Correlation between air flow rate and pollutant concentrations during two-stage oak log combustion in a 25 KW residential boiler by Juszczak Marek

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Research on correction method of borehole response in slim hole array lateral logging based on PSO-BP hybrid model prediction by Zhiqiang Li, Shaojie Xing, Junyan Lin, Fangong Li, Jianye Wang, Xiaohui Song, Wei Zhang

“…Especially for slim hole array lateral logging instruments, which are significantly affected by the borehole, borehole correction processing is urgently needed. …”
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A model of feature extraction for well logging data based on graph regularized non-negative matrix factorization with optimal estimation by Kehong Yuan, Youlin Shang, Haixiang Guo, Yongsheng Dong, Zhonghua Liu

“…Abstract Reservoir oil-bearing recognition is the process of predicting reservoir types based on well logging data, which determines the accuracy of recognition. …”
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Logging identification of karstified Jurassic conglomerate aquifer in the Zhuxianzhuang coal mine: implications for water abundance heterogeneity and mining risk mitigation by Zhu Guanyu, Zhu Guanyu, Jiang Bo, Jiang Bo, Li Ming, Li Ming, Song Yu, Song Yu, Cheng Guoxi, Cheng Guoxi

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ARKAIV: Predicting Data Exfiltration Using Supervised Machine Learning Based on Tactics Mapping From Threat Reports and Event Logs by Arif Rahman Hakim, Kalamullah Ramli, Muhammad Salman, Bernardi Pranggono, Esti Rahmawati Agustina

“…Despite this, no prior research has focused on predicting exfiltration occurrences based on sequences of tactics identified from low-level logs. Additionally, integrating low-level logs with high-level conceptual frameworks remains a critical challenge. …”
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Application of log-based specific surface area prediction for permeability modeling in a highly heterogeneous carbonate reservoir in the middle east by Mojtaba Homaie, Ida Lykke Fabricius, Morten Leth Hjuler, Asadollah Mahboubi, Ali Kadkhodaie, Reza Moussavi Harami

“…Abstract In contrast to the well-studied North Sea chalks, the effectiveness of log-based specific surface area modeling techniques for heterogeneous Iranian (Middle Eastern) carbonates is underexplored. …”
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Petrophysical evaluation of clastic formations in boreholes with incomplete well log dataset by using joint inversion technique and machine learning algorithms by Felipe Santana-Román, Ambrosio Aquino López, Manuel Romero Salcedo (+), Raúl del Valle García, Oscar Campos Enriquez

“…Unfortunately, it is not always possible to fulfill these conditions, and in many cases the set of well logs is incomplete. To determine petrophysical parameters (i.e., volumes of laminar, structural and disperse shale) in clastic rocks from incomplete well log data we followed three approaches which are based on a hierarchical model, and on a joint inversion technique: 1) Available well log data (excluding the incomplete well log) are used to train machine learning algorithms to generate a predictive model; 2) the first step of the second approach machine learning algorithms are used to generate the missing data which are subsequently included a joint inversion; 3) in the third approach, machine learning process is used to estimate the missing data which are subsequently included in the prediction of the petrophysical properties. …”
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Analysis of Conti Ransomware Attack on Computer Network with Live Forensic Method by Rusydi Umar, Imam Riadi, Ridho Surya Kusuma

“…This study analyzes the Conti virus attack through a network forensic process based on network behavior logs. The research process consists of three stages, the first stage is simulating attacks on the host computer, the second stage is carrying network forensics by using live forensics methods, and the third stage is analysing malware by using statistical and dynamic analysis. …”
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An Electro-Magnetic Log (EML) Integrated Navigation Algorithm Based on Hidden Markov Model (HMM) and Cross-Noise Linear Kalman Filter by Haosu Zhang, Liang Yang, Lei Zhang, Yong Du, Chaoqi Chen, Wei Mu, Lingji Xu

“…The principle analysis of the algorithm, the modeling process, and the flow chart of the algorithm are given in this paper. …”
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Enhancing water saturation predictions from conventional well logs in a carbonate gas reservoir with a hybrid CNN-LSTM model by Ali Gohari Nezhad, Mohammad Emami Niri

“…Four machine learning algorithms: XGBoost, long short-term memory (LSTM), 1-dimensional convolutional neural network (1D-CNN), and a hybrid CNN-LSTM were developed to predict experimental water saturation values from conventional well logs. A total of 10,674 data points were collected from four wells in the South Pars gas field, where well logging evaluations and core measurements were available. …”
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Scalable <i>O</i>(<i>log</i>₂<i>n</i>) Dynamics Control for Soft Exoskeletons by Julian D. Colorado, Diego Mendez, Andres Gomez-Bautista, John E. Bermeo, Catalina Alvarado-Rojas, Fredy Cuellar

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Reduction of mangrove carbon stock ecosystems due to illegal logging using a combination of unmanned aerial vehicle imagery and field surveys by M. Basyuni, R. Amelia, A.A. Aznawi, A. Wirasatriya, S.B. Iryanthony, B. Slamet, S.S. Al Mustaniroh, R. Rahmania, Y.I. Rahmila, E. Sumarga, S.H. Larekeng, S. Salmo III, T. Kajita, I. Sivaipram, H.M. Ali

“…Both research sites produced orthophotos and digital surface models, and the integration of unmanned aerial vehicle with the photometry approach led to the development of the structure from motion method of data processing.FINDINGS: This study compared carbon stores in the mangrove forest of Lubuk Kertang Village in 2022 with carbon stock in 2023 or after the recurrence of illegal logging using an unmanned aerial vehicle photogrammetric field survey. …”
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Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based on Well Log Data by Urip Nurwijayanto Prabowo*, Akmal Ferdiyan, Sukmaji Anom Raharjo, Sehah Sehah, Arya Dwi Candra

“…Facies classification is the process of identifying rock lithology based on indirect measurements such as well log measurements. …”
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Application of a geostatistical algorithm for correcting well logging data when modelling complex hydrocarbon deposits at the stage of additional field exploration by V. L. Shuster, O. V. Tjukavkina, I. S. Permyakova, I. L. Kapitonova

“…Additional exploration of oil and gas reserves requires the application of information technologies for modelling all technological processes and interpreting the results of geophysical well logging. …”
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Model Analisis Aktivitas Tutor Dalam Learning Management System Berdasarkan Data Log Menggunakan K-Means Dan Deteksi Outlier by Agusriandi Agusriandi, Elihami Elihami, Irman Syarif, Ita Sarmita Samad

“… Pembelajaran tutor di LMS menyimpan data berupa log yang dapat dimanfaatkan menjadi pengetahuan tentang kinerja tutor. …”
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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…These recordings encompass depth data; well logs, including NPHI, GR, DT, RD, RHOB, RS, and RT; drilling activities, specifically ROP; and petrophysical parameters, including BVW, K, PHIF, SW, and VCL. …”
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Risk Assessment of Urban Water-Logging Disaster Based on Weight-improved AHP Method-Taking Haojiang District of Shantou City as an Example by ZHOU Jiaqi, LIN Kairong, XIE Xue, CHEN Haiyan, GAO Xin

“…Under the background of global climate change,the frequency of extreme rainfall events increases,and the urban water-logging disaster occurs frequently.The risk assessment of water-logging disaster can effectively reduce the loss.Taking Haojiang District of Shantou City as case study,this paper improves the weights of the analytic hierarchy process (AHP) by neural network,expands the traditional nine-point scaling,and constructs the water-logging disaster risk evaluation model.The results show that the water-logging disaster risk in Haojiang District is generally high in the south-central region and low in the northwest region.Especially,Yuxin Street,Binhai Street,Majiao Street and Dahao Street have higher risk values,which need to take preventive measures.After verification of evaluation results with historical data,it is shown that about 80% of historical flood disaster points are distributed in high-risk areas,which is consistent with the verification results of historical disaster points.The weight determination method of AHP is improved by neural network,the intermediate variables of the traditional nine-point method is expanded to three decimal places,and the weight is determined by the computer to reduce subjectivity to a certain extent.The results of risk assessment can provide technical support for flood warning and flood control scheduling within a certain time limit.…”
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Fast 2D forward modeling of electromagnetic propagation well logs using finite element method and data-driven deep learning by A.M. Petrov, A.R. Leonenko, K.N. Danilovskiy, O.V. Nechaev

“…We propose a novel workflow for fast forward modeling of well logs in axially symmetric 2D models of the near-wellbore environment. …”
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A novel strategy to precisely adjust partition coefficient, effectively eliminate matrix interference and achieve accurate and fast gold immunochromatographic assay of ethoxyquin i... by Qifan Sun, Lin Zhang, Shaoen Zhang, Qingzhou Chen, Jinjun Ying, Hong Lin, Jianxin Sui, Kaiqiang Wang, Xiudan Wang, Limin Cao

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Automated Detection of Deviations in Bankruptcy Processes Using Process Mining by Ivan P. Malashin, Igor S. Masich, Daniel A. Ageev, Dmitriy A. Evsyukov, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin, Vadim S. Tynchenko

“…This study investigates the application of process mining (PM) techniques for the analysis of bankruptcy processes based on digital trace logs. …”
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