624 resultados para Analytical hierarchical process


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The Beauty Leaf tree (Calophyllum inophyllum) is a potential source of non-edible vegetable oil for producing future generation biodiesel because of its ability to grow in a wide range of climate conditions, easy cultivation, high fruit production rate, and the high oil content in the seed. This plant naturally occurs in the coastal areas of Queensland and the Northern Territory in Australia, and is also widespread in south-east Asia, India and Sri Lanka. Although Beauty Leaf is traditionally used as a source of timber and orientation plant, its potential as a source of second generation biodiesel is yet to be exploited. In this study, the extraction process from the Beauty Leaf oil seed has been optimised in terms of seed preparation, moisture content and oil extraction methods. The two methods that have been considered to extract oil from the seed kernel are mechanical oil extraction using an electric powered screw press, and chemical oil extraction using n-hexane as an oil solvent. The study found that seed preparation has a significant impact on oil yields, especially in the screw press extraction method. Kernels prepared to 15% moisture content provided the highest oil yields for both extraction methods. Mechanical extraction using the screw press can produce oil from correctly prepared product at a low cost, however overall this method is ineffective with relatively low oil yields. Chemical extraction was found to be a very effective method for oil extraction for its consistence performance and high oil yield, but cost of production was relatively higher due to the high cost of solvent. However, a solvent recycle system can be implemented to reduce the production cost of Beauty Leaf biodiesel. The findings of this study are expected to serve as the basis from which industrial scale biodiesel production from Beauty Leaf can be made.

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An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.

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The need for a house rental model in Townsville, Australia is addressed. Models developed for predicting house rental levels are described. An analytical model is built upon a priori selected variables and parameters of rental levels. Regression models are generated to provide a comparison to the analytical model. Issues in model development and performance evaluation are discussed. A comparison of the models indicates that the analytical model performs better than the regression models.

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Semiconducting metal oxide based gas sensors usually operate in the temperature range 200–500 °C. In this paper, we present a new WO3 thin film based gas sensor for H2 and C2H5OH, operating at 150 °C. Nanostructured WO3 thin films were synthesized by thermal evaporation method. The properties of the as-deposited films were modified by annealing in air at 300 °C and 400 °C. Various analytical techniques such as AFM, TEM, XPS, XRD and Raman spectroscopy have been employed to characterize their properties. A clear indication from TEM and XRD analysis is that the as-deposited WO3 films are highly amorphous and no improvement is observed in the crystallinity of the films after annealing at 300 °C. Annealing at 400 °C significantly improved the crystalline properties of the films with the formation of about 5 nm grains. The films annealed at 300 °C show no response to C2H5OH (ethanol) and a little response to H2, with maximum response obtained at 280 °C. The films annealed at 400 °C show a very good response to H2 and a moderate response to C2H5OH (ethanol) at 150 °C. XPS analysis revealed that annealing of the WO3 thin films at 400 °C produces a significant change in stoichiometry, increasing the number of oxygen vacancies in the film, which is highly beneficial for gas sensing. Our results demonstrate that gas sensors with significant performance at low operating temperatures can be obtained by annealing the WO3 films at 400 °C and optimizing the crystallinity and nanostructure of the as-deposited films.

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Knowledge Management (KM) is a process that focuses on knowledge-related activities to facilitate knowledge creation, capture, transformation and use, with the ultimate aim of leveraging organisations’ intellectual capital to achieve organisational objectives. The KM process receives input from its context (e.g. internal business environment), and produces output (i.e. knowledge). It is argued that the validity of such knowledge should be justified by business performance. The study, this paper reports on, provides enhanced empirical understanding of such an input-process-output relationship through investigating the interactions among different KM activities in the context of how construction organisations in Hong Kong manage knowledge. To this end, a theoretical framework along with a number of hypotheses are proposed and empirically tested through correlation, regression and path analyses. A questionnaire survey was administered to a sample of construction contractors operating in Hong Kong to facilitate testing the proposed relationships. More than 140 respondents from 99 organisations responded to the survey. The study findings demonstrate that both organisational and technical environments have the potential to predict the intensity of KM activities. Furthermore, different categories of KM activities interact with each other, and collectively they could be used to predict business performance.

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Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

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Knowledge Management (KM) is a process that focuses on knowledge-related activities to facilitate knowledge creation, capture, transformation and use, with the ultimate aim of leveraging organisations’ intellectual capital to achieve organisational objectives. Organisational culture and climate have been identified as major catalysts to knowledge creation and sharing, and hence are considered important dimensions of KM research. The fragmented and hierarchical nature of the construction industry illustrates its difficulties to operate in a co-ordinated and homogeneous way when dealing with knowledge-related issues such as research and development, training and innovation. The culture and climate of organisations operating within the construction industry are profoundly shaped by the long-established characteristics of the industry, whilst also being influenced by the changes within the sector. Meanwhile, the special project-based structure of construction organisations constitutes additional challenges in facing knowledge production. The study this paper reports on addresses the impact of organisational culture and climate on the intensity of KM activities within construction organisations, with specific focus on the managerial activities that help to manage these challenges and to facilitate KM. A series of semi-structured interviews were undertaken to investigate the KM activities of the contractors operating in Hong Kong. The analysis on the qualitative data revealed that leadership on KM, innovation management, communication management and IT development were key factors that impact positively on the KM activities within the organisations under investigation.

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Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

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Drink driving is a major public health issue and this report examines the experiences of convicted offenders who participated in an established drink driving rehabilitation program Under the Limit (UTL). Course completers were surveyed at least three months after they had finished the 11-week UTL course. The aim of this study was to examine whether the UTL program reduced the level of alcohol consumption either directly as a result of participation in the UTL drink driving program or through increased use of community alcohol program by participants. The research involved a self-report outcome evaluation to determine whether the self-reported levels of alcohol use after the course had changed from the initial alcohol use reported by offenders. The findings are based on the responses of 30 drink-driving offenders who had completed the UTL program (response rate: 20%). While a process evaluation was proposed in the initial application, the low response rate meant that this follow up research was not feasible. The response rate was low for two reasons, it was difficult to: recruit participants who consented to follow up, and subsequently locate and survey those who had consented to involvement.

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Self reported driving behaviour in the occupational driving context has typically been measured through scales adapted from the general driving population (i.e. the Manchester Driver Behaviour Questionnaire (DBQ)). However, research suggests that occupational driving is influenced by unique factors operating within the workplace environment, and thus, a behavioural scale should reflect those behaviours prevalent and unique within the driving context. To overcome this limitation, developed the Occupational Driver Behaviour Questionnaire (ODBQ) which utilises a relevant theoretical model to assess the impact of the broader workplace context on driving behaviour. Although the theoretical argument has been established, research is yet to examine whether the ODBQ or the DBQ is a more sensitive measure of the workplace context. As such, this paper identifies selected organisational factors (i.e. safety climate and role overload) as predictors of the DBQ and the ODBQ and compares the relative predictive value in both models. In undertaking this task, 248 occupational drivers were recruited from a community-oriented nursing population. As predicted, hierarchical regression analyses revealed that the organisational factors accounted for a significantly greater proportion of variance in the ODBQ than the DBQ. These findings offer a number of practical and theoretical applications for occupational driving practice and future research.

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Purpose – Business process management (BPM) requires a holistic perspective that includes managing the culture of an organization to achieve objectives of efficient and effective business processes. Still, the specifics of a BPM-supportive organizational culture have not been examined so far. Thus, the purpose of this paper is to identify the characteristics of a cultural setting supportive of BPM objectives. Design/methodology/approach – The paper examines the constituent values of a BPM-supportive cultural setting through a global Delphi study with BPM experts from academia and practice and explore these values in a cultural value framework. Findings – The paper empirically identifies and defines four key cultural values supporting BPM, viz., customer orientation, excellence, responsibility, and teamwork. The paper discusses the relationships between these values and identifies a particular challenge in managing these seemingly competing values. Research limitations/implications – The identification and definition of these values represents a first step towards the operationalization (and empirical analysis) of what has been identified as the concept of BPM culture, i.e. a culture supportive of achieving BPM objectives. Practical implications – Identifying these cultural values provides the basis for developing an instrument that can measure how far an existing cultural context is supportive of BPM. This, in turn, is fundamental for identifying measures towards achieving a BPM culture as a necessary, yet not sufficient means to obtain BPM success. Originality/value – The paper examines which cultural values create an environment receptive for BPM and, thus, specifies the important theoretical construct BPM culture. In addition, the paper raises awareness for realizing these values in a BPM context.

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Norms regulate the behaviour of their subjects and define what is legal and what is illegal. Norms typically describe the conditions under which they are applicable and the normative effects as a results of their applications. On the other hand, process models specify how a business operation or service is to be carried out to achieve a desired outcome. Norms can have significant impact on how business operations are conducted and they can apply to the whole or part of a business process. For example, they may impose conditions on the different aspects of a process (e.g., perform tasks in a specific sequence (control-flow), at a specific time or within a certain time frame (temporal aspect), by specific people (resources)). We propose a framework that provides the formal semantics of the normative requirements for determining whether a business process complies with a normative document (where a normative document can be understood in a very broad sense, ranging from internal policies to best practice policies, to statutory acts). We also present a classification of normal requirements based on the notion of different types of obligations and the effects of violating these obligations.

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Enterprise Systems (ES) can be understood as the de facto standard for holistic operational and managerial support within an organization. Most commonly ES are offered as commercial off-the-shelf packages, requiring customization in the user organization. This process is a complex and resource-intensive task, which often prevents small and midsize enterprises (SME) from undertaking configuration projects. Especially in the SME market independent software vendors provide pre-configured ES for a small customer base. The problem of ES configuration is shifted from the customer to the vendor, but remains critical. We argue that the yet unexplored link between process configuration and business document configuration must be closer examined as both types of configuration are closely tied to one another.

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The common presupposition of Enterprise Systems (ES) is that they lead to significant efficiency gains. However, this is only the case for well-implemented ES that meet organisational requirements. The list of major ES implementation failures is as long as the list of success stories. We argue here that this arises from a more fundamental problem, the functionalist approach to ES development and provision. As long as vendors will continue to develop generic, difficult-to-adapt ES packages, this problem will prevail because organisations have a non-generic character. A solution to this problem can only consist in rethinking the way ES packages are provided. We propose a strict abstraction layer of ES functionalities and their representation as conceptual models. ES vendors must provide sufficient means for configuring these conceptual models. We discuss in this paper what generic situations can occur during process model configuration in order to understand process model configuration in depth.

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Process-Aware Information Systems (PAIS) support organizations in managing and automating their processes. A full automation of processes is in particular industries, such as service-oriented markets, not practicable. The integration of humans in PAIS is necessary to manage and perform processes that require human capabilities, judg- ments and decisions. A challenge of interdisciplinary PAIS research is to provide concepts and solutions that support human integration in PAIS and human orientation of PAIS in a way that provably increase the PAIS users' satisfaction and motivation with working with the Human-Centric Process Aware Information System (HC-PAIS) and consequently in uence users' performance of tasks. This work is an initial step of research that aims at providing a definition of Human-Centric Process Aware Information Systems (HC-PAIS) and future research challenges of HC-PAIS. Results of focus group research are presented.