Evaluating the Integrated Measurement and Evaluation System IMES: A Success Story

This case study serves to illustrate an integrated and practical methodology for evaluating advanced information database systems. The goal of the integration is to create a top-down evaluation process that reduces user and data requirements to a standard evaluation structure. In this framework, the evaluation of the Integrated Measurement and Evaluation System IMES was implemented by the Energy Policy Unit of the National Technical University of Athens. Evaluation team members successfully followed the proposed evaluation methodology

The Current State of ERP Systems in Banking Sector

Abstract—Enterprise resource planning (ERP) systems integrate the organizations business functions allowing efficient information sharing across all business divisions. Through the information sharing is achieved not only better coordination but also faster and more efficient adjustment to the potential risks and business opportunities alike. This paper examines the particularities of ERP systems implementation and operation for the banking sector by considering a wide range of sources such as journal and conference papers, empirical studies and reports. Finally, through the thorough examination of the available literature, we draw conclusions about the effect by the implementation of ERP systems in the banking sector

Diabetes Advisor - A Medical Expert System for Diabetes Management

Access to medical services in rural communities, especially in the developing world, is extremely limited. Medical expert systems can play a significant role in alleviating this problem by providing decision support in the giving of advice on diagnosis, treatment and disease management. This study built a prototype for diabetes, a chronic illness affecting millions across the globe. Preliminary evaluation suggests that such a system could be useful for expanding medical services in rural communities and as an educational tool for unskilled medical staff

GA-ANN Short-Term Electricity Load Forecasting

This paper presents a methodology for short-term load forecasting based on genetic algorithm feature selection and artificial neural network modeling. A feed forward artificial neural network is used to model the 24-h ahead load based on past consumption, weather and stock index data. A genetic algorithm is used in order to find the best subset of variables for modeling. Three data sets of different geographical locations, encompassing areas of different dimensions with distinct load profiles are used in order to evaluate the methodology. The developed approach was found to generate models achieving a minimum mean average percentage error under 2 %. The feature selection algorithm was able to significantly reduce the number of used features and increase the accuracy of the models

Market risk management in a post-Basel II regulatory environment

We propose a novel method of Mean-Capital Requirement portfolio optimization. The optimization is performed using a parallel framework for optimization based on the Nondominated Sorting Genetic Algorithm II. Capital requirements for market risk include an additional stress component introduced by the recent Basel 2.5 regulation. Our optimization with the Basel 2.5 formula in the objective function produces superior results to those of the old (Basel II) formula in stress scenarios in which the correlations of asset returns change considerably. These improvements are achieved at the expense of reduced cardinality of Pareto-optimal portfolios. This reduced cardinality (and thus portfolio diversification) in periods of relatively low market volatility may have unintended consequences for banks’ risk exposure

Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives

[EN] Digital transformation provide supply chains (SCs) with extensive accurate data that should be combined with analytical techniques to improve their management. Among these techniques Artificial Intelligence (AI) has proved their suitability, memory and ability to manage uncertain and constantly changing information. Despite the fact that a number of AI literature reviews exist, no comprehensive review of reviews for the SC operations planning has yet been conducted. This paper aims to provide a comprehensive review of AI literature reviews in a structured manner to gain insights into their evolution in incorporating new ICTs and collaboration. Results show that hybrization man-machine and collaboration and ethical aspects are understudied.This research has been funded by the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE). 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