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Evaluation of GCC optimization parameters

Rodrigo D. Escobar, Alekya R. Angula, Mark Corsi • Ingenierías USBMed (2012)

Compile-time optimization of code can result in significant performance gains. The amount of these gains varies widely depending upon the code being optimized, the hardware being compiled for, the specific performance increase attempted (e....

DOAJ Open Access (DOAJ)

Development of Machine Learning Models to Predict Compressed Sward Height in Walloon Pastures Based on Sentinel-1, Sentinel-2 and Meteorological Data Using Multiple Data Transformations

Charles Nickmilder, Anthony Tedde, Isabelle Dufrasne, Françoise Lessire et al. • Remote Sensing (2021)

Accurate information about the available standing biomass on pastures is critical for the adequate management of grazing and its promotion to farmers. In this paper, machine learning models are developed to predict available biomass express...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs13030408

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

Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics

Ji-Hoon Kim, Seunghee Han, Kwanghyun Park, Soo-Young Ji et al. • IEEE Access (2024)

The ability to perform machine learning (ML) tasks in a database management system (DBMS) is a new paradigm for conventional database systems as it enables advanced data analytics on top of well-established capabilities of DBMSs. However, t...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3347725

An ensemble approach for imbalanced multiclass malware classification using 1D-CNN

Binayak Panda, Sudhanshu Shekhar Bisoyi, Sidhanta Panigrahy • PeerJ Computer Science (2023)

Dependence on the internet and computer programs demonstrates the significance of computer programs in our day-to-day lives. Such demands motivate malware developers to create more malware, both in terms of quantity and variety. Researchers...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.1677

Machine learning and applications in microbiology

Stephen J. Goodswen, Joel Barratt, Paul J Kennedy, Alexa Kaufer et al. • FEMS Microbiology Reviews (2021)

To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial intelligence applica...

OPENALEX cc-by-nc DOI: https://doi.org/10.1093/femsre/fuab015 PMC: 8498514

A metaheuristic with a neural surrogate function for Word Sense Disambiguation

Azim Keshavarzian Nodehi, Nasrollah Moghadam Charkari • Machine Learning with Applications (2022)

Word Sense Disambiguation (WSD) is one of the earliest problems in natural language processing which aims to determine the correct sense of words in context. The semantic information provided by WSD systems is highly beneficial to many task...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mlwa.2022.100369

Evaluation of Predictive Maintenance by Marginal Utility: A Case Study on Offshore Wind

Rasmus Dovnborg Frederiksen, Grzegorz Radzki, Grzegorz Bocewicz, Peter Nielsen et al. • Applied Sciences (2026)

This paper investigates the relationship between the benefits achieved by predictive maintenance implementation and the related costs incurred intentionally or not. Specifically, we seek to establish an evaluation method for predictive main...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16178708

Evaluation of PCA with variable selection for cluster typological domains

Silvânia Alves Braga de Castro, André Carlos Silva • REM: International Engineering Journal (2024)

Abstract The modeling of mineral deposits has been improved over the years with the incorporation of mineralogical and metallurgical information obtained from drilling samples that make up the pillars for the construction of resource models...

DOAJ Open Access (DOAJ) DOI: 10.1590/0370-44672023770071

Aerosol Optical Depth Retrieval from MODIS Using a Physically Informed Machine Learning Framework

Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing (2026)

Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs18172862

Machine Learning and Its Applications to Biology

Adi Laurentiu Tarca, Vincent J. Carey, Xuewen Chen, Roberto J. Romero et al. • PLoS Computational Biology (2007)

The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...

OPENALEX public-domain DOI: https://doi.org/10.1371/journal.pcbi.0030116 PMC: 1904382

Machine learning in automated text categorization

Fabrizio Sebastiani • ACM Computing Surveys (2002)

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing need to organize them...

OPENALEX Open Access DOI: https://doi.org/10.1145/505282.505283

From Causes to Forecasts: Granger Causality and Machine Learning Predictions of Housing Sales in Türkiye

Musa Gün, Ahmet Akusta, Haydar Karadağ • İstanbul İktisat Dergisi (2025)

This study aims to examine the impact of macro-financial indicators on the housing sales volume in Türkiye and evaluate the forecasting performance of traditional time-series models versus modern machine-learning algorithms. Using monthly d...

DOAJ Open Access (DOAJ) DOI: 10.26650/ISTJECON2025-1707729

Hands-On Machine Learning with R

Brad Boehmke, Brandon Greenwell • Chapman & Hall/CRC eBooks (2019)

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process a...

OPENALEX DOI: https://doi.org/10.1201/9780367816377

Predicting Urban Quality of Life Using Machine Learning on Street Images and Personal Information with Statistical Feature Selection: A Comparative Study of Bangkok and London

Ployrada Suvarnakuta, Intouch Prakaisak, Pittipol Kantavat, Boonserm Kijsirikul et al. • Engineered Science (2025)

This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...

DOAJ Open Access (DOAJ) DOI: 10.30919/es1972

lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making (2024)

Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-024-02652-7

Design and Pilot Feasibility of a Low-Cost Wearable for Mexican Sign Language in Inclusive Higher Education

Juan Carlos Ramírez-Vázquez, Guadalupe Esmeralda Rivera-García, Marco Antonio Gómez-Guzmán, Marco Antonio Díaz-Martínez et al. • Technologies (2026)

A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies14030189