Quantitative Analysis of the Main Controlling Factors of Oil Saturation Variation by Ruijie Huang, Chenji Wei, Jian Yang, Xin Xu, Baozhu Li, Suwei Wu, Lihui Xiong

“…A total of 10 machine learning algorithms are tested and compared in the dataset. Random forest (RF) and gradient boosting (GBT) are optimal and selected to conduct quantitative analysis of the main controlling factors. …”
Get full text

An Embedded Reconfigurable IP Core with Variable Grain Logic Cell Architecture by Motoki Amagasaki, Ryoichi Yamaguchi, Masahiro Koga, Masahiro Iida, Toshinori Sueyoshi

“…The key feature of the VGLC architecture is that the variable granularity is a tradeoff between coarse-grained and fine-grained types required for the implementation arithmetic and random logic, respectively. Finally, we evaluate the proposed logic cell using the newly developed technology mapping tool, which improves logic depth by 31% and reduces the number of configuration data by 55% on average, as compared to the Virtex-4 logic cell architecture.…”
Get full text

Understanding collective behavior in biological systems through potential field mechanisms by Junqiao Zhang, Qiang Qu, Xuebo Chen

“…Our simulations span a variety of environmental conditions, including standard environments where organisms interact under typical conditions, high noise environments where interactions are disrupted by random fluctuations, high density environments with increased competition for space, high risk environments featuring areas of strong negative potential field, and multiple resource environments with varying degrees of resource availability. …”
Get full text

INFLUENCE OF SECURITY CHALLENGES ON STUDENT ACADEMIC PERFORMANCE IN COLLEGE OF EDUCATION BILLIRI, GOMBE STATE, NIGERIA by MOHAMMED ABUBAKAR SABO, YAKUBU MUHAMMAD BELLO, MUHAMMAD AUWAL

“…The survey design and simple random sampling techniques were employed in this study. …”
Get full text

The Effect of Growth Regulator Substance in Cultural Media PHM on Protein Content of Chlorella sp. by M.W. Lewaru

“…The method used in this research was experimental laboratory using a completely random design which comprised of five treatments with triplicates per treatment. …”
Get full text

Smart Grid Dispatching Optimization for System Resilience Improvement by Li Liao, Chengjun Ji

“…The real-time algorithm proposed in the paper is based on a distributed control strategy, which can not only realize dynamic compensation for random fluctuations in renewable energy power generation but also satisfy the load curve optimization under the premise of making full use of power supply resources. …”
Get full text

Automatic Screening and Grading of Age-Related Macular Degeneration from Texture Analysis of Fundus Images by Thanh Vân Phan, Lama Seoud, Hadi Chakor, Farida Cheriet

“…A support vector machine and a random forest were used to classify images according to the different AMD stages following the AREDS protocol and to evaluate the features’ relevance. …”
Get full text

Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF by Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini

“…We evaluate several methods, including Long Short-Term Memory, Random Forest, and various neural networks, assessing their Accuracy and sensitivity in distinguishing normal from anomalous behaviors. …”
Get full text

Multilevel Attention and Multiscale Feature Fusion Network for Author Classification of Chinese Ink-Wash Paintings by Wei Jiang, Xianglian Meng, Ji Xi

“…Moreover, the conditional random field module is adopted to fuse the optimized three-scale feature maps, and the channel attention module is followed to refine the features. …”
Get full text

Credit risk prediction with corruption perception index: machine learning approaches by Cuong Nguyen Thanh, Tam Phan Huy, Tuyet Pham Hong, An Bui Nguyen Quoc

“…Analyzing data from 70 banks over a decade, it employs Decision Tree, Random Forest, Gradient Boosted Trees, and XGBoost models, evaluated using R², RMSE, and MAE. …”
Get full text

Assesment of static panel model of tourist demand in Croatia by Ivana Beljo, Kristina Devčić, Laura Pavelić

“…The analysis was carried out for the nine-year time period from 2010 to 2018 based on data for 32 countries from which tourists come, and OLS model, a panel model with fixed effects and a panel model with random effects were estimated. The adequacy of the model was tested with the Hausman test, Breusch-Pagan Lagrange test and F-test. …”
Get full text

Development of a High‐Latitude Convection Model by Application of Machine Learning to SuperDARN Observations by W. A. Bristow, C. A. Topliff, M. B. Cohen

“…Abstract A new model of northern hemisphere high‐latitude convection derived using machine learning (ML) is presented. The ML algorithm random forests regression was applied to a database of velocities derived from the Super Dual Auroral Radar Network (SuperDARN) observations processed with the potential mapping technique, Map‐Potential (Ruohoniemi & Baker, 1998, https://doi.org/10.1029/98ja01288). …”
Get full text

Lévy walk of pions in heavy-ion collisions by Dániel Kincses, Márton Nagy, Máté Csanád

“…., movement patterns described by heavy-tailed random walks, plays a role in various phenomena, from chemical and microbiological systems through marine predators to climate change. …”
Get full text

Deciphering the Immune Subtypes and Signature Genes: A Novel Approach Towards Diagnosing and Prognosticating Severe Asthma Through Interpretable Machine Learning by Yue Hu, Yating Lin, Bo Peng, Chunyan Xiang, Wei Tang

“…We employ single-sample gene set enrichment analysis (ssGSEA) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms to identify differentially expressed immune cells and utilize machine learning techniques, including Extreme Gradient Boosting (XGBoost) and random forest, to predict severe asthma outcomes and identify key genes associated with immune cells. …”
Get full text

Statistical Analysis of the Possibility of Hail in Northern Zagros by Mohammad Reza Salimi Sobhan, zahra beygom Hejazizadeh, fariba sayadi, fatemeh qaderi

“…In choosing the best method for calculating the distribution of precipitation probabilities, different types of probability distributions of discrete random variables were tested by means of both Kolmogorov and Anderson-Darling testsThe results showed that the good Poisson distribution test had a good fit for hail occurrence at a high level of 90.99%. …”
Get full text

PTH1R-CaSR Cross Talk: New Treatment Options for Breast Cancer Osteolytic Bone Metastases by Yanmei Yang, Bin Wang

“…Recent findings have established that the distribution of BrCa metastases to the skeleton is not a random process but due to the favorable microenvironment for tumor invasion and growth. …”
Get full text

The association between organizational culture and teachers’ organizational commitment in Bahir Dar Polytechnic College, the State of Amhara by Berhan Kefyalew Taye, Melaku Mengistu Gebremeskel

“…These participants were recruited through a systematic random sampling technique. Data were analyzed using descriptive (mean, standard deviations, and one sample t-test) as well as inferential statistics (correlation and multiple linear regression). …”
Get full text

Machine learning analysis of rivaroxaban solubility in mixed solvents for application in pharmaceutical crystallization by Mohammed Alqarni, Ali Alqarni

“…Using a dataset with over 250 data points and including solvents encoded with one-hot encoding, four models were compared: Gradient Boosting (GB), Light Gradient Boosting (LGB), Extra Trees (ET), and Random Forest (RF). The Jellyfish Optimizer (JO) algorithm was applied to tune hyperparameters, enhancing model performance. …”
Get full text

POI Data Fusion Method Based on Multi-Feature Matching and Optimization by Yue Wang, Cailin Li, Hongjun Zhang, Baoyun Guo, Xianlong Wei, Zhao Hai

“…Firstly, when dealing with POI (point of interest) data, the similarity of POI data in terms of name, address, and distance is calculated by combining the improved hybrid similarity method, the Jaccard method, and the Euclidean metric method. Secondly, the random forest algorithm is utilized to dynamically determine the information weights of each attribute and calculate the comprehensive similarity. …”
Get full text

Accurate identification of primary site in tumors of unknown origin (TUO) using DNA methylation by Drew Duckett, Erica R. Vormittag-Nocito, Pouya Jamshidi, Madina Sukhanova, Stephanie Parker, Daniel J. Brat, Lawrence J. Jennings, Lucas Santana-Santos

“…Identification of the site of origin in TUO patients is paramount to their improved treatment and survival but is difficult to obtain with current methods. Here, we develop a random forest machine learning TUO methylation classifier using a large number of primary and metastatic tumor samples. …”
Get full text