Decisional systems are crucial for enterprise improvement. They allow the consolidation of heterogeneous data from distributed stores into strategic indicators. An essential component this is Extract, Transform, and Load (ETL) process. In research literature there has been very few work defining conceptual models ETL processes. At same time, currently many tools that manage such However, each tool uses its own model, which not necessarily able to communicate with other tools. paper, we...

ETL processes are the backbone component of a data warehouse, since they supply warehouse with necessary integrated and reconciled from heterogeneous distributed sources. However, process development, particularly its design phase, is still perceived as time-consuming task. This mainly due to fact that typically designed by considering specific technology very beginning development process. Thus, it difficult share reuse methodologies best practices among projects implemented different...

Business Intelligence (BI) applications require the design, implementation, and maintenance of processes that extract, transform, load suitable data for analysis. The development these (known as ETL) is an inherently complex problem typically costly time consuming. In a previous work, authors have proposed vendor-independent language reducing design complexity due to disparate ETL languages tailored specific tools with steep learning curves. Nevertheless, designer still faces two major...

This study proposes a novel approach to address the multi-objective challenge of traffic control on congested freeways using Deep Reinforcement Learning (DRL). The involves developing Learning-based Variable Speed Limit (VSL) agent specifically designed optimize efficiency while enhancing road safety. employs reward function, striking delicate balance between safety and mobility by optimizing speed limits minimize collision risks maximize flow simultaneously. To illustrate architecture...

The paramount importance of project portfolios for business drives managers to search highly efficient support tools overcome complex challenges their management. A major tradeoff is acquire able produce a convenient portfolio prioritization process, on which investments are decided. However, by using existing Project Portfolio Management Systems (PPMS), many concurrent projects in usually prioritized and planned the upstream life-cycle phases according financial criteria, overlooking...

Road traffic crashes are a public health issue due to their terrible impact on individuals, communities, and countries. Studies affirmed that vehicle speed is major contributor crash likelihood severity. At the same time, they identified Automated Speed Enforcement (ASE) systems, namely cameras, as highly effective measure reduce excessive inappropriate speed, thus improving road safety. However, identifying optimum sites for fixed camera placement stays an open in literature, although it...

The growth in mobility due to the growing global economy has increased transportation's contribution energy waste and its various ecological impacts. Vehicle Routing Problem (VRP) represents study of distribution strategies adopted by companies; with a major focus on reducing economic costs customer satisfaction. Green logistics recently received more attention supply chain management field, address environmental considerations companies' operations reduce impact. In this paper, we present...

Federated learning has emerged as a robust framework for distributed machine learning, enabling model training across decentralized data sources while preserving privacy. Despite its advantages, persistent challenge remains: the high communication overhead during update process results in energy consumption on client devices. This paper introduces new approach that combines (1) weights sparsification technique with (2) single layer of shared neural network model. Our proposal serves dual...

Data classification problems have been intensively studied by several groups of researchers including computer scientists, statisticians, engineers, biologists. Within the context widespread use databases and explosive growth in their sizes, "Big Data", new challenges are introduced order to permit organizations take benefits efficiently utilize data. The main objective this paper is review published works which propose mathematical programming approaches solve data with Support Vector Machine (SVM).

All production lines are continuously confronted with the phenomenon of waste, especially in IT operations. A waste is assessed terms required resources and cost employed to solve problem behind it. Eliminating daily operations essential improve service management. This article aims provide an estimation level potential where generation trends provoked by activities management processes. We going focus particularly on possibility applying a Lean improvement process services processes when...