23 resultados para Territorial Intelligence Community System

em Aston University Research Archive


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Product recommender systems are often deployed by e-commerce websites to improve user experience and increase sales. However, recommendation is limited by the product information hosted in those e-commerce sites and is only triggered when users are performing e-commerce activities. In this paper, we develop a novel product recommender system called METIS, a MErchanT Intelligence recommender System, which detects users' purchase intents from their microblogs in near real-time and makes product recommendation based on matching the users' demographic information extracted from their public profiles with product demographics learned from microblogs and online reviews. METIS distinguishes itself from traditional product recommender systems in the following aspects: 1) METIS was developed based on a microblogging service platform. As such, it is not limited by the information available in any specific e-commerce website. In addition, METIS is able to track users' purchase intents in near real-time and make recommendations accordingly. 2) In METIS, product recommendation is framed as a learning to rank problem. Users' characteristics extracted from their public profiles in microblogs and products' demographics learned from both online product reviews and microblogs are fed into learning to rank algorithms for product recommendation. We have evaluated our system in a large dataset crawled from Sina Weibo. The experimental results have verified the feasibility and effectiveness of our system. We have also made a demo version of our system publicly available and have implemented a live system which allows registered users to receive recommendations in real time. © 2014 ACM.

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The Models@run.time (MRT) workshop series offers a discussion forum for the rising need to leverage modeling techniques for the software of the future. The main goals are to explore the benefits of models@run.time and to foster collaboration and cross-fertilization between different research communities like for example like model-driven engineering (e.g. MODELS), self-adaptive/autonomous systems communities (e.g., SEAMS and ICAC), the control theory community and the artificial intelligence community. © 2012 Authors.

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The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

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The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical, and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again until the statutory regulatory authority approves the project. Moreover, project analysis through the above process often results in suboptimal projects as financial analysis may eliminate better options as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select an optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated. © 2008, IGI Global.

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Expert systems, and artificial intelligence more generally, can provide a useful means for representing decision-making processes. By linking expert systems software to simulation software an effective means of including these decision-making processes in a simulation model can be achieved. This paper demonstrates how a commercial-off-the-shelf simulation package (Witness) can be linked to an expert systems package (XpertRule) through a Visual Basic interface. The methodology adopted could be used for models, and possibly software, other than those presented here.

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The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

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Objective: To measure changes in dispensing activity in a UK repeat dispensing pilot study and to estimate any associated cost savings. Method: Patients were provided with two successive three-monthly repeat prescriptions containing all of the items on their "repeat medicines list" and valid at a study pharmacy. Pharmacists consulted with patients at the time of supply and completed a patient-monitoring form. Prescriptions with pricing data were returned by the UK Prescription Pricing Authority. These data were used to calculate dispensing activity, the cost of dispensed items and an estimate of cost savings on non-dispensed items. A retrospective identification of items prescribed during the six months prior to the project was used to provide a comparison with those dispensed during the project and thus a more realistic estimate of changes. Setting: 350 patients from two medical practices in a large English City, with inner city and suburban locations, and served by seven pharmacies. Key findings: There were methodological challenges in establishing a robust framework for calculating changes. Based on all of the items that patients could have obtained from their repeat list, 23.8% were not dispensed during the intervention period. A correction was then made to allow for a comparison with usage in the six months prior to the study. Based on the corrected data, there was an estimated 11.3% savings in drug costs compared with the pre-intervention period. There was a marked difference in changes between the two practices, the pharmacies and individual patients. The capitation-based remuneration method was acceptable to all but one of the community pharmacists. Conclusion: The repeat dispensing system reduced dispensing volume in comparison with the control period. A repeat dispensing system with a focus on patients' needs and their use of medicines might be cost neutral.

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Report on a pilot project funded by the Dept of Health and involving 350 repeat dispensing patients at 7 community pharmacies and two medical practices. 82% of patients approached were willing to enter a repeat dispensing service and after 6 months 86% liked the system. Concludes that successful repeat dispensing depends on a good infrastructure in both the pharmacy and the medical practice, and requires established inter-professional communication.

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This paper examined the joint predictive effects of trait emotional intelligence (trait-EI), Extraversion, Conscientiousness, and Neuroticism on 2 facets of general well-being and job satisfaction. An employed community sample of 123 individuals from the Indian subcontinent participated in the study, and completed measures of the five-factor model of personality, trait-EI, job satisfaction, and general well-being facets worn-out and up-tight. Trait-EI was related but distinct from the 3 personality variables. Trait-EI demonstrated the strongest correlation with job satisfaction, but predicted general well-being no better than Neuroticism. In regression analyses, trait-EI predicted between 6% and 9% additional variance in the well-being criteria, beyond the 3 personality traits. It was concluded that trait-EI may be useful in examining dispositional influences on psychological well-being.

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Health and safety policies may be regarded as the cornerstone for positive prevention of occupational accidents and diseases. The Health and Safety at Work, etc Act 1974 makes it a legal duty for employers to prepare and revise a written statement of a general policy with respect to the health and safety at work of employees as well as the organisation and arrangements for carrying out that policy. Despite their importance and the legal equipment to prepare them, health and safety policies have been found, in a large number of plastics processing companies (particularly small companies), to be poorly prepared, inadequately implemented and monitored. An important cause of these inadequacies is the lack of necessary health and safety knowledge and expertise to prepare, implement and monitor policies. One possible way of remedying this problem is to investigate the feasibility of using computers to develop expert system programs to simulate the health and safety (HS) experts' task of preparing the policies and assisting companies implement and monitor them. Such programs use artificial intelligence (AI) techniques to solve this sort of problems which are heuristic in nature and require symbolic reasoning. Expert systems have been used successfully in a variety of fields such as medicine and engineering. An important phase in the feasibility of development of such systems is the engineering of knowledge which consists of identifying the knowledge required, eliciting, structuring and representing it in an appropriate computer programming language.

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This system is concerned with the design and implementation of a community health information system which fulfils some of the local needs of fourteen nursing and para-medical professions in a district health authority, whilst satisfying the statutory requirements of the NHS Korner steering group for those professions. A national survey of community health computer applications, documented in the form of an applications register, shows the need for such a system. A series of general requirements for an informations systems design methodology are identified, together with specific requirements for this problem situation. A number of existing methodologies are reviewed, but none of these were appropriate for this application. Some existing approaches, tools and techniques are used to define a more suitable methodology. It is unreasonable to rely on one single general methodology for all types of application development. There is a need for pragmatism, adaptation and flexibility. In this research, participation in the development stages by those who will eventually use the system was thought desirable. This was achieved by forming a representative design group. Results would seem to show a highly favourable response from users to this participation which contributed to the overall success of the system implemented. A prototype was developed for the chiropody and school nursing staff groups of Darlington health authority, and evaluations show that a significant number of the problems and objectives of those groups have been successfully addressed; the value of community health information has been increased; and information has been successfully fed back to staff and better utilised.

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This thesis examines the reasons for Cadburys' move from a city centre site to a greenfield site in Bournville in 1879 and the subsequent development of the factory and the Bournville community. The founding of the Bournville Village Trust by George Cadbury is discussed in relation to the Garden City movement. The welfare and personnel management policies which Cadburys adopted in the 1900s are considered in relation to welfarism in general, especially in the United States. The extent to which the idea of a `Quaker employer' can explain Cadburys policies is questioned both methodologically and empirically. The early use of scientific management at Bournville is described and related to Edward Cadbury's writings on the subject. Finally, the institution of a Works Council Scheme in 1918 is described and its uses are discussed. It is concluded that Cadburys instituted a new factory system in this period which consisted of a synthesis of ideas borrowed from elsewhere and that for a variety of reasons Cadburys was an appropriate site for their implementation.

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Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such as ecosystem monitoring and disaster management. One key challenge posed by Dynamically Adaptive Systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. Berry et al. previously identified four levels of RE that should be performed for a DAS. In this paper, we propose the Levels of RE for Modeling that reify the original levels to describe RE modeling work done by DAS developers. Specifically, we identify four types of developers: the system developer, the adaptation scenario developer, the adaptation infrastructure developer, and the DAS research community. Each level corresponds to the work of a different type of developer to construct goal model(s) specifying their requirements. We then leverage the Levels of RE for Modeling to propose two complementary processes for performing RE for a DAS. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed to monitor the River Ribble in Yorkshire, England.

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The semantic web vision is one in which rich, ontology-based semantic markup will become widely available. The availability of semantic markup on the web opens the way to novel, sophisticated forms of question answering. AquaLog is a portable question-answering system which takes queries expressed in natural language and an ontology as input, and returns answers drawn from one or more knowledge bases (KBs). We say that AquaLog is portable because the configuration time required to customize the system for a particular ontology is negligible. AquaLog presents an elegant solution in which different strategies are combined together in a novel way. It makes use of the GATE NLP platform, string metric algorithms, WordNet and a novel ontology-based relation similarity service to make sense of user queries with respect to the target KB. Moreover it also includes a learning component, which ensures that the performance of the system improves over the time, in response to the particular community jargon used by end users.

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Online communities of consumption (OCCs) represent highly diverse groups of consumers whose interests are not always aligned. Social control in OCCs aims to effectively manage problems arising from this heterogeneity. Extant literature on social control in OCCs is fragmented as some studies focus on the principles of social control, while others focus on the implementation. Moreover, the domain is undertheorized. This article integrates the disparate literature on social control in OCCs providing a first unified conceptualization of the topic. The authors conceptualize social control as a system, or configuration, of moderation practices. Moderation practices are executed during interactions operating under different governance structures (market, hierarchy, and clan) and serving different purposes (interaction initiation, maintenance, and termination). From this conceptualization, important areas of future research emerge and research questions are developed. The framework also serves as a community management tool for OCC managers, enabling the diagnosis of social control problems and the elaboration of strategies and tactics to address them.