247 resultados para Industrial automation, Programmable logic controllers.


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The importance of the isoform CYP2E1 of the human cytochrome P-450 superfamily of enzymes for occupational and environmental medicine is derived from its unique substrate spectrum that includes a number of highly important high-production chemicals, such as aliphatic and aromatic hydrocarbons, solvents and industrial monomers (i.a. alkanes, alkenes, aromatic and halogenated hydrocarbons). Many polymorphic genes, such as CYP2E1, show considerable differences in allelic distribution between different human populations. The polymorphic nature of the human CYP2E1 gene is significant for inter-individual differences in toxicity of its substrates. Since the substrate spectrum of CYP2E1 includes many compounds of basic relevance to industrial toxicology, a rationale for metabolic interactions of different CYP2E1 substrates is provided. In-depth research into the inter-individual phenotypic differences of human CYP2E1 enzyme activities was enabled by the recognition that the 6-hydroxylation of the drug chlorzoxazone is mediated by CYP2E1. Studies on CYP2E1 phenotyping have pointed to inter-individual variations in enzyme activities. There are consistent ethnic differences in CYP2E1 enzyme expression, mostly demonstrated between European and Japanese populations, which point to a major impact of genetic factors. The most frequently studied genetic polymorphisms are the restriction fragment length polymorphisms PstI/RsaI (mutant allele: CYP2E1*5B) located in the 5′-flanking region of the gene, as well as the DraI polymorphism (mutant allele: CYP2E1*6) located in intron 6. These polymorphisms are partly related, as they form the common allele designated CYP2E1*5A. Striking inter-ethnic differences between Europeans and Asians appear with respect to the frequencies of the CYP2E1*5A allele (only approximately 5% of Europeans are heterozygous, but 37% of Asians are, whilst 6% of Asians are homozygous). Available studies indicate a wide variation in human CYP2E1 expression, which are very likely based on complex gene-environment interactions. Major inter-ethnic differences are apparent on the genotyping and the phenotyping levels. Selected cases are presented where inter-ethnic variations of CYP2E1 may provide likely explanations for unexplained findings concerning industrial chemicals that are CYP2E1 substrates. Possible consequences of differential inter-individual and inter-ethnic susceptibilities are related to individual expressions of clinical symptoms of chemical toxicity, to results of biological monitoring of exposed workers, and to the interpretation of results of epidemiological or molecular-epidemiological studies.

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Since the 1980s the calls for further criminalisation of organisational conduct causing harm to workers, the public and the environment have intensified in Australia, Canada and England and Wales.' One focal point of this movement has been the criminal law's response to organisations (and their personnel) failing to comply with occupational health and safety ('OHS') standards, particularly when physical harm (death and serious injury) has resulted from those breaches. Some governments have responded with proposals to enable manslaughter prosecutions to be initiated 'more effectively' against organisations causing the deaths of workers or, in some cases, members of the public (Archibald et al, 2004; Haines and Hall, 2004; Hall et al, 2004; Tombs and Whyte, 2003). In Australia governments have also increased monetary penalties for regulatory OHS offences, a few have introduced other contemporary organisational sanctions, and some have initiated OHS prosecutions more vigorously and with larger fines.

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The institutional and regulatory interlinkages between industrial relations (IR) and occupational health and safety (OHS) are seldom explored in the IR literature. This article begins to address this gap by examining regulatory initiatives in Australia during a period of neoliberal government. It examines the laws enacted by the federal government during this period and events and cases arising from these laws that go some way to illustrating their effects. Evidence is also drawn from detailed research on a number of state OHS inspectorates between 2004 and 2006. It is argued that de-collectivist changes to IR laws exacerbated problems posed by the growth of flexible work arrangements and a drop in union density, weakening participatory provisions in OHS laws and promoting work arrangements that undermined OHS standards. The study provides evidence of the implications of a divergence in the trajectory of IR and OHS laws and the importance of better integrating worker protection laws.

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This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

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Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

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Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.

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This paper details the initial design and planning of a Field Programmable Gate Array (FPGA) implemented control system that will enable a path planner to interact with a MAVLink based flight computer. The design is aimed at small Unmanned Aircraft Vehicles (UAV) under autonomous operation which are typically subject to constraints arising from limited on-board processing capabilities, power and size. An FPGA implementation for the de- sign is chosen for its potential to address such limitations through low power and high speed in-hardware computation. The MAVLink protocol offers a low bandwidth interface for the FPGA implemented path planner to communicate with an on-board flight computer. A control system plan is presented that is capable of accepting a string of GPS waypoints generated on-board from a previously developed in- hardware Genetic Algorithm (GA) path planner and feeding them to the open source PX4 autopilot, while simultaneously respond- ing with flight status information.

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The construction industry is a crucial component of the Hong Kong economy, and the safety and efficiency of workers are two of its main concerns. The current approach to training workers relies primarily on instilling practice and experience in conventional teacher-apprentice settings on and off site. Both have their limitations however, on-site training is very inefficient and interferes with progress on site, while off-site training provides little opportunity to develop the practical skills and awareness needed through hands-on experience. A more effective way is to train workers in safety awareness and efficient working by current novel information technologies. This paper describes a new and innovative prototype system – the Proactive Construction Management System (PCMS) – to train precast installation workers to be highly productive while being fully aware of the hazards involved. PCMS uses Chirp-Spread-Spectrum-based (CSS) real-time location technology and Unity3D-based data visualisation technology to track construction resources (people, equipment, materials, etc.) and provide real-time feedback and post-event visualisation analysis in a training environment. A trial of a precast facade installation on a real site demonstrates the benefits gained by PCMS in comparison with equivalent training using conventional methods. It is concluded that, although the study is based on specific industrial conditions found in Hong Kong construction projects, PCMS may well attract wider interest and use in future.

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Hot metal carriers (HMCs) are large forklift-type vehicles used to move molten metal in aluminum smelters. This paper reports on field experiments that demonstrate that HMCs can operate autonomously and in particular can use vision as a primary sensor to locate the load of aluminum. We present our complete system but focus on the vision system elements and also detail experiments demonstrating reliable operation of the materials handling task. Two key experiments are described, lasting 2 and 5 h, in which the HMC traveled 15 km in total and handled the load 80 times.

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We describe our experiences with automating a large fork-lift type vehicle that operates outdoors and in all weather. In particular, we focus on the use of independent and robust localisation systems for reliable navigation around the worksite. Two localisation systems are briefly described. The first is based on laser range finders and retro-reflective beacons, and the second uses a two camera vision system to estimate the vehicle’s pose relative to a known model of the surrounding buildings. We show the results from an experiment where the 20 tonne experimental vehicle, an autonomous Hot Metal Carrier, was conducting autonomous operations and one of the localisation systems was deliberately made to fail.

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Player experiences and expectations are connected. The presumptions players have about how they control their gameplay interactions may shape the way they play and perceive videogames. A successfully engaging player experience might rest on the way controllers meet players' expectations. We studied player interaction with novel controllers on the Sony PlayStation Wonderbook, an augmented reality (AR) gaming system. Our goal was to understand player expectations regarding game controllers in AR game design. Based on this preliminary study, we propose several interaction guidelines for hybrid input from both augmented reality and physical game controllers

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In this paper, dynamic modeling and simulation of the hydropurification reactor in a purified terephthalic acid production plant has been investigated by gray-box technique to evaluate the catalytic activity of palladium supported on carbon (0.5 wt.% Pd/C) catalyst. The reaction kinetics and catalyst deactivation trend have been modeled by employing artificial neural network (ANN). The network output has been incorporated with the reactor first principle model (FPM). The simulation results reveal that the gray-box model (FPM and ANN) is about 32 percent more accurate than FPM. The model demonstrates that the catalyst is deactivated after eleven months. Moreover, the catalyst lifetime decreases about two and half months in case of 7 percent increase of reactor feed flowrate. It is predicted that 10 percent enhancement of hydrogen flowrate promotes catalyst lifetime at the amount of one month. Additionally, the enhancement of 4-carboxybenzaldehyde concentration in the reactor feed improves CO and benzoic acid synthesis. CO is a poison to the catalyst, and benzoic acid might affect the product quality. The model can be applied into actual working plants to analyze the Pd/C catalyst efficient functioning and the catalytic reactor performance.