DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…Each input data point is represented by a low-dimensional representation and a probability of reconstruction by the algorithm. …”
Get full text

Zootechnical and growth performance of tambaqui (Colossoma macropomum) under different productive models of intensification by C. A. S. Lima, A. S. Lavareda, C. T. S. Farias, L. M. Barbosa, T. C. S. Oliveira, J. Pantoja-Lima, K. C. Yamamoto

“…Abstract The objective of this study was to evaluate the zootechnical performance of tambaqui (Colossoma macropomum) for fattening (> 2 kg) under three management strategies on nine fish farms, which were equally distributed as follows: Low Productive Efficiency (LPE) – 6-8 tons year-1 without aeration; Medium Productive Efficiency (MPE) – 9-14 tons year-1 with emergency aeration and High Productive Efficiency (HPE) – 15-22 tons year-1 with supplemental aeration. …”
Get full text

Mean-reverting diffusion model-enhanced acoustic-resolution photoacoustic microscopy for resolution enhancement: Toward optical resolution by Yiyang Cao, Shunfeng Lu, Cong Wan, Yiguang Wang, Xuan Liu, Kangjun Guo, Yubin Cao, Zilong Li, Qiegen Liu, Xianlin Song

“…By modeling the degradation process from high-resolution image to low-resolution AR-PAM image with stable Gaussian noise (i.e., mean state), a mean-reverting diffusion model is trained to learn prior information of the data distribution. …”
Get full text

Data-driven cluster analysis on the association of aging, obesity and insulin resistance with new-onset diabetes in Chinese adults: a multicenter retrospective cohort study by Yazhi Wang, Mingkang Zhang, Peng Wang

Get full text

A feedback-driven ventilation model for assessing airway secretions in mechanically ventilated patients by D. Vijay Anand, Manuel Teixeira Cabeleira, Claire Black, Vanessa Diaz-Zuccarini, Nicholas C. Ovenden

“…Analysis of patient data using clustering methods identified distinct groups corresponding to low, medium, and high levels of secretion. …”
Get full text

Twin Support Vector Regression Model Based on Heteroscedastic Gaussian Noise and Its Application by Shiguang Zhang, Ge Feng, Feng Yuan, Shuangle Guo

“…The main purpose of twin support vector regression (TSVR) is to find linear or nonlinear relationships in sample data, and then predict future data. TSVR is the decomposition of a large convex quadratic programming problem into two small convex quadratic programming problems. …”
Get full text

Spatial heterogeneity of forest carbon stocks in the Xiangjiang river Basin urban agglomeration: analysis and assessment based on the multiscale geographically weighted regression... by Yingfeng Kuang, Xiaolong Chen

“…By constructing and comparing the ordinary least squares model (OLS) and four geographically weighted regression (GWR) models, it is hoped to provide a more reliable method for accurately estimating the spatial distribution of large-scale forest carbon stocks and provide a scientific basis for the construction of the Xiangjiang River Basin forest urban agglomeration.MethodBased on the data of the 10th continuous forest resource inventory and climate data in Hunan Province, this study identified five key variables, including average breast diameter of the stand, stand density, average age of the stand, average tree height of the stand, and average annual precipitation. …”
Get full text

Remote Sensing Survey of Chlorophyll-a Concentration in River-Type Reservoirs Based on GF-1 Image Data: Taking Feilaixia–Changhu Reservoir Area as an Example by ZOU Zhengxin, DENG Ruru, LIANG Yeheng, CHAI Zhuoqun, KUANG Zhiyuan, YANG Junying, ZHAO Zixi

“…By taking the Feilaixia–Changhu Reservoir area in Guangdong Province, China as an example, the wide field view (WFV) multispectral image data of China's Gaofen-1 (spatial resolution of 16 m) was used, and the remote sensing physical analysis model for water quality (Deng model) based on radiation transfer theory was used to perform remote sensing inversion of the chlorophyll-a concentration in the river-type reservoir. …”
Get full text

The proposed model of the body of knowledge of digital transformation for the Central Bank of the Islamic Republic of Iran by Samira Tahmasebi Ashtiani, Mohammad Hasanzadeh, Atefeh Sharif, Mostafa Amini

“…After distributing and collecting the data from the questionnaire, confirmatory factor analysis was used with the help of SMART PLS software to estimate the parameters and all calculations. …”
Get full text

An updated systematic review with meta-analysis and meta-regression of the factors associated with human visceral leishmaniasis in the Americas by Anna Gabryela Sousa Duarte, Guilherme Loureiro Werneck, Sarah de Farias Lelis, Thays Santos Mendonça, Daniela Dias Vasconcelos, Tiago Silveira Gontijo, Álisson Oliveira dos Santos, Lucas Edel Donato, Vinícius Silva Belo

“…The level of evidence for associations of VL with sex and age was classified as moderate whilst that for all other associations was either low or very low. The methodological quality of recent studies showed a positive progression but shortcomings were still evident regarding selection criteria and methods of data analysis. …”
Get full text

Videos of Savi Oriented Learning Model Based on Sparcol Scribe in Class IV Students by Niya Selfiana Panggabean, I Kadek Suartama, I Made Tegeh

“…This type of research is the development of the ADDIE model. Data collection methods consist of interviews, observation, document recording, and distributing questionnaires. …”
Get full text

MapSAM: adapting segment anything model for automated feature detection in historical maps by Xue Xia, Daiwei Zhang, Wenxuan Song, Wei Huang, Lorenz Hurni

“…However, this process is often constrained by the time-consuming task of manually digitizing sufficient high-quality training data. The emergence of visual foundation models, such as the Segment Anything Model (SAM), offers a promising solution due to their remarkable generalization capabilities and rapid adaptation to new data distributions. …”
Get full text

Learned Regularizations for Multi‐Parameter Elastic Full Waveform Inversion Using Diffusion Models by Mohammad H. Taufik, Fu Wang, Tariq Alkhalifah

“…We also empirically demonstrate that, unlike traditional regularization schemes, our framework converges to better model estimates that fit the observed data better.…”
Get full text

The potential impact of COVID-19 in refugee camps in Bangladesh and beyond:  A modeling study. by Shaun Truelove, Orit Abrahim, Chiara Altare, Stephen A Lauer, Krya H Grantz, Andrew S Azman, Paul Spiegel

“…Due to limited data at the time of analyses, we assumed that age was the primary determinant of infection severity and hospitalization. …”
Get full text

High‐Resolution Modeling and Projecting Local Dynamics of Differential Vulnerability to Urban Heat Stress by I. Marginean, J. Crespo Cuaresma, R. Hoffmann, R. Muttarak, J. Gao, Anne Sophie Daloz

“…This study aims to address the research gaps by presenting a new population projection exercise at high‐resolution based on the Bayesian modeling framework for the case study of Madrid, using demographic data under the scenarios compatible with the Shared Socioeconomic Pathways. …”
Get full text

A blood test-based machine learning model for predicting lung cancer risk by Lihi Schwartz, Naor Matania, Matanel Levi, Teddy Lazebnik, Teddy Lazebnik, Shiri Kushnir, Noga Yosef, Assaf Hoogi, Dekel Shlomi, Dekel Shlomi

“…Machine learning (ML) is a promising method to identify complex patterns in the data that can reveal personalized disease predictors.MethodsAn ML-based model was used on blood test data collected before the diagnosis of LC, and sociodemographic factors such as age and gender among LC patients and controls were incorporated to predict the risk for future LC diagnosis.ResultsIn addition to age and gender, we identified 22 blood tests that contributed to the model. …”
Get full text

BIM Adoption in Construction Companies of Tehran Province, Using Technology Acceptance Model (TAM) by Sahar Taheripour, Mojtaba Azizi, Ehsanallah Eshtehardian

“…According to previous research in this field, unfortunately, the adoption of BIM in Iran is very slow and undesirable.Methodology: The present study obtained the BIM adoption status using the Technology Acceptance Model (TAM) by distributing a questionnaire among the first-ranked construction companies in Tehran province.Findings: The data analysis using Structural Equation Modeling showed that BIM adoption was below average in all 87 valid samples. …”
Get full text

Predictive modeling of punchouts in continuously reinforced concrete pavement: a machine learning approach by Ghazi Al-Khateeb, Ali Alnaqbi, Waleed Zeiada

“…It is noteworthy that ensemble methods such as boosted trees and Gaussian process regression models exhibit promising predictive performance, with low root mean square error (RMSE) and high R-squared values. …”
Get full text

Investigating surgical risk in coronary artery disease: Utilizing ordinal regression for predictive modeling by Hewir Abdulqadir Khidir, Azhin Mohammed Khudhur, Dler Hussein Kadir, Nozad H. Mahmood, Dlshad Mahmood Saleh

“…Significant predictors identified include blood urea, low-density lipoprotein (LDL) cholesterol levels, hemoglobin (HGB), red cell distribution width (RDW), and smoking status (smoker: yes). …”
Get full text

Comparing the effectiveness of landslide susceptibility mapping by using the frequency ratio and hybrid MCDM models by Jonmenjoy Barman, Syed Sadath Ali, Teachersunday Nongrem, Brototi Biswas, K. Srinivasa Rao, Malay Pramanik, Fahdah Falah Ben Hasher, Mohamed Zhran

“…In opposite, the overall ranking was used to generate landslide susceptibility map (LSM) for the AHP-VIKOR model. Subsequently, the generated LSM was classified into five hierarchical zones from very low to very high based on the natural breaking classification. …”
Get full text