This article discusses the possibilities to study relevant quality aspects of food, such as color,
nutrient content, and safety, in a quantitative way via mathematical models. These quality …

The level of quality that food maintains as it travels down the production-to-consumption
path is largely determined by the chemical, biochemical, physical, and microbiological …

As more and more companies have captured and analyzed huge volumes of data to
improve the performance of supply chain, this paper develops a big data harvest model that …

Precise comprehension of a file system state at any given time is vital for performing digital
forensic analyses. To uncover evidence of the digital crime, the logical representation of file …

Computers have transformed the design of everything from cars to coffee cups. Now the food
industry faces the same revolution, with intelligent computer models being used in the …

Agri-food chains are complex systems involving multiple multifaceted firms usually working
together within specific industry sectors (eg grains, beef, wool, dairy) to satisfy an …

Sažetak Bayes network modelling for structural causal analysis between wine
physicochemical data and quantitative human quality blind assessments is applied. The …

The construct of “feature fatigue” represents the phenomenon of customer's inconsistent
satisfaction: customers prefer to choose products with more features and capacities initially …

Learning preferences is a useful task in application fields such as collaborative filtering,
information retrieval, adaptive assistants or analysis of sensory data provided by panels …

Poor definition and uncertainty are primary characteristics of conceptual design processes.
During the initial stages of these generally human-centric activities, little knowledge …