245 resultados para resource coordination


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Evidence suggests that both nascent and young firms (henceforth: “new firms”)—despite typically being small and resource-constrained—are sometimes able to innovate effectively. Such firms are seldom able to invest in lengthy and expensive development processes, which suggests that they may frequently rely instead on other pathways to generate innovativeness within the firm. In this paper, we develop and test arguments that “bricolage,” defined as making do by applying combinations of the resources at hand to new problems and opportunities, provides an important pathway to achieve innovation for new resource-constrained firms. Through bricolage, resource-constrained firms engage in the processes of “recombination” that are core to creating innovative outcomes. Based on a large longitudinal dataset, our results suggest that variations in the degree to which firms engage in bricolage behaviors can provide a broadly applicable explanation of innovativeness under resource constraints by new firms. We find no general support for our competing hypothesis that the positive effects may level off or even turn negative at high levels of bricolage..

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Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

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Designers need to consider both the functional and production process requirements at the early stage of product development. A variety of the research works found in the literature has been proposed to assist designers in selecting the most viable manufacturing process chain. However, they do not provide any assistance for designers to evaluate the processes according to the particular circumstances of their company. This paper describes a framework of an Activity and Resource Advisory System (ARAS) that generates advice about the required activities and the possible resources for various manufacturing process chains. The system provides more insight, more flexibility, and a more holistic and suitable approach for designers to evaluate and then select the most viable manufacturing process chain at the early stage of product development.

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Some of Queensland's regions are experiencing rapid changes related to the recent and growing capacity to more effectively exploit significant energy sources. These changes have triggered land-use conflicts between the mining sector and other economic sectors, mainly agriculture. These conflicts fuel existing uncertainty surrounding the current and future economic, social and environmental impacts of extractive industries. This paper explores the concept of uncertainty as it applies to planning for resource-based regions through a scoping analysis of regional stakeholders' perceptions of land-use uncertainty. It then investigates solutions to alleviate such an issue.

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Advancing the development of good practice around the teaching team has been the focus of a recently completed, nationally funded Australian grant entitled Coordinators Leading Advancement of Sessional Staff (CLASS). The project focused on developing leadership capacity of subject coordinators to provide supportive contexts for sessional staff to enhance their knowledge of teaching practice and contribute to subject improvement through a team approach. An action learning approach and notions of distributed leadership underpinned the activities of the teaching teams in the program. This paper provides an overview of a practical approach, led by the subject coordinator, to engaging sessional staff through the facilitation of a supportive network within the teaching team. It addresses some of the gaps identified in the recent literature which includes lack of role clarity for all members of the team and provides some examples of initiatives that teams engaged with to address some of the challenges identified. Resources to support this approach were developed and are shared through the project website. Recommendations for future direction include improved policy and practice at the institutional level, better recognition and reward for subject coordinators and resourcing to support the participation and professional development needs of sessional staff.

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This thesis addresses the process simulation and validation in Business Process Management. It proposes that the hybrid Multi Agent System (MAS) / 3D Virtual World approach is a valid method for better simulating the behaviour of human resources in business processes, supporting a wide range of rich visualization applications that can facilitate communication between business analysts and stakeholders. It is expected that the findings of this thesis may be fruitfully extended from BPM to other application domains, such as social simulation in video games and computer-based training animations.

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Carrying capacity assessments model a population’s potential self-sufficiency. A crucial first step in the development of such modelling is to examine the basic resource-based parameters defining the population’s production and consumption habits. These parameters include basic human needs such as food, water, shelter and energy together with climatic, environmental and behavioural characteristics. Each of these parameters imparts land-usage requirements in different ways and varied degrees so their incorporation into carrying capacity modelling also differs. Given that the availability and values of production parameters may differ between locations, no two carrying capacity models are likely to be exactly alike. However, the essential parameters themselves can remain consistent so one example, the Carrying Capacity Dashboard, is offered as a case study to highlight one way in which these parameters are utilised. While examples exist of findings made from carrying capacity assessment modelling, to date, guidelines for replication of such studies in other regions and scales have largely been overlooked. This paper addresses such shortcomings by describing a process for the inclusion and calibration of the most important resource-based parameters in a way that could be repeated elsewhere.

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This thesis presents an analysis of the resource allocation problem in Orthogonal Frequency Division Multiplexing based multi-hop wireless communications systems. The study analyzed the tractable nature of the problem and designed several heuristic and fairness-aware resource allocation algorithms. These algorithms are fast and efficient and therefore can improve power management in wireless systems significantly.

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This concept paper examines the positioning of Change Management (CM) in relation to IHRM, and suggests that the emerging field of CM should be seen as collaborative with HRM in providing for the dynamic needs of organisations in contemporary international conditions of uncertainty and environmental turbulence.

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Integration of small-scale electricity generators, known as Distributed Generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of synchronous-type generator has potential to give the DG a better chance in participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimizes interaction with other active devices, such as On-load Tap Changing Transformer (OLTC) and voltage regulator. The technique has been developed based on the concept of control zone, Line Drop Compensation (LDC), as well as the choice of controller's parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

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We evaluated the effectiveness of a woman-held pregnancy record ('The Pregnancy Pocketbook') on improving health behaviors important for maternal and infant health. The Pregnancy Pocketbook was developed as a woman-focused preventive approach to pregnancy health based on antenatal management guidelines, behavior-change evidence, and formative research with the target population and health service providers. The Pregnancy Pocketbook was evaluated using a quasi-experimental, two-group design; one clinic cohort received the Pregnancy Pocketbook (n = 163); the other received Usual Care (n = 141). Smoking, fruit and vegetable intake, and physical activity were assessed at baseline (service-entry) and 12-weeks. Approximately two-thirds of women in the Pregnancy Pocketbook clinic recalled receiving the resource. A small, but significantly greater proportion of women at the Pregnancy Pocketbook site (7.6%) than the UC site (2.1%) quit smoking. No significant effect was observed of the Pregnancy Pocketbook on fruit and vegetable intake or physical activity. Few women completed sections that required health professional assistance. The Pregnancy Pocketbook produced small, but significant effects on smoking cessation, despite findings that indicate minimal interaction about the resource between health staff and the women in their care. A refocus of antenatal care toward primary prevention is required to provide essential health information and behavior change tools more consistently for improved maternal and infant health outcomes.

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This overview article for the special series “Bayesian Networks in Environmental and Resource Management” reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.

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TCNQ·− radical anions (TCNQ = 7,7,8,8,-tetracyanoquinodimethane) form a wide range of semiconducting coordination polymers when coordinated to transition metals. Some such as CuTCNQ and AgTCNQ exhibit molecular switching and memory storage properties; others have intriguing magnetic properties and for example may behave as molecular magnets at low temperature. In this review, the electro- and photo-chemical synthesis and characterization of this important class of material is reviewed. In particular, the electrochemistry and the redox properties of TCNQ derivatives of coordination polymers based on Cu, Ag, Mn, Fe, Co, Ni, Zn and Cd transition metals are surveyed, with an emphasis on the mechanistic aspects of their electrochemical formation via nucleation–growth processes. Given that TCNQ is an extremely good electron acceptor, readily forming TCNQ•− and TCNQ2-, electrochemical reduction of TCNQ in the presence of a transition metal ion provides an ideal method for synthesis of metal-TCNQ materials by electrocrystallization from organic solvents and ionic liquids or solid-solid transformation using TCNQ modified electrodes from aqueous media containing transition metal electrolytes. The significance of the reversible formal potential (E0f) in these studies is discussed. The coupling of electrocrystallisation on electrode surfaces and microscopic characterization of the electrodeposited materials reveals a wide range of morphologies and phases which strongly influence their properties and applications. Since TCNQ also can be photo-reduced in the presence of suitable electron donors, analogous photochemical approaches to the synthesis of TCNQ-transition metal derivatives are available. The advantages of electrochemical and photochemical methods of synthesis relative to chemical synthesis are outlined.

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Introduction Multidisciplinary models of organising and providing care have been proposed to decrease the health services gap between urban and rural populations but health workforce shortages exist across most professions and are further exacerbated by maldistribution. Flexibility and expansion of the range of tasks that a health professional can undertake were proposed. Dispensing doctors (DDs) are such an example. As part of DDs’ routine medical practice, DDs are able to both prescribe and dispense medicines to their patients. The granting of a dispensing licence to a doctor is intended to improve rural community access to medicines where there is no pharmacy within a reasonable distance. Method An iterative, qualitative descriptive methodology was used to identify factors which influenced DDs’ practice. Qualitative data were collected by in-depth face-to-face and telephone interviews with DDs. A combination of processes: qualitative content analysis and constant comparison were used to analyse the interview transcripts thematically. Member checking and separate coding were utilised to ensure rigour. Result Thirty-one interviews were conducted. The respondents universally acknowledged that the main reason for dispensing were for the convenience and benefits of their patients and to ensure continuity of care. DDs’ communities were generally more isolated and smaller when compared to their non-dispensing counterparts. DD-respondents viewed their dispensary as a service to the community. Peer pressure on prescribing was a key factors in self-regulating prescribing and dispensing. Conclusion DDs fulfill an important area of unmet needs by providing continuity of pharmaceutical care but the practice is hindered by significant barriers

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Business processes depend on human resources and managers must regularly evaluate the performance of their employees based on a number of measures, some of which are subjective in nature. As modern organisations use information systems to automate their business processes and record information about processes’ executions in event logs, it now becomes possible to get objective information about resource behaviours by analysing data recorded in event logs. We present an extensible framework for extracting knowledge from event logs about the behaviour of a human resource and for analysing the dynamics of this behaviour over time. The framework is fully automated and implements a predefined set of behavioural indicators for human resources. It also provides a means for organisations to define their own behavioural indicators, using the conventional Structured Query Language, and a means to analyse the dynamics of these indicators. The framework's applicability is demonstrated using an event log from a German bank.