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Connectionist Approaches to Natural Language Processing

Chris Sinha, Ronan G. Reilly, NOEL E. SHARKEY • The American Journal of Psychology (1994)

Preface, N. Sharkey and R. Reilly connectionist natural language processing semantics, M.D. Dyer, et al distributed symbol discovery through symbol recirculation - toward natural language processing in distributed connectionist networks, R....

OPENALEX DOI: https://doi.org/10.2307/1423043

THE NORTHERN LABOR MARKET IN A RESOURCE-BASED REGIONAL ECONOMY: THE CASE OF THE KHANTY-MANSIYSK AUTONOMOUS OKRUG—YUGRA

Alexander V. Prokopev, Nadezhda V. Puchkova, Natalya V. Timofeeva, Anna V. Simakova et al. • Север и рынок: формирование экономического порядка (2025)

This study examines the labor market of the Khanty-Mansi Autonomous Okrug–Yugra. The relevance of the research stems from the region’s strong dependence on natural resource reserves and production volumes, driven by the dominance of the min...

DOAJ Open Access (DOAJ) DOI: 10.37614/2220-802X.4.2025.90.004

Assessing GPT's capabilities in consumer food survey analysis: A comparative approach for understanding food technophobia and novel protein perceptions

Peihua Ma, Si Chen, Wenfan Su, Jiping Sheng et al. • Journal of Agriculture and Food Research (2025)

This study explores the application of GPT models for automating consumer food survey analysis, focusing on Chinese consumers' acceptance of plant-based foods, cultured meat, insect-based proteins, and microbial proteins. Traditional survey...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jafr.2025.102086

Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions

Siham Essahraui, Ismail Lamaakal, Yassine Maleh, Khalid El Makkaoui et al. • IEEE Access (2025)

Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3589938

Computer vision for computer games

William T. Freeman, Kazuhiro Tanaka, Jun Ohta, Kazuo Kyuma • International Conference on Automatic Face and Gesture Recognition (2002)

The appeal of computer games may be enhanced by vision-based user inputs. The high speed and low cost requirements for near-term, mass-market game applications make system design challenging. The response time of the vision interface should...

OPENALEX DOI: https://doi.org/10.1109/afgr.1996.557250

Fruits and vegetables quality evaluation using computer vision: A review

Anuja Bhargava, Atul Bansal • Journal of King Saud University - Computer and Information Sciences (2018)

In agriculture science, automation increases the quality, economic growth and productivity of the country. The export market and quality evaluation are affected by assorting of fruits and vegetables. The crucial sensory characteristic of fr...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jksuci.2018.06.002

Distribution of Marbling Throughout the M. Longissimus Thoracis et Lumborum of Beef Carcasses Using an Instrument-Grading System

Clinton E. Walenciak, Dale R Woerner, Michael J. Colle, Phillip D. Bass et al. • Meat and Muscle Biology (2018)

Beef Loin, Strip Loins (IMPS #180; n = 20) with marbling scores between Modest00 and Modest30 at the 12th and 13th rib interface of the M. longissimus thoracis et lumborum (LL) were collected. Each strip loin was fabricated into 6 samples t...

DOAJ Open Access (DOAJ) DOI: 10.22175/mmb2018.04.0005

Building neural networks

David M. Skapura (1995)

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

OPENALEX

Neural Networks and Brain Function

Edmund T. Rolls, Alessandro Treves • Oxford University Press eBooks (1997)

The aim of this book is to describe the types of computation that can be performed by biologically plausible neural networks, and to show how these may be implemented in different systems in the brain. The book is structured in three sectio...

OPENALEX DOI: https://doi.org/10.1093/acprof:oso/9780198524328.001.0001

Deep Learning for Time Series Anomaly Detection: A Survey

Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charų C. Aggarwal et al. • ACM Computing Surveys (2024)

Time series anomaly detection is important for a wide range of research fields and applications, including financial markets, economics, earth sciences, manufacturing, and healthcare. The presence of anomalies can indicate novel or unexpect...

OPENALEX cc-by DOI: https://doi.org/10.1145/3691338

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

Deep learning applications and challenges in big data analytics

Maryam Mousaarab Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar, Naeem Seliya et al. • Journal Of Big Data (2015)

Abstract Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can con...

OPENALEX cc-by DOI: https://doi.org/10.1186/s40537-014-0007-7

A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm.

Kaixuan Sun, Qi Yao, Yanhui Li • PLoS ONE (2025)

The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challengi...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0337103

Bi-Objective Portfolio Optimization Under ESG Volatility via a MOPSO-Deep Learning Algorithm

Imma Lory Aprea, Gianni Bosi, Gabriele Sbaiz, Salvatore Scognamiglio • Mathematics (2025)

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) informati...

DOAJ Open Access (DOAJ) DOI: 10.3390/math13203308