Development and validation of MRI-based radiomics model for clinical symptom stratification of extrinsic adenomyosis by Man Sun, Jianzhang Wang, Ping Xu, Libo Zhu, Gen Zou, Shuyi Chen, Yuanmeng Liu, Xinmei Zhang

“…Radiomic features were extracted from MRI-T2 image. Random forest algorithm was used to select the key radiomics features of different symptoms and develop the radiomic model by support vector machine algorithm. …”
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ON ESTIMATED ACCURACY OF PART CUTTING UNDER MACHINE INTELLIGENT CONTROL by Alexey Fedorovich Lysenko, Andrey Igorevich Izyumov, Oleg Valentinovich Goncharov

“…The novelty of the approach is in analyzing the effect of the combined characteristics that is more informative versus the effect estimate of each of them. An algorithm for the function calculation program of distributing the cutterpath coordinates used to evaluate entering the acceptable range is presented. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, E. N. Dzhakhnaeva

“…Some features that could be useful in detecting fraudulent job ads include job location, job description, job requirements, job responsibilities, company information, and recruiter data. Subsequently, different machine learning algorithms can be trained on prepared datasets using standard methods such as cross-validation to assess their performance. …”
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Research on intelligent video recognition method for roof water inrush signs in coal mines by Huiqing LIAN, Jia KANG, Shangxian YIN, Bin XU, Guocheng YAN, Xiangxue XIA, Baotong XU

“…The results demonstrate that compared with the OTSU algorithm, the self-supervised recognition algorithm based on SAM-XMem exhibits superior performance in terms of intersection over union (IoU), precision (P), recall (R), and F1 score, with evaluation metrics exceeding 90%, which represents 20% improvement over the recognition rate of conventional algorithms. …”
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Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…The GA algorithm significantly enhanced the predictive accuracy of the BPNN model. …”
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Optimizing wind-PV-battery microgrids for sustainable and resilient residential communities by Jyotismita Mishra, Ajay Shankar

“…To address the global energy trilemma, the microgrid is modeled with economic, reliability, and energy indices, ensuring a balanced three-dimensional objective. The proposed algorithm is evaluated across three different configurations, with a numerical analysis of the capacity degradation factor to assess battery lifetime.…”
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Nanosecond level time synchronization in datacenter network based on Telemetry architecture by Qianli ZHANG, Chaofan ZHANG, Jilong WANG, Xiangyu TANG, Zhengchen SHEN, Hui WANG

“…To solve the problems of the traditional local time synchronization architecture being disconnected from centralized management, requiring extra interaction overhead, meanwhile with less time data susceptible to outliers, the nanosecond level time synchronization system was proposed based on Telemetry for the high-precision time synchronization requirements of data center networks.Combined with the outlier factor detection algorithm, timestamp information within the background traffic of the data center was collected, the large amount of time information reported was processed and analyzed, and a centralized automatic synchronization with nanosecond level precision was eventually achieved, which was convenient for subsequent global network scheduling.The proposed system was implemented and evaluated on the programmable switch.Experimental results show that between multiple hops and at different link rates, the nodes can achieve high-precision time synchronization at the nanosecond level.…”
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Monte Carlo Simulation Approach to Calculate Value at Risk: Application to WIG20 and mWIG40 by Aleksandra Helena Pasieczna

“…Our approach involves obtaining Monte Carlo parameters by fitting real historical data of different periods to probability distributions. We applied the algorithm to the WIG20 and mWIG40 stock indices, and performed simulations for the Value at Risk at 95% and 99% confidence intervals over six estimation periods ranging from 1 trading day to 250 trading days. …”
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Normalization of Multifocal Acoustic Radiation Force Impulse Images by Nuria GONZÁLEZ-SALIDO, Jorge CAMACHO

“…Performance of the proposed algorithm is experimentally evaluated with tissue mimicking phantoms.…”
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Engineered feature embeddings meet deep learning: A novel strategy to improve bone marrow cell classification and model transparency by Jonathan Tarquino, Jhonathan Rodríguez, David Becerra, Lucia Roa-Peña, Eduardo Romero

“…Cytomorphology evaluation of bone marrow cell is the initial step to diagnose different hematological diseases. …”
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Decentralized coordinated emergency frequency control strategy for renewables-rich power systems based on multi-agent reinforcement learning by Zhenglong Sun, Junpeng Han, Weihan Chen, Rui Zhang, Yong Liu, Yoash Levron, Juri Belikov

“…Combined with the system frequency response (SFR) model parameter identification method, the grid frequency regulation capability of different fault conditions is evaluated. A MADRL algorithm with integrated SFR model is developed to overcome the problem of inaccurate assessment of centralized action values in the MADRL algorithm used for EFC, and a decentralized and cooperative EFC strategy is realized. …”
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Spatiotemporal High-Resolution Cloud Mapping with a Ground-Based IR Scanner by Benjamin Brede, Boris Thies, Jörg Bendix, Uwe Feister

“…This study presents a retrieval algorithm that evaluates observations of a hemispherically scanning thermal infrared radiometer, the NubiScope, to produce georeferenced, spatially explicit cloud maps. …”
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Uso de Métodos Monte Carlo na Modelagem de Fontes Radioativas Naturais by Gutemberg Luiz Sales Claudino, José Vieira, Viriato Leal Neto, Fernando Lima, José Santos

“…To perform the simulations was adapted MCE MSTA, composed by phantom MASH (Male Adult meSH) in orthostatic position coupled to EGSnrc, with the algorithm of FDP NT allowing execution for different values of rmax. …”
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From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy by Rafael Herschberg, Lisa Rateau, Laure Martinelli, Fanny Balbaud-Célérier, Jean Dhers, Anna Fraczkiewicz, Gérard Ramstein, Franck Tancret

“…A pairwise comparison algorithm is used to assess a particular property among a group of different alloys tested simultaneously in identical conditions. …”
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Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…The proposed WCAPSO-XGB model tunes the hyperparameters of XGBoost and classifies the credit scoring, and the experimental results are compared with various classifier such as Random Forest (RF), K-neighbors (KNN), Gaussian Naive Bayes (NB), AdaBoost, Gradient Boosting, Logistic Regression (LR), Neural Network (NN), Decision Tree (DT) and Linear Discriminant Analysis (LDA), and hyperparameter optimization methods, such as Grid Search (GS), Random Search (RS), Bays Optimization, Optuna Optimization, Hybrid Snake Optimizer Algorithm (HSOA), Exploratory Cuckoo Search, island Cuckoo Search (iCSPM and iCSPM2), and Improved SSA (ISSA) with HDPM, on four different datasets with a varying number of instances from small to large. …”
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Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction by Rui Yang, Tao Huang, Renqi Yao, Di Wang, Yang Hu, Longbing Ren, Shaojie Li, Yali Zhao, Zhijun Dai

“…Conclusion: We built the BRF model and the web-based tool by the model algorithm. The model effect has been verified externally. …”
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Comparing and Combining Artificial Intelligence and Spectral/Statistical Approaches for Elevating Prostate Cancer Assessment in a Biparametric MRI: A Pilot Study by Rulon Mayer, Yuan Yuan, Jayaram Udupa, Baris Turkbey, Peter Choyke, Dong Han, Haibo Lin, Charles B. Simone

“…Recently, a different spectral/statistical approach has been used to successfully evaluate spatially registered biparametric MRIs for prostate cancer. …”
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Initial experience of parenchyma-sparing liver resection with systematic selective hepatic vein reconstruction for colorectal metastases by Yevhenii Trehub, Åsmund Avdem Fretland, Artem Zelinskyi, Dzmitrii Kharkov, Oleksii Babashev, Dmytro Chieverdiuk, Artem Shchebetun, Kyrylo Khyzhniak, Maksym Pavlovskii, Andrii Strokan, Sergii Zemskov

“…Objectives This study aims to assess the feasibility and short-term and intermediate-term technical success rate of the concept of systematic selective hepatic vein (HV) reconstruction for parenchyma-sparing hepatectomies (PSHs) in patients with colorectal liver metastases (CRLM) in accordance with stage 2a of the IDEAL framework.Design The prospective case series of patients deemed eligible and operated on according to the concept.Setting All patients were treated by a single surgical team in three hospitals in Ukraine from June 2022 to November 2023.Participants The study included nine cases of resectable CRLM with at least one lesion located in the hepatocaval confluence with HV(s) invasion, for whom reconstruction of the HV(s) allowed for additional parenchyma preservation, being an alternative to major or extended hepatectomy.Interventions Liver resections with different types of HVs reconstruction (primary closure, patching, end-to-end anastomosis with or without grafting) were performed after a thorough evaluation of the future liver remnant volume, volume of potentially additionally preserved parenchyma and possibility of future repeat hepatectomies.Main outcome measures Postoperative morbidity, short-term and long-term patency of the reconstructed vessels, and the volume of additionally preserved parenchyma were the focus.Results Segmental resection was performed in four cases, two with graft interposition. …”
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Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools by Shymaa S. Soliman, Nisreen F Abo- Talib, Mohamed R. Elghobashy, Mona A. Abdel Rahman

“…During the current study, a pioneering statistical technique namely, Latin Hypercube Sampling (LHS) was integrated with different multivariate chemometric models namely; Partial Least Squares (PLS), Genetic Algorithm‑Partial Least Squares (GA-PLS), Artificial Neural Networks (ANN), and Multivariate Curve Resolution‑Alternating Least Squares (MCR-ALS). …”
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The application of artificial intelligence models in predicting the risk of diabetic foot: a multicenter study by Yao Li, Siyuan Zhou, Bichen Ren, Shuai Ju, Xiaoyan Li, Wenqiang Li, Bingzhe Li, Yunmin Cai, Chunlei Chang, Lihong Huang, Zhihui Dong

“…Future work will focus on algorithm optimization, expanded datasets, and real-time monitoring integration to enable more precise, dynamic risk evaluation for improved DF prevention and early intervention.…”
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