Survivability Prediction of Open Source Software with Polynomial Regression by Sohee Park, Ryeonggu Kwon, Gihwon Kwon

“…In this paper, we conduct data collection and extraction, generating model, and model testing and evaluation to predict survivability using these data. …”
Get full text

Fixed wh-expressions in classroom second language acquisition: databases of computational properties or utterance schemas? by Thomas Hammond, Kook-Hee Gil

“…From this, we argue that such a unified account of learners’ L2 development can offer a better description of the trends observed in the corpus than either usage-based or generative models can do independently.…”
Get full text

Supervised diagnostic classification of cognitive attributes using data augmentation. by Ji-Young Yoon, Gahgene Gweon, Yun Joo Yoo

“…This method is designed to utilize the augmented data using a data generation model constructed by leveraging the probability of correct responses for each attribute mastery pattern derived from the expert-labeled dataset. …”
Get full text

Hydrometeorological Conditions of the Volga Flow Generation into the Caspian Sea during the Last Glacial Maximum by Andrey Kalugin, Polina Morozova

“…The second approach is based on the spatially distributed process-based runoff generation model using PMIP4-CMIP6 model data as boundary conditions. …”
Get full text

Functional traits predict species co‐occurrence patterns in a North American Odonata metacommunity by Francesco Cerini, Leonardo Vignoli, Michael Blust, Giovanni Strona

“…Then, we used machine learning to generate models which proved capable of predict accurately the observed co‐occurrence patterns from species functional traits. …”
Get full text

A Wasserstein Generative Adversarial Network–Gradient Penalty-Based Model with Imbalanced Data Enhancement for Network Intrusion Detection by Gwo-Chuan Lee, Jyun-Hong Li, Zi-Yang Li

“…Experimental results revealed that the WGAN-GP generation model is the most effective for detecting sparse data probes. …”
Get full text

Unsupervised inference approach to facial attractiveness by Miguel Ibanez-Berganza, Ambra Amico, Gian Luca Lancia, Federico Maggiore, Bernardo Monechi, Vittorio Loreto

“…The application of such generative models to the supervised classification of the gender of the subject that sculpted the face reveals that it may be predicted with astonishingly high accuracy. …”
Get full text

Automatic High-Accuracy Sea Ice Mapping in the Arctic Using MODIS Data by Liyuan Jiang, Yong Ma, Fu Chen, Jianbo Liu, Wutao Yao, Erping Shang

“…In this paper, an ice map generation model based on Moderate-Resolution Imaging Spectroradiometer (MODIS) reflectance bands is constructed to obtain sea ice data with a high temporal and spatial resolution. …”
Get full text

A Method for Retrieving Cloud-Top Height Based on a Machine Learning Model Using the Himawari-8 Combined with Near Infrared Data by Yan Dong, Xuejin Sun, Qinghui Li

“…The algorithm comprehensively utilizes AHI L1 multi-channel radiance data and calculates the input parameters of the generated model according to the characteristics of the cloud phase, texture, and the local brightness temperature change of the cloud. …”
Get full text

Learning a restricted Boltzmann machine using biased Monte Carlo sampling by Nicolas Béreux, Aurélien Decelle, Cyril Furtlehner, Beatriz Seoane

“…Restricted Boltzmann Machines are simple and powerful generative models that can encode any complex dataset. …”
Get full text

High-spatial resolution epidemic surveillance of bacterial meningitis in the African meningitis belt in Burkina Faso by Maxime Woringer, Souleymane Porgho, Christophe Fermanian, Nadège Martiny, Avner Bar-Hen, Judith E. Mueller

“…We used suspected meningitis surveillance data at health centre (HC) resolution from Burkina Faso from 14 health districts spanning years 2004–2014 and analysed them using spatio-temporal statistics and generative models. An operational analysis compared epidemic signals at district and HC-level using weekly incidence thresholds. …”
Get full text

Dialogue system based on spoken conversations with access to an unstructured knowledge base by Sergei M. Masliukhin

“…The tasks are solved by adapting the retrieval augmented text generation model Retrieval Augmented Generation. The proposed method tested on the data from the 10th Dialogue System Technology Challenge. …”
Get full text

A Systematic Literature Review on Binary Neural Networks by Ratshih Sayed, Haytham Azmi, Heba Shawkey, A. H. Khalil, Mohamed Refky

“…Although there are many advantages of BNN, the binarization process has a significant impact on the performance and accuracy of the generated models. To reflect the state-of-the-art in BNN and explore how to develop and improve BNN-based models, we conduct a systematic literature review on BNN with data extracted from 239 research studies. …”
Get full text

Estimating plant biomass in agroecosystems using a drop-plate meter by Stephen M. Robertson, Ryan B. Schmid, Jonathan G. Lundgren

“…Methods Drop-plate data collected by more than 20 individuals from 16 crop types on 312 farms across 15 states were used to generate models to estimate plant biomass among and within crop types. …”
Get full text

Analysis of the influence of different thermal boundary conditions on thermoelectric generators by Wei He, Zihan Cai, Rui Guo, Shixue Wang, Xingyu Liang, Yulong Zhao, Lei Miao, Yulin Wang

Get full text

A New Methodology to Obtain a Feasible Thermal Operation in Power Systems in a Medium-Term Horizon by Luis Montero, Antonio Bello, Javier Reneses

“…Temporal aggregation, integer programming relaxation or less accurate generation modeling are usually employed to obtain reasonable computation times. …”
Get full text

Should multiple imputation be stratified by exposure group when estimating causal effects via outcome regression in observational studies? by Jiaxin Zhang, S Ghazaleh Dashti, John B. Carlin, Katherine J. Lee, Margarita Moreno-Betancur

“…We conducted an extensive simulation study based on an illustrative case study from the Victorian Adolescent Health Cohort Study, assessing a range of scenarios, including seven outcome generation models with exposure-confounder interactions of differing strength. …”
Get full text

Compressive Strength Prediction for Industrial Waste-Based SCC Using Artificial Neural Network by Md Akram Hossain, G M Sadiqul Islam, Amit Mallick

“…The experimental and expected outcomes were compared with the model prediction to evaluate the predictive capacity, generalize the generated model, and observe suitable matches. The developed ANN network can predict the desired output, i.e., compressive strength incorporating industrial waste. …”
Get full text

An Adaptive Strategy for Medium-Term Electricity Consumption Forecasting for Highly Unpredictable Scenarios: Case Study Quito, Ecuador during the Two First Years of COVID-19 by Manuel Jaramillo, Diego Carrión

“…All these approaches evaluate the prediction error when comparing the generated models with the data that fed the model, but they do not compare these values with the actual data of electricity demand once these are obtained, in addition, these techniques present high error values when there are unexpected changes in the trend of electricity consumption. …”
Get full text

Investigation and improvement of vehicle A/C system compressor noise by 6sigma approach by Mehdi YILDIZ

“…Besides, a regression analysis is performed to identify the compressor noise generation model (equation describing the noise model) based on these highly correlated factors. …”
Get full text