728 resultados para Administrative Service Delivery Models


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This paper explores the organisational experiences of governmental policy change and implementation on the third sector. Using a four-year longitudinal study of 13 third sector organisations (TSOs) it provides evidence based on the experiences of, and effects on, third sector organisations involved in the UK’s Work Programme in Scotland. The paper explores third sector experiences of the Work Programme during the preparation and introductory phase, as well as the effects of subsequent Work Programme implementation. By gathering evidence contemporaneously and longitudinally a unique in-depth analysis is provided of the introduction and implementation of a major new policy. The resource cost and challenges to third sector ways of working for the organisations in the Work Programme supply chain, as well as those not in the supply chain, are considered. The paper considers some of the responses adopted by the third sector to manage the opportunities and challenges presented to them through the implementation of the Work Programme. The paper also reflects on the broader context of the employability services landscape and raises questions as to whether, as a result of the manner in which the Work Programme was contracted, there is evidence of a move towards service homogenisation, challenging perceived TSO characteristics of service innovation and personalisation.

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To serve asynchronous requests using multicast, two categories of techniques, stream merging and periodic broadcasting have been proposed. For sequential streaming access where requests are uninterrupted from the beginning to the end of an object, these techniques are highly scalable: the required server bandwidth for stream merging grows logarithmically as request arrival rate, and the required server bandwidth for periodic broadcasting varies logarithmically as the inverse of start-up delay. However, sequential access is inappropriate to model partial requests and client interactivity observed in various streaming access workloads. This paper analytically and experimentally studies the scalability of multicast delivery under a non-sequential access model where requests start at random points in the object. We show that the required server bandwidth for any protocols providing immediate service grows at least as the square root of request arrival rate, and the required server bandwidth for any protocols providing delayed service grows linearly with the inverse of start-up delay. We also investigate the impact of limited client receiving bandwidth on scalability. We optimize practical protocols which provide immediate service to non-sequential requests. The protocols utilize limited client receiving bandwidth, and they are near-optimal in that the required server bandwidth is very close to its lower bound.

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The advent of virtualization and cloud computing technologies necessitates the development of effective mechanisms for the estimation and reservation of resources needed by content providers to deliver large numbers of video-on-demand (VOD) streams through the cloud. Unfortunately, capacity planning for the QoS-constrained delivery of a large number of VOD streams is inherently difficult as VBR encoding schemes exhibit significant bandwidth variability. In this paper, we present a novel resource management scheme to make such allocation decisions using a mixture of per-stream reservations and an aggregate reservation, shared across all streams to accommodate peak demands. The shared reservation provides capacity slack that enables statistical multiplexing of peak rates, while assuring analytically bounded frame-drop probabilities, which can be adjusted by trading off buffer space (and consequently delay) and bandwidth. Our two-tiered bandwidth allocation scheme enables the delivery of any set of streams with less bandwidth (or equivalently with higher link utilization) than state-of-the-art deterministic smoothing approaches. The algorithm underlying our proposed frame-work uses three per-stream parameters and is linear in the number of servers, making it particularly well suited for use in an on-line setting. We present results from extensive trace-driven simulations, which confirm the efficiency of our scheme especially for small buffer sizes and delay bounds, and which underscore the significant realizable bandwidth savings, typically yielding losses that are an order of magnitude or more below our analytically derived bounds.

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The pervasiveness of personal computing platforms offers an unprecedented opportunity to deploy large-scale services that are distributed over wide physical spaces. Two major challenges face the deployment of such services: the often resource-limited nature of these platforms, and the necessity of preserving the autonomy of the owner of these devices. These challenges preclude using centralized control and preclude considering services that are subject to performance guarantees. To that end, this thesis advances a number of new distributed resource management techniques that are shown to be effective in such settings, focusing on two application domains: distributed Field Monitoring Applications (FMAs), and Message Delivery Applications (MDAs). In the context of FMA, this thesis presents two techniques that are well-suited to the fairly limited storage and power resources of autonomously mobile sensor nodes. The first technique relies on amorphous placement of sensory data through the use of novel storage management and sample diffusion techniques. The second approach relies on an information-theoretic framework to optimize local resource management decisions. Both approaches are proactive in that they aim to provide nodes with a view of the monitored field that reflects the characteristics of queries over that field, enabling them to handle more queries locally, and thus reduce communication overheads. Then, this thesis recognizes node mobility as a resource to be leveraged, and in that respect proposes novel mobility coordination techniques for FMAs and MDAs. Assuming that node mobility is governed by a spatio-temporal schedule featuring some slack, this thesis presents novel algorithms of various computational complexities to orchestrate the use of this slack to improve the performance of supported applications. The findings in this thesis, which are supported by analysis and extensive simulations, highlight the importance of two general design principles for distributed systems. First, a-priori knowledge (e.g., about the target phenomena of FMAs and/or the workload of either FMAs or DMAs) could be used effectively for local resource management. Second, judicious leverage and coordination of node mobility could lead to significant performance gains for distributed applications deployed over resource-impoverished infrastructures.

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The majority of the traffic (bytes) flowing over the Internet today have been attributed to the Transmission Control Protocol (TCP). This strong presence of TCP has recently spurred further investigations into its congestion avoidance mechanism and its effect on the performance of short and long data transfers. At the same time, the rising interest in enhancing Internet services while keeping the implementation cost low has led to several service-differentiation proposals. In such service-differentiation architectures, much of the complexity is placed only in access routers, which classify and mark packets from different flows. Core routers can then allocate enough resources to each class of packets so as to satisfy delivery requirements, such as predictable (consistent) and fair service. In this paper, we investigate the interaction among short and long TCP flows, and how TCP service can be improved by employing a low-cost service-differentiation scheme. Through control-theoretic arguments and extensive simulations, we show the utility of isolating TCP flows into two classes based on their lifetime/size, namely one class of short flows and another of long flows. With such class-based isolation, short and long TCP flows have separate service queues at routers. This protects each class of flows from the other as they possess different characteristics, such as burstiness of arrivals/departures and congestion/sending window dynamics. We show the benefits of isolation, in terms of better predictability and fairness, over traditional shared queueing systems with both tail-drop and Random-Early-Drop (RED) packet dropping policies. The proposed class-based isolation of TCP flows has several advantages: (1) the implementation cost is low since it only requires core routers to maintain per-class (rather than per-flow) state; (2) it promises to be an effective traffic engineering tool for improved predictability and fairness for both short and long TCP flows; and (3) stringent delay requirements of short interactive transfers can be met by increasing the amount of resources allocated to the class of short flows.

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The concept of police accountability is not susceptible to a universal or concise definition. In the context of this thesis it is treated as embracing two fundamental components. First, it entails an arrangement whereby an individual, a minority and the whole community have the opportunity to participate meaningfully in the formulation of the principles and policies governing police operations. Second, it presupposes that those who have suffered as victims of unacceptable police behaviour should have an effective remedy. These ingredients, however, cannot operate in a vacuum. They must find an accommodation with the equally vital requirement that the burden of accountability should not be so demanding that the delivery of an effective police service is fatally impaired. While much of the current debate on police accountability in Britain and the USA revolves around the issue of where the balance should be struck in this accommodation, Ireland lacks the very foundation for such a debate as it suffers from a serious deficit in research and writing on police generally. This thesis aims to fill that gap by laying the foundations for an informed debate on police accountability and related aspects of police in Ireland. Broadly speaking the thesis contains three major interrelated components. The first is concerned with the concept of police in Ireland and the legal, constitutional and political context in which it operates. This reveals that although the Garda Siochana is established as a national force the legal prescriptions concerning its role and governance are very vague. Although a similar legislative format in Britain, and elsewhere, have been interpreted as conferring operational autonomy on the police it has not stopped successive Irish governments from exercising close control over the police. The second component analyses the structure and operation of the traditional police accountability mechanisms in Ireland; namely the law and the democratic process. It concludes that some basic aspects of the peculiar legal, constitutional and political structures of policing seriously undermine their capacity to deliver effective police accountability. In the case of the law, for example, the status of, and the broad discretion vested in, each individual member of the force ensure that the traditional legal actions cannot always provide redress where individuals or collective groups feel victimised. In the case of the democratic process the integration of the police into the excessively centralised system of executive government, coupled with the refusal of the Minister for Justice to accept responsibility for operational matters, project a barrier between the police and their accountability to the public. The third component details proposals on how the current structures of police accountability in Ireland can be strengthened without interfering with the fundamentals of the law, the democratic process or the legal and constitutional status of the police. The key elements in these proposals are the establishment of an independent administrative procedure for handling citizen complaints against the police and the establishment of a network of local police-community liaison councils throughout the country coupled with a centralised parliamentary committee on the police. While these proposals are analysed from the perspective of maximising the degree of police accountability to the public they also take into account the need to ensure that the police capacity to deliver an effective police service is not unduly impaired as a result.

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The aim of this research, which focused on the Irish adult population, was to generate information for policymakers by applying statistical analyses and current technologies to oral health administrative and survey databases. Objectives included identifying socio-demographic influences on oral health and utilisation of dental services, comparing epidemiologically-estimated dental treatment need with treatment provided, and investigating the potential of a dental administrative database to provide information on utilisation of services and the volume and types of treatment provided over time. Information was extracted from the claims databases for the Dental Treatment Benefit Scheme (DTBS) for employed adults and the Dental Treatment Services Scheme (DTSS) for less-well-off adults, the National Surveys of Adult Oral Health, and the 2007 Survey of Lifestyle Attitudes and Nutrition in Ireland. Factors associated with utilisation and retention of natural teeth were analysed using count data models and logistic regression. The chi-square test and the student’s t-test were used to compare epidemiologically-estimated need in a representative sample of adults with treatment provided. Differences were found in dental care utilisation and tooth retention by Socio-Economic Status. An analysis of the five-year utilisation behaviour of a 2003 cohort of DTBS dental attendees revealed that age and being female were positively associated with visiting annually and number of treatments. Number of adults using the DTBS increased, and mean number of treatments per patient decreased, between 1997 and 2008. As a percentage of overall treatments, restorations, dentures, and extractions decreased, while prophylaxis increased. Differences were found between epidemiologically-estimated treatment need and treatment provided for those using the DTBS and DTSS. This research confirms the utility of survey and administrative data to generate knowledge for policymakers. Public administrative databases have not been designed for research purposes, but they have the potential to provide a wealth of knowledge on treatments provided and utilisation patterns.

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Huntington’s Disease (HD) is a rare autosomal dominant neurodegenerative disease caused by the expression of a mutant Huntingtin (muHTT) protein. Therefore, preventing the expression of muHTT by harnessing the specificity of the RNA interference (RNAi) pathway is a key research avenue for developing novel therapies for HD. However, the biggest caveat in the RNAi approach is the delivery of short interfering RNA (siRNAs) to neurons, which are notoriously difficult to transfect. Indeed, despite the great advances in the field of nanotechnology, there remains a great need to develop more effective and less toxic carriers for siRNA delivery to the Central Nervous System (CNS). Thus, the aim of this thesis was to investigate the utility of modified amphiphilic β-cyclodextrins (CDs), oligosaccharide-based molecules, as non-viral vectors for siRNA delivery for HD. Modified CDs were able to bind and complex siRNAs forming nanoparticles capable of delivering siRNAs to ST14A-HTT120Q cells and to human HD fibroblasts, and reducing the expression of the HTT gene in these in vitro models of HD. Moreover, direct administration of CD.siRNA nanoparticles into the R6/2 mouse brain resulted in significant HTT gene expression knockdown and selective alleviation of rotarod motor deficits in this mouse model of HD. In contrast to widely used transfection reagents, CD.siRNA nanoparticles only induced limited cytotoxic and neuroinflammatory responses in multiple brain-derived cell-lines, and also in vivo after single direct injections into the mouse brain. Alternatively, we have also described a PEGylation-based formulation approach to further stabilise CD.siRNA nanoparticles and progress towards a systemic delivery nanosystem. Resulting PEGylated CD.siRNA nanoparticles showed increased stability in physiological saltconditions and, to some extent, reduced protein-induced aggregation. Taken together, the work outlined in this thesis identifies modified CDs as effective, safe and versatile siRNA delivery systems that hold great potential for the treatment of CNS disorders, such as HD.

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The conventional meaning of culture is ‘widely shared and strongly held values’ of a particular group or society (Bradley and Parker, 2006: 89). Culture is not a rigid concept; it can be influenced or altered by new ideas or forces. This research examines the ways in which one set of ideas in particular, that is, those associated with New Public Management, have impacted upon the administrative culture of 'street-level' bureaucrats and professionals within Irish social policy. Lipsky (1980: 3) defined 'street-level' bureaucrats as ‘public service workers who interact directly with citizens in the course of their jobs, and who have substantial discretion in the execution of their work’. Utilising the Competing Values Framework (CVF) in the analysis of eighty three semi-structured interviews with 'street-level' bureaucrats and professionals, an evaluation is made as to the impact of NPM ideas on both visible and invisible aspects of administrative culture. Overall, the influence of NPM is confined to superficial aspects of administrative culture such as; increased flexibility in working hours and to some degree job contracts; increased time commitment; and a customer service focus. However, the extent of these changes varies depending on policy sector and occupational group. Aspects of consensual and hierarchical cultures remain firmly in place. These coincide with features of developmental and market cultures. Contrary to the view that members of hierarchical and consensual culture would pose resistance to change, this research clearly illustrates that a very large appetite for change exists in the attitudes of 'street-level' bureaucrats and professionals within Irish social policy, with many of them suggesting changes that correspond to NPM ideas. This study demonstrates the relevance of employing the CVF model as it is clear that administrative culture is very much a dynamic system of competing and co-existing cultures.

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Gene therapy has emerged as a realistic prospect for the treatment of cancer due to its potential for selective tumour cell targeting. The greatest challenge gene delivery vectors face is the ability to safely and efficiently deliver genes into target cells. The overall objectives of this thesis are to evaluate the efficacy of various gene delivery methods in a clinically relevant tumour model and to also investigate potential strategies for tumour selective delivery. We began with the development of a tumour slice model system using patient waste tissue. This model involves the use of fresh human tumour tissue, cut into thin slices and maintained ex vivo and is universally applicable to gene delivery methods, using a real-time luminescence detection method to assess gene delivery. The nature of the ex vivo culture system permitted examination of specific physiological variables, the influence of intratumoural factors and tissue specific effects on vector expression. Adenoviral vectors under the control of the human CXCR4 promoter demonstrated a 'tumour on' and 'normal off' expression profile when compared with the ubiquitously active CMV promoter when tested in patient tumour tissue. In addition, we developed an ex vivo system of changing oxygenation using the hypoxia inducer, cobalt, to mimic the transient hypoxic conditions found in solid tumours. We found that Adenoviral transgene expression was robust in the cycling hypoxic conditions relevant to solid tumours and re-oxygenation of chronically hypoxic tissue enhanced transgene expression. Finally, we demonstrated an AAV-based tumour targeting strategy using a tumour-selective promoter allowing for the efficient targeting of AAV vectors to cancer cells and the sparing of normal tissue in both murine metastatic liver tumours models and patient tissue. The thesis highlights the importance of indepth preclinical assessment of novel therapeutics and may serve as a platform for further testing of novel gene delivery approaches.

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Recent years have witnessed a rapid growth in the demand for streaming video over the Internet, exposing challenges in coping with heterogeneous device capabilities and varying network throughput. When we couple this rise in streaming with the growing number of portable devices (smart phones, tablets, laptops) we see an ever-increasing demand for high-definition videos online while on the move. Wireless networks are inherently characterised by restricted shared bandwidth and relatively high error loss rates, thus presenting a challenge for the efficient delivery of high quality video. Additionally, mobile devices can support/demand a range of video resolutions and qualities. This demand for mobile streaming highlights the need for adaptive video streaming schemes that can adjust to available bandwidth and heterogeneity, and can provide us with graceful changes in video quality, all while respecting our viewing satisfaction. In this context the use of well-known scalable media streaming techniques, commonly known as scalable coding, is an attractive solution and the focus of this thesis. In this thesis we investigate the transmission of existing scalable video models over a lossy network and determine how the variation in viewable quality is affected by packet loss. This work focuses on leveraging the benefits of scalable media, while reducing the effects of data loss on achievable video quality. The overall approach is focused on the strategic packetisation of the underlying scalable video and how to best utilise error resiliency to maximise viewable quality. In particular, we examine the manner in which scalable video is packetised for transmission over lossy networks and propose new techniques that reduce the impact of packet loss on scalable video by selectively choosing how to packetise the data and which data to transmit. We also exploit redundancy techniques, such as error resiliency, to enhance the stream quality by ensuring a smooth play-out with fewer changes in achievable video quality. The contributions of this thesis are in the creation of new segmentation and encapsulation techniques which increase the viewable quality of existing scalable models by fragmenting and re-allocating the video sub-streams based on user requirements, available bandwidth and variations in loss rates. We offer new packetisation techniques which reduce the effects of packet loss on viewable quality by leveraging the increase in the number of frames per group of pictures (GOP) and by providing equality of data in every packet transmitted per GOP. These provide novel mechanisms for packetizing and error resiliency, as well as providing new applications for existing techniques such as Interleaving and Priority Encoded Transmission. We also introduce three new scalable coding models, which offer a balance between transmission cost and the consistency of viewable quality.

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This research investigates whether a reconfiguration of maternity services, which collocates consultant- and midwifery-led care, reflects demand and value for money in Ireland. Qualitative and quantitative research is undertaken to investigate demand and an economic evaluation is performed to evaluate the costs and benefits of the different models of care. Qualitative research is undertaken to identify women’s motivations when choosing place of delivery. These data are further used to inform two stated preference techniques: a discrete choice experiment (DCE) and contingent valuation method (CVM). These are employed to identify women’s strengths of preferences for different features of care (DCE) and estimate women’s willingness to pay for maternity care (CVM), which is used to inform a cost-benefit analysis (CBA) on consultant- and midwifery-led care. The qualitative research suggests women do not have a clear preference for consultant or midwifery-led care, but rather a hybrid model of care which closely resembles the Domiciliary Care In and Out of Hospital (DOMINO) scheme. Women’s primary concern during care is safety, meaning women would only utilise midwifery-led care when co-located with consultant-led care. The DCE also finds women’s preferred package of care closely mirrors the DOMINO scheme with 39% of women expected to utilise this service. Consultant- and midwifery-led care would then be utilised by 34% and 27% of women, respectively. The CVM supports this hierarchy of preferences where consultant-led care is consistently valued more than midwifery-led care – women are willing to pay €956.03 for consultant-led care and €808.33 for midwifery-led care. A package of care for a woman availing of consultant- and midwifery-led care is estimated to cost €1,102.72 and €682.49, respectively. The CBA suggests both models of care are cost-beneficial and should be pursued in Ireland. This reconfiguration of maternity services would maximise women’s utility, while fulfilling important objectives of key government policy.

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BACKGROUND: Outpatient palliative care, an evolving delivery model, seeks to improve continuity of care across settings and to increase access to services in hospice and palliative medicine (HPM). It can provide a critical bridge between inpatient palliative care and hospice, filling the gap in community-based supportive care for patients with advanced life-limiting illness. Low capacities for data collection and quantitative research in HPM have impeded assessment of the impact of outpatient palliative care. APPROACH: In North Carolina, a regional database for community-based palliative care has been created through a unique partnership between a HPM organization and academic medical center. This database flexibly uses information technology to collect patient data, entered at the point of care (e.g., home, inpatient hospice, assisted living facility, nursing home). HPM physicians and nurse practitioners collect data; data are transferred to an academic site that assists with analyses and data management. Reports to community-based sites, based on data they provide, create a better understanding of local care quality. CURRENT STATUS: The data system was developed and implemented over a 2-year period, starting with one community-based HPM site and expanding to four. Data collection methods were collaboratively created and refined. The database continues to grow. Analyses presented herein examine data from one site and encompass 2572 visits from 970 new patients, characterizing the population, symptom profiles, and change in symptoms after intervention. CONCLUSION: A collaborative regional approach to HPM data can support evaluation and improvement of palliative care quality at the local, aggregated, and statewide levels.

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Osteoarthritis (OA) is a degenerative joint disease that can result in joint pain, loss of joint function, and deleterious effects on activity levels and lifestyle habits. Current therapies for OA are largely aimed at symptomatic relief and may have limited effects on the underlying cascade of joint degradation. Local drug delivery strategies may provide for the development of more successful OA treatment outcomes that have potential to reduce local joint inflammation, reduce joint destruction, offer pain relief, and restore patient activity levels and joint function. As increasing interest turns toward intra-articular drug delivery routes, parallel interest has emerged in evaluating drug biodistribution, safety, and efficacy in preclinical models. Rodent models provide major advantages for the development of drug delivery strategies, chiefly because of lower cost, successful replication of human OA-like characteristics, rapid disease development, and small joint volumes that enable use of lower total drug amounts during protocol development. These models, however, also offer the potential to investigate the therapeutic effects of local drug therapy on animal behavior, including pain sensitivity thresholds and locomotion characteristics. Herein, we describe a translational paradigm for the evaluation of an intra-articular drug delivery strategy in a rat OA model. This model, a rat interleukin-1beta overexpression model, offers the ability to evaluate anti-interleukin-1 therapeutics for drug biodistribution, activity, and safety as well as the therapeutic relief of disease symptoms. Once the action against interleukin-1 is confirmed in vivo, the newly developed anti-inflammatory drug can be evaluated for evidence of disease-modifying effects in more complex preclinical models.

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An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.