931 resultados para Peace process
Resumo:
The value of information technology (IT) is often realized when continuously being used after users’ initial acceptance. However, previous research on continuing IT usage is limited for dismissing the importance of mental goals in directing users’ behaviors and for inadequately accommodating the group context of users. This in-progress paper offers a synthesis of several literature to conceptualize continuing IT usage as multilevel constructs and to view IT usage behavior as directed and energized by a set of mental goals. Drawing from the self-regulation theory in the social psychology, this paper proposes a process model, positioning continuing IT usage as multiple-goal pursuit. An agent-based modeling approach is suggested to further explore causal and analytical implications of the proposed process model.
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This project explores issues confronted when authoring a previously authored story, one received from history. Using the defection of Soviet spies, Vladimir and Evdokia Petrov as its focal point, it details how a screenwriter addresses issues arising in the adaptation of both fictional and biographical representations suitable for contemporary cinema. Textual fidelity and concepts of interpretation, aesthetics and audience, negotiating factual and fictional imperatives, authorial visibility and invisibility, moral and ethical conundrums are negotiated and a set of guiding principles emerge from this practice-led investigation.
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The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.
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Large arrays and networks of carbon nanotubes, both single- and multi-walled, feature many superior properties which offer excellent opportunities for various modern applications ranging from nanoelectronics, supercapacitors, photovoltaic cells, energy storage and conversation devices, to gas- and biosensors, nanomechanical and biomedical devices etc. At present, arrays and networks of carbon nanotubes are mainly fabricated from the pre-fabricated separated nanotubes by solution-based techniques. However, the intrinsic structure of the nanotubes (mainly, the level of the structural defects) which are required for the best performance in the nanotube-based applications, are often damaged during the array/network fabrication by surfactants, chemicals, and sonication involved in the process. As a result, the performance of the functional devices may be significantly degraded. In contrast, directly synthesized nanotube arrays/networks can preclude the adverse effects of the solution-based process and largely preserve the excellent properties of the pristine nanotubes. Owing to its advantages of scale-up production and precise positioning of the grown nanotubes, catalytic and catalyst-free chemical vapor depositions (CVD), as well as plasma-enhanced chemical vapor deposition (PECVD) are the methods most promising for the direct synthesis of the nanotubes.
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The Association of South East Asian Nations (ASEAN) Secretariat and its member states have repeatedly professed their commitment to the protection and advancement of women’s economic and human rights. Such commitments have included the Declaration on the Advancement of Women in ASEAN in 1988, the ASEAN Declaration on the Elimination of Violence Against Women in 2004, and the ASEAN Declaration of Human Rights in 2012, as well as the establishment of the ASEAN Committee on Women in 2002 and the ASEAN Commission on the Promotion and Protection of Women and Children in 2009. However, none of these regional commitments or institutions expressly take up the core concern of the Women, Peace and Security (WPS) agenda set out in United Nations Security Council (UNSC) Resolution 1325 in 2000. ASEAN has no 1325 regional action plan and amongst the ASEAN membership, the Philippines is the only state that has adopted a 1325 National Action Plan (NAP). We explore the possible reasons for lack of ASEAN institutional engagement with 1325, outline the case for regional engagement, and suggest specific roles for ASEAN Secretariat, donor governments and individual member states to commit to UNSCR 1325 as a regional priority.
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This book constitutes the proceedings of the Second Asia Pacific Conference on Business Process Management held in Brisbane, QLD, Australia, in July 2014. In all, 33 contributions from 12 countries were submitted. After each submission was reviewed by at least three Program Committee members, nine full papers were accepted for publication in this volume. These nine papers cover various topics that can be categorized under four main research focuses in BPM: process mining, process modeling and repositories, process model comparison, and process analysis.
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Variations that exist in the treatment of patients (with similar symptoms) across different hospitals do substantially impact the quality and costs of healthcare. Consequently, it is important to understand the similarities and differences between the practices across different hospitals. This paper presents a case study on the application of process mining techniques to measure and quantify the differences in the treatment of patients presenting with chest pain symptoms across four South Australian hospitals. Our case study focuses on cross-organisational benchmarking of processes and their performance. Techniques such as clustering, process discovery, performance analysis, and scientific workflows were applied to facilitate such comparative analyses. Lessons learned in overcoming unique challenges in cross-organisational process mining, such as ensuring population comparability, data granularity comparability, and experimental repeatability are also presented.
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The purpose of this study is to discover the significant factors causing the bubble defect on the outsoles manufactured by the Case Company. The bubble defect occurs approximately 1.5 per cent of the time or in 36 pairs per day. To understand this problem, experimental studies are undertaken to identify various factors such as injector temperature, mould temperature; that affects the production of waste. The work presented in this paper comprises a review of the relevant literature on the Six Sigma DMAIC improvement process, quality control tools, and the design of the experiments. After the experimentation following the Six Sigma process, the results showed that the defect occurred in approximately 0.5 per cent of the products or in 12 pairs per day; this decreased the production cost from 6,120 AUD per month to 2,040 AUD per month. This research aimed to reduce the amount of waste in men’s flat outsoles. Hence, the outcome of research presented in this paper should be used as a guide for applying the appropriate process for each type of outsole.
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The increased interest in the area of process improvement persuaded Rabobank Group ICT in examining its own Change-process in order to improve its competitiveness. The group is looking for answers about the effectiveness of changes applied as part of this process, with particular interest toward the presence of predictive patterns and their parameters. We conducted an analysis of the log using well established process mining techniques (i.e. Fuzzy Miner). The results of the analysis conducted on the log of the process show that a visible impact is missing.
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Artemisinin (ART) based combination therapy (ACT) is used as the first line treatment of uncomplicated falciparum malaria in over 100 countries and is the cornerstone of malaria control and elimination programs in these areas. However, despite the high potency and rapid parasite killing action of ART derivatives there is a high rate of recrudescence associated with ART monotherapy and recrudescence is not uncommon even when ACT is used. Compounding this problem are reports that some parasites in Cambodia, a known foci of drug resistance, have decreased in vivo sensitivity to ART. This raises serious concerns for the development of ART resistance in the field even though no major phenotypic and genotypic changes have yet been identified in these parasites. In this article we review available data on the characteristics of ART, its effects on Plasmodium falciparum parasites and present a hypothesis to explain the high rate of recrudescence associated with this potent class of drugs and the current enigma surrounding ART resistance.
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This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.
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Notwithstanding the interest over many years by scholars in modeling the internationalization of the firm, the initial transition for the firm from domestic to international operations remains under-researched. We identify the behavioral factors that are important at the pre-internationalization state and discuss how they may interrelate to influence a decision to commit to internationalization through export commencement. We study export commitment by proposing and constructing an index that incorporates the factors that influence a firm’s propensity to commit to export activities. Utilizing the items from this index in a logistic regression analysis, we distinguish between the pre-internationalization characteristics of exporting and non-exporting firms to better understand the key influences in export commitment. Implications are discussed.
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In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.
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Knowledge Integration (KI) is one of the major aspects driving innovation within an organisation. In this paper, we attempt to develop a better understanding of responses to the challenges of knowledge integration within the innovation process in technology-based firms. Using four technology-based Australian firms, we investigated how knowledge integration may be managed within the context of innovation in technology firms. Previous research highlights the role of four KI tasks that affect the innovation capability within technology-oriented firms, namely team building capability, capturing tacit knowledge, role of Knowledge Management (KM) systems and technological systemic integration. Our findings indicate that in addition to these four tasks, a strategic approach to integrating knowledge for innovation, as well as leadership and management, are essential to achieving effective KI across multiple levels of engagement. Our findings also offer practical insights into how knowledge can be integrated within innovation process, with specific implications for managers.