Search results for "Decision Support System."

showing 10 items of 300 documents

An expert system for vineyard management based upon pervasive computer technologies

2009

Determining the optimal maturity level for performing viticulture operations and harvesting activities is a difficult task, because, depending on the variety, the climatic conditions and cultural practices, the phenologic maturation process occurs at different times. Recently, ubiquitous computing technologies allow an extremely precise and cost effective monitoring of environmental conditions by means of an RFID based sensor networks. The implementation of such technologies in vineyard management is nowadays under development, however, besides the possibility of gathering data, the need is perceived of developing decision support tools to fully exploit the potential opportunities of these …

Decision support system RFID Production planningSettore ING-IND/17 - Impianti Industriali Meccanici
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Understanding Decision Support in Large-Scale Disasters: Challenges in Humanitarian Logistics Distribution

2017

Disasters are characterized by conflicting, uncertain, or lacking data. Nevertheless, humanitarian responders need to make rapid decisions. This is particularly true for the immediate response to a sudden onset disaster. Since most humanitarian decision support systems (DSS) make important assumptions on data availability and quality that are often not fulfilled in practice, decision-makers are largely left to their experience. In this paper, we identify three major challenges for an operational DSS to support distribution planning: (i) deep uncertainty; (ii) reflecting field conditions and constraints; and (iii) rapid humanitarian logistics modeling. We review the relevant theories and pro…

Decision support system021103 operations researchHumanitarian LogisticsEmergency managementManagement sciencebusiness.industrymedia_common.quotation_subject05 social sciences0211 other engineering and technologies02 engineering and technologyScheduling (computing)System requirementsRisk analysis (engineering)Service levelScale (social sciences)0502 economics and businessQuality (business)business050203 business & managementmedia_common
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Requirements for Relief Distribution Decision-Making in Humanitarian Logistics

2020

Making efficient and effective decisions in the chaotic environment of humanitarian relief distribution (HRD) is challenging. Decision-makers need to concentrate on numerous decision factors categorized into decision objectives, variables, and constraints. Recent HRD literature focuses on optimizing procedures while neglecting the quantification of essential requirements (decision factors) for information systems to provide decision-making support. In this article, we address this gap by accumulating affecting decision factors from both literature and practice. We investigated the practical implications of these factors in HRD decision-making by measuring the preferences of a Delphi panel c…

Decision support system021103 operations researchHumanitarian LogisticsManagement scienceProcess (engineering)Computer science05 social sciences0211 other engineering and technologiesDelphi method02 engineering and technologyWork (electrical)0502 economics and businessInformation systemNatural disasterSet (psychology)050203 business & management
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Economic Intelligence: Using Innovation to Reinvent the Business

2020

This paper is about showing how economic intelligence could be a tool for relevant innovation decision support and how its integration within the firm can strengthen its innovation capabilities, protect itself from competitors and ensure an essential competitive edge. Innovation is a difficult concept to identify. It’s a complex process that involves all of the firm’s behaviors. Innovation is a decisive choice and risk-taking. Today, it holds a prominent place in corporate strategy. Innovative firms need information about their environments that are characterized by stiffer competition, resulting in the need to keep abreast of competitors’ movements, vendor characteristics and changing tech…

Decision support systemAbsorptive capacityVendorOrder (exchange)Critical success factorStrategic managementCompetitor analysisBusinessCompetitive advantageIndustrial organization
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Essential Enabling Technologies

2016

The previous chapter contained presentations of several relevant collaboration methods. Section 3.1 indicated that the evolution in e-collaboration was associated with a number of technological breakthroughs.

Decision support systemBiometric systemComputer sciencebusiness.industrySection (typography)020206 networking & telecommunicationsCloud computingmacromolecular substances02 engineering and technologyData sciencehumanitiesBusiness intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessMobile device
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SUP R DSS: A sustainability-based decision support & system for road pavements

2019

Road pavement community members are increasingly becoming aware of the need to incorporating the principles of sustainable development into the sector. Policies are also going in this direction and as a consequence in the recent years researchers and practitioners are coming up with new materials, technologies and practices designed to reduce the negative impacts of their activities in the surroundings. Within this framework the road pavements sector is witnessing a paradigm shift towards the development of pavement technologies incorporating high-content of recycled materials, as well as best practices to decrease the overall carbon footprint. These are all promising solutions that to the …

Decision support systemCHAUSSEEComputer science020209 energyStrategy and ManagementStrategy and Management1409 TourismContext (language use)02 engineering and technologyIndustrial and Manufacturing Engineering12. Responsible consumptionTransport engineeringLife cycle thinking; Multi-criteria decision analysis; Sustainability assessment; Sustainable design; Sustainable engineering; Sustainable pavements; Renewable Energy Sustainability and the Environment; 2300; Strategy and Management1409 Tourism Leisure and Hospitality Management; Industrial and Manufacturing Engineering[SPI]Engineering Sciences [physics]11. Sustainability0202 electrical engineering electronic engineering information engineeringSustainable designSettore ICAR/04 - Strade Ferrovie Ed AeroportiSustainable engineeringRenewable EnergySUSTAINABILITY ASSESSMENT0505 lawGeneral Environmental ScienceSustainable developmentSUSTAINABLE DESIGNSustainability and the Environment2300Renewable Energy Sustainability and the EnvironmentSustainability assessment Sustainable pavements Sustainable design Sustainable engineering Life cycle thinking Multi-criteria decision analysisLeisure and Hospitality Management05 social sciencesMULTI-CRITERIA DECISION ANALYSISMultiple-criteria decision analysisSUSTAINABLE ENGINEERING13. Climate actionSustainability050501 criminologyMATERIAU RECYCLEDEVELOPPEMENT DURABLESUSTAINABLE PAVEMENTSLIFE CYCLE THINKINGDecision analysis
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Leveraging a Wiki to EnhanceVirtual Collaboration in the Emergency Domain

2008

In a crisis situation, critical success factors include good preparedness, the availability of trustworthy information and reliable people, and the responders' ability to improvise with the available, functioning tools. Wikis can be used as collaborative group support systems to support these activities, especially for communities of practice that must operate as high reliability organizations. The advantages of using a wiki are especially beneficial in volatile environments, such as those in the emergency domain, where critical real-time decision making is required. An international wiki emergenciWiki.org - has been created and is being used by both practitioners and academics. The conclus…

Decision support systemCollaborative softwareKnowledge managementComputer sciencebusiness.industrymedia_common.quotation_subjectDomain (software engineering)Overhead (business)Virtual collaborationPreparednessCritical success factorInformation systemBureaucracybusinessmedia_commonProceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008)
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Building energy demand assessment through heating degree days: the importance of a climatic dataset

2019

Abstract The weather is one of the main factors to consider when designing a building because it represents the most important boundary condition to affect the dynamic behaviour of the building. In the literature, many studies use the degree day to predict building energy demand. However, linking the results obtained from a generic building simulation tool with defined degree days, will not give reliable energy evaluation. The goal of this study is to demonstrate that the assessment of building energy demand through the use of the degree day is correct only if the determination of the climate index is a function of the same weather data. The relationship between Heating Degree-Day and heati…

Decision support systemComputer science020209 energymedia_common.quotation_subject02 engineering and technologyManagement Monitoring Policy and LawDegree (temperature)Heating energy demandDegree day020401 chemical engineering0202 electrical engineering electronic engineering information engineeringSettore ING-IND/10 - Fisica Tecnica Industriale0204 chemical engineeringFunction (engineering)Reliability (statistics)media_commonHeating energy demand Degree days Building thermal balance Weather data Building simulation model Empirical correlationsSettore ING-IND/11 - Fisica Tecnica AmbientaleDegree dayMechanical EngineeringWork (physics)Building simulation modelBuilding and ConstructionEmpirical correlationsIndustrial engineeringGeneral EnergyEnergy (all)Weather dataEmpirical correlationBuilding thermal balanceDegree daysHeating degree dayEnergy (signal processing)
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Building energy performance forecasting: A multiple linear regression approach

2019

Abstract Different ways to evaluate the building energy balance can be found in literature, including comprehensive techniques, statistical and machine-learning methods and hybrid approaches. The identification of the most suitable approach is important to accelerate the preliminary energy assessment. In the first category, several numerical methods have been developed and implemented in specialised software using different mathematical languages. However, these tools require an expert user and a model calibration. The authors, in order to overcome these limitations, have developed an alternative, reliable linear regression model to determine building energy needs. Starting from a detailed …

Decision support systemComputer scienceCalibration (statistics)020209 energy02 engineering and technologyManagement Monitoring Policy and LawBuilding energy demandsymbols.namesake020401 chemical engineeringLinear regression0202 electrical engineering electronic engineering information engineeringSensitivity (control systems)0204 chemical engineeringReliability (statistics)Multiple linear regressionSettore ING-IND/11 - Fisica Tecnica AmbientaleMechanical EngineeringBuilding and ConstructionIndustrial engineeringPearson product-moment correlation coefficientDynamic simulationIdentification (information)Black box methodGeneral EnergysymbolsForecast methodSensitivity analysisDynamic simulation
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Not a Target. A Deep Learning Approach for a Warning and Decision Support System to Improve Safety and Security of Humanitarian Aid Workers

2019

Humanitarian aid workers who try to provide aid to the most vulnerable populations in the Middle East or Africa are risking their own lives and safety to help others. The current lack of a collaborative real-time information system to predict threats prevents responders and local partners from developing a shared understanding of potentially threatening situations, causing increased response times and leading to inadequate protection. To solve this problem, this paper presents a threat detection and decision support system that combines knowledge and information from a network of responders with automated and modular threat detection. The system consists of three parts. It first collects te…

Decision support systemComputer scienceHumanitarian aidbusiness.industryDeep learningSystem testing02 engineering and technologyComputer securitycomputer.software_genreClassified information020204 information systems0202 electrical engineering electronic engineering information engineeringInformation systemCollaborative intelligence020201 artificial intelligence & image processingSocial mediaArtificial intelligencebusinesscomputerIEEE/WIC/ACM International Conference on Web Intelligence
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