32,535 research outputs found
A knowledge-based decision support system for roofing materials selection and cost estimating: a conceptual framework and data modelling
A plethora of materials is available to the modern day house designer but selecting the appropriate material is a complex task. It requires synthesising a multitude of performance criteria such as initial cost, maintenance cost, thermal performance and sustainability among others. This research aims to develop a Knowledge-based Decision support System for Material Selection (KDSMS) that facilitates the selection of optimal material for different sub elements of a roof design. The proposed system also has a facility for estimating roof cost based on the identified criteria. This paper presents the data modelling conceptual framework for the proposed system. The roof sub elements are modelled on the Building Cost Information Service (BCIS) Standard Form of Cost Analysis. This model consists of a knowledge base and a database to store different types of roofing materials with their corresponding performance characteristics and rankings. The system s knowledge is elicited from an extensive review of literature and the use of a domain expert forum. The proposed system employs the multi criteria decision method of TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution), to resolve the materials selection and optimisation problem. The KDSMS is currently being developed for the housing sector of Northern Ireland
EcoGIS – GIS tools for ecosystem approaches to fisheries management
Executive Summary:
The EcoGIS project was launched in September 2004 to investigate how Geographic Information Systems (GIS), marine data, and custom analysis tools can better enable fisheries scientists and managers to adopt Ecosystem Approaches to Fisheries Management (EAFM). EcoGIS is a collaborative effort between NOAA’s National Ocean Service (NOS) and National Marine Fisheries Service (NMFS), and four regional Fishery Management Councils.
The project has focused on four priority areas: Fishing Catch and Effort Analysis, Area Characterization, Bycatch Analysis, and Habitat Interactions. Of these four functional areas, the project team first focused on developing a working prototype for catch and effort analysis: the Fishery Mapper Tool. This ArcGIS extension creates time-and-area summarized maps of fishing catch and effort from logbook, observer, or fishery-independent survey data sets. Source data may come from Oracle, Microsoft Access, or other file formats. Feedback from beta-testers of the Fishery Mapper was used to debug the prototype, enhance performance, and add features.
This report describes the four priority functional areas, the development of the Fishery Mapper tool, and several themes that emerged through the parallel evolution of the EcoGIS project, the concept and implementation of the broader field of Ecosystem Approaches to Management (EAM), data management practices, and other EAM toolsets. In addition, a set of six succinct recommendations are proposed on page 29.
One major conclusion from this work is that there is no single “super-tool” to enable Ecosystem Approaches to Management; as such, tools should be developed for specific purposes with attention given to interoperability and automation. Future work should be coordinated with other GIS development projects in order to provide “value added” and minimize duplication of efforts.
In addition to custom tools, the development of cross-cutting Regional Ecosystem Spatial Databases will enable access to quality data to support the analyses required by EAM. GIS tools will be useful in developing Integrated Ecosystem Assessments (IEAs) and providing pre- and post-processing capabilities for spatially-explicit ecosystem models.
Continued funding will enable the EcoGIS project to develop GIS tools that are immediately applicable to today’s needs. These tools will enable simplified and efficient data query, the ability to visualize data over time, and ways to synthesize multidimensional data from diverse sources. These capabilities will provide new information for analyzing issues from an ecosystem perspective, which will ultimately result in better understanding of fisheries and better support for decision-making. (PDF file contains 45 pages.
Memos and Mega Projects: Applying Planners’ Perceptions of Their Software to a Framework for the Future of Planning
Software powers the modern urban planning department. However, the majority of academic attention on software in the planning profession has focused on highly specialized land use models, ignoring the importance of common applications that most planners rely upon throughout their workdays. For example, email’s impact on planning has gone largely undiscussed in the literature despite its role as one of the most commonly used software by planners. This report has a twofold purpose: 1) create a protocol for interviewing planners about the software they use routinely; 2) synthesize needs and expectations of planners gathered during interviews with relevant literature on planning technologies into a framework for the future of planning software. The framework presented in this report unifies, for the first time, disparate fields of research on software related to urban planning into a single set of guidelines for developing the future of software for public agencies. This framework provides a research agenda for urban planning software systems that mutually strengthen one another, and a valuable conceptual overview of the diverse information systems involved in the planning profession. Eleven interviews were conducted with mid- and senior-level planners in local governments across Santa Clara County, better known around the world as Silicon Valley. Santa Clara County was selected as the study area for two reasons: well-resourced governments in the area can invest in modern planning software, and to question if the stereotype of the area’s technological leadership extends to its local governments. Senior-level planners were interviewed in a semi-structured format with the interview adjusted based on a short survey about the software most used in the individual’s professional role. Key findings from the interviews informing the framework include: Planners in local governments in Silicon Valley are transitioning into modern software tools, like electronic plan review and permit management systems. There is no special technological advantage in Silicon Valley among public agencies. Planners were eager to fully implement and adopt software features available to them, particularly features that would improve communication about project status with applicants; Planners were unafraid of software automation. Limited automation features available in electronic plan review systems were yet to be fully implemented, and planners embraced the time-saving potential; The volume of email burdened interviewees. This draws attention to the significance of generalized productivity software in the practice of planning; Planners had no immediate need for “big data,” despite the recognized importance of big data in the urban planning technology literature. Perceptions from planners about the software that they use informed key problems and set goals for the framework developed here. Extensive research into emerging software targeting the construction and engineering trades with relevance to planners, as well as software designed to assist creative knowledge workers, informed the development of the future framework for planning software. Features of the framework include: A planning data model that underpins land use codes, development guidelines, and planning department procedures, providing machine-readable logic that underpins rulebased systems in email, project tracking, permit management, electronic plan review, and staff reports; Template-based and data type-aware word processing that encodes standardized practices for writing documents and requires numeric data be stored and represented as such. Electronic plan review systems that assist in checking both objective zoning codes and subjective design guidelines using generalized adaptable rule language; Integrated BIM-GIS supporting both the plan review and permit management process by organizing and visualizing spatial and physical data about the built environment; and Predictable, structured times to respond to email from applicants and the public and process-integrated calendars that recover time for focusing on long-term planning efforts; The generalized productivity software that planners have been using for over thirty years is inadequate for the predicted era of big data generated by networked urban environments. Excel is not designed to support real-time analytics, Word is not designed to assist in describing or associating analytics with textual information, and no application has yet been designed to visualize or organize such data for engaging the public. This framework gives planners and researchers of planning technology insight into the range of software used by planners and develop an innovative class of software fit for stewarding the cities of the coming century
The Faculty Notebook, September 2016
The Faculty Notebook is published periodically by the Office of the Provost at Gettysburg College to bring to the attention of the campus community accomplishments and activities of academic interest. Faculty are encouraged to submit materials for consideration for publication to the Associate Provost for Faculty Development. Copies of this publication are available at the Office of the Provost
Integrated collaborative tools for precast supply chain management
Precast construction projects are associated with many activities, numerous parties, enormous effort, and different processes. For effective communication, this requires delivering appropriate and up-to-date information to enhance collaboration and improve integration. The purpose of this paper is to develop the system architecture and prototype of Context-Aware Cloud Computing Building Information Modelling (CACCBIM) for precast supply chain management. The findings of this research are grounded on the literature of cloud computing, context-awareness, building information modelling, and, ultimately, the analysis of interviews with stakeholders in precast construction. Findings determine that lack of integration, improper planning and scheduling, poor production timing, poor coordination, lack of good communication among parties, wrong deliveries, and poor control and supervision are the major issues within the precast supply chain. These issues could result in adverse consequences for the objectives and success of the precast project. Eventually, to reduce and eliminate these issues, the proposed prototype will support appropriate deliveries, efficient monitoring, facilitation of coordination, and collaboration with improved communication. It is anticipated that this research will establish a unique perception in the precast construction industry, which will finally enhance its productivity, improve its efficiency, and maximise its effectiveness
Acquisition Data Analytics for Supply Chain Cybersecurity
Acquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsCybersecurity is a national priority, but the analysis required for acquisition personnel to objectively assess the integrity of the supply chain for cyber compromise is highly complex. This paper presents a process for supply chain data analytics for acquisition decision makers, addressing data collection, assessment, and reporting. The method includes workflows from initial purchase request through vendor selection and maintenance to audits across the lifecycle of an asset. Artificial intelligence can help acquisition decision makers automate the complexity of supply chain information assurance.Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited
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Supporting location-based inquiry learning across school, field and home contexts
Here we explore how technology can be applied to support inquiry learning spanning a range of contexts. The development process of a location-based inquiry learning toolset is presented for a secondary school GCSE Geography project. The design framework used and the process of participatory development is discussed with regard to the co-development of the activities and tools involved in an inquiry project. The lessons learned relate to the formation of a motivational context for the inquiry; the role of personal data collection in the field; the use of bridging representations across field and classroom activities; and the development of flexible, re-usable tools to support and bridge sequences of activities
Advancing Water Resources Systems Modeling Cyberinfrastructure to Enable Systematic Data Analysis, Modeling, and Comparisons
Water resources systems models aid in managing water resources holistically considering water, economic, energy, and environmental needs, among others. Developing such models require data that represent a water system’s physical and operational characteristics such as inflows, demands, reservoir storage, and release rules. However, such data is stored and described in different formats, metadata, and terminology. Therefore, Existing tools to store, query, and visualize modeling data are model, location, and dataset-specific, and developing such tools is time-consuming and requires programming experience. This dissertation presents an architecture and three software tools to enable researchers to more readily and consistently prepare and reuse data to develop, compare, and synthesize results from multiple models in a study area: (1) a generalized database design for consistent organization and storage of water resources datasets independent of study area or model, (2) software to extract data out of and populate data for any study area into the Water Evaluation and Planning system, and (3) software tools to visualize online, compare, and publish water management networks and their data for many models and study areas. The software tools are demonstrated using dozens of example and diverse local, regional, and national datasets from three watersheds for four models; the Bear and Weber Rivers in the USA and the Monterrey River in Mexico
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