Browsing by Issue Date, starting with "2020-03-03"
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Fraud Prediction in Smart Supply Chains Using Machine Learning TechniquesPublication . Constante-Nicolalde, Fabián-Vinicio; Guerra-Terán, Paulo; Pérez-Medina, Jorge-LuisIn the domain of Big Data, the company’s supply chain has a very high-risk exposure and this must be observed from a preventive perspective, that is, act before such situations occur. As a company grows and diversifies the number of suppliers, customers and therefore increases its number of daily transactions and associated risks. Despite the innovation and improvements that have been incorporated into financial management, credit and debit cards are the main means of exchanging cash online, with the expansion of e-commerce, online shopping has also increased number of extortion cases that have been identified and that continues to expand greatly. It takes a lot of time, effort and investment to restore the impact of these damages. In this paper, we work with machine learning techniques, used in predicting smart supply chain fraud, are valuable for estimating, classifying whether a transaction is normal or fraudulent, and mitigating future dangers.
- Social Role in Organizational Management Understanding People Behavior and MotivationPublication . Maia, Nuno; Neves, Mariana; Barbosa, Agostinho; Carrulo, Bruno; Araújo, Nuno; Fernandes, Ana; Vicente, Dinis; Ribeiro, Jorge; Vicente, Henrique; Neves, JoséThe aim of this work is to respond to the need to rethink the behavior and motivation of employees in their relationship with managers and social groups, i.e., one’s main goal is based on increasing engagement in order to reach organizational goals and job workers satisfaction, a complex concept that is influenced by different causes. Indeed, in this work it is analyzed the impact of working conditions on job satisfaction. This is where attention is drawn to the concept of entropy, since we are not focusing on the value a variable can take, but on the effort that has been expended to obtain it. The idea of entropy comes from a principle of thermodynamics dealing with energy. It usually refers to the idea that everything in the universe eventually moves from order to disorder, and entropy is the measurement of that change, that is used here to understand and assess the workers behavior and motivation. The subsequent formal model is based on a set of logical structures for knowledge representation and reasoning that conform to the above entropic view, then leading to an Artificial Neural Network approach to computation, an archetypal that considers the motive behind the action.