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Application of Artificial Neural Networks for Predicting Relative Permeability in Talang Akar Formation

Fathaddin Muhammad Taufiq, Sari Alvita Kumala, Sutansyah Daddy, Ulfah Baiq Maulinda et al. • E3S Web of Conferences (2024)

Relative permeability is a substantial parameter for estimating multi-phase fluid flow in porous rocks. It is a complex physical property that is influenced by the behavior and interactions between the fluid and rock phases. Relative permea...

DOAJ Open Access (DOAJ) DOI: 10.1051/e3sconf/202450003019

A Revision of Empirical Models of Stirling Engine Performance Using Simple Artificial Neural Networks

Enrique González-Plaza, David García, Jesús-Ignacio Prieto • Inventions (2023)

Stirling engines are currently of interest due to their adaptability to a wide range of energy sources. Since simple tools are needed to guide the sizing of prototypes in preliminary studies, this paper proposes two groups of simple models ...

DOAJ Open Access (DOAJ) DOI: 10.3390/inventions8040088

An optimized deep learning framework for temporally stable real-time face detection in unconstrained video streams

P. E. Janani Pappu, B. Devanthan • Discover Artificial Intelligence (2026)

Abstract Face detection in real-time video streams remains challenging because of dynamic variations in illumination, pose, motion blur, and partial occlusion. This paper proposes an optimized deep learning framework that integrates YOLOv12...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-02275-z

Deep Learning for Portfolio Optimization

Zihao Zhang, Stefan Zohren, Stephen Roberts • The Journal of Financial Data Science (2020)

In this article, the authors adopt deep learning models to directly optimize the portfolio Sharpe ratio. The framework they present circumvents the requirements for forecasting expected returns and allows them to directly optimize portfolio...

OPENALEX Open Access DOI: https://doi.org/10.3905/jfds.2020.1.042

Landslide Susceptibility Mapping Based on Deep Learning Algorithms Using Information Value Analysis Optimization

Junjie Ji, Yongzhang Zhou, Qiuming Cheng, Shoujun Jiang et al. • Land (2023)

Selecting samples with non-landslide attributes significantly impacts the deep-learning modeling of landslide susceptibility mapping. This study presents a method of information value analysis in order to optimize the selection of negative ...

DOAJ Open Access (DOAJ) DOI: 10.3390/land12061125

Review: Deep Learning on 3D Point Clouds

Saifullahi Aminu Bello, Shangshu Yu, Cheng Wang, Jibril Muhammad Adam et al. • Remote Sensing (2020)

A point cloud is a set of points defined in a 3D metric space. Point clouds have become one of the most significant data formats for 3D representation and are gaining increased popularity as a result of the increased availability of acquisi...

OPENALEX cc-by DOI: https://doi.org/10.3390/rs12111729

Deep Learning-Based Prediction of Wind Power for Multi-turbines in a Wind Farm

Xiaojiao Chen, Xiuqing Zhang, Mi Dong, Liansheng Huang et al. • Frontiers in Energy Research (2021)

The prediction of wind power plays an indispensable role in maintaining the stability of the entire power grid. In this paper, a deep learning approach is proposed for the power prediction of multiple wind turbines. Starting from the time s...

DOAJ Open Access (DOAJ) DOI: 10.3389/fenrg.2021.723775

Correlation analysis between preoperative MRI image features based on image reconstruction algorithms and incision healing in patients with benign hepatobiliary diseases undergoing postoperative drainage tube placement

Chunlong Shao, Ning Zhang, Wei Du, Han Li et al. • Journal of Radiation Research and Applied Sciences (2026)

Objective: This study was designed to examine the association between preoperative abdominal MRI features derived using a deep learning-based reconstruction (DL-Recon) algorithm and postoperative surgical incision-healing outcomes, while ev...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrras.2026.102395

Hyperspectral Image Classification With Deep Learning Models

Xiaofei Yang, Yunming Ye, Xutao Li, Raymond Y.K. Lau et al. • IEEE Transactions on Geoscience and Remote Sensing (2018)

Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem. In contrast to conventional computer vision task...

OPENALEX DOI: https://doi.org/10.1109/tgrs.2018.2815613

Presenting the students’ academic achievement causal model based on goal orientation

EBRAHIM NASIRI, ALI POUR-SAFAR, MAHDOKHT TAHERI, ABDULLAH SEDIGHI PASHAKY et al. • Journal of Advances in Medical Education and Professionalism (2017)

Introduction: Several factors play a role in academic achievement, individual’s excellence and capability to do actions and tasks that the learner is in charge of in learning areas. The main goal of this study was to present academic ach...

DOAJ Open Access (DOAJ)

Exhaust Emissions from Gasoline Vehicles with Different Fuel Detergency and the Prediction Model Using Deep Learning

Rongshuo Zhang, Hongfei Chen, Peiyuan Xie, Lei Zu et al. • Sensors (2023)

Enhancing gasoline detergency is pivotal for enhancing fuel efficiency and mitigating exhaust emissions in gasoline vehicles. This study investigated gasoline vehicle emission characteristics with different gasoline detergency, explored syn...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23177655

A 2D and 3D segmentation-based microstructure study on the role of brittle phases in diffusion brazed AISI 304L/NiCrSiFeMoB joints

Johannes L. Otto, Lukas M. Sauer, Malte Brink, Thorge Schaum et al. • Materials & Design (2023)

Nickel-based filler metals are frequently used in high temperature vacuum diffusion brazing for austenitic stainless-steel joints when components are subjected to high static or dynamic loads, corrosive environments and elevated temperature...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.matdes.2023.112401

Deep learning in optical metrology: a review

Chao Zuo, Jiaming Qian, Shijie Feng, Wei Yin et al. • Light Science & Applications (2022)

With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, n...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41377-022-00714-x PMC: 8866517

Some results of the digital analysis of the semantic similarity of audiovisual translation texts (based on the films directed by Denis Villeneuve)

Aishat I. Lepshakova, Oleg V. Kurskikh • Актуальные проблемы филологии и педагогической лингвистики (2025)

The article analyses different translation versions of science fiction films directed by Denis Villeneuve with the aim of determining their semantic similarity through NLP analysis. There are four groups of metrics used in text analysis: se...

DOAJ Open Access (DOAJ) DOI: 10.29025/2079-6021-2025-1-132-150

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

Orges Koci, Richard K. Russell, M. Guftar Shaikh, Christine Edwards et al. • Microbiome (2024)

Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40168-024-01834-9

MARKETING ACTIVITIES OF IT COMPANIES: INFORMATION AND ORGANISATIONAL CAPABILITIES FOR DIGITAL PRODUCT DEVELOPMENT

Kostiantyn Fuks • Green, Blue and Digital Economy Journal (2024)

The purpose of this article is to provide a comprehensive examination of the informational and organisational capabilities of marketing activities in the market for digital products and services. It highlights the importance of data analysi...

DOAJ Open Access (DOAJ) DOI: 10.30525/2661-5169/2024-1-4

Statistical Characteristics of Nighttime Medium‐Scale Traveling Ionospheric Disturbances From 10‐Years of Airglow Observation by the Machine Learning Method

Chang Lai, Jiyao Xu, Zhishuang Lin, Kun Wu et al. • Space Weather (2023)

Abstract For the first time, we used the machine learning method to analyze the statistical occurrence and propagation characteristics of nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) from October 2011 to December 2021 ...

DOAJ Open Access (DOAJ) DOI: 10.1029/2023SW003430