Search results for "Turing"
showing 10 items of 2644 documents
A preliminary comparison between finite element and meshless simulations of extrusion
2009
In this paper the extrusion process of a cross-shaped profile was investigated. In particular, the study was focused on the distortion of extruding profiles when the workpiece and die axis are not aligned. The process was simulated using the finite element method (FEM) and the natural element method (NEM), both implemented in an updated-Lagrangian formulation, in order to avoid the burden associated with the description of free surfaces in ALE or Eulerian formulations. Furthermore, an experimental equipment was developed in order to obtain reliable data in terms of deformed entity, required process load and calculated pressure. At the end, a comparison between the numerical predictions and …
Critical success factors for successful globalised e-learning
2009
As we move from an information-based to a knowledge-based society, the need for reengineering, retraining and restructuring is emerging. Online programme development/enhancement requires experience and planning. Since e-learning entry requires little investments, it can be tempting to start programmes without appropriate infrastructure or planning, resulting in huge losses and in many cases closure. The new entrants can learn from the early adopters of online learning and from their experiences, both good and bad without reinventing the wheel. This paper discusses factors that must be considered and planned before venturing into e-learning. These factors are derived from discussions with fa…
Tool-life modelling as a stochastic process
1998
Abstract In a previous paper [G. Galante, A. Lombardo, A. Passannanti, Proceedings of XXXVII Scientific Meeting of the Italian Statistical Society, 1994, p. 553] the Authors proposed to model cutting tool wear behaviour as a stochastic process with independent Gaussian increments plus drift. Such a model implies that the tool-life, i.e. the time to reach a fixed value of flank wear, has an inverse Gaussian probability distribution. The model has several practical and theoretical advantages. In fact, it is based on an easily and cheaply experimentally verifiable wear behaviour hypothesis, it is more flexible because it is not limited to a particular wear level and, finally, the data are bett…
Comparison of problem solving tools in lean organizations
2017
As global market competition is getting fiercer, and companies are looking at ways to stay on top, more and more organizations are looking at Lean Manufacturing and lean tools to support them in achieving their goals. Especially within the automotive industry, lean practices are very well received. The speed at which the automotive industry is evolving, especially but not only, in countries like Romania, leads to the need to carefully analyze lean manufacturing concepts, examine them against local production conditions, and to develop and standardize them. One of the most important things to take into consideration here is the application of an adequate problem solving technique to avoid wa…
An exact algorithm for preventive maintenance planning of series-parallel systems
2009
Reliability is a meaningful parameter in assessing the performance of systems such as chemical processing facilities, power plant, aircrafts, ships, etc. In the literature, reliability optimization is widely considered during the system design phase and it is carried out by an opportune selection of both system components and redundancy. On the other hand, the problem of maintaining a required level of reliability by an opportune maintenance policy has been poorly examined. The paper tackles this problem for a system whose major components can be maintained only during a planned system downtime. An exact algorithm is proposed in order to single out the set of components that must be maintai…
Relative evaluation of regression tools for urban area electrical energy demand forecasting
2019
Abstract Load forecasting is the most fundamental application in Smart-Grid, which provides essential input to Demand Response, Topology Optimization and Abnormally Detection, facilitating the integration of intermittent clean energy sources. In this work, several regression tools are analyzed using larger datasets for urban area electrical load forecasting. The regression tools which are used are Random Forest Regressor, k-Nearest Neighbour Regressor and Linear Regressor. This work explores the use of regression tool for regional electric load forecasting by correlating lower distinctive categorical level (season, day of the week) and weather parameters. The regression analysis has been do…
Behavioral reasoning theory (BRT) perspectives on E-waste recycling and management
2021
Abstract Each year, millions of tons of electronic waste (or e-waste) are generated worldwide, thus, fueling concerns among scholars, practitioners, policymakers, and governments about e-waste recycling and management. The past few years have witnessed a growing interest among scholars to examine the behavioral issues concerning e-waste recycling. However, most of the existing studies have focused on adopting e-waste recycling and related innovations. It is already known that ‘reasons for’ and ‘reasons against’ the adoption of any innovation are quantitatively different. The current study bridges this gap by utilizing a novel consumer behavior framework called behavioral reasoning theory (B…
Materialistic values impact on pro-environmental behavior: The case of transition country as Lithuania
2020
Abstract Materialism is becoming a global phenomenon and is increasing exponentially. Lithuania, which has survived a long period of occupation, experienced privatization and goods’ famine is attributed to the transition countries. In terms of materialistic values, Lithuania is not an exception, as material wealth and image are also very important. Thus, the main question of this paper was whether materialistic values could be reconciled with the pro-environmental behavior, which can be considered as one of the main aspects seeking sustainability. According to the Lithuanian representative survey and by applying the approach of structural equation modeling, the results showed that materiali…
Machine learning study of the molecular drivers of natural product prices
2021
The price of chemicals is a very complex variable. It can be impacted by production costs but also by market and managerial factors, which may have complex relationships with molecular characteristics and the state of technology and society. In this work, we explore the extent to which molecular characteristics can help explain natural product prices with the aid of machine learning tools. We interpret models trained on molecular descriptors and molecular fingerprints. These models can explain a notable proportion of the variation in prices, suggesting that production and separation costs are a major contributor to current natural product prices. Some molecular properties stand out as key p…
ANN modelling of CO2 refrigerant cooling system COP in a smart warehouse
2020
Author's accepted manuscript Industrial cooling systems consume large quantities of energy with highly variable power demand. To reduce environmental impact and overall energy consumption, and to stabilize the power requirements, it is recommended to recover surplus heat, store energy, and integrate renewable energy production. To control these operations continuously in a complex energy system, an intelligent energy management system can be employed using operational data and machine learning. In this work, we have developed an artificial neural network based technique for modelling operational CO2 refrigerant based industrial cooling systems for embedding in an overall energy management s…