14,824 research outputs found

    Assessing New York City's Youth Gun Violence Crisis: Crews - Volume II - CompStat for Violence Prevention Programs: Collecting Program Specific Data to Manage Performance and Inform Policy

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    The success or failure of community strategies to address the youth gun violence crisis is often attributed in part to how well the problem is understood and diagnosed. With support from The New York Community Trust, the Crime Commission has undertaken an analysis of youth gun violence and crew activity -- violent turf rivalries among less-organized, smaller and normally younger groups than traditional gangs -- in select New York City communities. Our initial findings from available data, existing research and interviews with stakeholders are presented in a series of papers titled, "Assessing New York City's Youth Gun Violence Crisis: Crews.

    Status of introductory computer education in the Netherlands: results of a survey

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    The International Association for the Evaluation of Educational Achievement (IEA) is conducting an international comparative study on educational computer use in more than 20 countries. This paper analyzes some of the Dutch results of the IEA survey on the use of computers in lower secondary schools. The findings show that at present computers are mainly used for introductory computer courses, but that the integration of computers into existing subjects is still limited. The main problems identified in the study are: insufficient availability of courseware and hardware, time constraints and a high need for teacher training

    The importance of ICT: Information and communication technology in primary and secondary schools, 2005/2008

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    Planning Support Systems: Progress, Predictions, and Speculations on the Shape of Things to Come

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    In this paper, we review the brief history of planning support systems, sketching the way both the fields of planning and the software that supports and informs various planning tasks have fragmented and diversified. This is due to many forces which range from changing conceptions of what planning is for and who should be involved, to the rapid dissemination of computers and their software, set against the general quest to build ever more generalized software products applicable to as many activities as possible. We identify two main drivers – the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web. We attempt a brief and somewhat unsatisfactory classification of tools for PSS in terms of the planning process and the software that has evolved, but this does serve to point up the state-ofthe- art and to focus our attention on the near and medium term future. We illustrate many of these issues with three exemplars: first a land usetransportation model (LUTM) as part of a concern for climate change, second a visualization of cities in their third dimension which is driving an interest in what places look like and in London, a concern for high buildings, and finally various web-based services we are developing to share spatial data which in turn suggests ways in which stakeholders can begin to define urban issues collaboratively. All these are elements in the larger scheme of things – in the development of online collaboratories for planning support. Our review far from comprehensive and our examples are simply indicative, not definitive. We conclude with some brief suggestions for the future

    Conversion to Organic Production Software (OrgPlan, OF0159)

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    This is the final report for Defra Project OF0159. The Organic Conversion Planner (OrgPlan) is a computer program for farmers and advisors reducing the time input necessary for planning a conversion to organic farming. Conversion planning can help to identify whether organic management is suited to the farm and potential problems during the conversion period itself. This involves an assessment of the current situation of the farm, based on which proposals for an organic 'target (endpoint)' can be developed. This includes proposed rotation(s), cropping and stocking plan for the specific farm situation and the proposals need to be tested for their technical and financial feasibility, including impact on forage supply, nutrient requirements and financial budgets. In a final step a more detailed strategy for getting from the current situation to the target situation needs to be worked out. On the basis of such a plan a farmers can make an informed choice about the feasibility of a conversion and planning can help to reduce the risk of conversion. General whole farm planning methods can be broadly split into budgeting and optimisation methods. The former uses input and output data from existing enterprises or standard data, whereas the latter uses mathematical models to determine the optimal choice of enterprises for a maximisation of a key indicator, e.g. profit. OrgPlan uses the budgeting approach, building on experience with mainly German speaking budgeting software for organic conversion. It overcomes a number of key limitations of spreadsheet based budgeting approaches in relation to access to standard enterprise data, additional support tools (e.g. rotation planner) and ease of use. The software is structured into three major sections: In Central Resources basic standard data and farm profiles are entered, viewed and adjusted, and rotations can be planned. Access is also provided to the advisory section, containing documents about organic production standards, organic managmenet notes and a software help file. It is also possible to access these from other sections of the software. In the Scenario Planning section new files for a scenario are created, where a scenario refers to a period of several years of a farm during conversion and/or under organic management. Cropping and livestock plans are generated and a first assessment of the scenario of key farm mangement indicators, nutrients and forage budgets is provided. After adding whole farm financial data the results are transferred into the Report Builder where profit and loss and cash-flow forecasts for the scenario can be generated. Reports can be viewed on screen, printed (HTML format) or exported for further analysis in other packages (spreadsheets). A key aim in developing the software was to reduce the time input needed for conversion planning. The software is windows based and follows the layout of the EMA software (developed by UH). It was programmed in Microsoft (MS) Visual Basic, using MS Access databases for the storage of data. It used results of several DEFRA funded research projects and has relevance to the Organic Conversion Information Service (OCIS). A series of nine basic steps are needed to use the software to plan conversion. These are: viewing and modifying standard enterprise data, viewing and modifying rotations, creating a farm profile, creating and planning a conversion scenario, getting first feedback on the scenario, adding whole farm financial data, planning new investment during the scenario period and viewing and printing reports and/or export data for further analysis in other packages. The basic planning tool has been released as part of the EMA 2002 software (EMA Plan). Because of the sensitive nature of the financial calculations that are the main feature of OrgPlan, further field testing of the programme in conjunction with the Organic Standard Data Collection is envisaged in the autumn of 2002 for with experienced Organic Farming Consultants

    Research on knowledge representation, machine learning, and knowledge acquisition

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    Research in knowledge representation, machine learning, and knowledge acquisition performed at Knowledge Systems Lab. is summarized. The major goal of the research was to develop flexible, effective methods for representing the qualitative knowledge necessary for solving large problems that require symbolic reasoning as well as numerical computation. The research focused on integrating different representation methods to describe different kinds of knowledge more effectively than any one method can alone. In particular, emphasis was placed on representing and using spatial information about three dimensional objects and constraints on the arrangement of these objects in space. Another major theme is the development of robust machine learning programs that can be integrated with a variety of intelligent systems. To achieve this goal, learning methods were designed, implemented and experimented within several different problem solving environments

    Plan recognition for space telerobotics

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    Current research on space telerobots has largely focused on two problem areas: executing remotely controlled actions (the tele part of telerobotics) or planning to execute them (the robot part). This work has largely ignored one of the key aspects of telerobots: the interaction between the machine and its operator. For this interaction to be felicitous, the machine must successfully understand what the operator is trying to accomplish with particular remote-controlled actions. Only with the understanding of the operator's purpose for performing these actions can the robot intelligently assist the operator, perhaps by warning of possible errors or taking over part of the task. There is a need for such an understanding in the telerobotics domain and an intelligent interface being developed in the chemical process design domain addresses the same issues

    Virtual reality and program comprehension: application using spreadsheet visualisation

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    Program comprehension is an important function undertaken in the process of software maintenance. Compared to other research subjects, program comprehension has received little attention even though it is one of the biggest influences on a programmer's output. Research into aiding program comprehension has led to software visualisations, but these are mainly two-dimensional views and overload the viewer with information. With the advent of more powerful computers, virtual reality can be used to create three dimensional visualisations, in which the viewer is able to navigate freely. Spreadsheets were studied in this work on visualisation because programming languages are extremely complex and a model employing spreadsheets was developed. Spreadsheets offer many similarities to programming languages, for example, cell referencing and formulas in spreadsheets are similar to procedure calls, variable referencing and data manipulation in conventional programming languages. Common mistakes made in spreadsheets have been shown to be very difficult to locate, mainly because the spreadsheet user has a reduced ability to make hypotheses about the computational domain of a spreadsheet. Therefore, in order to address this shortcoming a visualisation model was developed to allow a spreadsheet user to be able to view both the problem domain (the what) and the computational domain (the how) simultaneously. A spreadsheet, a spreadsheet description language and a virtual reality system were the objects in the model, and a generator and translator were the links between those objects. Implementing the model indicated that spreadsheets could be visualised in virtual reality, and this technique was shown to improve the process of spreadsheet comprehension

    Teachers Know Best: Making Data Work For Teachers and Students

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    The Teachers Know Best research project seeks to encourage innovation in K - 12 education by helping product developers and those who procure resources for teachers better understand teachers' views. The intent of Making Data Work is to drill down to help educators, school leaders, and product developers better understand the challenges teachers face when working with this critical segment of digital instructional tools. More than 4,600 teachers from a nationally representative sample were surveyed about their use of data to drive instruction and the use of these tools.This study focuses on the potential of a specific subset of digital instructional tools: those that help teachers collect and make use of student data to tailor and improve instruction for individual students. The use of data is a crucial component in personalized learning, which ensures that student learning experiences -- what they learn and how, when, and where they learn it -- are tailored to their individual needs, skills, and interests and enable them to take ownership of their learning. Personalized learning is critical to meeting all students where they are, so they are neither bored with assignments that are too easy nor overwhelmed by work that is too hard
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