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Can Geopolitical Risk Improve the Forecasting of Thai Stock-Market Returns? Evidence from Econometrics and Machine-Learning Models

Tanattrin Bunnag • Forecasting (2026)

Geopolitical uncertainty may affect financial markets, but its incremental value for forecasting emerging-market stock returns remains unclear. Using monthly data from January 1990 to July 2026, this study compares ARIMA-GARCH and ARIMAX-GA...

DOAJ Open Access (DOAJ) DOI: 10.3390/forecast8050087

A machine-learning approach for predicting the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome

Dong-Dong Wang, Ya-Feng Li, Yi-Zhen Mao, Su-Mei He et al. • Frontiers in Nutrition (2022)

The present study aimed to explore the effect of carnitine supplementation on body weight in patients with polycystic ovary syndrome (PCOS) and predict an appropriate dosage schedule using a machine-learning approach. Data were obtained fro...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnut.2022.851275

DaDianNao: A Machine-Learning Supercomputer

Yunji Chen, Tao Luo, Shaoli Liu, Shijin Zhang et al. • IEEE/ACM International Symposium on Microarchitecture (MICRO) (2014)

Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learni...

OPENALEX DOI: https://doi.org/10.1109/micro.2014.58

Machine learning in breast MRI

Beatriu Reig, Laura C. Heacock, Krzysztof J. Geras, Linda P. Moy • Journal of Magnetic Resonance Imaging (2019)

Machine-learning techniques have led to remarkable advances in data extraction and analysis of medical imaging. Applications of machine learning to breast MRI continue to expand rapidly as increasingly accurate 3D breast and lesion segmenta...

OPENALEX DOI: https://doi.org/10.1002/jmri.26852 PMC: 7085409

miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles.

Upendra Kumar Pradhan, Nitesh Kumar Sharma, Prakash Kumar, Ashwani Kumar et al. • PLoS ONE (2021)

Formation of mature miRNAs and their expression is a highly controlled process. It is very much dependent upon the post-transcriptional regulatory events. Recent findings suggest that several RNA binding proteins beyond Drosha/Dicer are inv...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0258550

Machine learning unifies the modeling of materials and molecules

Albert P. Bartók, Sandip De, Carl R. Poelking, Noam Bernstein et al. • Science Advances (2017)

Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a...

OPENALEX cc-by-nc DOI: https://doi.org/10.1126/sciadv.1701816 PMC: 5729016

Machine Learning with TensorFlow

Nishant Shukla • CERN Document Server (European Organization for Nuclear Research) (2018)

Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...

OPENALEX

Generative-Adversarial-Network-Based Image Reconstruction for the Capacitively Coupled Electrical Impedance Tomography of Stroke

Mikhail Ivanenko, Damian Wanta, Waldemar T. Smolik, Przemysław Wróblewski et al. • Life (2024)

This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...

DOAJ Open Access (DOAJ) DOI: 10.3390/life14030419

Machine-learning reprogrammable metasurface imager

Lianlin Li, Hengxin Ruan, Che Liu, Ying Li et al. • Nature Communications (2019)

Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we e...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41467-019-09103-2 PMC: 6403242

Machine Learning in Compiler Optimization

Zheng Wang, Michael F. P. O’boyle • Proceedings of the IEEE (2018)

In the last decade, machine-learning-based compilation has moved from an obscure research niche to a mainstream activity. In this paper, we describe the relationship between machine learning and compiler optimization and introduce the main ...

OPENALEX Open Access DOI: https://doi.org/10.1109/jproc.2018.2817118

Revealing the dynamic evolution of interfacial water during Mg anodic dissolution

Xinchen Xu, Xingpeng Liao, Gaoning Shi, Yuyang Chen et al. • Journal of Magnesium and Alloys (2026)

Though magnesium alloys possess attractive mechanical properties, their applications are severely limited by galvanic corrosion, due to the rapid anodic dissolution and anomalous hydrogen evolution. In this work, well-tempered metadynamics ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jma.2026.102217

MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation

C. Roychoudhury, R. Kumar, C. He, W. Y. Y. Cheng et al. • Earth System Science Data (2026)

We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...

DOAJ Open Access (DOAJ) DOI: 10.5194/essd-18-5209-2026

Interactive machine learning

Jerry Alan Fails, Dan R. Olsen • ACM International Conference on Intelligent User Interfaces (IUI) (2003)

Perceptual user interfaces (PUIs) are an important part of ubiquitous computing. Creating such interfaces is difficult because of the image and signal processing knowledge required for creating classifiers. We propose an interactive machine...

OPENALEX DOI: https://doi.org/10.1145/604045.604056

Memristor Synapse—A Device-Level Critical Review

Sridhar Chandrasekaran, Yao-Feng Chang, Firman Mangasa Simanjuntak • Nanomaterials (2026)

The memristor has long been known as a nonvolatile memory technology alternative and has recently been explored for neuromorphic computing, owing to its capability to mimic the synaptic plasticity of the human brain. The architecture of a m...

DOAJ Open Access (DOAJ) DOI: 10.3390/nano16030179

A machine learning based scheme for enhancing the detection of position falsification attacks in vehicular ad hoc networks

Eslam Abdelkreem, Sherif Hussein, Ashraf Tammam • Scientific Reports (2026)

Abstract Vehicular Ad Hoc Networks (VANETs) are wireless networks established between vehicles and their surrounding infrastructure, enabling the exchange of information. Consequently, many applications that can enhance passengers’ safety a...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-39867-9

A Deep Dive into a Groundbreaking Approach to Machine Learning-Powered E-Learning

Subhabrata Sengupta, Rupayan Das, Satyajit Chakrabarti • Emitter: International Journal of Engineering Technology (2024)

Information retrieval aims to find the most important data for specific queries. The challenge is retrieving relevant data efficiently due to the large search area. Existing solutions lead to unnecessary processing costs. Additionally, iden...

DOAJ Open Access (DOAJ) DOI: 10.24003/emitter.v12i2.855