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Unveiling livestock trade trends: A beginner's guide to generative AI-powered visualization.

Research in veterinary science
This tutorial, rooted in the context of livestock research, is designed to assist novice or non-programmers in visualizing trends in livestock exports between the US and Japan using Python and generative AI systems such as Microsoft's Copilot and Goo...

Exploring Internet of Things adoption challenges in manufacturing firms: A Delphi Fuzzy Analytical Hierarchy Process approach.

PloS one
Innovation is key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies...

Parametric seasonal-trend autoregressive neural network for long-term crop price forecasting.

PloS one
Crop price forecasting is difficult in that supply is not as elastic as demand, therefore, supply and demand should be stabilized through long-term forecasting and pre-response to the price. In this study, we propose a Parametric Seasonal-Trend Autor...

Factor-GAN: Enhancing stock price prediction and factor investment with Generative Adversarial Networks.

PloS one
Deep learning, a pivotal branch of artificial intelligence, has increasingly influenced the financial domain with its advanced data processing capabilities. This paper introduces Factor-GAN, an innovative framework that utilizes Generative Adversaria...

Heteroscedasticity effects as component to future stock market predictions using RNN-based models.

PloS one
Heteroscedasticity effects are useful for forecasting future stock return volatility. Stock volatility forecasting provides business insight into the stock market, making it valuable information for investors and traders. Predicting stock volatility ...

Innovative entrepreneurial market trend prediction model based on deep learning: Case study and performance evaluation.

Science progress
In the current economic landscape, the growing importance of innovation and entrepreneurship underscores an urgent need for accurate market trend prediction. Addressing this challenge, our study introduces an innovative entrepreneurial market trend p...

Predicting pharmaceutical prices. Advances based on purchase-level data and machine learning.

BMC public health
BACKGROUND: Increased costs in the health sector have put considerable strain on the public budgets allocated to pharmaceutical purchases. Faced with such pressures amplified by financial crises and pandemics, national purchasing authorities are pres...

Early warning of trends in commercial wildlife trade through novel machine-learning analysis of patent filing.

Nature communications
Unsustainable wildlife trade imperils thousands of species, but efforts to identify and reduce these threats are hampered by rapidly evolving commercial markets. Businesses trading wildlife-derived products innovate to remain competitive, and the pat...

Preventing illegal seafood trade using machine-learning assisted microbiome analysis.

BMC biology
BACKGROUND: Seafood is increasingly traded worldwide, but its supply chain is particularly prone to frauds. To increase consumer confidence, prevent illegal trade, and provide independent validation for eco-labelling, accurate tools for seafood trace...

Predicting Short Time-to-Crime Guns: a Machine Learning Analysis of California Transaction Records (2010-2021).

Journal of urban health : bulletin of the New York Academy of Medicine
Gun-related crime continues to be an urgent public health and safety problem in cities across the US. A key question is: how are firearms diverted from the legal retail market into the hands of gun offenders? With close to 8 million legal firearm tra...