.9 and overall accuracy of 93%) compared to traditional machine learning methods. …”
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Fundus Images-Based Detection and Grading of Macular Edema Using Robust Macula Localization by Adeel M. Syed, M. Usman Akram, Tahir Akram, Muhammad Muzammal, Shehzad Khalid, Muazzam Ahmed Khan

“…The detailed grading of ME&#x2014;as both clinically significant ME and non-clinically significant ME&#x2014;is done using localized foveae and segmented exudates. The proposed algorithm is validated using public and local data sets. …”
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Shock Response Spectra Reconstruction of Pointwise Explosive-Induced Pyroshock Based on Signal Processing of Laser Shocks by S. Y. Chong, J. R. Lee, C. W. Kong

“…The signal processing algorithm for the laser shock-based pyroshock reconstruction is developed in a LabVIEW platform and consists of subbands decomposition, SRS matching in decomposed bands, and wave synthesizing. …”
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Model for sustainable carbon emission reduction energy development and smart grid technology strategy by Kangli Xiang, Keren Chen, Simin Chen, Wanqing Chen, Jinyu Chen

“…The model used the carbon trading mechanism to further reduce carbon emissions and the carnivorous plant algorithm to optimize the scheduling strategy. The results indicate that the model demonstrates significant advantages in terms of carbon emission, total operating cost, prediction accuracy, and energy utilization efficiency, respectively, at 60.8 kg, 2517.5 yuan, 96.5%, and 90.2%, indicating that it utilizes energy more fully and helps to enhance the overall energy efficiency of the system. …”
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Similarity Measure Learning in Closed-Form Solution for Image Classification by Jing Chen, Yuan Yan Tang, C. L. Philip Chen, Bin Fang, Zhaowei Shang, Yuewei Lin

“…Based on this similarity measure, we present a specific algorithm under the SML framework, called correlation similarity measure learning (CSML), to learn a parameterized similarity measure over input space. …”
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Preprocessing Approach for Power Transformer Maintenance Data Mining Based on k-Nearest Neighbor Completion and Principal Component Analysis by Moïse Manyol, Samuel Eke, Alphonse J. M. Massoma, Alain Biboum, Ruben Mouangue

“…The accuracy of a knowledge extraction algorithm in a large database depends on the quality of the data preprocessing and the methods used. …”
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Model Predictive Control for an Aerial Tree-Pruning Robot Based on Alternating Direction Method of Multipliers by Changliang Xu, Zhong Yang, Hao Xu, Qiuyan Zhang, Dongsheng Zhou, Kaiwen Lu, Jiaming Han, Luwei Liao

“…One of the main contributions is that an ADMM (alternating direction method of multipliers) algorithm that solves the constrained QP (quadratic programming) is adopted to implement the model predictive control on embedded computers with limited computational power. …”
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Efficient and accurate determination of the degree of substitution of cellulose acetate using ATR-FTIR spectroscopy and machine learning by Frank Rhein, Timo Sehn, Michael A. R. Meier

“…By applying a n-best feature selection algorithm based on the F-statistic of the Pearson correlation coefficient, several relevant areas were identified and the optimized model achieved an improved MAE of 0.052. …”
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Optimizing SVM for argan tree classification using Sentinel-2 data: A case study in the Sous-Massa Region, Morocco by Abdelhak El Kharki, Jamila Mechbouh, Miriam Wahbi, Otmane Yazidi Alaoui, Hakim Boulaassal, Mustapha Maatouk, Omar El Kharki

“…This study aimed to optimize the hyperparameters of the Support Vector Machine (SVM) algorithm using the grid search method to map the distribution of the Argan forest in the Souss-Massa region of Morocco from Sentinel-2 satellite image. …”
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Efficient Probabilistic and Geometric Anatomical Mapping Using Particle Mesh Approximation on GPUs by Linh Ha, Marcel Prastawa, Guido Gerig, John H. Gilmore, Cláudio T. Silva, Sarang Joshi

“…In this paper, we present a solution based on two key ideas: a new registration method that generates a mapping between anatomies represented as a multicompartment model of class posterior images and geometries and an implementation of the algorithm using particle mesh approximation on Graphical Processing Units (GPUs) to fulfill the computational requirements. …”
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Novel Dynamic Partial Reconfiguration Implementation of K-Means Clustering on FPGAs: Comparative Results with GPPs and GPUs by Hanaa M. Hussain, Khaled Benkrid, Ali Ebrahim, Ahmet T. Erdogan, Huseyin Seker

“…In this work, a parameterized implementation of the K-means clustering algorithm in Field Programmable Gate Array (FPGA) is presented and compared with previous FPGA implementation as well as recent implementations on Graphics Processing Units (GPUs) and GPPs. …”
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Performance of the Priority Control Strategies for Bus Rapid Transit: Comparative Study from Scenario Microsimulation Using VISSIM by Min Yang, Wei Wang, Bo Wang, Jing Han

“…Signal priority using advanced detection is a strategy which detects one cycle ahead of buses’ arrival in order to adapt a more flexible control algorithm to provide signal priority for buses. Another is transit speed control, which provides priority at intersections for buses by controlling the speed of them and predicting their arrival at certain intersection. …”
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Raman Microspectral Study and Classification of the Pathological Evolution of Breast Cancer Using Both Principal Component Analysis-Linear Discriminant Analysis and Principal Compo... by Heping Li, Yu Ren, Fan Yu, Dongliang Song, Lizhe Zhu, Shibo Yu, Siyuan Jiang, Shuang Wang

“…Both classification models were principal component analysis-linear discriminant analysis to be extremely efficient on discriminating tissue pathological types with 99% accuracy for PCA-LDA and 100%, 100%, and 96.7% for PCA-SVM analysis based on linear kernel, polynomial kernel, and radial basis function (RBF), respectively, while PCA-SVM algorithm greatly simplified the complexity of calculation without sacrificing performance. …”
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Optimization Method of Underwater Flapping Foil Propulsion Performance Based on Gaussian Process Regression and Deep Reinforcement Learning by YANG Yinghe, WEI Handi, FAN Dixia, LI Ang

“…Under different propulsion performance requirements, the TD3 algorithm in deep reinforcement learning (DRL) is trained for maximizing rewards and obtaining the optimal combination of multiple parameter actions in continuous intervals. …”
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Exploring the Potential Imaging Biomarkers for Parkinson’s Disease Using Machine Learning Approach by Illia Mushta, Sulev Koks, Anton Popov, Oleksandr Lysenko

“…This study aims to identify a biomarker from DATSCAN images and develop a machine learning (ML) algorithm for PD diagnosis. Using 13 DATSCAN-derived parameters and patient handedness from 1309 individuals in the Parkinson’s Progression Markers Initiative (PPMI) database, we trained an AdaBoost classifier, achieving an accuracy of 98.88% and an area under the receiver operating characteristic (ROC) curve of 99.81%. …”
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