999 resultados para correctional services


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This paper presents an intelligent procurement marketplace for finding the best mix of web services to dynamically compose the business process desired by a web service requester. We develop a combinatorial auction approach that leads to an integer programming formulation for the web services composition problem. The model takes into account the Quality of Service (QoS) and Service Level Agreements (SLA) for differentiating among multiple service providers who are capable of fulfilling a functionality. An important feature of the model is interface aware composition.

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A customer reported problem (or Trouble Ticket) in software maintenance is typically solved by one or more maintenance engineers. The decision of allocating the ticket to one or more engineers is generally taken by the lead, based on customer delivery deadlines and a guided complexity assessment from each maintenance engineer. The key challenge in such a scenario is two folds, un-truthful (hiked up) elicitation of ticket complexity by each engineer to the lead and the decision of allocating the ticket to a group of engineers who will solve the ticket with in customer deadline. The decision of allocation should ensure Individual and Coalitional Rationality along with Coalitional Stability. In this paper we use game theory to examine the issue of truthful elicitation of ticket complexities by engineers for solving ticket as a group given a specific customer delivery deadline. We formulate this problem as strategic form game and propose two mechanisms, (1) Division of Labor (DOL) and (2) Extended Second Price (ESP). In the proposed mechanisms we show that truth telling by each engineer constitutes a Dominant Strategy Nash Equilibrium of the underlying game. Also we analyze the existence of Individual Rationality (IR) and Coalitional Rationality (CR) properties to motivate voluntary and group participation. We use Core, solution concept from co-operative game theory to analyze the stability of the proposed group based on the allocation and payments.

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A theoretical framework to analyse the interaction of planning and governance on the extent of outgrowth and level of services is proposed. An indicator framework for quantifying sprawl is also proposed and the same is operationalised for Bangalore. The indicators comprise spatial metrics (derived from temporal satellite remote sensing data) and other metrics obtained from a house-hold survey. The interaction of different indicators with respect to the core city and the outgrowth is determined by multi-dimensional scaling. The analysis reveals the underlying similarities (and dissimilarities) that relate with the different governance structures that prevail here. The paper concludes outlining the challenges in addressing urban sprawl while ensuring adequate level of services that planning and governance have to ensure towards achieving sustainable urbanisation.

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Context-aware computing is useful in providing individualized services focusing mainly on acquiring surrounding context of user. By comparison, only very little research has been completed in integrating context from different environments, despite of its usefulness in diverse applications such as healthcare, M-commerce and tourist guide applications. In particular, one of the most important criteria in providing personalized service in a highly dynamic environment and constantly changing user environment, is to develop a context model which aggregates context from different domains to infer context of an entity at the more abstract level. Hence, the purpose of this paper is to propose a context model based on cognitive aspects to relate contextual information that better captures the observation of certain worlds of interest for a more sophisticated context-aware service. We developed a C-IOB (Context-Information, Observation, Belief) conceptual model to analyze the context data from physical, system, application, and social domains to infer context at the more abstract level. The beliefs developed about an entity (person, place, things) are primitive in most theories of decision making so that applications can use these beliefs in addition to history of transaction for providing intelligent service. We enhance our proposed context model by further classifying context information into three categories: a well-defined, a qualitative and credible context information to make the system more realistic towards real world implementation. The proposed model is deployed to assist a M-commerce application. The simulation results show that the service selection and service delivery of the system are high compared to traditional system.

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Transaction processing is a key constituent of the IT workload of commercial enterprises (e.g., banks, insurance companies). Even today, in many large enterprises, transaction processing is done by legacy "batch" applications, which run offline and process accumulated transactions. Developers acknowledge the presence of multiple loosely coupled pieces of functionality within individual applications. Identifying such pieces of functionality (which we call "services") is desirable for the maintenance and evolution of these legacy applications. This is a hard problem, which enterprises grapple with, and one without satisfactory automated solutions. In this paper, we propose a novel static-analysis-based solution to the problem of identifying services within transaction-processing programs. We provide a formal characterization of services in terms of control-flow and data-flow properties, which is well-suited to the idioms commonly exhibited by business applications. Our technique combines program slicing with the detection of conditional code regions to identify services in accordance with our characterization. A preliminary evaluation, based on a manual analysis of three real business programs, indicates that our approach can be effective in identifying useful services from batch applications.

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The capacity of species to track shifting climates into the future will strongly influence outcomes for biodiversity under a rapidly changing climate. However, we know remarkably little about the dispersal abilities of most species and how these may be influenced by climate change. Here we show that climate change is projected to substantially reduce the seed dispersal services provided by frugivorous vertebrates in rainforests across the Australian Wet Tropics. Our model projections show reductions in both median and long-distance seed dispersal, which may markedly reduce the capacity of many rainforest plant species to track shifts in suitable habitat under climate change. However, our analyses suggest that active management to maintain the abundances of a small set of important frugivores under climate change could markedly reduce the projected loss of seed dispersal services and facilitate shifting distributions of rainforest plant species.

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Protection-based ant-plant mutualisms may vary in strength due to differences in ant rewards, abundance of protective ants and herbivory pressure. We investigated geographical and temporal variation in host plant traits and herbivory pressure at five sites spanning the distribution range of the myrmecophyte Humboldtia brunonis (Fabaceae) in the Indian Western Ghats. Southern siteshad, onaverage, 2.4 times greater abundance of domatia-bearing individuals, 1.6 times greater extrafloral nectary numbers per leaf, 1.2 times larger extrafloral nectary sizes, 2.2 times greater extrafloral nectar (EFN) volumes and a two-fold increase in total amino acid and total sugar concentrations in EFN compared with northern sites. Astrong protection-based mutualismwith ants occurred at only one southern site where herbivory was highest, suggesting that investments in attracting ants correlate with anti-herbivore benefits gained from the presence of protective ants. Our results confirm a temporally stable north-south gradient in myrmecophytic traits in this ant-plant as several of these traits were re-sampled after a 5-y interval. However, the chemical composition of EFN varied at both spatial and short-term temporal scales suggesting that only repeated measurements of rewards such as EFN can reveal the real spectrum of trait variation in an ant-plant mutualistic system.

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Virtualization is one of the key enabling technologies for Cloud computing. Although it facilitates improved utilization of resources, virtualization can lead to performance degradation due to the sharing of physical resources like CPU, memory, network interfaces, disk controllers, etc. Multi-tenancy can cause highly unpredictable performance for concurrent I/O applications running inside virtual machines that share local disk storage in Cloud. Disk I/O requests in a typical Cloud setup may have varied requirements in terms of latency and throughput as they arise from a range of heterogeneous applications having diverse performance goals. This necessitates providing differential performance services to different I/O applications. In this paper, we present PriDyn, a novel scheduling framework which is designed to consider I/O performance metrics of applications such as acceptable latency and convert them to an appropriate priority value for disk access based on the current system state. This framework aims to provide differentiated I/O service to various applications and ensures predictable performance for critical applications in multi-tenant Cloud environment. We demonstrate through experimental validations on real world I/O traces that this framework achieves appreciable enhancements in I/O performance, indicating that this approach is a promising step towards enabling QoS guarantees on Cloud storage.