A GIS-based Spatial Decision Support System for environmentally valuable areas in the context of sustainable development of Poland

Science.gov (United States)

Kubacka, Marta

2013-04-01

The issue of spatial development, and thus proper environmental management and protection at naturally valuable areas is today considered a major hazard to the stability of the World ecological system. The increasing demand for areas with substantial environmental and landscape assets, incorrect spatial development, improper implementation of law as well as low citizen awareness bring about significant risk of irrevocable loss of naturally valuable areas. The elaboration of a Decision Support System in the form of collection of spatial data will facilitate solving complex problems concerning spatial development. The elaboration of a model utilizing a number of IT tools will boost the effectiveness of taking spatial decisions by decision-makers. Proper spatial data management becomes today a key element in management based on knowledge, namely sustainable development. Decision Support Systems are definied as model-based sets of procedures for processing data and judgments to assist a manager in his decision-making. The main purpose of the project was to elaborate the spatial decision support system for the Sieraków Landscape Park. A landscape park in Poland comprises a protected area due to environmental, historic and cultural values as well as landscape assets for the purpose of maintaining and popularizing these values in the conditions of sustainable development. It also defines the forms of protected area management and introduces bans concerning activity at these areas by means of the obligation to prepare and implement environmental protection plans by a director of the complex of landscape parks. As opposed to national parks and reserves, natural landscape parks are not the areas free from economic activity, thus agricultural lands, forest lands and other real properties located within the boundaries of natural landscape parks are subject to economic utilization Research area was subject to the analysis with respect to the implementation of investment

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

Science.gov (United States)

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

Directory of Open Access Journals (Sweden)

Hongoh Valerie

2011-12-01

Full Text Available Abstract The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector

Caterpillar C7 and GEP 6.5L (T) Fuel System Durability Using 25% ATJ Fuel Blend

Science.gov (United States)

2015-02-01

6.5L(T) diesel engines. With the technical issues presented in this report related to the CAT C7 evaluation and the desert operating condition GEP 6.5L...General Engine Products (GEP) 6.5L(T) diesel engines. These engines are representative of high density vehicles fielded by the U.S. Army tactical...Southwest Research Institute T - turbo TARDEC – Tank Automotive Research, Development, and Engineering Center TFLRF – TARDEC Fuels and Lubricants

A group-based spatial decision support system for wind farm site selection in Northwest Ohio

International Nuclear Information System (INIS)

Gorsevski, Pece V.; Cathcart, Steven C.; Mirzaei, Golrokh; Jamali, Mohsin M.; Ye, Xinyue; Gomezdelcampo, Enrique

2013-01-01

The purpose of this paper is to demonstrate the benefits of applying a spatial decision support system (SDSS) framework for evaluating the suitability for wind farm siting in Northwest Ohio. The multiple criteria evaluation (MCE) prototype system is intended for regional planning but also for promoting group decision making that could involve participants with different interests in the development of decision alternatives. The framework integrates environmental and economic criteria and builds a hierarchy for wind farm siting using weighted linear combination (WLC) techniques and GIS functionality. The SDSS allows the multiple participants to interact and develop an understanding of the spatial data for assigning importance values to each factor. The WLC technique is used to combine the assigned values with map layers, which are standardized using fuzzy set theory, to produce individual suitability maps. The maps created by personal preferences from the participants are aggregated for producing a group solution using the Borda method. Sensitivity analysis is performed on the group solution to examine how small changes in the factor weights affect the calculated suitability scores. The results from the sensitivity analysis are intended to aid understanding of compromised solutions through changes in the input data from the participant's perspective. - Highlights: ► We present a prototype tool that we developed for wind farm site selection. ► Multiple participants rank the factors for promoting group-based decision making. ► The factors are aggregated by WLC technique to generate maps from participants. ► Group-based solution uses Borda method to aggregate the maps from participants. ► Sensitivity analysis is performed on the group solution to examine solution affects

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

Science.gov (United States)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

NO99 lavastust "GEP" nägi Moskvas 800 krooni eest / Dagmar Reinolt

Index Scriptorium Estoniae

Reinolt, Dagmar

2009-01-01

27. märtsil Moskvas alanud 15. teatrifestivalist "Kuldne mask" ja Eesti teatrite - NO99 lavastusega "GEP", Eesti Nuku- ja Noorsooteater lavastusega "Mängurid" ja Rahvusooper Estonia kahe lühiballetiga "Hamlet" ja "Libahunt" - osalemisest festivali eriprogrammis "Kuldne mask pluss"

Decision Performance Using Spatial Decision Support Systems: A Geospatial Reasoning Ability Perspective

Science.gov (United States)

Erskine, Michael A.

2013-01-01

As many consumer and business decision makers are utilizing Spatial Decision Support Systems (SDSS), a thorough understanding of how such decisions are made is crucial for the information systems domain. This dissertation presents six chapters encompassing a comprehensive analysis of the impact of geospatial reasoning ability on…

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

International Nuclear Information System (INIS)

Wanderer, Thomas; Herle, Stefan

2015-01-01

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

Energy Technology Data Exchange (ETDEWEB)

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sites are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.

Development of GP and GEP models to estimate an environmental issue induced by blasting operation.

Science.gov (United States)

Faradonbeh, Roohollah Shirani; Hasanipanah, Mahdi; Amnieh, Hassan Bakhshandeh; Armaghani, Danial Jahed; Monjezi, Masoud

2018-05-21

Air overpressure (AOp) is one of the most adverse effects induced by blasting in the surface mines and civil projects. So, proper evaluation and estimation of the AOp is important for minimizing the environmental problems resulting from blasting. The main aim of this study is to estimate AOp produced by blasting operation in Miduk copper mine, Iran, developing two artificial intelligence models, i.e., genetic programming (GP) and gene expression programming (GEP). Then, the accuracy of the GP and GEP models has been compared to multiple linear regression (MLR) and three empirical models. For this purpose, 92 blasting events were investigated, and subsequently, the AOp values were carefully measured. Moreover, in each operation, the values of maximum charge per delay and distance from blast points, as two effective parameters on the AOp, were measured. After predicting by the predictive models, their performance prediction was checked in terms of variance account for (VAF), coefficient of determination (CoD), and root mean square error (RMSE). Finally, it was found that the GEP with VAF of 94.12%, CoD of 0.941, and RMSE of 0.06 is a more precise model than other predictive models for the AOp prediction in the Miduk copper mine, and it can be introduced as a new powerful tool for estimating the AOp resulting from blasting.

Influence of Li10GeP2S12-type solid electrolyte on cell thermodynamics

Directory of Open Access Journals (Sweden)

Jishnu Bhattacharya

2016-06-01

Full Text Available We elucidate few critical facts about the lithium superionic conductor (Li10GeP2S12 and few other compounds of the same family as the electrolyte in Li-ion cells. The dimensionality of diffusion process and existence of ‘structural’ lithiums are not well understood in this material. From the ab-initio MD simulations, we find that the material transport Li-ions predominantly in the crystallographic c-direction. Nevertheless, the cross-channel diffusion is significant as well. We explored the mobility of individual Li-ions and do not find evidence that supports the proposition of structural Li-ions in LGPS. We find nominal effect of local Ge-P ordering and of Li-concentration change on diffusivity, which not only provides information about the invariance of diffusivity at different conditions of operation, but also ensures that identification of the ground state structure in LGPS having partially occupied Li and Ge/P sublattices should have minimal effect on the diffusion analysis. We computed the dilute Li insertion and extraction voltages for LGPS from ab-initio total energy calculation. The dilute voltages indicate that the material is prone to react by exchanging Li-ions with the electrodes at typical operating range of voltages indicating formation of some interphase at the electrode-electrolyte interface, which necessitates further experimental investigation

The SBAS Sentinel-1 Surveillance service for automatic and systematic generation of Earth surface displacement within the GEP platform.

Science.gov (United States)

Casu, Francesco; De Luca, Claudio; Lanari, Riccardo; Manunta, Michele; Zinno, Ivana

2017-04-01

The Geohazards Exploitation Platform (GEP) is an ESA activity of the Earth Observation (EO) ground segment to demonstrate the benefit of new technologies for large scale processing of EO data. GEP aims at providing both on-demand processing services for scientific users of the geohazards community and an integration platform for new EO data analysis processors dedicated to scientists and other expert users. In the Remote Sensing scenario, a crucial role is played by the recently launched Sentinel-1 (S1) constellation that, with its global acquisition policy, has literally flooded the scientific community with a huge amount of data acquired over large part of the Earth on a regular basis (down to 6-days with both Sentinel-1A and 1B passes). Moreover, the S1 data, as part of the European Copernicus program, are openly and freely accessible, thus fostering their use for the development of tools for Earth surface monitoring. In particular, due to their specific SAR Interferometry (InSAR) design, Sentinel-1 satellites can be exploited to build up operational services for the generation of advanced interferometric products that can be very useful within risk management and natural hazard monitoring scenarios. Accordingly, in this work we present the activities carried out for the development, integration, and deployment of the SBAS Sentinel-1 Surveillance service of CNR-IREA within the GEP platform. This service is based on a parallel implementation of the SBAS approach, referred to as P-SBAS, able to effectively run in large distributed computing infrastructures (grid and cloud) and to allow for an efficient computation of large SAR data sequences with advanced DInSAR approaches. In particular, the Surveillance service developed on GEP platform consists on the systematic and automatic processing of Sentinel-1 data on selected Areas of Interest (AoI) to generate updated surface displacement time series via the SBAS-InSAR algorithm. We built up a system that is

The influence of endogenous and exogenous spatial attention on decision confidence

OpenAIRE

Kurtz, Phillipp; Shapcott, Katharine A.; Kaiser , Jochen; Schmiedt, Joscha T.; Schmid, Michael C.

2017-01-01

Spatial attention allows us to make more accurate decisions about events in our environment. Decision confidence is thought to be intimately linked to the decision making process as confidence ratings are tightly coupled to decision accuracy. While both spatial attention and decision confidence have been subjected to extensive research, surprisingly little is known about the interaction between these two processes. Since attention increases performance it might be expected that confidence wou...

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

Science.gov (United States)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

Science.gov (United States)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

Sentinel-1 automatic processing chain for volcanic and seismic areas monitoring within the Geohazards Exploitation Platform (GEP)

Science.gov (United States)

De Luca, Claudio; Zinno, Ivana; Manunta, Michele; Lanari, Riccardo; Casu, Francesco

2016-04-01

The microwave remote sensing scenario is rapidly evolving through development of new sensor technology for Earth Observation (EO). In particular, Sentinel-1A (S1A) is the first of a sensors' constellation designed to provide a satellite data stream for the Copernicus European program. Sentinel-1A has been specifically designed to provide, over land, Differential Interferometric Synthetic Aperture Radar (DInSAR) products to analyze and investigate Earth's surface displacements. S1A peculiarities include wide ground coverage (250 km of swath), C-band operational frequency and short revisit time (that will reduce from 12 to 6 days when the twin system Sentinel-1B will be placed in orbit during 2016). Such characteristics, together with the global coverage acquisition policy, make the Sentinel-1 constellation to be extremely suitable for volcanic and seismic areas studying and monitoring worldwide, thus allowing the generation of both ground displacement information with increasing rapidity and new geological understanding. The main acquisition mode over land is the so called Interferometric Wide Swath (IWS) that is based on the Terrain Observation by Progressive Scans (TOPS) technique and that guarantees the mentioned S1A large coverage characteristics at expense of a not trivial interferometric processing. Moreover, the satellite spatial coverage and the reduced revisit time will lead to an exponential increase of the data archives that, after the launch of Sentine-1B, will reach about 3TB per day. Therefore, the EO scientific community needs from the one hand automated and effective DInSAR tools able to address the S1A processing complexity, and from the other hand the computing and storage capacities to face out the expected large amount of data. Then, it is becoming more crucial to move processors and tools close to the satellite archives, being not efficient anymore the approach of downloading and processing data with in-house computing facilities. To address

Development of SOVAT: a numerical-spatial decision support system for community health assessment research.

Science.gov (United States)

Scotch, Matthew; Parmanto, Bambang

2006-01-01

The development of numerical-spatial routines is frequently required to solve complex community health problems. Community health assessment (CHA) professionals who use information technology need a complete system that is capable of supporting the development of numerical-spatial routines. Currently, there is no decision support system (DSS) that is effectively able to accomplish this task as the majority of public health geospatial information systems (GIS) are based on traditional (relational) database architecture. On-Line Analytical Processing (OLAP) is a multidimensional data warehouse technique that is commonly used as a decision support system in standard industry. OLAP alone is not sufficient for solving numerical-spatial problems that frequently occur in CHA research. Coupling it with GIS technology offers the potential for a very powerful and useful system. A community health OLAP cube was created by integrating health and population data from various sources. OLAP and GIS technologies were then combined to develop the Spatial OLAP Visualization and Analysis Tool (SOVAT). The synergy of numerical and spatial environments within SOVAT is shown through an elaborate and easy-to-use drag and drop and direct manipulation graphical user interface (GUI). Community health problem-solving examples (routines) using SOVAT are shown through a series of screen shots. The impact of the difference between SOVAT and existing GIS public health applications can be seen by considering the numerical-spatial problem-solving examples. These examples are facilitated using OLAP-GIS functions. These functions can be mimicked in existing GIS public applications, but their performance and system response would be significantly worse since GIS is based on traditional (relational) backend. OLAP-GIS system offer great potential for powerful numerical-spatial decision support in community health analysis. The functionality of an OLAP-GIS system has been shown through a series of

Integrated Dialogue System for Spatial Decision Process

International Nuclear Information System (INIS)

Nishiyama, Yumi; Fukui, Hiromichi; Kaneyasu, Iwao; Nagasaka, Toshinari; Usuda, Yuichiro; Sakamoto, Ai; Kusafuka, Minako

2003-01-01

The disposal of high-level radioactive waste (HLW) is a difficult challenge for all countries that uses nuclear energy. In Japan, an implementing agency for HLW was authorized in 2001, and now seeking for municipalities that voluntarily apply to be a preliminary investigation area for a final disposal site. Along with these policy progresses, the HLW disposal program has been gaining social attentions. This leads to high demand for a systematic process for evaluating the proposed policy and environmental impact of geological disposal so that policy decisions can adequately address technical, ethical, and social considerations. As a step toward this objective, we have developed a participatory decision support system on the web. Web-based communication is in its infancy but may be viable support tool to engage different people. Through the study, we aimed to examine the possibility of web-based dialogue system for spatial decision process. One conclusion from the web-based dialogue is that it is possible to create a working environment on the web within those who have different backgrounds and interests. From the results, we found many findings that should be taken into account for further development. One is the need to re-construct the data, model imagery and opinions to judge the problem objectively. We will reexamine the contents based on the international activities so that participants can understand what the information means in the context. Facilitation is key element on the web, also. He or she is expected to make the atmosphere where even those who don't have high-level knowledge can participate in and arouse their opinion from the faceless communication. In the point, the auto navigation comes in very useful

GEP-based method to formulate adhesion strength and hardness of Nb PVD coated on Ti-6Al-7Nb aimed at developing mixed oxide nanotubular arrays.

Science.gov (United States)

Rafieerad, A R; Bushroa, A R; Nasiri-Tabrizi, B; Fallahpour, A; Vadivelu, J; Musa, S N; Kaboli, S H A

2016-08-01

PVD process as a thin film coating method is highly applicable for both metallic and ceramic materials, which is faced with the necessity of choosing the correct parameters to achieve optimal results. In the present study, a GEP-based model for the first time was proposed as a safe and accurate method to predict the adhesion strength and hardness of the Nb PVD coated aimed at growing the mixed oxide nanotubular arrays on Ti67. Here, the training and testing analysis were executed for both adhesion strength and hardness. The optimum parameter combination for the scratch adhesion strength and micro hardness was determined by the maximum mean S/N ratio, which was 350W, 20 sccm, and a DC bias of 90V. Results showed that the values calculated in the training and testing in GEP model were very close to the actual experiments designed by Taguchi. The as-sputtered Nb coating with highest adhesion strength and microhardness was electrochemically anodized at 20V for 4h. From the FESEM images and EDS results of the annealed sample, a thick layer of bone-like apatite was formed on the sample surface after soaking in SBF for 10 days, which can be connected to the development of a highly ordered nanotube arrays. This novel approach provides an outline for the future design of nanostructured coatings for a wide range of applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

Afforest sDSS: a metamodel based spatial decision support system for afforestation of agricultural land

NARCIS (Netherlands)

Gilliams, S.; Orshoven, van J.; Muys, B.; Kros, J.; Heil, G.W.; Deursen, van W.

2005-01-01

The concept and structure of the Spatial Decision Support System AFFOREST sDSS dealing with environmental performance (EP) of afforestation on agricultural land in northwestern Europe, is presented. EP is defined in terms of three environmental impact categories: (1) carbon sequestration (2)

Communicating uncertainty in spatial decision support systems - a case study of bioenergy-crop potentials in Mozambique.

NARCIS (Netherlands)

Verstegen, J.A.; van der Hilst, F.|info:eu-repo/dai/nl/314099905; Karssenberg, D.J.|info:eu-repo/dai/nl/241557119; Faaij, A.

2011-01-01

Spatial Decision Support Systems (SDSSs) are interactive, computer-based systems designed to support policy making. Important components of SDSSs are models that can be used to assess the impact of possible decisions. These models usually simulate complex spatio-temporal phenomena, with input

The Influence of Endogenous and Exogenous Spatial Attention on Decision Confidence.

Science.gov (United States)

Kurtz, Phillipp; Shapcott, Katharine A; Kaiser, Jochen; Schmiedt, Joscha T; Schmid, Michael C

2017-07-25

Spatial attention allows us to make more accurate decisions about events in our environment. Decision confidence is thought to be intimately linked to the decision making process as confidence ratings are tightly coupled to decision accuracy. While both spatial attention and decision confidence have been subjected to extensive research, surprisingly little is known about the interaction between these two processes. Since attention increases performance it might be expected that confidence would also increase. However, two studies investigating the effects of endogenous attention on decision confidence found contradictory results. Here we investigated the effects of two distinct forms of spatial attention on decision confidence; endogenous attention and exogenous attention. We used an orientation-matching task, comparing the two attention conditions (endogenous and exogenous) to a control condition without directed attention. Participants performed better under both attention conditions than in the control condition. Higher confidence ratings than the control condition were found under endogenous attention but not under exogenous attention. This finding suggests that while attention can increase confidence ratings, it must be voluntarily deployed for this increase to take place. We discuss possible implications of this relative overconfidence found only during endogenous attention with respect to the theoretical background of decision confidence.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

Science.gov (United States)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in

The Role of Low-Spatial Frequencies in Lexical Decision and Masked Priming

Science.gov (United States)

Boden, C.; Giaschi, D.

2009-01-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch…

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

Science.gov (United States)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Prospective study of the impact of the Prosigna assay on adjuvant clinical decision-making in unselected patients with estrogen receptor positive, human epidermal growth factor receptor negative, node negative early-stage breast cancer.

Science.gov (United States)

Martín, Miguel; González-Rivera, Milagros; Morales, Serafín; de la Haba-Rodriguez, Juan; González-Cortijo, Lucía; Manso, Luis; Albanell, Joan; González-Martín, Antonio; González, Sónia; Arcusa, Angels; de la Cruz-Merino, Luis; Rojo, Federico; Vidal, María; Galván, Patricia; Aguirre, Elena; Morales, Cristina; Ferree, Sean; Pompilio, Kristen; Casas, Maribel; Caballero, Rosalía; Goicoechea, Uxue; Carrasco, Eva; Michalopoulos, Steven; Hornberger, John; Prat, Aleix

2015-06-01

Improved understanding of risk of recurrence (ROR) is needed to reduce cases of recurrence and more effectively treat breast cancer patients. The purpose of this study was to examine how a gene-expression profile (GEP), identified by Prosigna, influences physician adjuvant treatment selection for early breast cancer (EBC) and the effects of this influence on optimizing adjuvant treatment recommendations in clinical practice. A prospective, observational, multicenter study was carried out in 15 hospitals across Spain. Participating medical oncologists completed pre-assessment, post-assessment, and follow-up questionnaires recording their treatment recommendations and confidence in these recommendations, before and after knowing the patient's ROR. Patients completed questionnaires on decision-making, anxiety, and health status. Between June 2013 and January 2014, 217 patients enrolled and a final 200 were included in the study. Patients were postmenopausal, estrogen receptor positive, human epidermal growth hormone factor negative, and node negative with either stage 1 or stage 2 tumors. After receiving the GEP results, treatment recommendations were changed for 40 patients (20%). The confidence of medical oncologists in their treatment recommendations increased in 41.6% and decreased in 6.5% of total cases. Patients reported lower anxiety after physicians made treatment recommendations based on the GEP results (p anxiety about the selected adjuvant therapy decreased with use of the GEP.

Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.

Science.gov (United States)

Bui, Thanh Quang; Pham, Hai Minh

2016-01-01

There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.

Implication of the first decision on visual information-sampling in the spatial frequency domain in pulmonary nodule recognition

Science.gov (United States)

Pietrzyk, Mariusz W.; Manning, David; Donovan, Tim; Dix, Alan

2010-02-01

Aim: To investigate the impact on visual sampling strategy and pulmonary nodule recognition of image-based properties of background locations in dwelled regions where the first overt decision was made. . Background: Recent studies in mammography show that the first overt decision (TP or FP) has an influence on further image reading including the correctness of the following decisions. Furthermore, the correlation between the spatial frequency properties of the local background following decision sites and the first decision correctness has been reported. Methods: Subjects with different radiological experience were eye tracked during detection of pulmonary nodules from PA chest radiographs. Number of outcomes and the overall quality of performance are analysed in terms of the cases where correct or incorrect decisions were made. JAFROC methodology is applied. The spatial frequency properties of selected local backgrounds related to a certain decisions were studied. ANOVA was used to compare the logarithmic values of energy carried by non redundant stationary wavelet packet coefficients. Results: A strong correlation has been found between the number of TP as a first decision and the JAFROC score (r = 0.74). The number of FP as a first decision was found negatively correlated with JAFROC (r = -0.75). Moreover, the differential spatial frequency profiles outcomes depend on the first choice correctness.

A Web-based spatial decision supporting system for land management and soil conservation

Science.gov (United States)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-07-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) as well as many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a spatial decision support system based on geospatial cyberinfrastructure (GCI) can address all of the above, so producing a smart system for supporting decision making for agriculture, forestry, and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on land management and soil conservation. The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry, and urban planning issues through the Web. The system has been applied to and tested in an area of about 20 000 ha in the south of Italy, within the framework of a European LIFE+ project (SOILCONSWEB). The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart Web-based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (www.landconsultingweb.eu). This may help bridge the last very important divide between scientists working on the landscape and end users.

A web based spatial decision supporting system for land management and soil conservation

Science.gov (United States)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-02-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) but also many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a Spatial Decision Support System based on geospatial cyber-infrastructure (GCI) can embody all of the above, so producing a smart system for supporting decision making for agriculture, forestry and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on soil and land conservation (SOILCONSWEB-LIFE+ project). The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry and urban planning issues through the web. The system has been applied to and tested in an area of about 20 000 ha in the South of Italy, within the framework of a European LIFE+ project. The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart web based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (http://www.landconsultingweb.eu). This may help bridge the last much important divide between scientists working on the landscape and end users.

SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

Science.gov (United States)

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

The Effects of Spatial and Temporal Decisions on Orange Marketing in Babol County

Directory of Open Access Journals (Sweden)

H. Najafi Alamdarlo

2016-10-01

in adjacent villages, since it has the lowest income for farmers per unit of sales. Conclusion: In wholesale, decision of the previous year is more effective than the spatial lag. Hence, in this type of selling, past tendencies which have been accumulated in the grower`s mind, are more important than others’ decisions to sell their product. Therefore, changing this type of marketing is more difficult than the two other methods. In broker methods, gardener always disobeys his last year decisions and tries to sell his product in a different way. In this method, he is also affected by decisions made by others. In general, this method is less desirable for orchardist and usually will be selected as the last option. In retail method, neighbors’ decisions have had more impact on the choice of marketing system rather than the farmers’ past decisions. In the retail channel, the neighbors’ decisions have the most influence on the gardeners’ decisions. According to the highest orchardist configuration has occurred in retail marketing, creating a successful marketing model based on this method can effectively contribute to the changing in the marketing of this product and can lead to reduce the marketing margin.

Hysteresis as an Implicit Prior in Tactile Spatial Decision Making

Science.gov (United States)

Thiel, Sabrina D.; Bitzer, Sebastian; Nierhaus, Till; Kalberlah, Christian; Preusser, Sven; Neumann, Jane; Nikulin, Vadim V.; van der Meer, Elke; Villringer, Arno; Pleger, Burkhard

2014-01-01

Perceptual decisions not only depend on the incoming information from sensory systems but constitute a combination of current sensory evidence and internally accumulated information from past encounters. Although recent evidence emphasizes the fundamental role of prior knowledge for perceptual decision making, only few studies have quantified the relevance of such priors on perceptual decisions and examined their interplay with other decision-relevant factors, such as the stimulus properties. In the present study we asked whether hysteresis, describing the stability of a percept despite a change in stimulus property and known to occur at perceptual thresholds, also acts as a form of an implicit prior in tactile spatial decision making, supporting the stability of a decision across successively presented random stimuli (i.e., decision hysteresis). We applied a variant of the classical 2-point discrimination task and found that hysteresis influenced perceptual decision making: Participants were more likely to decide ‘same’ rather than ‘different’ on successively presented pin distances. In a direct comparison between the influence of applied pin distances (explicit stimulus property) and hysteresis, we found that on average, stimulus property explained significantly more variance of participants’ decisions than hysteresis. However, when focusing on pin distances at threshold, we found a trend for hysteresis to explain more variance. Furthermore, the less variance was explained by the pin distance on a given decision, the more variance was explained by hysteresis, and vice versa. Our findings suggest that hysteresis acts as an implicit prior in tactile spatial decision making that becomes increasingly important when explicit stimulus properties provide decreasing evidence. PMID:24587045

Perspectives on Spatial Decision Support Concerning Location of Biogas Production

DEFF Research Database (Denmark)

Bojesen, Mikkel

in biogas production. This ambition requires that more than 20 new large scale centralised biogas plants are built. The location of these plants is associated with a number of externalities and uncertainties and the existing biogas sector struggles to establish itself as a viable energy producing sector....... Meanwhile planners and decision makers struggle to find sustainable locations that comprehensively balance the multiple concerns the location of biogas facilities includes. This PhD project examines how spatial decision support models can be used to ensure sustainable locations of future biogas plants......, understand the industrial economic aspects of such a role. Through the use of spatial multi-criteria evaluation models stakeholder preferences to decision criteria are included in a sustainable biogas facility location analysis. By the use of these models it is demonstrated how overall biogas production...

Spatial Decision Assistance of Watershed Sedimentation (SDAS: Development and Application

Directory of Open Access Journals (Sweden)

Poerbandono

2014-04-01

Full Text Available This paper discusses the development and application of a spatial tool for erosion modeling named Spatial Decision Assistance of Watershed Sedimentation (SDAS. SDAS computes export (yield of sediment from watershed as product of erosion rate and sediment delivery ratio (SDR. The erosion rate is calculated for each raster grid according to a digital elevation model, soil, rain fall depth, and land cover data using the Universal Soil Loss Equation. SDR calculation is carried out for each spatial unit. A spatial unit is the smallest sub-watershed considered in the model and generated according to the TauDEM algorithm. The size of one spatial unit is assigned by the user as the minimum number of raster grids. SDR is inversely proportional to sediment resident time and controlled by rainfall, slope, soil, and land cover. Application of SDAS is demonstrated in this paper by simulating the spatial distribution of the annual sediment yield across the Citarum watershed in the northwest of Java, Indonesia. SDAS calibration was carried out based on sediment discharge observations from the upper catchment. We considered factors for hillslope flow depth and for actual and effective rainfall duration to fit the computed sediment yield to the observed sediment discharge. The computed sediment yield agreed with the observation data with a 7% mean relative accuracy.

Reserch on Urban Spatial Expansion Model Based on Multi-Object Gray Decision-Making and Ca: a Case Study of Pidu District, Chengdu City

Science.gov (United States)

Liu, Z.; Li, Y.

2018-04-01

This paper from the perspective of the Neighbor cellular space, Proposed a new urban space expansion model based on a new multi-objective gray decision and CA. The model solved the traditional cellular automata conversion rules is difficult to meet the needs of the inner space-time analysis of urban changes and to overcome the problem of uncertainty in the combination of urban drivers and urban cellular automata. At the same time, the study takes Pidu District as a research area and carries out urban spatial simulation prediction and analysis, and draws the following conclusions: (1) The design idea of the urban spatial expansion model proposed in this paper is that the urban driving factor and the neighborhood function are tightly coupled by the multi-objective grey decision method based on geographical conditions. The simulation results show that the simulation error of urban spatial expansion is less than 5.27 %. The Kappa coefficient is 0.84. It shows that the model can better capture the inner transformation mechanism of the city. (2) We made a simulation prediction for Pidu District of Chengdu by discussing Pidu District of Chengdu as a system instance.In this way, we analyzed the urban growth tendency of this area.presenting a contiguous increasing mode, which is called "urban intensive development". This expansion mode accorded with sustainable development theory and the ecological urbanization design theory.

Generation of Digital Surface Models from satellite photogrammetry: the DSM-OPT service of the ESA Geohazards Exploitation Platform (GEP)

Science.gov (United States)

Stumpf, André; Michéa, David; Malet, Jean-Philippe

2017-04-01

The continuously increasing fleet of agile stereo-capable very-high resolution (VHR) optical satellites has facilitated the acquisition of multi-view images of the earth surface. Theoretical revisit times have been reduced to less than one day and the highest spatial resolution which is commercially available amounts now to 30 cm/pixel. Digital Surface Models (DSM) and point clouds computed from such satellite stereo-acquisitions can provide valuable input for studies in geomorphology, tectonics, glaciology, hydrology and urban remote sensing The photogrammetric processing, however, still requires significant expertise, computational resources and costly commercial software. To enable a large Earth Science community (researcher and end-users) to process easily and rapidly VHR multi-view images, the work targets the implementation of a fully automatic satellite-photogrammetry pipeline (i.e DSM-OPT) on the ESA Geohazards Exploitation Platform (GEP). The implemented pipeline is based on the open-source photogrammetry library MicMac [1] and is designed for distributed processing on a cloud-based infrastructure. The service can be employed in pre-defined processing modes (i.e. urban, plain, hilly, and mountainous environments) or in an advanced processing mode (i.e. in which expert-users have the possibility to adapt the processing parameters to their specific applications). Four representative use cases are presented to illustrate the accuracy of the resulting surface models and ortho-images as well as the overall processing time. These use cases consisted of the construction of surface models from series of Pléiades images for four applications: urban analysis (Strasbourg, France), landslide detection in mountainous environments (South French Alps), co-seismic deformation in mountain environments (Central Italy earthquake sequence of 2016) and fault recognition for paleo-tectonic analysis (North-East India). Comparisons of the satellite-derived topography to airborne

A web-based spatial decision supporting system (S-DSS) for grapevine quality: the viticultural tool of the SOILCONS-WEB Project

Science.gov (United States)

Manna, Piero; Bonfante, Antonello; Basile, Angelo; Langella, Giuliano; Agrillo, Antonietta; De Mascellis, Roberto; Florindo Mileti, Antonio; Minieri, Luciana; Orefice, Nadia; Terribile, Fabio

2014-05-01

The SOILCONSWEB Project aims to create a decision support system operating at the landscape scale (Spatial-DSS) for the protection and the management of soils in both agricultural and environmental issues; it is a cyber-infrastructure built on remote servers operating through the web at www.landconsultingweb.eu. It includes - among others - a series of tools specifically designed to a Viticulture aiming at high quality wines production. The system is realized thanks to a collaboration between the University of Naples Federico II, CNR ISAFoM, Ariespace srl and SeSIRCA-Campania Region within a 5-years LIFE+ project funded by European Community. The system includes tools based on modelling procedures at different level of complexity some of which specifically designed for viticulture issues. One of the implemented models arise from the original desktop based SWAP model (Kroes et al, 2008). It can be run "on the fly" through a very user friendly web-interface. The specific tool, thanks to the model based on the Richard's equation can produce data on vineyard water stress, simulating the soil water balances of the different soil types within an area of interest. Thanks to a specific program developed within the project activities, the Spatial-DSS every day acquires punctual weather data and automatically spatialize them with geostatistical approaches in order to use the data as input for the SPA (Soil Plant Atmosphere ) model running. In particular for defining the upper boundary condition (rainfall and temperatures to estimate ET0 by the Hargraves model). Soil hydraulic properties (47 soil profiles within the study area), also essential for modelling simulation, were measured in laboratory using the Wind's approach or estimated through HYPRES PTF. Water retention and hydraulic conductivity relationships were parameterized according to the van Genuchten-Mualem model; Decision makers (individuals, groups of interests and public bodies) through the DSS can have real

Spatial forecast of landslides in three gorges based on spatial data mining.

Science.gov (United States)

Wang, Xianmin; Niu, Ruiqing

2009-01-01

The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc). China-Brazil Earth Resources Satellite (Cbers) images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County) in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods.

SADA: Ecological Risk Based Decision Support System for Selective Remediation

Science.gov (United States)

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Science.gov (United States)

Erin J. Belval; Yu Wei; Michael. Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

Science.gov (United States)

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial

[Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

Science.gov (United States)

Wu, Dehua

2016-01-01

The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

Spatial Decision Support Systems

Directory of Open Access Journals (Sweden)

Silviu Ioan Bejinariu

2015-10-01

Full Text Available The satellite image processing is an important tool for decision making in domains like agriculture, forestry, hydrology, for normal activity tracking but also in special situations caused by natural disasters. In this paper it is proposed a method for forestry surface evaluation in terms of occupied surface and also as number of trees. The segmentation method is based on watershed transform which offers good performances in case the objects to detect have connected borders. The method is applied for automatic multi-temporal analysis of forestry areas and represents a useful instrument for decision makers.

Research on the decision-making model of land-use spatial optimization

Science.gov (United States)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

Environmental condition assessment of US military installations using GIS based spatial multi-criteria decision analysis.

Science.gov (United States)

Singer, Steve; Wang, Guangxing; Howard, Heidi; Anderson, Alan

2012-08-01

Environment functions in various aspects including soil and water conservation, biodiversity and habitats, and landscape aesthetics. Comprehensive assessment of environmental condition is thus a great challenge. The issues include how to assess individual environmental components such as landscape aesthetics and integrate them into an indicator that can comprehensively quantify environmental condition. In this study, a geographic information systems based spatial multi-criteria decision analysis was used to integrate environmental variables and create the indicator. This approach was applied to Fort Riley Military installation in which land condition and its dynamics due to military training activities were assessed. The indicator was derived by integrating soil erosion, water quality, landscape fragmentation, landscape aesthetics, and noise based on the weights from the experts by assessing and ranking the environmental variables in terms of their importance. The results showed that landscape level indicator well quantified the overall environmental condition and its dynamics, while the indicator at level of patch that is defined as a homogeneous area that is different from its surroundings detailed the spatiotemporal variability of environmental condition. The environmental condition was mostly determined by soil erosion, then landscape fragmentation, water quality, landscape aesthetics, and noise. Overall, environmental condition at both landscape and patch levels greatly varied depending on the degree of ground and canopy disturbance and their spatial patterns due to military training activities and being related to slope. It was also determined the environment itself could be recovered quickly once military training was halt or reduced. Thus, this study provided an effective tool for the army land managers to monitor environmental dynamics and plan military training activities. Its limitation lies at that the obtained values of the indicator vary and are

Developing and Testing an Online Tool for Teaching GIS Concepts Applied to Spatial Decision-Making

Science.gov (United States)

Carver, Steve; Evans, Andy; Kingston, Richard

2004-01-01

The development and testing of a Web-based GIS e-learning resource is described. This focuses on the application of GIS for siting a nuclear waste disposal facility and the associated principles of spatial decision-making using Boolean and weighted overlay methods. Initial student experiences in using the system are analysed as part of a research…

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

Science.gov (United States)

2011-01-01

Background Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Methods Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. Results The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. Conclusions In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain.

Science.gov (United States)

Dominkovics, Pau; Granell, Carlos; Pérez-Navarro, Antoni; Casals, Martí; Orcau, Angels; Caylà, Joan A

2011-11-29

Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web

Feasibility and utility of re-treatment with 177Lu-DOTATATE in GEP-NENs relapsed after treatment with 90Y-DOTATOC

International Nuclear Information System (INIS)

Severi, Stefano; Sansovini, Maddalena; Ianniello, Annarita; Nicolini, Silvia; Caroli, Paola; Paganelli, Giovanni; Bodei, Lisa; Ibrahim, Toni; Di Iorio, Valentina; D'Errico, Vincenzo; Monti, Manuela

2015-01-01

Peptide receptor radionuclide therapy (PRRT) is a valid therapy for grade 1/2 gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs). Although a median progression-free survival (PFS) of more than 20 months is frequently observed, the majority of patients relapse after 2 - 3 years. In the present study, we investigated the use of low dosage re-treatment with 177 Lu-DOTATATE (Lu-PRRT) in patients with GEP-NENs who relapsed after treatment with 90 Y-DOTATOC (Y-PRRT). Upon tumour progression, 26 patients with a PFS of at least 12 months after Y-PRRT were consecutively enrolled in a phase II study of re-treatment with Lu-PRRT. All patients had preserved kidney and haematological parameters and received 14.8 - 18.5 GBq of Lu-PRRT in four or five cycles. The disease control rate (DCR), toxicity, PFS and prognostic factors were evaluated. Median total activity of Lu-PRRT was 16.5 GBq in five cycles. The DCR was 84.6 %, median PFS was 22 months (95 % CI 16 months - not reached) compared to 28 months (95 % CI 20 - 36 months) after Y-PRRT. Tumour burden and number of liver metastases were important prognostic factors. Toxicity was mild after Lu-PRRT re-treatment in the majority of patients, with only two patients with grade 2 and one with grade 3 bone marrow toxicity; one patient had grade 2 and one grade 3 renal toxicity. Patients with GEP-NEN who have previously responded to Y-PRRT are suitable candidates for Lu-PRRT re-treatment on progression. Although our sample size was limited, low-dosage Lu-PRRT was safe, and led to DCR and PFS rates comparable with those observed when Y-PRRT was used as primary treatment. (orig.)

Spatial Forecast of Landslides in Three Gorges Based On Spatial Data Mining

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Xianmin Wang

2009-03-01

Full Text Available The Three Gorges is a region with a very high landslide distribution density and a concentrated population. In Three Gorges there are often landslide disasters, and the potential risk of landslides is tremendous. In this paper, focusing on Three Gorges, which has a complicated landform, spatial forecasting of landslides is studied by establishing 20 forecast factors (spectra, texture, vegetation coverage, water level of reservoir, slope structure, engineering rock group, elevation, slope, aspect, etc. China-Brazil Earth Resources Satellite (Cbers images were adopted based on C4.5 decision tree to mine spatial forecast landslide criteria in Guojiaba Town (Zhigui County in Three Gorges and based on this knowledge, perform intelligent spatial landslide forecasts for Guojiaba Town. All landslides lie in the dangerous and unstable regions, so the forecast result is good. The method proposed in the paper is compared with seven other methods: IsoData, K-Means, Mahalanobis Distance, Maximum Likelihood, Minimum Distance, Parallelepiped and Information Content Model. The experimental results show that the method proposed in this paper has a high forecast precision, noticeably higher than that of the other seven methods.

RiskChanges Spatial Decision Support system for the analysis of changing multi-hazard risk

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van Westen, Cees; Zhang, Kaixi; Bakker, Wim; Andrejchenko, Vera; Berlin, Julian; Olyazadeh, Roya; Cristal, Irina

2015-04-01

Within the framework of the EU FP7 Marie Curie Project CHANGES and the EU FP7 Copernicus project INCREO a spatial decision support system was developed with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. Central to the SDSS are the stakeholders. The envisaged users of the system are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. The SDSS should be able to function in different countries with different legal frameworks and with organizations with different mandates. These could be subdivided into Civil protection organization with the mandate to design disaster response plans, Expert organizations with the mandate to design structural risk reduction measures (e.g. dams, dikes, check-dams etc), and planning organizations with the mandate to make land development plans. The SDSS can be used in different ways: analyzing the current level of risk, analyzing the best alternatives for risk reduction, the evaluation of the consequences of possible future scenarios to the risk levels, and the evaluation how different risk reduction alternatives will lead to risk reduction under different future scenarios. The SDSS is developed based on open source software and following open standards, for code as well as for data formats and service interfaces. Code development was based upon open source software as well. The architecture of the system is modular. The various parts of the system are loosely coupled, extensible, using standards for interoperability, flexible and web-based. The Spatial Decision Support System is composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to

Designing a socio-spatial need indicator for urban social services analysis and decision making. A case study

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Antonio Morenos Jiménez

2015-01-01

Full Text Available Decision taking on social services requires, as a previous step, to appraise the human needs and their spatial distribution, a key issue particularly sensitive in less developed zones or during economic crisis periods, as far as socio-spatial cohesion is then strongly challenged. Vari-ous methods have been used for measuring social needs, provided that these are diverse in nature and sometimes elusive. Incorporating the spatial dimension in this task involves an additional challenge, but the results add meaningful value for socio-spatial planning. Along this concern, in this work it is tackled the problema of estimating the needs typically met by local social service centers (SSC. To this end, it is designed a novel statistical indicator for intra-urban zones, incorporating in the formula the main components of the actual observed de-mand as well as the per capita income, to take into account the relevant spatial equity principle. Using a geographical information systems (GIS, the indicator for estimating SSC need has been experimentally obtained for two types of spatial units in the city of Madrid: municipal districts and small statistical areas, looking for complementary applied uses. The results reveal the intra-urban inequalities for these types of needs and may support public decision making on spatial provision and location of this kind of social resources. In addition, a preliminary and statistically based exam of the indicator potentialities and limitations is carried out for both types of spatial units.

Evaluating Michigan's community hospital access: spatial methods for decision support

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Varnakovida Pariwate

2006-09-01

.1%. Conclusion Both modeling approaches enable policymakers to identify under-served areas. Ultimately this paper is concerned with the intersection of spatial analysis and policymaking. Using the best scientific practice to identify locations of under-served populations based on many factors provides policymakers with a powerful tool for making good decisions.

Gaze behaviour during space perception and spatial decision making.

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Wiener, Jan M; Hölscher, Christoph; Büchner, Simon; Konieczny, Lars

2012-11-01

A series of four experiments investigating gaze behavior and decision making in the context of wayfinding is reported. Participants were presented with screenshots of choice points taken in large virtual environments. Each screenshot depicted alternative path options. In Experiment 1, participants had to decide between them to find an object hidden in the environment. In Experiment 2, participants were first informed about which path option to take as if following a guided route. Subsequently, they were presented with the same images in random order and had to indicate which path option they chose during initial exposure. In Experiment 1, we demonstrate (1) that participants have a tendency to choose the path option that featured the longer line of sight, and (2) a robust gaze bias towards the eventually chosen path option. In Experiment 2, systematic differences in gaze behavior towards the alternative path options between encoding and decoding were observed. Based on data from Experiments 1 and 2 and two control experiments ensuring that fixation patterns were specific to the spatial tasks, we develop a tentative model of gaze behavior during wayfinding decision making suggesting that particular attention was paid to image areas depicting changes in the local geometry of the environments such as corners, openings, and occlusions. Together, the results suggest that gaze during a wayfinding tasks is directed toward, and can be predicted by, a subset of environmental features and that gaze bias effects are a general phenomenon of visual decision making.

An Environmental Decision Support System for Spatial Assessment and Selective Remediation

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Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates environmental assessment tools for effective problem-solving. The software integrates modules for GIS, visualization, geospatial analysis, statistical analysis, human health and ecolog...

Intelligent judgements over health risks in a spatial agent-based model.

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Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

Design and implementation of a risk assessment module in a spatial decision support system

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Zhang, Kaixi; van Westen, Cees; Bakker, Wim

2014-05-01

The spatial decision support system named 'Changes SDSS' is currently under development. The goal of this system is to analyze changing hydro-meteorological hazards and the effect of risk reduction alternatives to support decision makers in choosing the best alternatives. The risk assessment module within the system is to assess the current risk, analyze the risk after implementations of risk reduction alternatives, and analyze the risk in different future years when considering scenarios such as climate change, land use change and population growth. The objective of this work is to present the detailed design and implementation plan of the risk assessment module. The main challenges faced consist of how to shift the risk assessment from traditional desktop software to an open source web-based platform, the availability of input data and the inclusion of uncertainties in the risk analysis. The risk assessment module is developed using Ext JS library for the implementation of user interface on the client side, using Python for scripting, as well as PostGIS spatial functions for complex computations on the server side. The comprehensive consideration of the underlying uncertainties in input data can lead to a better quantification of risk assessment and a more reliable Changes SDSS, since the outputs of risk assessment module are the basis for decision making module within the system. The implementation of this module will contribute to the development of open source web-based modules for multi-hazard risk assessment in the future. This work is part of the "CHANGES SDSS" project, funded by the European Community's 7th Framework Program.

Spatial frequency characteristics at image decision-point locations for observers with different radiological backgrounds in lung nodule detection

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Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim

2009-02-01

Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.

Aspects of decision support in water management--example Berlin and Potsdam (Germany) I--spatially differentiated evaluation.

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Simon, Ute; Brüggemann, Rainer; Pudenz, Stefan

2004-04-01

Decisions about sustainable development demand spatially differentiated evaluations. As an example, we demonstrate the evaluation of water management strategies in the cities of Berlin and Potsdam (Germany) with respect to their ecological effects in 14 sections of the surface water system. Two decision support systems were compared, namely PROMETHEE, which is designed to obtain a clear decision (linear ranking), and Hasse Diagram Technique (HDT), normally providing more than one favourable solution (partial order). By PROMETHEE, the spatial differentiation had unwanted effects on the result, negating the stakeholders determined weighting of indicators. Therefore, the stakeholder can barely benefit from the convenience of obtaining a clear decision (linear ranking). In contrast, the result obtained by HDT was not influenced by spatial differentiation. Furthermore, HDT provided helpful tools to analyse the evaluation result, such as the concept of antagonistic indicators to discover conflicts in the evaluation process.

Effects of pulvinar inactivation on spatial decision-making between equal and asymmetric reward options.

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Wilke, Melanie; Kagan, Igor; Andersen, Richard A

2013-08-01

The ability to selectively process visual inputs and to decide between multiple movement options in an adaptive manner is critical for survival. Such decisions are known to be influenced by factors such as reward expectation and visual saliency. The dorsal pulvinar connects to a multitude of cortical areas that are involved in visuospatial memory and integrate information about upcoming eye movements with expected reward values. However, it is unclear whether the dorsal pulvinar is critically involved in spatial memory and reward-based oculomotor decision behavior. To examine this, we reversibly inactivated the dorsal portion of the pulvinar while monkeys performed a delayed memory saccade task that included choices between equally or unequally rewarded options. Pulvinar inactivation resulted in a delay of saccade initiation toward memorized contralesional targets but did not affect spatial memory. Furthermore, pulvinar inactivation caused a pronounced choice bias toward the ipsilesional hemifield when the reward value in the two hemifields was equal. However, this choice bias could be alleviated by placing a high reward target into the contralesional hemifield. The bias was less affected by the manipulation of relative visual saliency between the two competing targets. These results suggest that the dorsal pulvinar is involved in determining the behavioral desirability of movement goals while being less critical for spatial memory and reward processing.

A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making

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Michael F. Goodchild

2013-05-01

Full Text Available Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1 widespread sharing and seamless integration of distributed geospatial data; (2 an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3 the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and (4 capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations.

Feasibility and utility of re-treatment with {sup 177}Lu-DOTATATE in GEP-NENs relapsed after treatment with {sup 90}Y-DOTATOC

Energy Technology Data Exchange (ETDEWEB)

Severi, Stefano; Sansovini, Maddalena; Ianniello, Annarita; Nicolini, Silvia; Caroli, Paola; Paganelli, Giovanni [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Nuclear Medicine Unit, Meldola, FC (Italy); Bodei, Lisa [European Institute of Oncology, Division of Nuclear Medicine, Milan (Italy); Ibrahim, Toni [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Osteoncology and Rare Tumors Center, Meldola (Italy); Di Iorio, Valentina [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Oncology Pharmacy Laboratory, Meldola (Italy); D' Errico, Vincenzo [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Medical Physics Unit, Meldola (Italy); Monti, Manuela [Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Unit of Biostatistics and Clinical Trials, Meldola (Italy)

2015-12-15

Peptide receptor radionuclide therapy (PRRT) is a valid therapy for grade 1/2 gastroenteropancreatic (GEP) neuroendocrine neoplasms (NENs). Although a median progression-free survival (PFS) of more than 20 months is frequently observed, the majority of patients relapse after 2 - 3 years. In the present study, we investigated the use of low dosage re-treatment with {sup 177}Lu-DOTATATE (Lu-PRRT) in patients with GEP-NENs who relapsed after treatment with {sup 90}Y-DOTATOC (Y-PRRT). Upon tumour progression, 26 patients with a PFS of at least 12 months after Y-PRRT were consecutively enrolled in a phase II study of re-treatment with Lu-PRRT. All patients had preserved kidney and haematological parameters and received 14.8 - 18.5 GBq of Lu-PRRT in four or five cycles. The disease control rate (DCR), toxicity, PFS and prognostic factors were evaluated. Median total activity of Lu-PRRT was 16.5 GBq in five cycles. The DCR was 84.6 %, median PFS was 22 months (95 % CI 16 months - not reached) compared to 28 months (95 % CI 20 - 36 months) after Y-PRRT. Tumour burden and number of liver metastases were important prognostic factors. Toxicity was mild after Lu-PRRT re-treatment in the majority of patients, with only two patients with grade 2 and one with grade 3 bone marrow toxicity; one patient had grade 2 and one grade 3 renal toxicity. Patients with GEP-NEN who have previously responded to Y-PRRT are suitable candidates for Lu-PRRT re-treatment on progression. Although our sample size was limited, low-dosage Lu-PRRT was safe, and led to DCR and PFS rates comparable with those observed when Y-PRRT was used as primary treatment. (orig.)

Planning Support Systems (PSS-Based Spatial Plan Alternatives and Environmental Assessment

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Hee-Sun Choi

2016-03-01

Full Text Available Spatial planning is at the core of national land and urban development. Many countries and cities seek sustainable development through various means such as coordinated environmental planning, environmental assessment, and internalization of environmental analysis and planning. A Planning Support System (PSS is a GIS (Geographic Information System-based, spatial decision-making support system that incorporates a variety of theories and pertinent models. This study adopted the “What if?” model to design an alternative spatial plan that includes generation of predictive scenarios and is relatively easy to use. In the cities studied, we identified a total of six scenarios based on the main drivers of development—namely, population and spatial policies. Subsequently, we assessed the alternatives for their environmental impact, preparing sensitivity maps for each major environmental issue in the target area (natural ecosystem, air and microclimate, natural disasters. One projected advantage of the “What if?” model is that its digital visualization of proposed plans may improve public awareness and involvement. Furthermore, the tool is expected to be highly useful in ensuring the objectivity of quantitative analyses. However, it is necessary to develop a PSS that is both standardized and tailored to the particular needs of each area. Finally, the development of an e-governance system will be beneficial in ensuring public access to the decision making process.

A Flood Risk Assessment of Quang Nam, Vietnam Using Spatial Multicriteria Decision Analysis

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Chinh Luu

2018-04-01

Full Text Available Vietnam is highly vulnerable to flood and storm impacts. Holistic flood risk assessment maps that adequately consider flood risk factors of hazard, exposure, and vulnerability are not available. These are vital for flood risk preparedness and disaster mitigation measures at the local scale. Unfortunately, there is a lack of knowledge about spatial multicriteria decision analysis and flood risk analysis more broadly in Vietnam. In response to this need, we identify and quantify flood risk components in Quang Nam province through spatial multicriteria decision analysis. The study presents a new approach to local flood risk assessment mapping, which combines historical flood marks with exposure and vulnerability data. The flood risk map output could assist and empower decision-makers in undertaking flood risk management activities in the province. Our study demonstrates a methodology to build flood risk assessment maps using flood mark, exposure and vulnerability data, which could be applied in other provinces in Vietnam.

Relational Algebra in Spatial Decision Support Systems Ontologies.

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Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

2017-01-01

Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.

An efficient model for auxiliary diagnosis of hepatocellular carcinoma based on gene expression programming.

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Zhang, Li; Chen, Jiasheng; Gao, Chunming; Liu, Chuanmiao; Xu, Kuihua

2018-03-16

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. The early diagnosis of HCC is greatly helpful to achieve long-term disease-free survival. However, HCC is usually difficult to be diagnosed at an early stage. The aim of this study was to create the prediction model to diagnose HCC based on gene expression programming (GEP). GEP is an evolutionary algorithm and a domain-independent problem-solving technique. Clinical data show that six serum biomarkers, including gamma-glutamyl transferase, C-reaction protein, carcinoembryonic antigen, alpha-fetoprotein, carbohydrate antigen 153, and carbohydrate antigen 199, are related to HCC characteristics. In this study, the prediction of HCC was made based on these six biomarkers (195 HCC patients and 215 non-HCC controls) by setting up optimal joint models with GEP. The GEP model discriminated 353 out of 410 subjects, representing a determination coefficient of 86.28% (283/328) and 85.37% (70/82) for training and test sets, respectively. Compared to the results from the support vector machine, the artificial neural network, and the multilayer perceptron, GEP showed a better outcome. The results suggested that GEP modeling was a promising and excellent tool in diagnosis of hepatocellular carcinoma, and it could be widely used in HCC auxiliary diagnosis. Graphical abstract The process to establish an efficient model for auxiliary diagnosis of hepatocellular carcinoma.

Ontology Based Quality Evaluation for Spatial Data

Science.gov (United States)

Yılmaz, C.; Cömert, Ç.

2015-08-01

Many institutions will be providing data to the National Spatial Data Infrastructure (NSDI). Current technical background of the NSDI is based on syntactic web services. It is expected that this will be replaced by semantic web services. The quality of the data provided is important in terms of the decision-making process and the accuracy of transactions. Therefore, the data quality needs to be tested. This topic has been neglected in Turkey. Data quality control for NSDI may be done by private or public "data accreditation" institutions. A methodology is required for data quality evaluation. There are studies for data quality including ISO standards, academic studies and software to evaluate spatial data quality. ISO 19157 standard defines the data quality elements. Proprietary software such as, 1Spatial's 1Validate and ESRI's Data Reviewer offers quality evaluation based on their own classification of rules. Commonly, rule based approaches are used for geospatial data quality check. In this study, we look for the technical components to devise and implement a rule based approach with ontologies using free and open source software in semantic web context. Semantic web uses ontologies to deliver well-defined web resources and make them accessible to end-users and processes. We have created an ontology conforming to the geospatial data and defined some sample rules to show how to test data with respect to data quality elements including; attribute, topo-semantic and geometrical consistency using free and open source software. To test data against rules, sample GeoSPARQL queries are created, associated with specifications.

An Isometric Mapping Based Co-Location Decision Tree Algorithm

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Zhou, G.; Wei, J.; Zhou, X.; Zhang, R.; Huang, W.; Sha, H.; Chen, J.

2018-05-01

Decision tree (DT) induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information) as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT) method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT), which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1) The extraction method of exposed carbonate rocks is of high accuracy. (2) The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

AN ISOMETRIC MAPPING BASED CO-LOCATION DECISION TREE ALGORITHM

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G. Zhou

2018-05-01

Full Text Available Decision tree (DT induction has been widely used in different pattern classification. However, most traditional DTs have the disadvantage that they consider only non-spatial attributes (ie, spectral information as a result of classifying pixels, which can result in objects being misclassified. Therefore, some researchers have proposed a co-location decision tree (Cl-DT method, which combines co-location and decision tree to solve the above the above-mentioned traditional decision tree problems. Cl-DT overcomes the shortcomings of the existing DT algorithms, which create a node for each value of a given attribute, which has a higher accuracy than the existing decision tree approach. However, for non-linearly distributed data instances, the euclidean distance between instances does not reflect the true positional relationship between them. In order to overcome these shortcomings, this paper proposes an isometric mapping method based on Cl-DT (called, (Isomap-based Cl-DT, which is a method that combines heterogeneous and Cl-DT together. Because isometric mapping methods use geodetic distances instead of Euclidean distances between non-linearly distributed instances, the true distance between instances can be reflected. The experimental results and several comparative analyzes show that: (1 The extraction method of exposed carbonate rocks is of high accuracy. (2 The proposed method has many advantages, because the total number of nodes, the number of leaf nodes and the number of nodes are greatly reduced compared to Cl-DT. Therefore, the Isomap -based Cl-DT algorithm can construct a more accurate and faster decision tree.

Theoretical Approaches in the Context of Spatial Planning Decisions and the Relation with Urban Sustainability

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Kumlu, Kadriye Burcu Yavuz; Tüdeş, Şule

2017-10-01

The sustainability agenda has maintained its importance since the days, when the production system took its capitalist form, as well as the population in the urban areas started to rise. Increasing number of both goods and the people have caused the degradation of the certain systems, which generate the urban areas. These systems could mainly be classified as social, environmental, physical and economical systems. Today, urban areas still have difficulty to protect those systems, due to the significant demand of the population. Therefore, studies related with the sustainable issues are significant in the sense of continuity of the urban systems. Therefore, in this paper, those studies in the context of the effects of physical decisions taken in the spatial planning process on urban sustainability, will be examined. The components of the physical decisions are limited to land use, density and design. Land use decisions will be examined in the context of mixed land use. On the other hand, decisions related with density will be analyzed in the sense of population density and floor area ratio (FAR). Besides, design decisions will be examined, by linking them with neighborhood design criteria. Additionally, the term of urban sustainability will only be limited to its social and environmental contexts in this study. Briefly stated, studies in the sustainable literature concerned with the effects of land use, density and design decisions taken in the spatial planning process on the social and environmental sustainability will be examined in this paper. After the compilation and the analyze of those studies, a theoretical approach will be proposed to determine social and environmental sustainability in the context of land use, density and design decisions, taken in the spatial planning process.

Rule-based decision making model

International Nuclear Information System (INIS)

Sirola, Miki

1998-01-01

A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

A Web-based graphical user interface for evidence-based decision making for health care allocations in rural areas

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Schuurman, Nadine; Leight, Margo; Berube, Myriam

2008-01-01

Background The creation of successful health policy and location of resources increasingly relies on evidence-based decision-making. The development of intuitive, accessible tools to analyse, display and disseminate spatial data potentially provides the basis for sound policy and resource allocation decisions. As health services are rationalized, the development of tools such graphical user interfaces (GUIs) is especially valuable at they assist decision makers in allocating resources such that the maximum number of people are served. GIS can used to develop GUIs that enable spatial decision making. Results We have created a Web-based GUI (wGUI) to assist health policy makers and administrators in the Canadian province of British Columbia make well-informed decisions about the location and allocation of time-sensitive service capacities in rural regions of the province. This tool integrates datasets for existing hospitals and services, regional populations and road networks to allow users to ascertain the percentage of population in any given service catchment who are served by a specific health service, or baskets of linked services. The wGUI allows policy makers to map trauma and obstetric services against rural populations within pre-specified travel distances, illustrating service capacity by region. Conclusion The wGUI can be used by health policy makers and administrators with little or no formal GIS training to visualize multiple health resource allocation scenarios. The GUI is poised to become a critical decision-making tool especially as evidence is increasingly required for distribution of health services. PMID:18793428

Diverting the tourists: a spatial decision-support system for tourism planning on a developing island

Science.gov (United States)

Beedasy, Jaishree; Whyatt, Duncan

Mauritius is a small island (1865 km 2) in the Indian Ocean. Tourism is the third largest economic sector of the country, after manufacturing and agriculture. A limitation of space and the island's vulnerable ecosystem warrants a rational approach to tourism development. The main problems so far have been to manipulate and integrate all the factors affecting tourism planning and to match spatial data with their relevant attributes. A Spatial Decision Support System (SDSS) for sustainable tourism planning is therefore proposed. The proposed SDSS design would include a GIS as its core component. A first GIS model has already been constructed with available data. Supporting decision-making in a spatial context is implicit in the use of GIS. However the analytical capability of the GIS has to be enhanced to solve semi-structured problems, where subjective judgements come into play. The second part of the paper deals with the choice, implementation and customisation of a relevant model to develop a specialised SDSS. Different types of models and techniques are discussed, in particular a comparison of compensatory and non-compensatory approaches to multicriteria evaluation (MCE). It is concluded that compensatory multicriteria evaluation techniques increase the scope of the present GIS model as a decision-support tool. This approach gives the user or decision-maker the flexibility to change the importance of each criterion depending on relevant objectives.

Spatial UTA (S-UTA) - a new approach for raster-based GIS multicriteria suitability analysis and its use in implementing natural systems for wastewater treatment.

Science.gov (United States)

Demesouka, O E; Vavatsikos, A P; Anagnostopoulos, K P

2013-08-15

The identification of sites for locating new natural systems for wastewater treatment (NSWT), such as stabilization ponds and constructed wetlands, should combine multiple crucial factors (environmental, design, social and economic), and thus the implementation of multicriteria decision-making (MCDM) methods is required. In addition, the spatial nature of the site selection process necessitates the use of geographic information systems (GISs) because they are unanimously recognized as the most appropriate tool capable of supporting sophisticated spatial decision making. The resulting multicriteria spatial decision support systems (MC-SDSSs) provide a consistent framework for dealing with conflicting objectives while integrating the decision makers' (DMs') preferences in spatially related patterns/problems. A map-based, interactive UTAII implementation is presented, which provides a link between a well-understood decision support method and exploratory geographic visualization. Spatial UTA (S-UTA) is applied in a real case study concerning the ranking of candidate sites for implementing natural systems for wastewater treatment in the Evros-Rodopi prefectures of northeastern Greece. Finally, the obtained results are compared with those derived using other MCDM approaches to evaluate the performance of S-UTA in GIS-based land use suitability analyses. Copyright © 2013 Elsevier Ltd. All rights reserved.

A ROUGH SET DECISION TREE BASED MLP-CNN FOR VERY HIGH RESOLUTION REMOTELY SENSED IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

C. Zhang

2017-09-01

Full Text Available Recent advances in remote sensing have witnessed a great amount of very high resolution (VHR images acquired at sub-metre spatial resolution. These VHR remotely sensed data has post enormous challenges in processing, analysing and classifying them effectively due to the high spatial complexity and heterogeneity. Although many computer-aid classification methods that based on machine learning approaches have been developed over the past decades, most of them are developed toward pixel level spectral differentiation, e.g. Multi-Layer Perceptron (MLP, which are unable to exploit abundant spatial details within VHR images. This paper introduced a rough set model as a general framework to objectively characterize the uncertainty in CNN classification results, and further partition them into correctness and incorrectness on the map. The correct classification regions of CNN were trusted and maintained, whereas the misclassification areas were reclassified using a decision tree with both CNN and MLP. The effectiveness of the proposed rough set decision tree based MLP-CNN was tested using an urban area at Bournemouth, United Kingdom. The MLP-CNN, well capturing the complementarity between CNN and MLP through the rough set based decision tree, achieved the best classification performance both visually and numerically. Therefore, this research paves the way to achieve fully automatic and effective VHR image classification.

Computational modelling and analysis of hippocampal-prefrontal information coding during a spatial decision-making task

Directory of Open Access Journals (Sweden)

Thomas eJahans-Price

2014-03-01

Full Text Available We introduce a computational model describing rat behaviour and the interactions of neural populations processing spatial and mnemonic information during a maze-based, decision-making task. The model integrates sensory input and implements a working memory to inform decisions at a choice point, reproducing rat behavioural data and predicting the occurrence of turn- and memory-dependent activity in neuronal networks supporting task performance. We tested these model predictions using a new software toolbox (Maze Query Language, MQL to analyse activity of medial prefrontal cortical (mPFC and dorsal hippocampal (dCA1 neurons recorded from 6 adult rats during task performance. The firing rates of dCA1 neurons discriminated context (i.e. the direction of the previous turn, whilst a subset of mPFC neurons was selective for current turn direction or context, with some conjunctively encoding both. mPFC turn-selective neurons displayed a ramping of activity on approach to the decision turn and turn-selectivity in mPFC was significantly reduced during error trials. These analyses complement data from neurophysiological recordings in non-human primates indicating that firing rates of cortical neurons correlate with integration of sensory evidence used to inform decision-making.

Thematic and spatial resolutions affect model-based predictions of tree species distribution.

Science.gov (United States)

Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei

2013-01-01

Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.

Spatial decision support for strategic environmental assessment of land use plans. A case study in southern Italy

International Nuclear Information System (INIS)

Geneletti, Davide; Bagli, Stefano; Napolitano, Paola; Pistocchi, Alberto

2007-01-01

This paper presents and discusses the construction of a spatial decision-support tool for the Strategic Environmental Assessment (SEA) of a land use plan: the spatial coordination plan of the Province of Naples, in southern Italy. The decision-support tool organises the relevant information, spatially resolves the actions of the plan, predicts their environmental impacts, and generates overall performance maps. Its final goal is to provide a suitable technical support to a formal SEA procedure. The expected implications of the plan, such as changes in land use and traffic flows and urban expansion, were modelled and assessed against a set of environmental criteria using SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis and mapping. It was found that the SWOT analysis provided a good basis for assessment and strategy formulation. The paper also intends to contribute to the topic of data and scale issues in SEA, by exemplifying the role played by spatial data and spatial analyses to support informative SEA

Design and implementation of visualization methods for the CHANGES Spatial Decision Support System

Science.gov (United States)

Cristal, Irina; van Westen, Cees; Bakker, Wim; Greiving, Stefan

2014-05-01

The CHANGES Spatial Decision Support System (SDSS) is a web-based system aimed for risk assessment and the evaluation of optimal risk reduction alternatives at local level as a decision support tool in long-term natural risk management. The SDSS use multidimensional information, integrating thematic, spatial, temporal and documentary data. The role of visualization in this context becomes of vital importance for efficiently representing each dimension. This multidimensional aspect of the required for the system risk information, combined with the diversity of the end-users imposes the use of sophisticated visualization methods and tools. The key goal of the present work is to exploit efficiently the large amount of data in relation to the needs of the end-user, utilizing proper visualization techniques. Three main tasks have been accomplished for this purpose: categorization of the end-users, the definition of system's modules and the data definition. The graphical representation of the data and the visualization tools were designed to be relevant to the data type and the purpose of the analysis. Depending on the end-users category, each user should have access to different modules of the system and thus, to the proper visualization environment. The technologies used for the development of the visualization component combine the latest and most innovative open source JavaScript frameworks, such as OpenLayers 2.13.1, ExtJS 4 and GeoExt 2. Moreover, the model-view-controller (MVC) pattern is used in order to ensure flexibility of the system at the implementation level. Using the above technologies, the visualization techniques implemented so far offer interactive map navigation, querying and comparison tools. The map comparison tools are of great importance within the SDSS and include the following: swiping tool for comparison of different data of the same location; raster subtraction for comparison of the same phenomena varying in time; linked views for comparison

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

Science.gov (United States)

Mochizuki, Kei

2015-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. PMID:26490287

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis☆

Science.gov (United States)

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-01-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster–Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty–sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights. PMID:25843987

A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis.

Science.gov (United States)

Feizizadeh, Bakhtiar; Jankowski, Piotr; Blaschke, Thomas

2014-03-01

GIS multicriteria decision analysis (MCDA) techniques are increasingly used in landslide susceptibility mapping for the prediction of future hazards, land use planning, as well as for hazard preparedness. However, the uncertainties associated with MCDA techniques are inevitable and model outcomes are open to multiple types of uncertainty. In this paper, we present a systematic approach to uncertainty and sensitivity analysis. We access the uncertainty of landslide susceptibility maps produced with GIS-MCDA techniques. A new spatially-explicit approach and Dempster-Shafer Theory (DST) are employed to assess the uncertainties associated with two MCDA techniques, namely Analytical Hierarchical Process (AHP) and Ordered Weighted Averaging (OWA) implemented in GIS. The methodology is composed of three different phases. First, weights are computed to express the relative importance of factors (criteria) for landslide susceptibility. Next, the uncertainty and sensitivity of landslide susceptibility is analyzed as a function of weights using Monte Carlo Simulation and Global Sensitivity Analysis. Finally, the results are validated using a landslide inventory database and by applying DST. The comparisons of the obtained landslide susceptibility maps of both MCDA techniques with known landslides show that the AHP outperforms OWA. However, the OWA-generated landslide susceptibility map shows lower uncertainty than the AHP-generated map. The results demonstrate that further improvement in the accuracy of GIS-based MCDA can be achieved by employing an integrated uncertainty-sensitivity analysis approach, in which the uncertainty of landslide susceptibility model is decomposed and attributed to model's criteria weights.

Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

Science.gov (United States)

Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

2006-01-01

There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

Geo-Spatial Tactical Decision Aid Systems: Fuzzy Logic for Supporting Decision Making

National Research Council Canada - National Science Library

Grasso, Raffaele; Giannecchini, Simone

2006-01-01

.... This paper describes a tactical decision aid system based on fuzzy logic reasoning for data fusion and on current Open Geospatial Consortium specifications for interoperability, data dissemination...

Development of a Spatial Decision Support System for Analyzing Changes in Hydro-meteorological Risk

Science.gov (United States)

van Westen, Cees

2013-04-01

In the framework of the EU FP7 Marie Curie ITN Network "CHANGES: Changing Hydro-meteorological Risks, as Analyzed by a New Generation of European Scientists (http://www.changes-itn.eu)", a spatial decision support system is under development with the aim to analyze the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The SDSS is one of the main outputs of the CHANGES network, which will develop an advanced understanding of how global changes, related to environmental and climate change as well as socio-economical change, may affect the temporal and spatial patterns of hydro-meteorological hazards and associated risks in Europe; how these changes can be assessed, modeled, and incorporated in sustainable risk management strategies, focusing on spatial planning, emergency preparedness and risk communication. The CHANGES network consists of 11 full partners and 6 associate partners of which 5 private companies, representing 10 European countries. The CHANGES network has hired 12 Early Stage Researchers (ESRs) and is currently hiring 3-6 researchers more for the implementation of the SDSS. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task.

Science.gov (United States)

Mochizuki, Kei; Funahashi, Shintaro

2016-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. Copyright © 2016 the American Physiological Society.

H.264 SVC Complexity Reduction Based on Likelihood Mode Decision.

Science.gov (United States)

Balaji, L; Thyagharajan, K K

2015-01-01

H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.

Applications of decision theory to test-based decision making

NARCIS (Netherlands)

van der Linden, Willem J.

1987-01-01

The use of Bayesian decision theory to solve problems in test-based decision making is discussed. Four basic decision problems are distinguished: (1) selection; (2) mastery; (3) placement; and (4) classification, the situation where each treatment has its own criterion. Each type of decision can be

CHANGES SDSS: the development of a Spatial Decision Support System for analysing changing hydro-meteorological risk

Science.gov (United States)

van Westen, Cees; Bakker, Wim; Zhang, Kaixi; Jäger, Stefan; Assmann, Andre; Kass, Steve; Andrejchenko, Vera; Olyazadeh, Roya; Berlin, Julian; Cristal, Irina

2014-05-01

Within the framework of the EU FP7 Marie Curie Project CHANGES (www.changes-itn.eu) and the EU FP7 Copernicus project INCREO (http://www.increo-fp7.eu) a spatial decision support system is under development with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk

Real-time spatial optimization : based on the application in wood supply chain management

International Nuclear Information System (INIS)

Scholz, J.

2010-01-01

Real-time spatial optimization - a combination of Geographical Information Science and Technology and Operations Research - is capable of generating optimized solutions to given spatial problems in real-time. The basic concepts to develop a real-time spatial optimization system are outlined in this thesis. Geographic Information Science delivers the foundations for acquiring, storing, manipulating, visualizing and analyzing spatial information. In order to develop a system that consists of several independent components the concept of Service Oriented Architectures is applied. This facilitates communication between software systems utilizing standardized services that ensure interoperability. Thus, standards in the field of Geographic Information are inevitable for real-time spatial optimization. By exploiting the ability of mobile devices to determine the own position paired with standardized services Location Based Services are created. They are of interest in order to gather real-time data from mobile devices that are of importance for the optimization process itself. To optimize a given spatial problem, the universe of discourse has to be modeled accordingly. For the problem addressed in this thesis - Wood Supply Chain management - Graph theory is used. In addition, the problem of Wood Supply Chain management can be represented by a specific mathematical problem class, the Vehicle Routing problem - specifically the Vehicle Routing Problem with Pickup and Delivery and Time Windows. To optimize this problem class, exact and approximate solution techniques exist. Exact algorithms provide optimal solutions and guarantee their optimally, whereas approximate techniques - approximation algorithms or heuristics - do not guarantee that a global optimum is found. Nevertheless, the are capable of handling large problem instances in reasonable time. For optimizing the Wood Supply Chain Adaptive Large Neighborhood Search is selected as appropriate optimization technique

A SPATIAL DECISION SUPPORT SYSTEM FOR ECOTOURISM DEVELOPMENT IN CASPIAN HYRCANIAN MIXED FORESTS ECOREGION

Directory of Open Access Journals (Sweden)

ALI BALI

Full Text Available Ecotourism, as a form of sustainable nature-based tourism, promotes conservation of ecological and scenic values. In this study, a Spatial Decision Support System, SDSS, was developed based upon Multi Criteria Evaluation, MCE, for ecotourism development in the Caspian Hyrcanian Mixed Forests ecoregion, northern Iran. For this, important criteria and constraints for ecotourism development were shortlisted using the Delphi Method. The criteria were weighted using Analytical Hierarchy Process, AHP. The obtained results indicated that "distance from water resources", "land use", "slope", "soil", "climate", "distance from roads", "land cover density", "erosion", and "distance from residential areas" were the most important criteria, respectively. The findings suggest that GIS-based SDSS is suitable to engage the various criteria affecting the development of ecotourism destinations. This empirical research develops a new method that can significantly facilitate planning forecotourism development with respect to ecological capability of ecotourism destinations.

Hyperspectral Remote Sensing of Terrestrial Ecosystem Productivity from ISS

Science.gov (United States)

Huemmrich, K. F.; Campbell, P. K. E.; Gao, B. C.; Flanagan, L. B.; Goulden, M.

2017-12-01

Data from the Hyperspectral Imager for Coastal Ocean (HICO), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. The ISS orbit introduces both limitations and opportunities for observing ecosystem dynamics. Twenty six HICO images were used from four study sites representing different vegetation types: grasslands, shrubland, and forest. Gross ecosystem production (GEP) data from eddy covariance were matched with HICO-derived spectra. Multiple algorithms were successful relating spectral reflectance with GEP, including: Spectral Vegetation Indices (SVI), SVI in a light use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to Multiband Hyperspectral Indices (MHI) from stepwise regressions and Partial Least Squares Regression (PLSR). Algorithms were able to achieve r2 better than 0.7 for both GEP at the overpass time and daily GEP. These algorithms were successful using a diverse set of observations combining data from multiple years, multiple times during growing season, different times of day, with different view angles, and different vegetation types. The demonstrated robustness of the algorithms presented in this study over these conditions provides some confidence in mapping spatial patterns of GEP, describing variability within fields as well as the regional patterns based only on spectral reflectance information. The ISS orbit provides periods with multiple observations collected at different times of the day within a period of a few days. Diurnal GEP patterns were estimated comparing the half-hourly average GEP from the flux tower against HICO estimates of GEP (r2=0.87) if morning, midday, and afternoon observations were available for average fluxes in the time period.

Location of Road Emergency Stations in Fars Province, Using Spatial Multi-Criteria Decision Making.

Science.gov (United States)

Goli, Ali; Ansarizade, Najmeh; Barati, Omid; Kavosi, Zahra

2015-01-01

To locate the road emergency stations in Fars province based on using spatial multi-criteria decision making (Delphi method). In this study, the criteria affecting the location of road emergency stations have been identified through Delphi method and their importance was determined using Analytical Hierarchical Process (AHP). With regard to the importance of the criteria and by using Geographical Information System (GIS), the appropriateness of the existing stations with the criteria and the way of their distribution has been explored, and the appropriate arenas for creating new emergency stations were determined. In order to investigate the spatial distribution pattern of the stations, Moran's Index was used. The accidents (0.318), placement position (0.235), time (0.198), roads (0.160), and population (0.079) were introduced as the main criteria in location road emergency stations. The findings showed that the distribution of the existing stations was clustering (Moran's I=0.3). Three priorities were introduced for establishing new stations. Some arenas including Abade, north of Eghlid and Khoram bid, and small parts of Shiraz, Farashband, Bavanat, and Kazeroon were suggested as the first priority. GIS is a useful and applicable tool in investigating spatial distribution and geographical accessibility to the setting that provide health care, including emergency stations.

Fuel Maps for the GEP 6.5LT Engine When Operating on at J/JP-8 Fuel Blends at Ambient and Elevated Temperatures

Science.gov (United States)

2015-04-01

system. The new calibrated fuel injection pump and injectors were installed, and the fuel injection timing of the new fuel injection system was set to...Product 6.5L Turbocharged diesel engine at two inlet temperature conditions. The GEP 6.5LT engine represents legacy diesel engine design with...derived cetane number DF-2 Diesel Fuel number 2 ft Foot HEFA Hydro-treated Esters and Fatty Acid(s) HP or hp Horsepower hr Hour in Inch in³ cubic

Dephasing rates for weak localization and universal conductance fluctuations in two dimensional Si:P and Ge:P δ-layers.

Science.gov (United States)

Shamim, Saquib; Mahapatra, S; Scappucci, G; Klesse, W M; Simmons, M Y; Ghosh, Arindam

2017-05-04

We report quantum transport measurements on two dimensional (2D) Si:P and Ge:P δ-layers and compare the inelastic scattering rates relevant for weak localization (WL) and universal conductance fluctuations (UCF) for devices of various doping densities (0.3-2.5 × 10 18 m -2 ) at low temperatures (0.3-4.2 K). The phase breaking rate extracted experimentally from measurements of WL correction to conductivity and UCF agree well with each other within the entire temperature range. This establishes that WL and UCF, being the outcome of quantum interference phenomena, are governed by the same dephasing rate.

H.264 SVC Complexity Reduction Based on Likelihood Mode Decision

Directory of Open Access Journals (Sweden)

L. Balaji

2015-01-01

Full Text Available H.264 Advanced Video Coding (AVC was prolonged to Scalable Video Coding (SVC. SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.

The added value of stochastic spatial disaggregation for short-term rainfall forecasts currently available in Canada

Science.gov (United States)

Gagnon, Patrick; Rousseau, Alain N.; Charron, Dominique; Fortin, Vincent; Audet, René

2017-11-01

Several businesses and industries rely on rainfall forecasts to support their day-to-day operations. To deal with the uncertainty associated with rainfall forecast, some meteorological organisations have developed products, such as ensemble forecasts. However, due to the intensive computational requirements of ensemble forecasts, the spatial resolution remains coarse. For example, Environment and Climate Change Canada's (ECCC) Global Ensemble Prediction System (GEPS) data is freely available on a 1-degree grid (about 100 km), while those of the so-called High Resolution Deterministic Prediction System (HRDPS) are available on a 2.5-km grid (about 40 times finer). Potential users are then left with the option of using either a high-resolution rainfall forecast without uncertainty estimation and/or an ensemble with a spectrum of plausible rainfall values, but at a coarser spatial scale. The objective of this study was to evaluate the added value of coupling the Gibbs Sampling Disaggregation Model (GSDM) with ECCC products to provide accurate, precise and consistent rainfall estimates at a fine spatial resolution (10-km) within a forecast framework (6-h). For 30, 6-h, rainfall events occurring within a 40,000-km2 area (Québec, Canada), results show that, using 100-km aggregated reference rainfall depths as input, statistics of the rainfall fields generated by GSDM were close to those of the 10-km reference field. However, in forecast mode, GSDM outcomes inherit of the ECCC forecast biases, resulting in a poor performance when GEPS data were used as input, mainly due to the inherent rainfall depth distribution of the latter product. Better performance was achieved when the Regional Deterministic Prediction System (RDPS), available on a 10-km grid and aggregated at 100-km, was used as input to GSDM. Nevertheless, most of the analyzed ensemble forecasts were weakly consistent. Some areas of improvement are identified herein.

Uncertainty in spatial planning proceedings

Directory of Open Access Journals (Sweden)

Aleš Mlakar

2009-01-01

Full Text Available Uncertainty is distinctive of spatial planning as it arises from the necessity to co-ordinate the various interests within the area, from the urgency of adopting spatial planning decisions, the complexity of the environment, physical space and society, addressing the uncertainty of the future and from the uncertainty of actually making the right decision. Response to uncertainty is a series of measures that mitigate the effects of uncertainty itself. These measures are based on two fundamental principles – standardization and optimization. The measures are related to knowledge enhancement and spatial planning comprehension, in the legal regulation of changes, in the existence of spatial planning as a means of different interests co-ordination, in the active planning and the constructive resolution of current spatial problems, in the integration of spatial planning and the environmental protection process, in the implementation of the analysis as the foundation of spatial planners activities, in the methods of thinking outside the parameters, in forming clear spatial concepts and in creating a transparent management spatial system and also in the enforcement the participatory processes.

Artificial intelligence based decision support for trumpeter swan management

Science.gov (United States)

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988

GIS and remote sensing components of a spatial decision system in support of sustainable forest management

Energy Technology Data Exchange (ETDEWEB)

St-Onge, B.A.; Waaub, J.P.; Alleaume, S.; Couture, M. [Quebec Univ., Dept. of Geography, Montreal, PQ (Canada)

1999-05-01

The development of a tool used in decision making processes in forest management was discussed with special focus on two critical aspects of the decision aid system which pertain to spatial information. These are: (1) the use of up-to-date precise information, and (2) the accessibility of this information. This paper focuses on two approaches designed to provide accessible high quality information to the users of the decision aid system: i.e. the development of high resolution remote sensing methods, and a GIS data warehouse accessible over the Internet. 4 refs., 2 figs.

Regulating outdoor advertisement boards; employing spatial decision support system to control urban visual pollution

Science.gov (United States)

Wakil, K.; Hussnain, MQ; Tahir, A.; Naeem, M. A.

2016-06-01

Unmanaged placement, size, location, structure and contents of outdoor advertisement boards have resulted in severe urban visual pollution and deterioration of the socio-physical living environment in urban centres of Pakistan. As per the regulatory instruments, the approval decision for a new advertisement installation is supposed to be based on the locational density of existing boards and their proximity or remoteness to certain land- uses. In cities, where regulatory tools for the control of advertisement boards exist, responsible authorities are handicapped in effective implementation due to the absence of geospatial analysis capacity. This study presents the development of a spatial decision support system (SDSS) for regularization of advertisement boards in terms of their location and placement. The knowledge module of the proposed SDSS is based on provisions and restrictions prescribed in regulatory documents. While the user interface allows visualization and scenario evaluation to understand if the new board will affect existing linear density on a particular road and if it violates any buffer restrictions around a particular land use. Technically the structure of the proposed SDSS is a web-based solution which includes open geospatial tools such as OpenGeo Suite, GeoExt, PostgreSQL, and PHP. It uses three key data sets including road network, locations of existing billboards and building parcels with land use information to perform the analysis. Locational suitability has been calculated using pairwise comparison through analytical hierarchy process (AHP) and weighted linear combination (WLC). Our results indicate that open geospatial tools can be helpful in developing an SDSS which can assist solving space related iterative decision challenges on outdoor advertisements. Employing such a system will result in effective implementation of regulations resulting in visual harmony and aesthetic improvement in urban communities.

Multicriteria Spatial Decision Support Systems for Future Urban Energy Retrofitting Scenarios

Directory of Open Access Journals (Sweden)

Patrizia Lombardi

2017-07-01

Full Text Available Nowadays, there is an increasing concern about sustainable urban energy development taking into account national priorities of each city. Many cities have started to define future strategies and plans to reduce energy consumption and greenhouse gas emissions. Urban energy scenarios involve the consideration of a wide range of conflicting criteria, both socio-economic and environmental ones. Moreover, decision-makers (DMs require proper tools that can support their choices in a context of multiple stakeholders and a long-term perspective. In this context, Multicriteria Spatial Decision Support Systems (MC-SDSS are often used in order to define and analyze urban scenarios since they support the comparison of different solutions, based on a combination of multiple factors. The main problem, in relation to urban energy retrofitting scenarios, is the lack of appropriate knowledge and evaluation criteria. The latter are crucial for delivering and assessing urban energy scenarios through a MC-SDSS tool. The main goal of this paper is to analyze and test two different methods for the definition and ranking of the evaluation criteria. More specifically, the paper presents an on-going research study related to the development of a MC-SDSS tool able to identify and evaluate alternative energy urban scenarios in a long-term period perspective. This study refers to two Smart City and Communities research projects, namely: DIMMER (District Information Modeling and Management for Energy Reduction and EEB (Zero Energy Buildings in Smart Urban Districts.

Temperature based daily incoming solar radiation modeling based on gene expression programming, neuro-fuzzy and neural network computing techniques.

Science.gov (United States)

Landeras, G.; López, J. J.; Kisi, O.; Shiri, J.

2012-04-01

The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using Gene Expression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

Decision Making on Allocating Urban Green Spaces Based upon Spatially-Varying Relationships between Urban Green Spaces and Urban Compaction Degree

Directory of Open Access Journals (Sweden)

Hsueh-Sheng Chang

2015-09-01

Full Text Available The compact city is becoming a prevailing paradigm in the world to control urban sprawl and achieve a pattern of sustainable urban development. However, discussions of the area's overcrowded neighborhoods, its health problems, and the destruction of its green areas have inspired self-examination with respect to the compact city paradigm. High population density attracts even more residents and frequently renders the existing urban green space (UGS insufficient for use as part of a living environment. Due to the unique benefits that these qualities confer, UGS allocation is now considered a significant contributing factor to urban livability. In addition, the UGS allocation may be different due to the presence of many spatial non-stationarity processes. Therefore, this study employs geographically-weighted regression (GWR to explore the unique and spatially-explicit relationships between the degree of urban compaction and UGS within the Taipei metropolitan area. Maps summarizing the GWR results demonstrate that there is significantly insufficient UGS allocation in the central area, which consists mainly of Taipei City. Townships with higher parameters contain UGS levels that better meet the needs of their residents. Overall, the exploration of conceptualizing spatial heterogeneity of relationships between the degree of urban compaction and UGS can provide insightful analyses for decision-making on allocating UGS.

Recommendations for the management of old uranium mining sites in France. From Limousin sites to other sites, from short- to medium- and long-terms. Final report of the pluralist expertise group on Limousin uranium mines (GEP). Synthesis and final report

International Nuclear Information System (INIS)

2010-01-01

The final report of the Pluralistic Experts Group for the Uranium mines of Limousin (GEP) brings together the main conclusions and recommendations arising from three and half years of work having mobilized, at the request and with the financial support of French authorities, more than forty experts from a varying range of disciplines and backgrounds. The mission given to GEP by the Ministers of Ecology, Industry and Health, as well as the President of the Nuclear safety Authority, was ambitious. It was not simply a matter of conducting an exhaustive and vigorous investigation of actual impacts, but also to analyse the present situation from a technical point of view starting with actual cases to clarify the options for management and monitoring, and to make recommendations on their development in order to reduce the current impacts and to foresee those in the long term according to the preparation of a long term plan. This final report attempts to develop a coherent framework of recommendations that are as operationally feasible as possible. Thus, the proposals of the GEP underline the need for an comprehensive approach, on the basis of work on the institutional perspectives, of a programme for improvement of knowledge and including a reinforcement of information and dialogue, to frame and guide the characterization of the risks and impacts, the evolution of the surveillance devices and the consolidation of the existing protection systems. These final proposals take account of a whole range of activities undertaken by Areva NC as well as the relevant local and national government organizations; and which integrate certain recommendations already produced by the GEP within the framework of its three interim reports. The GEP sets out six main areas of improvements, within which the GEP makes 15 major recommendations addressed to the public authorities, the owner and all of the stakeholders concerned. These recommendations, largely detailed in the report, aim to: - 1

Spatial Multi-Criteria Decision Support System and Strategic Environmental Assessment: A Case Study

Directory of Open Access Journals (Sweden)

Francesca Torrieri

2017-10-01

Full Text Available This contribution focuses on the Strategic Environmental Assessment (SEA as an important tool to ensure sustainable development and reach a high level of environmental protection. More specifically, this paper provides an evaluation method based on the integration of Geographic Information System (GIS and Multi-criteria Analysis—named Integrated Spatial Multi-criteria Decision Support System (ISMDSS—to support the preparation of environmental assessment reports and the construction of scenarios for the adoption of urban plans, as an innovative tool that integrates objectives and multidimensional (economic, environmental, and social components, as well as different approaches and models for the construction of a long-term shared vision. In particular, considerations are made by presenting a thought-provoking case study on the SEA of the urban plan of the municipality of Marzano di Nola, located in the province of Avellino in the Campania region. The experiment carried out showed the potentiality of the ISMDSS to evaluate the impacts of different scenarios with the aim of developing a sustainable urban municipal plan. The spatial dimension is useful in understanding the dynamics that characterize each environmental topic in a specific area, by considering not only the components of the natural and developed environment, but also the interactions with social and economic components.

Spatial planning of wind turbines

Energy Technology Data Exchange (ETDEWEB)

NONE

2004-01-01

This paper proposes guidelines for spatial planning for wind power, based on experience with spatial planning in Belgium, Denmark, France and the Netherlands. In addition experiences from Germany and Ireland have been used. This guidelines quotes all decisive criteria for successful implementation of wind energy: landscape integration, stakeholders involvement, noise and distance from buildings. (author)

Integrated environmental decision support tool based on GIS technology

International Nuclear Information System (INIS)

Doctor, P.G.; O'Neil, T.K.; Sackschewsky, M.R.; Becker, J.M.; Rykiel, E.J.; Walters, T.B.; Brandt, C.A.; Hall, J.A.

1995-01-01

Environmental restoration and management decisions facing the US Department of Energy require balancing trade-offs between diverse land uses and impacts over multiple spatial and temporal scales. Many types of environmental data have been collected for the Hanford Site and the Columbia River in Washington State over the past fifty years. Pacific Northwest National Laboratory (PNNL) is integrating these data into a Geographic Information System (GIS) based computer decision support tool. This tool provides a comprehensive and concise description of the current environmental landscape that can be used to evaluate the ecological and monetary trade-offs between future land use, restoration and remediation options before action is taken. Ecological impacts evaluated include effects to individual species of concern and habitat loss and fragmentation. Monetary impacts include those associated with habitat mitigation. The tool is organized as both a browsing tool for educational purposes, and as a framework that leads a project manager through the steps needed to be in compliance with environmental requirements

Texas Urban Triangle : pilot study to implement a spatial decision support system (SDSS) for sustainable mobility.

Science.gov (United States)

2011-03-01

This project addressed sustainable transportation in the Texas Urban Triangle (TUT) by conducting a pilot : project at the county scale. The project tested and developed the multi-attribute Spatial Decision Support : System (SDSS) developed in 2009 u...

Direct observation of a non-isothermal crystallization process in precursor Li10GeP2S12 glass electrolyte

Science.gov (United States)

Tsukasaki, Hirofumi; Mori, Shigeo; Shiotani, Shinya; Yamamura, Hideyuki; Iba, Hideki

2017-11-01

Crystallization of a precursor Li10GeP2S12 (LGPS) glass electrolyte by heat treatment significantly improves its ionic conductivity. The LGPS crystalline phase obtained by heat treatment above 450 °C shows an ionic conductivity on the order of 10-2 S/cm. To clarify the correlation between the crystallization behavior of precursor LGPS glasses and ionic conductivity, we developed an observation technique to visualize precipitated nanocrystallites and a new method to evaluate the crystallization degree via transmission electron microscopy (TEM). In-situ TEM observation revealed that LGPS nanocrystallites precipitated above 450 °C and their size remained fundamentally intact during heating. That is, the crystallization behavior could be characterized by only the formation of LGPS nanocrystallites in an amorphous matrix. In addition, the crystallization degree was quantitatively evaluated from electron diffraction patterns. The crystallization degree remarkably increased at around 450 °C and reached more than 60% above 450 °C. Based on these results, a high ionic conductivity of approximately 1.0 × 10-2 S/cm was confirmed to be directly associated with the appearance of the LGPS crystalline phase.

Advances in the application of decision theory to test-based decision making

NARCIS (Netherlands)

van der Linden, Willem J.

This paper reviews recent research in the Netherlands on the application of decision theory to test-based decision making about personnel selection and student placement. The review is based on an earlier model proposed for the classification of decision problems, and emphasizes an empirical

Knowledge-based decision tree approach for mapping spatial distribution of rice crop using C-band synthetic aperture radar-derived information

Science.gov (United States)

Mishra, Varun Narayan; Prasad, Rajendra; Kumar, Pradeep; Srivastava, Prashant K.; Rai, Praveen Kumar

2017-10-01

Updated and accurate information of rice-growing areas is vital for food security and investigating the environmental impact of rice ecosystems. The intent of this work is to explore the feasibility of dual-polarimetric C-band Radar Imaging Satellite-1 (RISAT-1) data in delineating rice crop fields from other land cover features. A two polarization combination of RISAT-1 backscatter, namely ratio (HH/HV) and difference (HH-HV), significantly enhanced the backscatter difference between rice and nonrice categories. With these inputs, a QUEST decision tree (DT) classifier is successfully employed to extract the spatial distribution of rice crop areas. The results showed the optimal polarization combination to be HH along with HH/HV and HH-HV for rice crop mapping with an accuracy of 88.57%. Results were further compared with a Landsat-8 operational land imager (OLI) optical sensor-derived rice crop map. Spatial agreement of almost 90% was achieved between outputs produced from Landsat-8 OLI and RISAT-1 data. The simplicity of the approach used in this work may serve as an effective tool for rice crop mapping.

Improving rural electricity system planning: An agent-based model for stakeholder engagement and decision making

International Nuclear Information System (INIS)

Alfaro, Jose F.; Miller, Shelie; Johnson, Jeremiah X.; Riolo, Rick R.

2017-01-01

Energy planners in regions with low rates of electrification face complex and high-risk challenges in selecting appropriate generating technologies and grid centralization. To better inform such processes, we present an Agent-Based Model (ABM) that facilitates engagement with stakeholders. This approach evaluates long-term plans using the cost of delivered electricity, resource mix, jobs and economic stimulus created within communities, and decentralized generation mix of the system, with results provided in a spatially-resolved format. This approach complements existing electricity planning methods (e.g., Integrated Resource Planning) by offering novel evaluation criteria based on typical stakeholder preferences. We demonstrate the utility of this approach with a case study based on a “blank-slate” scenario, which begins without generation or transmission infrastructure, for the long-term rural renewable energy plans of Liberia, West Africa. We consider five electrification strategies: prioritizing larger populations, deploying large resources, creating jobs, providing economic stimulus, and step-wise cost minimization. Through the case study we demonstrate how this approach can be used to engage stakeholders, supplement more established energy planning tools, and illustrate the effects of stakeholder decisions and preferences on the performance of the system. - Highlights: • An Agent Based Model, BABSTER, for electrification planning is presented. • BABSTER provides a highly engaging spatially resolved interface. • Allows flexible investigation of decision strategies with real-world incentives. • We show that decision strategies directly impact centralization and resource choice. • It is illustrated through the case study of Liberia, West Africa.

Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model

Science.gov (United States)

Summers, Lucia

2015-01-01

Research demonstrates that crime is spatially concentrated. However, most research relies on information about where crimes occur, without reference to where offenders reside. This study examines how the characteristics of neighborhoods and their proximity to offender home locations affect offender spatial decision making. Using a discrete choice model and data for detected incidents of theft from vehicles (TFV), we test predictions from two theoretical perspectives—crime pattern and social disorganization theories. We demonstrate that offenders favor areas that are low in social cohesion and closer to their home, or other age-related activity nodes. For adult offenders, choices also appear to be influenced by how accessible a neighborhood is via the street network. The implications for criminological theory and crime prevention are discussed. PMID:25866412

Testing Ecological Theories of Offender Spatial Decision Making Using a Discrete Choice Model.

Science.gov (United States)

Johnson, Shane D; Summers, Lucia

2015-04-01

Research demonstrates that crime is spatially concentrated. However, most research relies on information about where crimes occur, without reference to where offenders reside. This study examines how the characteristics of neighborhoods and their proximity to offender home locations affect offender spatial decision making. Using a discrete choice model and data for detected incidents of theft from vehicles (TFV) , we test predictions from two theoretical perspectives-crime pattern and social disorganization theories. We demonstrate that offenders favor areas that are low in social cohesion and closer to their home, or other age-related activity nodes. For adult offenders, choices also appear to be influenced by how accessible a neighborhood is via the street network. The implications for criminological theory and crime prevention are discussed.

Staged decision making based on probabilistic forecasting

Science.gov (United States)

Booister, Nikéh; Verkade, Jan; Werner, Micha; Cranston, Michael; Cumiskey, Lydia; Zevenbergen, Chris

2016-04-01

Flood forecasting systems reduce, but cannot eliminate uncertainty about the future. Probabilistic forecasts explicitly show that uncertainty remains. However, as - compared to deterministic forecasts - a dimension is added ('probability' or 'likelihood'), with this added dimension decision making is made slightly more complicated. A technique of decision support is the cost-loss approach, which defines whether or not to issue a warning or implement mitigation measures (risk-based method). With the cost-loss method a warning will be issued when the ratio of the response costs to the damage reduction is less than or equal to the probability of the possible flood event. This cost-loss method is not widely used, because it motivates based on only economic values and is a technique that is relatively static (no reasoning, yes/no decision). Nevertheless it has high potential to improve risk-based decision making based on probabilistic flood forecasting because there are no other methods known that deal with probabilities in decision making. The main aim of this research was to explore the ways of making decision making based on probabilities with the cost-loss method better applicable in practice. The exploration began by identifying other situations in which decisions were taken based on uncertain forecasts or predictions. These cases spanned a range of degrees of uncertainty: from known uncertainty to deep uncertainty. Based on the types of uncertainties, concepts of dealing with situations and responses were analysed and possible applicable concepts where chosen. Out of this analysis the concepts of flexibility and robustness appeared to be fitting to the existing method. Instead of taking big decisions with bigger consequences at once, the idea is that actions and decisions are cut-up into smaller pieces and finally the decision to implement is made based on economic costs of decisions and measures and the reduced effect of flooding. The more lead-time there is in

Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state-space models.

Science.gov (United States)

Polansky, Leo; Kilian, Werner; Wittemyer, George

2015-04-22

Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State-space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Simulating Spatial Growth Patterns in Developing Countries: an Agent Based Modelling Approach. A Case of Shama in the Western Region of Ghana

Science.gov (United States)

Inkoom, J. N.

2011-12-01

In Sub-Saharan Africa, rapid urban growth is characterized by prolific expansion of unplanned (informal) structures, and unguided spatial expansion. These unguided expansions by human agents have outstripped the regulatory capacities of Central and Local government. Governmental institutions in finding solutions to the unguided expansion in unplanned use of land have to call for the modelling of what influences the spatial decision and role of human agents in the growth of informal settlement. The objective of the study is to simulate spatial growth pattern of settlements in the Shama district using an agent based model. The study was conducted within a framework of NetLogo. The NetLogo assisted to incorporate and simulate driving forces that affect location decision-making by households and the growth of informal settlement. A survey was conducted to obtain household location decision preferences. The development of unplanned settlement has been a function of land price, proximity to economic centre's, household economic potential, and the location decision-making patterns of households. The exploratory analysis found particularly that majority of spontaneous development took place on areas liable to floods suggesting that some structures fall outside the required building regulations. The application of the proposed model indicates its potential to improve urban planning policies and decision-making processes in emerging cities of developing countries. Also, the result of the simulation suggests potential preferential location for residential development. The research justifies an approach in the area of simulating urban dynamics with agent-based models.

From Perceived Values to Shared Values: A Multi-Stakeholder Spatial Decision Analysis (M-SSDA for Resilient Landscapes

Directory of Open Access Journals (Sweden)

Maria Cerreta

2017-06-01

Full Text Available This paper puts forth a Multi-Stakeholder Spatial Decision Analysis (M-SSDA which combines Multi-Stakeholders Decision Analysis (M-SDA and GIS processing based on a collaborative, hybrid and adaptive evaluative approach to support the elaboration of enhancement strategies designed for resilient landscapes. This methodology has been tested in the research project “Cilento Labscape: An integrated model for the activation of a Living Lab in the National Park of Cilento, Vallo di Diano and Alburni”, which was conducted in the Cilento National Park (Southern Italy. The aim of the methodology is to find alternative touristic routes for the promotion of the Park. The different steps in the process will be described, as will the employment of multiple tools/techniques (interviews, GIS tools, Semantic Analysis, and Geo-Statistical Analysis to improve the reliability of the decision-making process. The most relevant results of the methodology will also be outlined in terms of the transition from the identification of the perceived landscape’s values to the acknowledgement of the shared values, and their consequent employment for the outlining of new thematic itineraries for the Park. To realise sustainable territorial strategies and preserve the landscape through bottom-up decision-making processes, the different local communities need to gain a new awareness of their identity shared values and make an active contribution towards promoting and managing their site-specific resources.

Cost-effectiveness of using a gene expression profiling test to aid in identifying the primary tumour in patients with cancer of unknown primary.

Science.gov (United States)

Hannouf, M B; Winquist, E; Mahmud, S M; Brackstone, M; Sarma, S; Rodrigues, G; Rogan, P; Hoch, J S; Zaric, G S

2017-06-01

We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget impact was $36.2 million per year. A value-of-information analysis revealed that the expected value of perfect information about the test's clinical impact was $4.2 million per year. The 2000-GEP test should be considered for adoption in CUP. Field evaluations of the test are associated with a large societal benefit.

Perceptual spatial differentiation of Ljubljana

Directory of Open Access Journals (Sweden)

Marko Krevs

2004-12-01

Full Text Available Geographical studies of human perception of places at local scale are usually aimed at bet-ter understanding of human spatial perception and knowledge about the places, and of using this knowledge in spatial decision-making or spatial behaviour. Our focus on the first part of these general research aims is presented based on a case study, revealing how residents of the Municipality of Ljubljana perceive and value neighbourhoods of “their” municipality at the beginning of the century1.

Optimal policy for value-based decision-making.

Science.gov (United States)

Tajima, Satohiro; Drugowitsch, Jan; Pouget, Alexandre

2016-08-18

For decades now, normative theories of perceptual decisions, and their implementation as drift diffusion models, have driven and significantly improved our understanding of human and animal behaviour and the underlying neural processes. While similar processes seem to govern value-based decisions, we still lack the theoretical understanding of why this ought to be the case. Here, we show that, similar to perceptual decisions, drift diffusion models implement the optimal strategy for value-based decisions. Such optimal decisions require the models' decision boundaries to collapse over time, and to depend on the a priori knowledge about reward contingencies. Diffusion models only implement the optimal strategy under specific task assumptions, and cease to be optimal once we start relaxing these assumptions, by, for example, using non-linear utility functions. Our findings thus provide the much-needed theory for value-based decisions, explain the apparent similarity to perceptual decisions, and predict conditions under which this similarity should break down.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

Science.gov (United States)

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Decision-Making Based on Emotional Images

OpenAIRE

Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

Decision making based on emotional images

OpenAIRE

Kentaro eKatahira; Kentaro eKatahira; Kentaro eKatahira; Tomomi eFujimura; Tomomi eFujimura; Kazuo eOkanoya; Kazuo eOkanoya; Kazuo eOkanoya; Masato eOkada; Masato eOkada; Masato eOkada

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward...

Risk-based emergency decision support

International Nuclear Information System (INIS)

Koerte, Jens

2003-01-01

In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach

Analysing malaria incidence at the small area level for developing a spatial decision support system: A case study in Kalaburagi, Karnataka, India.

Science.gov (United States)

Shekhar, S; Yoo, E-H; Ahmed, S A; Haining, R; Kadannolly, S

2017-02-01

Spatial decision support systems have already proved their value in helping to reduce infectious diseases but to be effective they need to be designed to reflect local circumstances and local data availability. We report the first stage of a project to develop a spatial decision support system for infectious diseases for Karnataka State in India. The focus of this paper is on malaria incidence and we draw on small area data on new cases of malaria analysed in two-monthly time intervals over the period February 2012 to January 2016 for Kalaburagi taluk, a small area in Karnataka. We report the results of data mapping and cluster detection (identifying areas of excess risk) including evaluating the temporal persistence of excess risk and the local conditions with which high counts are statistically associated. We comment on how this work might feed into a practical spatial decision support system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessing the users’ need for a spatial decision support system of smallholder farming in Kenya

Directory of Open Access Journals (Sweden)

Mike Teucher

2014-12-01

Full Text Available Accurate data of the natural conditions and agricultural systems with a good spatial resolution are a key factor to tackle food insecurity in developing countries. A broad variety of approaches exists to achieve precise data and information about agriculture. One system, especially developed for smallholder agriculture in East Africa, is the Farm Management Handbook of Kenya. It was first published in 1982/83 and fully revised in 2012, now containing 7 volumes. The handbooks contain detailed information on climate, soils, suitable crops and soil care based on scientific research results of the last 30 years. The density of facts leads to time consuming extraction of all necessary information. In this study we analyse the user needs and necessary components of a system for decision support for smallholder farming in Kenya based on a geographical information system (GIS. Required data sources were identified, as well as essential functions of the system. We analysed the results of our survey conducted in 2012 and early 2013 among agricultural officers. The monitoring of user needs and the problem of non-adaptability of an agricultural information system on the level of extension officers in Kenya are the central objectives. The outcomes of the survey suggest the establishment of a decision support tool based on already available open source GIS components. The system should include functionalities to show general information for a specific location and should provide precise recommendations about suitable crops and management options to support agricultural guidance on farm level.

[Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

Science.gov (United States)

Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

2012-02-01

In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

Tumor Classification Using High-Order Gene Expression Profiles Based on Multilinear ICA

Directory of Open Access Journals (Sweden)

Ming-gang Du

2009-01-01

Full Text Available Motivation. Independent Components Analysis (ICA maximizes the statistical independence of the representational components of a training gene expression profiles (GEP ensemble, but it cannot distinguish relations between the different factors, or different modes, and it is not available to high-order GEP Data Mining. In order to generalize ICA, we introduce Multilinear-ICA and apply it to tumor classification using high order GEP. Firstly, we introduce the basis conceptions and operations of tensor and recommend Support Vector Machine (SVM classifier and Multilinear-ICA. Secondly, the higher score genes of original high order GEP are selected by using t-statistics and tabulate tensors. Thirdly, the tensors are performed by Multilinear-ICA. Finally, the SVM is used to classify the tumor subtypes. Results. To show the validity of the proposed method, we apply it to tumor classification using high order GEP. Though we only use three datasets, the experimental results show that the method is effective and feasible. Through this survey, we hope to gain some insight into the problem of high order GEP tumor classification, in aid of further developing more effective tumor classification algorithms.

Michelson interferometer based spatial phase shift shearography.

Science.gov (United States)

Xie, Xin; Yang, Lianxiang; Xu, Nan; Chen, Xu

2013-06-10

This paper presents a simple spatial phase shift shearography based on the Michelson interferometer. The Michelson interferometer based shearographic system has been widely utilized in industry as a practical nondestructive test tool. In the system, the Michelson interferometer is used as a shearing device to generate a shearing distance by tilting a small angle in one of the two mirrors. In fact, tilting the mirror in the Michelson interferometer also generates spatial frequency shift. Based on this feature, we introduce a simple Michelson interferometer based spatial phase shift shearography. The Fourier transform (FT) method is applied to separate the spectrum on the spatial frequency domain. The phase change due to the loading can be evaluated using a properly selected windowed inverse-FT. This system can generate a phase map of shearography by using only a single image. The effects of shearing angle, spatial resolution of couple charge device camera, and filter methods are discussed in detail. The theory and the experimental results are presented.

Reasoning in explanation-based decision making.

Science.gov (United States)

Pennington, N; Hastie, R

1993-01-01

A general theory of explanation-based decision making is outlined and the multiple roles of inference processes in the theory are indicated. A typology of formal and informal inference forms, originally proposed by Collins (1978a, 1978b), is introduced as an appropriate framework to represent inferences that occur in the overarching explanation-based process. Results from the analysis of verbal reports of decision processes are presented to demonstrate the centrality and systematic character of reasoning in a representative legal decision-making task.

Spatial clustering of knowledge-based industries in the Helsinki Metropolitan Area

Directory of Open Access Journals (Sweden)

Juan Eduardo Chica

2016-01-01

Full Text Available The central locations of metropolitan areas have some specific attributes, leading to an accumulation of large knowledge exchanges and extensive knowledge externalities, which encourage the concentration of various economic activities, especially knowledge-based industries (KBI. Other agglomeration economies found in metropolitan areas – such as telecommunications and transport infrastructures connected to global productive circuits and complementary labour markets – are key factors for KBI employment growth. This paper explores the Helsinki Metropolitan Area’s (HMA spatial clustering of KBI at the sub-district level, and the role played by agglomeration economies (both specialization and diversity economies in fostering this process. The results reveal that KBI employment shows patterns of concentration in the core and adjacent areas. The specialization and diversity economies found in the metropolitan core and the specialization economies found in others areas lead to KBI spatial clustering in the HMA. Public policies regarding the promotion of science parks have also played a decisive role.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media.

Science.gov (United States)

Sonter, Laura J; Watson, Keri B; Wood, Spencer A; Ricketts, Taylor H

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18-20.2 at 95% confidence) to Vermont's tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making.

Decision-making based on emotional images.

Science.gov (United States)

Katahira, Kentaro; Fujimura, Tomomi; Okanoya, Kazuo; Okada, Masato

2011-01-01

The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants' choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the "reward value" of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants' choice data, we used reinforcement learning models that have successfully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures) was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

Decision making based on emotional images

Directory of Open Access Journals (Sweden)

Kentaro eKatahira

2011-10-01

Full Text Available The emotional outcome of a choice affects subsequent decision making. While the relationship between decision making and emotion has attracted attention, studies on emotion and decision making have been independently developed. In this study, we investigated how the emotional valence of pictures, which was stochastically contingent on participants’ choices, influenced subsequent decision making. In contrast to traditional value-based decision-making studies that used money or food as a reward, the reward value of the decision outcome, which guided the update of value for each choice, is unknown beforehand. To estimate the reward value of emotional pictures from participants’ choice data, we used reinforcement learning models that have success- fully been used in previous studies for modeling value-based decision making. Consequently, we found that the estimated reward value was asymmetric between positive and negative pictures. The negative reward value of negative pictures (relative to neutral pictures was larger in magnitude than the positive reward value of positive pictures. This asymmetry was not observed in valence for an individual picture, which was rated by the participants regarding the emotion experienced upon viewing it. These results suggest that there may be a difference between experienced emotion and the effect of the experienced emotion on subsequent behavior. Our experimental and computational paradigm provides a novel way for quantifying how and what aspects of emotional events affect human behavior. The present study is a first step toward relating a large amount of knowledge in emotion science and in taking computational approaches to value-based decision making.

Hedonic approaches based on spatial econometrics and spatial statistics: application to evaluation of project benefits

Science.gov (United States)

Tsutsumi, Morito; Seya, Hajime

2009-12-01

This study discusses the theoretical foundation of the application of spatial hedonic approaches—the hedonic approach employing spatial econometrics or/and spatial statistics—to benefits evaluation. The study highlights the limitations of the spatial econometrics approach since it uses a spatial weight matrix that is not employed by the spatial statistics approach. Further, the study presents empirical analyses by applying the Spatial Autoregressive Error Model (SAEM), which is based on the spatial econometrics approach, and the Spatial Process Model (SPM), which is based on the spatial statistics approach. SPMs are conducted based on both isotropy and anisotropy and applied to different mesh sizes. The empirical analysis reveals that the estimated benefits are quite different, especially between isotropic and anisotropic SPM and between isotropic SPM and SAEM; the estimated benefits are similar for SAEM and anisotropic SPM. The study demonstrates that the mesh size does not affect the estimated amount of benefits. Finally, the study provides a confidence interval for the estimated benefits and raises an issue with regard to benefit evaluation.

Health decision making: lynchpin of evidence-based practice.

Science.gov (United States)

Spring, Bonnie

2008-01-01

Health decision making is both the lynchpin and the least developed aspect of evidence-based practice. The evidence-based practice process requires integrating the evidence with consideration of practical resources and patient preferences and doing so via a process that is genuinely collaborative. Yet, the literature is largely silent about how to accomplish integrative, shared decision making. for evidence-based practice are discussed for 2 theories of clinician decision making (expected utility and fuzzy trace) and 2 theories of patient health decision making (transtheoretical model and reasoned action). Three suggestions are offered. First, it would be advantageous to have theory-based algorithms that weight and integrate the 3 data strands (evidence, resources, preferences) in different decisional contexts. Second, patients, not providers, make the decisions of greatest impact on public health, and those decisions are behavioral. Consequently, theory explicating how provider-patient collaboration can influence patient lifestyle decisions made miles from the provider's office is greatly needed. Third, although the preponderance of data on complex decisions supports a computational approach, such an approach to evidence-based practice is too impractical to be widely applied at present. More troublesomely, until patients come to trust decisions made computationally more than they trust their providers' intuitions, patient adherence will remain problematic. A good theory of integrative, collaborative health decision making remains needed.

Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

Science.gov (United States)

Mehdizadeh, Saeid

2018-04-01

Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external

Parallel constraint satisfaction in memory-based decisions.

Science.gov (United States)

Glöckner, Andreas; Hodges, Sara D

2011-01-01

Three studies sought to investigate decision strategies in memory-based decisions and to test the predictions of the parallel constraint satisfaction (PCS) model for decision making (Glöckner & Betsch, 2008). Time pressure was manipulated and the model was compared against simple heuristics (take the best and equal weight) and a weighted additive strategy. From PCS we predicted that fast intuitive decision making is based on compensatory information integration and that decision time increases and confidence decreases with increasing inconsistency in the decision task. In line with these predictions we observed a predominant usage of compensatory strategies under all time-pressure conditions and even with decision times as short as 1.7 s. For a substantial number of participants, choices and decision times were best explained by PCS, but there was also evidence for use of simple heuristics. The time-pressure manipulation did not significantly affect decision strategies. Overall, the results highlight intuitive, automatic processes in decision making and support the idea that human information-processing capabilities are less severely bounded than often assumed.

Effort-Based Decision-Making in Schizophrenia.

Science.gov (United States)

Culbreth, Adam J; Moran, Erin K; Barch, Deanna M

2018-08-01

Motivational impairment has long been associated with schizophrenia but the underlying mechanisms are not clearly understood. Recently, a small but growing literature has suggested that aberrant effort-based decision-making may be a potential contributory mechanism for motivational impairments in psychosis. Specifically, multiple reports have consistently demonstrated that individuals with schizophrenia are less willing than healthy controls to expend effort to obtain rewards. Further, this effort-based decision-making deficit has been shown to correlate with severity of negative symptoms and level of functioning, in many but not all studies. In the current review, we summarize this literature and discuss several factors that may underlie aberrant effort-based decision-making in schizophrenia.

Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

Science.gov (United States)

Zhang, W.; Li, X.; Xiao, W.

2018-05-01

The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the

Validating evidence based decision making in health care

DEFF Research Database (Denmark)

Nüssler, Emil Karl; Eskildsen, Jacob Kjær; Håkonsson, Dorthe Døjbak

Surgeons who perform prolapse surgeries face the dilemma of choosing to use mesh, with its assumed benefits, and the risks associated with mesh. In this paper, we examine whether decisions to use mesh is evidence based. Based on data of 30,398 patients from the Swedish National Quality Register o...... are highly influenced by the geographical placement of surgeons. Therfore, decisions to use mesh are boundedly rationality, rather than rational.......Surgeons who perform prolapse surgeries face the dilemma of choosing to use mesh, with its assumed benefits, and the risks associated with mesh. In this paper, we examine whether decisions to use mesh is evidence based. Based on data of 30,398 patients from the Swedish National Quality Register...... of Gynecological Surgery we examine factors related to decisions to use mesh. Our results indicate that decisions to use mesh are not evidence based, and cannot be explained neither by FDA safety communications, nor by medical conditions usually assumed to predict its usage. Instead, decisions to use mesh...

Activation of the cannabinoid system in the nucleus accumbens affects effort-based decision making.

Science.gov (United States)

Fatahi, Zahra; Haghparast, Abbas

2018-02-01

Effort-based decision making addresses how we make an action choice based on an integration of action and goal values. The nucleus accumbens (NAc) is implicated in allowing an animal to overcome effort constraints to obtain greater benefits, and it has been previously shown that cannabis derivatives may affect such processes. Therefore, in this study, we intend to evaluate the involvement of the cannabinoid system in the entire NAc on effort-based decision making. Rats were trained in a T-maze cost-benefit decision making the task in which they could choose either to climb a barrier to obtain a large reward in one arm or run into the other arm without a barrier to obtaining a small reward. Following training, the animals were bilaterally implanted with guide cannulae in the NAc. On test day, rats received cannabinoid agonist (Win 55,212-2; 2, 10 and 50μM) and/or antagonist (AM251; 45μM), afterward percentage of large reward choice and latency of reward attainment were investigated. Results revealed that the administration of cannabinoid agonist led to decrease of large reward choice percentage such that the animals preferred to receive a small reward with low effort instead of receiving a large reward with high effort. The administration of antagonist solely did not affect effort-based decision making, but did attenuate the Win 55,212-2-induced impairments in effort allocation. In agonist-treated animals, the latency of reward collection increased. Moreover, when the effort was equated on both arms, the animals returned to choosing large reward showing that obtained results were not caused by spatial memory impairment. Our finding suggested that activation of the cannabinoid system in the NAc impaired effort-based decision making and led to rats were less willing to invest the physical effort to gain large reward. Copyright © 2017 Elsevier Inc. All rights reserved.

OPEN SPATIAL DECISION SUPPORT SYSTEM: CASE FOR RADIOACTIVE WASTE DISPOSAL SITE SELECTION

Directory of Open Access Journals (Sweden)

Dario Perković

2012-07-01

Full Text Available In recent years the scientific and professional circles frequently discussed about radioactive waste and site selection for radioactive waste disposal. This issue will be further updated with accession of Republic of Croatia to the European Union and the only issue is politicized view of the fact that nuclear power plant Krško Croatia shares with neighbouring Republic of Slovenia. All the necessary studies have been made and these are attended by experts from different areas. Also, all Croatian residents should be familiar with this subject matter in a manner accessible to the general public through all available media. There are some questions: What are the institutions have taken on the issue of informing the public and can it be enough? When selecting a suitable site, with many parameters, the basic element is suitable geological formation, although the landfill must be socially acceptable. Well established methods used in the selection of eligible areas are multicriteria decision analysis (MCDA, geographic information system (GIS and combined GIS-MCDA method. The application of these methods is of great help in making decisions about the location of disposal of radioactive waste. Presentation of results, designed in the form of an open spatial decision support system, could help in education and informing the general public (the paper is published in Croatian.

Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing.

Science.gov (United States)

Gundogdu, Erhan; Ozkan, Huseyin; Alatan, A Aydin

2017-11-01

Correlation filters have been successfully used in visual tracking due to their modeling power and computational efficiency. However, the state-of-the-art correlation filter-based (CFB) tracking algorithms tend to quickly discard the previous poses of the target, since they consider only a single filter in their models. On the contrary, our approach is to register multiple CFB trackers for previous poses and exploit the registered knowledge when an appearance change occurs. To this end, we propose a novel tracking algorithm [of complexity O(D) ] based on a large ensemble of CFB trackers. The ensemble [of size O(2 D ) ] is organized over a binary tree (depth D ), and learns the target appearance subspaces such that each constituent tracker becomes an expert of a certain appearance. During tracking, the proposed algorithm combines only the appearance-aware relevant experts to produce boosted tracking decisions. Additionally, we propose a versatile spatial windowing technique to enhance the individual expert trackers. For this purpose, spatial windows are learned for target objects as well as the correlation filters and then the windowed regions are processed for more robust correlations. In our extensive experiments on benchmark datasets, we achieve a substantial performance increase by using the proposed tracking algorithm together with the spatial windowing.

Risk-based decision analysis for groundwater operable units

International Nuclear Information System (INIS)

Chiaramonte, G.R.

1995-01-01

This document proposes a streamlined approach and methodology for performing risk assessment in support of interim remedial measure (IRM) decisions involving the remediation of contaminated groundwater on the Hanford Site. This methodology, referred to as ''risk-based decision analysis,'' also supports the specification of target cleanup volumes and provides a basis for design and operation of the groundwater remedies. The risk-based decision analysis can be completed within a short time frame and concisely documented. The risk-based decision analysis is more versatile than the qualitative risk assessment (QRA), because it not only supports the need for IRMs, but also provides criteria for defining the success of the IRMs and provides the risk-basis for decisions on final remedies. For these reasons, it is proposed that, for groundwater operable units, the risk-based decision analysis should replace the more elaborate, costly, and time-consuming QRA

Spatial mode discriminator based on leaky waveguides

Science.gov (United States)

Xu, Jing; Liu, Jialing; Shi, Hongkang; Chen, Yuntian

2018-06-01

We propose a conceptually simple and experimentally compatible configuration to discriminate the spatial mode based on leaky waveguides, which are inserted in-between the transmission link. The essence of such a spatial mode discriminator is to introduce the leakage of the power flux on purpose for detection. Importantly, the leaky angle of each individual spatial mode with respect to the propagation direction are different for non-degenerated modes, while the radiation patterns of the degenerated spatial modes in the plane perpendicular to the propagation direction are also distinguishable. Based on these two facts, we illustrate the operation principle of the spatial mode discriminators via two concrete examples; a w-type slab leaky waveguide without degeneracy, and a cylindrical leaky waveguide with degeneracy. The correlation between the leakage angle and the spatial mode distribution for a slab leaky waveguide, as well as differences between the in-plane radiation patterns of degenerated modes in a cylindrical leaky waveguide, are verified numerically and analytically. Such findings can be readily useful in discriminating the spatial modes for optical communication or optical sensing.

Spatial and Temporal Dynamics and Value of Nature-Based Recreation, Estimated via Social Media

Science.gov (United States)

Watson, Keri B.; Wood, Spencer A.; Ricketts, Taylor H.

2016-01-01

Conserved lands provide multiple ecosystem services, including opportunities for nature-based recreation. Managing this service requires understanding the landscape attributes underpinning its provision, and how changes in land management affect its contribution to human wellbeing over time. However, evidence from both spatially explicit and temporally dynamic analyses is scarce, often due to data limitations. In this study, we investigated nature-based recreation within conserved lands in Vermont, USA. We used geotagged photographs uploaded to the photo-sharing website Flickr to quantify visits by in-state and out-of-state visitors, and we multiplied visits by mean trip expenditures to show that conserved lands contributed US $1.8 billion (US $0.18–20.2 at 95% confidence) to Vermont’s tourism industry between 2007 and 2014. We found eight landscape attributes explained the pattern of visits to conserved lands; visits were higher in larger conserved lands, with less forest cover, greater trail density and more opportunities for snow sports. Some of these attributes differed from those found in other locations, but all aligned with our understanding of recreation in Vermont. We also found that using temporally static models to inform conservation decisions may have perverse outcomes for nature-based recreation. For example, static models suggest conserved land with less forest cover receive more visits, but temporally dynamic models suggest clearing forests decreases, rather than increases, visits to these sites. Our results illustrate the importance of understanding both the spatial and temporal dynamics of ecosystem services for conservation decision-making. PMID:27611325

Spatiality of environmental law

DEFF Research Database (Denmark)

Baaner, Lasse; Hvingel, Line

2015-01-01

, examines legal regulation as spatial information. It aims to deepen the understanding of spatiality as a core element of environmental law, and to connect it to the basic concept of representation used in giscience. It concludes that the future path for e-Government demands a shift in legal paradigm, from...... maps showing representations of applied legal norms, to maps build on datasets that have legal authority. That will integrate legal and geographic information systems, and improve the legal accountability of decision support systems used in e-Government services based on spatio-legal data....

Protocol-based care: the standardisation of decision-making?

Science.gov (United States)

Rycroft-Malone, Jo; Fontenla, Marina; Seers, Kate; Bick, Debra

2009-05-01

To explore how protocol-based care affects clinical decision-making. In the context of evidence-based practice, protocol-based care is a mechanism for facilitating the standardisation of care and streamlining decision-making through rationalising the information with which to make judgements and ultimately decisions. However, whether protocol-based care does, in the reality of practice, standardise decision-making is unknown. This paper reports on a study that explored the impact of protocol-based care on nurses' decision-making. Theoretically informed by realistic evaluation and the promoting action on research implementation in health services framework, a case study design using ethnographic methods was used. Two sites were purposively sampled; a diabetic and endocrine unit and a cardiac medical unit. Within each site, data collection included observation, postobservation semi-structured interviews with staff and patients, field notes, feedback sessions and document review. Data were inductively and thematically analysed. Decisions made by nurses in both sites were varied according to many different and interacting factors. While several standardised care approaches were available for use, in reality, a variety of information sources informed decision-making. The primary approach to knowledge exchange and acquisition was person-to-person; decision-making was a social activity. Rarely were standardised care approaches obviously referred to; nurses described following a mental flowchart, not necessarily linked to a particular guideline or protocol. When standardised care approaches were used, it was reported that they were used flexibly and particularised. While the logic of protocol-based care is algorithmic, in the reality of clinical practice, other sources of information supported nurses' decision-making process. This has significant implications for the political goal of standardisation. The successful implementation and judicious use of tools such as

Evidence-based surgery: Dissemination, communication, decision aids

NARCIS (Netherlands)

Knops, A.M.

2013-01-01

Surgeons are expected to make treatment decisions that are based on the best available evidence. Moreover, they are called to recognise that important decisions should also be shared with patients. While dissemination of evidence-based surgery and communication of evidence to patients have been

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

Science.gov (United States)

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

Science.gov (United States)

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Quantifying Fast and Slow Responses of Terrestrial Carbon Exchange across a Water Availability Gradient in North American Flux Sites

Science.gov (United States)

Biederman, J. A.; Scott, R. L.; Goulden, M.

2014-12-01

Climate change is predicted to increase the frequency and severity of water limitation, altering terrestrial ecosystems and their carbon exchange with the atmosphere. Here we compare site-level temporal sensitivity of annual carbon fluxes to interannual variations in water availability against cross-site spatial patterns over a network of 19 eddy covariance flux sites. This network represents one order of magnitude in mean annual productivity and includes western North American desert shrublands and grasslands, savannahs, woodlands, and forests with continuous records of 4 to 12 years. Our analysis reveals site-specific patterns not identifiable in prior syntheses that pooled sites. We interpret temporal variability as an indicator of ecosystem response to annual water availability due to fast-changing factors such as leaf stomatal response and microbial activity, while cross-site spatial patterns are used to infer ecosystem adjustment to climatic water availability through slow-changing factors such as plant community and organic carbon pools. Using variance decomposition, we directly quantify how terrestrial carbon balance depends on slow- and fast-changing components of gross ecosystem production (GEP) and total ecosystem respiration (TER). Slow factors explain the majority of variance in annual net ecosystem production (NEP) across the dataset, and their relative importance is greater at wetter, forest sites than desert ecosystems. Site-specific offsets from spatial patterns of GEP and TER explain one third of NEP variance, likely due to slow-changing factors not directly linked to water, such as disturbance. TER and GEP are correlated across sites as previously shown, but our site-level analysis reveals surprisingly consistent linear relationships between these fluxes in deserts and savannahs, indicating fast coupling of TER and GEP in more arid ecosystems. Based on the uncertainty associated with slow and fast factors, we suggest a framework for improved

Spatially explicit simulation of peatland hydrology and carbon dioxide exchange: Influence of mesoscale topography

Science.gov (United States)

Sonnentag, O.; Chen, J. M.; Roulet, N. T.; Ju, W.; Govind, A.

2008-06-01

Carbon dynamics in peatlands are controlled, in large part, by their wetness as defined by water table depth and volumetric liquid soil moisture content. A common type of peatland is raised bogs that typically have a multiple-layer canopy of vascular plants over a Sphagnum moss ground cover. Their convex form restricts water supply to precipitation and water is shed toward the margins, usually by lateral subsurface flow. The hydraulic gradient for lateral subsurface flow is governed by the peat surface topography at the mesoscale (˜200 m to 5 km). To investigate the influence of mesoscale topography on wetness, evapotranspiration (ET), and gross primary productivity (GPP) in a bog during the snow-free period, we compare the outputs of a further developed version of the daily Boreal Ecosystem Productivity Simulator (BEPS) with observations made at the Mer Bleue peatland, located near Ottawa, Canada. Explicitly considering mesoscale topography, simulated total ET and GPP correlate well with measured ET (r = 0.91) and derived gross ecosystem productivity (GEP; r = 0.92). Both measured ET and derived GEP are simulated similarly well when mesoscale topography is neglected, but daily simulated values are systematically underestimated by about 10% and 12% on average, respectively, due to greater wetness resulting from the lack of lateral subsurface flow. Owing to the differences in moss surface conductances of water vapor and carbon dioxide with increasing moss water content, the differences in the spatial patterns of simulated total ET and GPP are controlled by the mesotopographic position of the moss ground cover.

Combining conservation value, vulnerability, and effectiveness of mitigation actions in spatial conservation decisions: an application to coastal oil spill combating.

Science.gov (United States)

Ihaksi, Taina; Kokkonen, Teemu; Helle, Inari; Jolma, Ari; Lecklin, Tiina; Kuikka, Sakari

2011-05-01

Increasing oil transportation and severe oil accidents in the past have led to the development of various sensitivity maps in different countries all over the world. Often, however, the areas presented on the maps are far too large to be safeguarded with the available oil combating equipment and prioritization is required to decide which areas must be safeguarded. While oil booms can be applied to safeguard populations from a drifting oil slick, decision making on the spatial allocation of oil combating capacity is extremely difficult due to the lack of time, resources and knowledge. Since the operational decision makers usually are not ecologists, a useful decision support tool including ecological knowledge must be readily comprehensible and easy to use. We present an index-based method that can be used to make decisions concerning which populations of natural organisms should primarily be safeguarded from a floating oil slick with oil booms. The indices take into account the relative exposure, mortality and recovery potential of populations, the conservation value of species and populations, and the effectiveness of oil booms to safeguard different species. The method has been implemented in a mapping software that can be used in the Gulf of Finland (Baltic Sea) for operational oil combating. It could also be utilized in other similar conservation decisions where species with varying vulnerability, conservational value, and benefits received from the management actions need to be prioritized.

Launching a virtual decision lab: development and field-testing of a web-based patient decision support research platform.

Science.gov (United States)

Hoffman, Aubri S; Llewellyn-Thomas, Hilary A; Tosteson, Anna N A; O'Connor, Annette M; Volk, Robert J; Tomek, Ivan M; Andrews, Steven B; Bartels, Stephen J

2014-12-12

Over 100 trials show that patient decision aids effectively improve patients' information comprehension and values-based decision making. However, gaps remain in our understanding of several fundamental and applied questions, particularly related to the design of interactive, personalized decision aids. This paper describes an interdisciplinary development process for, and early field testing of, a web-based patient decision support research platform, or virtual decision lab, to address these questions. An interdisciplinary stakeholder panel designed the web-based research platform with three components: a) an introduction to shared decision making, b) a web-based patient decision aid, and c) interactive data collection items. Iterative focus groups provided feedback on paper drafts and online prototypes. A field test assessed a) feasibility for using the research platform, in terms of recruitment, usage, and acceptability; and b) feasibility of using the web-based decision aid component, compared to performance of a videobooklet decision aid in clinical care. This interdisciplinary, theory-based, patient-centered design approach produced a prototype for field-testing in six months. Participants (n = 126) reported that: the decision aid component was easy to use (98%), information was clear (90%), the length was appropriate (100%), it was appropriately detailed (90%), and it held their interest (97%). They spent a mean of 36 minutes using the decision aid and 100% preferred using their home/library computer. Participants scored a mean of 75% correct on the Decision Quality, Knowledge Subscale, and 74 out of 100 on the Preparation for Decision Making Scale. Completing the web-based decision aid reduced mean Decisional Conflict scores from 31.1 to 19.5 (p development of a web-based patient decision support research platform that was feasible for use in research studies in terms of recruitment, acceptability, and usage. Within this platform, the web-based

Development and Application of a Planning Support System for Regional Spatial Functional Zoning Based on GIS

Directory of Open Access Journals (Sweden)

Xiaorui Zhang

2016-09-01

Full Text Available Regional spatial functional zoning in China is a large-scale strategic planning and requires very advanced planning decision support technology. With respect to spatial functional zoning, the planning support system (PSS is introduced as one of the most popular computer aided planning systems at the present time in this paper, and is further explained with the example of the latest regional main functional area (RMFA planning in China. On the Visual Studio.NET visualization development platform, the planning decision model, planning decision method, and GIS are organically integrated and customized by using the component-type secondary development technology of the ArcGIS Engine with the development language VB.NET. Hence, a highly efficient and flexible planning support system of regional main functional areas (RMFA-PSS is established. It was adopted in the research of the Beijing–Tianjin area in China and accordingly two types of main functional area planning are acquired. The RMFA-PSS offers an efficient and flexible decision support with regard to RMFA planning. The research can provide a reference for further PSS development and applications related to other types of spatial functional zoning.

Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management

Science.gov (United States)

Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Overton, Cory T.; Sanchez-Chopitea, Erika; Kroger, Travis; Mauch, Kimberly; Niell, Lara; Howe, Kristy; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

2014-01-01

Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use

The Geohazards Exploitation Platform: an advanced cloud-based environment for the Earth Science community

Science.gov (United States)

Manunta, Michele; Casu, Francesco; Zinno, Ivana; De Luca, Claudio; Pacini, Fabrizio; Caumont, Hervé; Brito, Fabrice; Blanco, Pablo; Iglesias, Ruben; López, Álex; Briole, Pierre; Musacchio, Massimo; Buongiorno, Fabrizia; Stumpf, Andre; Malet, Jean-Philippe; Brcic, Ramon; Rodriguez Gonzalez, Fernando; Elias, Panagiotis

2017-04-01

The idea to create advanced platforms for the Earth Observation community, where the users can find data but also state-of-art algorithms, processing tools, computing facilities, and instruments for dissemination and sharing, has been launched several years ago. The initiatives developed in this context have been supported firstly by the Framework Programmes of European Commission and the European Space Agency (ESA) and, progressively, by the Copernicus programme. In particular, ESA created and supported the Grid Processing on Demand (G-POD) environment, where the users can access to advanced processing tools implemented in a GRID environment, satellite data and computing facilities. All these components are located in the same datacentre to significantly reduce and make negligible the time to move the satellite data from the archive. From the experience of G-POD was born the idea of ESA to have an ecosystem of Thematic Exploitation Platforms (TEP) focused on the integration of Ground Segment capabilities and ICT technologies to maximize the exploitation of EO data from past and future missions. A TEP refers to a computing platform that deals with a set of user scenarios involving scientists, data providers and ICT developers, aggregated around an Earth Science thematic area. Among the others, the Geohazards Exploitation Platform (GEP) aims at providing on-demand and systematic processing services to address the need of the geohazards community for common information layers and to integrate newly developed processors for scientists and other expert users. Within GEP, the community benefits from a cloud-based environment, specifically designed for the advanced exploitation of EO data. A partner can bring its own tools and processing chains, but also has access in the same workspace to large satellite datasets and shared data processing tools. GEP is currently in the pre-operations phase under a consortium led by Terradue Srl and six pilot projects concerning

A cyber-enabled spatial decision support system to inventory Mangroves in Mozambique: coupling scientific workflows and cloud computing

Science.gov (United States)

Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Christina E. Stringer; Carl C. Trettin

2017-01-01

Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for...

Identification of high-risk cutaneous melanoma tumors is improved when combining the online American Joint Committee on Cancer Individualized Melanoma Patient Outcome Prediction Tool with a 31-gene expression profile-based classification.

Science.gov (United States)

Ferris, Laura K; Farberg, Aaron S; Middlebrook, Brooke; Johnson, Clare E; Lassen, Natalie; Oelschlager, Kristen M; Maetzold, Derek J; Cook, Robert W; Rigel, Darrell S; Gerami, Pedram

2017-05-01

A significant proportion of patients with American Joint Committee on Cancer (AJCC)-defined early-stage cutaneous melanoma have disease recurrence and die. A 31-gene expression profile (GEP) that accurately assesses metastatic risk associated with primary cutaneous melanomas has been described. We sought to compare accuracy of the GEP in combination with risk determined using the web-based AJCC Individualized Melanoma Patient Outcome Prediction Tool. GEP results from 205 stage I/II cutaneous melanomas with sufficient clinical data for prognostication using the AJCC tool were classified as low (class 1) or high (class 2) risk. Two 5-year overall survival cutoffs (AJCC 79% and 68%), reflecting survival for patients with stage IIA or IIB disease, respectively, were assigned for binary AJCC risk. Cox univariate analysis revealed significant risk classification of distant metastasis-free and overall survival (hazard ratio range 3.2-9.4, P risk by GEP but low risk by AJCC. Specimens reflect tertiary care center referrals; more effective therapies have been approved for clinical use after accrual. The GEP provides valuable prognostic information and improves identification of high-risk melanomas when used together with the AJCC online prediction tool. Copyright © 2016 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Web-based spatial analysis with the ILWIS open source GIS software and satellite images from GEONETCast

Science.gov (United States)

Lemmens, R.; Maathuis, B.; Mannaerts, C.; Foerster, T.; Schaeffer, B.; Wytzisk, A.

2009-12-01

This paper involves easy accessible integrated web-based analysis of satellite images with a plug-in based open source software. The paper is targeted to both users and developers of geospatial software. Guided by a use case scenario, we describe the ILWIS software and its toolbox to access satellite images through the GEONETCast broadcasting system. The last two decades have shown a major shift from stand-alone software systems to networked ones, often client/server applications using distributed geo-(web-)services. This allows organisations to combine without much effort their own data with remotely available data and processing functionality. Key to this integrated spatial data analysis is a low-cost access to data from within a user-friendly and flexible software. Web-based open source software solutions are more often a powerful option for developing countries. The Integrated Land and Water Information System (ILWIS) is a PC-based GIS & Remote Sensing software, comprising a complete package of image processing, spatial analysis and digital mapping and was developed as commercial software from the early nineties onwards. Recent project efforts have migrated ILWIS into a modular, plug-in-based open source software, and provide web-service support for OGC-based web mapping and processing. The core objective of the ILWIS Open source project is to provide a maintainable framework for researchers and software developers to implement training components, scientific toolboxes and (web-) services. The latest plug-ins have been developed for multi-criteria decision making, water resources analysis and spatial statistics analysis. The development of this framework is done since 2007 in the context of 52°North, which is an open initiative that advances the development of cutting edge open source geospatial software, using the GPL license. GEONETCast, as part of the emerging Global Earth Observation System of Systems (GEOSS), puts essential environmental data at the

From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

Science.gov (United States)

Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

2016-02-01

This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

Spatial decisions and cognitive strategies of monkeys and humans based on abstract spatial stimuli in rotation test

Czech Academy of Sciences Publication Activity Database

Nekovářová, Tereza; Nedvídek, Jan; Klement, Daniel; Bureš, Jan

2009-01-01

Roč. 136, č. 36 (2009), s. 15478-15482 ISSN 0027-8424 R&D Projects: GA MŠk(CZ) LC554; GA MŠk(CZ) 1M0517; GA ČR(CZ) GA309/09/0286; GA AV ČR KJB500110704 Institutional research plan: CEZ:AV0Z50110509 Keywords : spatial cognition * geometry of space * mental rotations Subject RIV: FH - Neuro logy Impact factor: 9.432, year: 2009

Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

OpenAIRE

Liu Xin; Zhang Shaoliang; Zheng Pulin

2015-01-01

Spatial local outlier factor (SLOF) algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO2 monitoring data obtained in the carbon capture and storage (CCS) project, the K-Nearest Neighbour (KNN) graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then ...

Involvement of cannabinoid system in the nucleus accumbens on delay-based decision making in the rat.

Science.gov (United States)

Fatahi, Zahra; Sadeghi, Bahman; Haghparast, Abbas

2018-01-30

The nucleus accumbens (NAc) plays a fundamental role in decision making and anticipation of reward. In addition, exogenous cannabinoids affect the behavior of humans and animals including disruption of short-term memory and cognitive impairments. Therefore, in this study, cannabinoid agonist and antagonist were administrated into the NAc to determine the effect of cannabinoid activation in the entire NAc on delay-based decision making. Rats were trained on a cost-benefit T-maze decision making task in which the animals were well-trained to choose between a small/immediate reward and a large/delay reward. After training, the animals were implanted with guide cannulae in the NAc. On test day, they received cannabinoid agonist (Win 55,212-2; 10, 50 and 100μM) and/or antagonist (AM251; 45μM) into the NAc. Percentage of high reward choice and latency of reward achievement were evaluated. Results showed that cannabinoid agonist administration caused a decrease in high reward choice such that rats selected small/immediate reward instead of large/delay reward. Moreover, in agonist-treated animals latency of reward achievement increased. Effects of cannabinoid activation on delay-based decision making with equivalent delays demonstrated that if the delay was equated on both arm goals, animals still had a preference for the high/delay reward, showing the results was not caused by an impairment of spatial preference or memory. These finding clarified that cannabinoid system activation in the entire NAc plays a critical role in the regulation of delay-based decision making. Copyright © 2017 Elsevier B.V. All rights reserved.

Risk-Based Decision Making for Deterioration Processes Using POMDP

DEFF Research Database (Denmark)

Nielsen, Jannie Sønderkær; Sørensen, John Dalsgaard

2015-01-01

This paper proposes a method for risk-based decision making for maintenance of deteriorating components, based on the partially observable Markov decision process (POMDP). Unlike most methods, the decision polices do not need to be stationary and can vary according to seasons and near the end...

Modeling strategic investment decisions in spatial markets

International Nuclear Information System (INIS)

Lorenczik, Stefan; Malischek, Raimund

2014-01-01

Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

Modeling strategic investment decisions in spatial markets

Energy Technology Data Exchange (ETDEWEB)

Lorenczik, Stefan; Malischek, Raimund [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Trueby, Johannes [International Energy Agency, 75 - Paris (France)

2014-04-15

Markets for natural resources and commodities are often oligopolistic. In these markets, production capacities are key for strategic interaction between the oligopolists. We analyze how different market structures influence oligopolistic capacity investments and thereby affect supply, prices and rents in spatial natural resource markets using mathematical programing models. The models comprise an investment period and a supply period in which players compete in quantities. We compare three models, one perfect competition and two Cournot models, in which the product is either traded through long-term contracts or on spot markets in the supply period. Tractability and practicality of the approach are demonstrated in an application to the international metallurgical coal market. Results may vary substantially between the different models. The metallurgical coal market has recently made progress in moving away from long-term contracts and more towards spot market-based trade. Based on our results, we conclude that this regime switch is likely to raise consumer rents but lower producer rents. The total welfare differs only negligibly.

Consequences of spatial autocorrelation for niche-based models

DEFF Research Database (Denmark)

Segurado, P.; Araújo, Miguel B.; Kunin, W. E.

2006-01-01

1.  Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2.  Analyses were based o...

Information integration in perceptual and value-based decisions

OpenAIRE

Tsetsos, K.

2012-01-01

Research on the psychology and neuroscience of simple, evidence-based choices has led to an impressive progress in capturing the underlying mental processes as optimal mechanisms that make the fastest decision for a specified accuracy. The idea that decision-making is an optimal process stands in contrast with findings in more complex, motivation-based decisions, focussed on multiple goals with trade-offs. Here, a number of paradoxical and puzzling choice behaviours have been r...

Frame-based safety analysis approach for decision-based errors

International Nuclear Information System (INIS)

Fan, Chin-Feng; Yihb, Swu

1997-01-01

A frame-based approach is proposed to analyze decision-based errors made by automatic controllers or human operators due to erroneous reference frames. An integrated framework, Two Frame Model (TFM), is first proposed to model the dynamic interaction between the physical process and the decision-making process. Two important issues, consistency and competing processes, are raised. Consistency between the physical and logic frames makes a TFM-based system work properly. Loss of consistency refers to the failure mode that the logic frame does not accurately reflect the state of the controlled processes. Once such failure occurs, hazards may arise. Among potential hazards, the competing effect between the controller and the controlled process is the most severe one, which may jeopardize a defense-in-depth design. When the logic and physical frames are inconsistent, conventional safety analysis techniques are inadequate. We propose Frame-based Fault Tree; Analysis (FFTA) and Frame-based Event Tree Analysis (FETA) under TFM to deduce the context for decision errors and to separately generate the evolution of the logical frame as opposed to that of the physical frame. This multi-dimensional analysis approach, different from the conventional correctness-centred approach, provides a panoramic view in scenario generation. Case studies using the proposed techniques are also given to demonstrate their usage and feasibility

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

Directory of Open Access Journals (Sweden)

Bo Sun

2012-01-01

Full Text Available According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negotiation and independent negotiation is established, and the heuristic rules applied to global and local maintenance decision making is proposed. Based on Contract Net Protocol and the heuristic rules, the maintenance decision making algorithm is put forward. Finally, a fleet consisting of 10 aircrafts on a 3-wave continuous mission is illustrated to verify this method. Simulation results indicate that this method can improve the availability of the fleet, meet mission demands, rationalize the utilization of support resources and provide support for online maintenance decision making among a mission oriented fleet.

Spatial Inference Based on Geometric Proportional Analogies

OpenAIRE

Mullally, Emma-Claire; O'Donoghue, Diarmuid P.

2006-01-01

We describe an instance-based reasoning solution to a variety of spatial reasoning problems. The solution centers on identifying an isomorphic mapping between labelled graphs that represent some problem data and a known solution instance. We describe a number of spatial reasoning problems that are solved by generating non-deductive inferences, integrating topology with area (and other) features. We report the accuracy of our algorithm on different categories of spatial reasoning tasks from th...

GCCS Spatial Data Base Module

National Research Council Canada - National Science Library

Bell, Paul

1998-01-01

.... JMTK is divided into three primary areas: (1) Visual, (2) Analysis (non-visual), and (3) Spatial Data Base (SDBM). The primary objective of the SDBM effort is to define, design, develop and test mapping, charting and geodesy...

Where spatial capacity building and spatial decision making meet. Publically debating participatory spatial planning via a newspaper.

OpenAIRE

Huybrechts, Liesbeth; Martens, Sarah; Devisch, Oswald

2015-01-01

This article reports on the in-between results of a Participatory Design research process in spatial planning in Godsheide, a small village in the Belgian Region of Limburg. The research explores how the language of newspapers enables citizens, policy makers, property developers and local organisations to build capacities (cfr. spatial capacity building) in ‘scripting’ their reflections on, but also actions in spatial change. In the heads of our participants, there existed a duality between -...

Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

Science.gov (United States)

Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

Seminal Quality Prediction Using Clustering-Based Decision Forests

Directory of Open Access Journals (Sweden)

Hong Wang

2014-08-01

Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

Association between genomic recurrence risk and well-being among breast cancer patients

International Nuclear Information System (INIS)

Retèl, Valesca P; Groothuis-Oudshoorn, Catharina GM; Aaronson, Neil K; Brewer, Noel T; Rutgers, Emiel JT; Harten, Wim H van

2013-01-01

Gene expression profiling (GEP) is increasingly used in the rapidly evolving field of personalized medicine. We sought to evaluate the association between GEP-assessed of breast cancer recurrence risk and patients’ well-being. Participants were Dutch women from 10 hospitals being treated for early stage breast cancer who were enrolled in the MINDACT trial (Microarray In Node-negative and 1 to 3 positive lymph node Disease may Avoid ChemoTherapy). As part of the trial, they received a disease recurrence risk estimate based on a 70-gene signature and on standard clinical criteria as scored via a modified version of Adjuvant! Online. /Women completed a questionnaire 6–8 weeks after surgery and after their decision regarding adjuvant chemotherapy. The questionnaire assessed perceived understanding, knowledge, risk perception, satisfaction, distress, cancer worry and health-related quality of life (HRQoL), 6–8 weeks after surgery and decision regarding adjuvant chemotherapy. Women (n = 347, response rate 62%) reported high satisfaction with and a good understanding of the GEP information they received. Women with low risk estimates from both the standard and genomic tests reported the lowest distress levels. Distress was higher predominately among patients who had received high genomic risk estimates, who did not receive genomic risk estimates, or who received conflicting estimates based on genomic and clinical criteria. Cancer worry was highest for patients with higher risk perceptions and lower satisfaction. Patients with concordant high-risk profiles and those for whom such profiles were not available reported lower quality of life. Patients were generally satisfied with the information they received about recurrence risk based on genomic testing. Some types of genomic test results were associated with greater distress levels, but not with cancer worry or HRQoL. ISRCTN: http://www.controlled-trials.com/ISRCTN18543567/MINDACT

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

Directory of Open Access Journals (Sweden)

Wei Tu

2015-10-01

Full Text Available Vehicle routing optimization (VRO designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW. Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of VRPTWs in a short time. This novel approach will contribute to spatial decision support community by developing an effective vehicle routing optimization method for large transportation applications in both public and private sectors.

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

Science.gov (United States)

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

Directory of Open Access Journals (Sweden)

Karel Doubravsky

Full Text Available Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (rechecked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

An Intuitionistic Fuzzy Stochastic Decision-Making Method Based on Case-Based Reasoning and Prospect Theory

Directory of Open Access Journals (Sweden)

Peng Li

2017-01-01

Full Text Available According to the case-based reasoning method and prospect theory, this paper mainly focuses on finding a way to obtain decision-makers’ preferences and the criterion weights for stochastic multicriteria decision-making problems and classify alternatives. Firstly, we construct a new score function for an intuitionistic fuzzy number (IFN considering the decision-making environment. Then, we aggregate the decision-making information in different natural states according to the prospect theory and test decision-making matrices. A mathematical programming model based on a case-based reasoning method is presented to obtain the criterion weights. Moreover, in the original decision-making problem, we integrate all the intuitionistic fuzzy decision-making matrices into an expectation matrix using the expected utility theory and classify or rank the alternatives by the case-based reasoning method. Finally, two illustrative examples are provided to illustrate the implementation process and applicability of the developed method.

Multiagent-Based Simulation of Temporal-Spatial Characteristics of Activity-Travel Patterns Using Interactive Reinforcement Learning

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Min Yang

2014-01-01

Full Text Available We propose a multiagent-based reinforcement learning algorithm, in which the interactions between travelers and the environment are considered to simulate temporal-spatial characteristics of activity-travel patterns in a city. Road congestion degree is added to the reinforcement learning algorithm as a medium that passes the influence of one traveler’s decision to others. Meanwhile, the agents used in the algorithm are initialized from typical activity patterns extracted from the travel survey diary data of Shangyu city in China. In the simulation, both macroscopic activity-travel characteristics such as traffic flow spatial-temporal distribution and microscopic characteristics such as activity-travel schedules of each agent are obtained. Comparing the simulation results with the survey data, we find that deviation of the peak-hour traffic flow is less than 5%, while the correlation of the simulated versus survey location choice distribution is over 0.9.

A singularity theorem based on spatial averages

Indian Academy of Sciences (India)

journal of. July 2007 physics pp. 31–47. A singularity theorem based on spatial ... In this paper I would like to present a result which confirms – at least partially – ... A detailed analysis of how the model fits in with the .... Further, the statement that the spatial average ...... Financial support under grants FIS2004-01626 and no.

Accrual based accounting implementation: An approach for modelling major decisions

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Ratno Agriyanto

2016-12-01

Full Text Available Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual based accounting to the accrual basis of accounting information use for decision-making basis. We used the survey questionnaires. The data were processed by SEM using statistical software WarpPLS. The results showed that the implementation of the accrual based accounting in City Government Semarang has significantly positively associated with decision-making. Another important finding is the City Government officials of Semarang have personality, low tolerance of ambiguity is a negative effect on the relationship between the implementation of the accrual based accounting for decision making

School-Based Decision-Making: The Canadian Perspective.

Science.gov (United States)

Peters, Frank

1997-01-01

In Canada, school-based decision making is a political expedient to co-opt public support for public education at the same time as financial resources to schools are being curtailed. School councils are advisory in nature and have no statutory position in either school or school-system decisions. (17 references) (MLF)

Multi-robot Cooperation Behavior Decision Based on Psychological Values

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Jian JIANG

2014-01-01

Full Text Available The method based on psychology concept has been proved to be a successful tool used for human-robot interaction. But its related research in multi-robot cooperation has remained scarce until recent studies. To solve the problem, a decision-making mechanism based on psychological values is presented to be regarded as the basis of the multi-robot cooperation. Robots give birth to psychological values based on the estimations of environment, teammates and themselves. The mapping relationship between psychological values and cooperation tendency threshold values is set up with artificial neural network. Robots can make decision on the bases of these threshold values in cooperation scenes. Experiments show that the multi-robot cooperation method presented in the paper not only can ensure the rationality of robots’ decision-making, but also can ensure the speediness of robots’ decision-making.

Rough set and rule-based multicriteria decision aiding

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Roman Slowinski

2012-08-01

Full Text Available The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA. DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems.

Interpatch foraging in honeybees-rational decision making at secondary hubs based upon time and motivation.

Science.gov (United States)

Najera, Daniel A; McCullough, Erin L; Jander, Rudolf

2012-11-01

For honeybees, Apis mellifera, the hive has been well known to function as a primary decision-making hub, a place from which foragers decide among various directions, distances, and times of day to forage efficiently. Whether foraging honeybees can make similarly complex navigational decisions from locations away from the hive is unknown. To examine whether or not such secondary decision-making hubs exist, we trained bees to forage at four different locations. Specifically, we trained honeybees to first forage to a distal site "CT" 100 m away from the hive; if food was present, they fed and then chose to go home. If food was not present, the honeybees were trained to forage to three auxiliary sites, each at a different time of the day: A in the morning, B at noon, and C in the afternoon. The foragers learned to check site CT for food first and then efficiently depart to the correct location based upon the time of day if there was no food at site CT. Thus, the honeybees were able to cognitively map motivation, time, and five different locations (Hive, CT, A, B, and C) in two spatial dimensions; these are the contents of the cognitive map used by the honeybees here. While at site CT, we verified that the honeybees could choose between 4 different directions (to A, B, C, and the Hive) and thus label it as a secondary decision-making hub. The observed decision making uncovered here is inferred to constitute genuine logical operations, involving a branched structure, based upon the premises of motivational state, and spatiotemporal knowledge.

Presentation of information for spatial decision support: a survey on the use of maps by participants in quantitative water management in the IJsselmeer region, the Netherlands

NARCIS (Netherlands)

Janssen, R.; Uran, O.

2003-01-01

Spatial decision support systems generate a diversity of information presented in tables, graphs, text and maps. Which form is used is dictated partially by the nature of the information but also by those who prepare information to be used in a decision-making process. The users of the information

Anytime decision making based on unconstrained influence diagrams

DEFF Research Database (Denmark)

Luque, Manuel; Nielsen, Thomas Dyhre; Jensen, Finn Verner

2016-01-01

. This paper addresses this problem by proposing an anytime algorithm that at any time provides a qualified recommendation for the first decisions of the problem. The algorithm performs a heuristic-based search in a decision tree representation of the problem. We provide a framework for analyzing......Unconstrained influence diagrams extend the language of influence diagrams to cope with decision problems in which the order of the decisions is unspecified. Thus, when solving an unconstrained influence diagram we not only look for an optimal policy for each decision, but also for a so-called step......-policy specifying the next decision given the observations made so far. However, due to the complexity of the problem, temporal constraints can force the decision maker to act before the solution algorithm has finished, and, in particular, before an optimal policy for the first decision has been computed...

Selecting a risk-based tool to aid in decision making

Energy Technology Data Exchange (ETDEWEB)

Bendure, A.O.

1995-03-01

Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

Optical spatial differentiator based on subwavelength high-contrast gratings

Science.gov (United States)

Dong, Zhewei; Si, Jiangnan; Yu, Xuanyi; Deng, Xiaoxu

2018-04-01

An optical spatial differentiator based on subwavelength high-contrast gratings (HCGs) is proposed experimentally. The spatial differentiation property of the subwavelength HCG is analyzed by calculating its spatial spectral transfer function based on the periodic waveguide theory. By employing the FDTD solutions, the performance of the subwavelength HCG spatial differentiator was investigated numerically. The subwavelength HCG differentiator with the thickness at the nanoscale was fabricated on the quartz substrate by electron beam lithography and Bosch deep silicon etching. Observed under an optical microscope with a CCD camera, the spatial differentiation of the incident field profile was obtained by the subwavelength HCG differentiator in transmission without Fourier lens. By projecting the images of slits, letter "X," and a cross on the subwavelength HCG differentiator, edge detections of images were obtained in transmission. With the nanoscale HCG structure and simple optical implementation, the proposed optical spatial differentiator provides the prospects for applications in optical computing systems and parallel data processing.

Toward the Modularization of Decision Support Systems

Science.gov (United States)

Raskin, R. G.

2009-12-01

Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

Parallelizing Gene Expression Programming Algorithm in Enabling Large-Scale Classification

Directory of Open Access Journals (Sweden)

Lixiong Xu

2017-01-01

Full Text Available As one of the most effective function mining algorithms, Gene Expression Programming (GEP algorithm has been widely used in classification, pattern recognition, prediction, and other research fields. Based on the self-evolution, GEP is able to mine an optimal function for dealing with further complicated tasks. However, in big data researches, GEP encounters low efficiency issue due to its long time mining processes. To improve the efficiency of GEP in big data researches especially for processing large-scale classification tasks, this paper presents a parallelized GEP algorithm using MapReduce computing model. The experimental results show that the presented algorithm is scalable and efficient for processing large-scale classification tasks.

Science-based natural resource management decisions: what are they?

Science.gov (United States)

T.J. Mills; T.M. Quigley; F.J. Everest

2001-01-01

While many people interested in natural resources management propose science-based decisions, it is not clear what “science-based” means. Science-based decisions are those that result from the full and complete consideration of the relevant science information. We offer five guidelines to focus the scientist’s contributions to science-based decisionmaking and use the...

Decision support tools for collaborative marine spatial planning: identifying potential sites for tidal energy devices around the Mull of Kintyre, Scotland

NARCIS (Netherlands)

Janssen, R.; Arciniegas, G.A.; Alexander, K.A.

2015-01-01

The expansion of offshore renewable energy production, such as wind, wave and tidal energy, is likely to lead to conflict between different users of the sea. Two types of spatial decision support tools were developed to support stakeholder workshops. A value mapping tool combines regional attributes

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Science.gov (United States)

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Directory of Open Access Journals (Sweden)

Johannes P M Heinonen

Full Text Available Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

Science.gov (United States)

Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

2016-01-01

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

Dopamine and Effort-Based Decision Making

Directory of Open Access Journals (Sweden)

Irma Triasih Kurniawan

2011-06-01

Full Text Available Motivational theories of choice focus on the influence of goal values and strength of reinforcement to explain behavior. By contrast relatively little is known concerning how the cost of an action, such as effort expended, contributes to a decision to act. Effort-based decision making addresses how we make an action choice based on an integration of action and goal values. Here we review behavioral and neurobiological data regarding the representation of effort as action cost, and how this impacts on decision making. Although organisms expend effort to obtain a desired reward there is a striking sensitivity to the amount of effort required, such that the net preference for an action decreases as effort cost increases. We discuss the contribution of the neurotransmitter dopamine (DA towards overcoming response costs and in enhancing an animal’s motivation towards effortful actions. We also consider the contribution of brain structures, including the basal ganglia (BG and anterior cingulate cortex (ACC, in the internal generation of action involving a translation of reward expectation into effortful action.

Ecosystem Model Performance at Wetlands: Results from the North American Carbon Program Site Synthesis

Science.gov (United States)

Sulman, B. N.; Desai, A. R.; Schroeder, N. M.; NACP Site Synthesis Participants

2011-12-01

Northern peatlands contain a significant fraction of the global carbon pool, and their responses to hydrological change are likely to be important factors in future carbon cycle-climate feedbacks. Global-scale carbon cycle modeling studies typically use general ecosystem models with coarse spatial resolution, often without peatland-specific processes. Here, seven ecosystem models were used to simulate CO2 fluxes at three field sites in Canada and the northern United States, including two nutrient-rich fens and one nutrient-poor, sphagnum-dominated bog, from 2002-2006. Flux residuals (simulated - observed) were positively correlated with measured water table for both gross ecosystem productivity (GEP) and ecosystem respiration (ER) at the two fen sites for all models, and were positively correlated with water table at the bog site for the majority of models. Modeled diurnal cycles at fen sites agreed well with eddy covariance measurements overall. Eddy covariance GEP and ER were higher during dry periods than during wet periods, while model results predicted either the opposite relationship or no significant difference. At the bog site, eddy covariance GEP had no significant dependence on water table, while models predicted higher GEP during wet periods. All models significantly over-estimated GEP at the bog site, and all but one over-estimated ER at the bog site. Carbon cycle models in peatland-rich regions could be improved by incorporating better models or measurements of hydrology and by inhibiting GEP and ER rates under saturated conditions. Bogs and fens likely require distinct treatments in ecosystem models due to differences in nutrients, peat properties, and plant communities.

AHP-based spatial analysis of water quality impact assessment due to change in vehicular traffic caused by highway broadening in Sikkim Himalaya

Science.gov (United States)

Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika

2018-05-01

Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.

Spatially explicit animal response to composition of habitat

Science.gov (United States)

Benjamin P. Pauli; Nicholas P. McCann; Patrick A. Zollner; Robert Cummings; Jonathan H. Gilbert; Eric J. Gustafson

2013-01-01

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-...

Cross-Industry Spatially Localized Innovation Networks

Directory of Open Access Journals (Sweden)

Aleksandr Evseevich Karlik

2016-12-01

Full Text Available This article’s objective is to develop conceptual approach to the study of key decision-making factors of cross-industry spatially localized innovation networks regularities by the application of quantitative and qualitative data of St. Petersburg Innovation and Technology Cluster of Machinery Manufacturing and Metalworking. The paper is based on the previous research findings which conclude that such networks have a set of opportunities and constraints for innovation. The hypothesis is that in the clusters, representing a special type of these networks, the spatial proximity partly offsets the negative impact of industrial distance. The authors propose a structural and logical model of strategic decision-making to analyze these effects on innovation. They specify network’s influences on performance: cognitive diversity; knowledge and expertise; structural autonomy and equivalence. The model is applied to spatially localized cross-industry cluster and then improved in accordance with the obtained results for accounting resource flows. It allowed to take into account the dynamics of innovation activity and to develop the practical implications in the particular business context. The analysis identified the peculiarities of spatially localized crossindustry innovation cooperation in perspective of the combinations of tangible resources, information and other intangible resources for the renewal of mature industries. The research results can be used in business as well as in industrial and regional economic policy. In the conclusion, the article outlines future research directions: a comprehensive empirical study with the analysis of data on the factors of cross-industry cooperation which were identified in this paper with testing of causal relations; the developing an approach to the study of spatially localized networks based on the exchange of primary resources in the economic system stability framework.

A Game-Chain-Based Approach for Decision Making

OpenAIRE

An, Tingyu; Watanabe, tsunami

2009-01-01

Nowadays, with the rapid development of information society, decision-making problems become more and more complicated especially in large scale systems such as infrastructure, environmental and industrial fields, which are usually accompanied by psychological competition between involved parties in a complicated, uncertain and dynamic situation. From a holistic perspective of system, a specific decision-making method which is described as game-chain-based decision making has been proposed in...

An Intelligent Fleet Condition-Based Maintenance Decision Making Method Based on Multi-Agent

OpenAIRE

Bo Sun; Qiang Feng; Songjie Li

2012-01-01

According to the demand for condition-based maintenance online decision making among a mission oriented fleet, an intelligent maintenance decision making method based on Multi-agent and heuristic rules is proposed. The process of condition-based maintenance within an aircraft fleet (each containing one or more Line Replaceable Modules) based on multiple maintenance thresholds is analyzed. Then the process is abstracted into a Multi-Agent Model, a 2-layer model structure containing host negoti...

Environmental decision support system on base of geoinformational technologies for the analysis of nuclear accident consequences

International Nuclear Information System (INIS)

Haas, T.C.; Maigan, M.; Arutyunyan, R.V.; Bolshov, L.A.; Demianov, V.V.

1996-01-01

The report deals with description of the concept and prototype of environmental decision support system (EDSS) for the analysis of late off-site consequences of severe nuclear accidents and analysis, processing and presentation of spatially distributed radioecological data. General description of the available software, use of modem achievements of geostatistics and stochastic simulations for the analysis of spatial data are presented and discussed

[Value-based cancer care. From traditional evidence-based decision making to balanced decision making within frameworks of shared values].

Science.gov (United States)

Palazzo, Salvatore; Filice, Aldo; Mastroianni, Candida; Biamonte, Rosalbino; Conforti, Serafino; Liguori, Virginia; Turano, Salvatore; De Simone, Rosanna; Rovito, Antonio; Manfredi, Caterina; Minardi, Stefano; Vilardo, Emmanuelle; Loizzo, Monica; Oriolo, Carmela

2016-04-01

Clinical decision making in oncology is based so far on the evidence of efficacy from high-quality clinical research. Data collection and analysis from experimental studies provide valuable insight into response rates and progression-free or overall survival. Data processing generates valuable information for medical professionals involved in cancer patient care, enabling them to make objective and unbiased choices. The increased attention of many scientific associations toward a more rational resource consumption in clinical decision making is mirrored in the Choosing Wisely campaign against the overuse or misuse of exams and procedures of little or no benefit for the patient. This cultural movement has been actively promoting care solutions based on the concept of "value". As a result, the value-based decision-making process for cancer care should not be dissociated from economic sustainability and from ethics of the affordability, also given the growing average cost of the most recent cancer drugs. In support of this orientation, the National Comprehensive Cancer Network (NCCN) has developed innovative and "complex" guidelines based on values, defined as "evidence blocks", with the aim of assisting the medical community in making overall sustainable choices.

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level.

Directory of Open Access Journals (Sweden)

Amanda Bourne

Full Text Available Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from

A Socio-Ecological Approach for Identifying and Contextualising Spatial Ecosystem-Based Adaptation Priorities at the Sub-National Level

Science.gov (United States)

Bourne, Amanda; Holness, Stephen; Holden, Petra; Scorgie, Sarshen; Donatti, Camila I.; Midgley, Guy

2016-01-01

Climate change adds an additional layer of complexity to existing sustainable development and biodiversity conservation challenges. The impacts of global climate change are felt locally, and thus local governance structures will increasingly be responsible for preparedness and local responses. Ecosystem-based adaptation (EbA) options are gaining prominence as relevant climate change solutions. Local government officials seldom have an appropriate understanding of the role of ecosystem functioning in sustainable development goals, or access to relevant climate information. Thus the use of ecosystems in helping people adapt to climate change is limited partially by the lack of information on where ecosystems have the highest potential to do so. To begin overcoming this barrier, Conservation South Africa in partnership with local government developed a socio-ecological approach for identifying spatial EbA priorities at the sub-national level. Using GIS-based multi-criteria analysis and vegetation distribution models, the authors have spatially integrated relevant ecological and social information at a scale appropriate to inform local level political, administrative, and operational decision makers. This is the first systematic approach of which we are aware that highlights spatial priority areas for EbA implementation. Nodes of socio-ecological vulnerability are identified, and the inclusion of areas that provide ecosystem services and ecological resilience to future climate change is innovative. The purpose of this paper is to present and demonstrate a methodology for combining complex information into user-friendly spatial products for local level decision making on EbA. The authors focus on illustrating the kinds of products that can be generated from combining information in the suggested ways, and do not discuss the nuance of climate models nor present specific technical details of the model outputs here. Two representative case studies from rural South Africa

GCCS Spatial Data Base Module Extensions

National Research Council Canada - National Science Library

Bell, Paul

1998-01-01

.... JMTK is divided into three primary areas: (1) Visual, (2) Analysis (nonvisual), and (3) Spatial Data Base (SDBM). The primary objective of the SDBM effort is to define, design, develop and test mapping, charting and geodesy...

An insight into intrinsic interfacial properties between Li metals and Li10GeP2S12 solid electrolytes.

Science.gov (United States)

Chen, Bingbing; Ju, Jiangwei; Ma, Jun; Zhang, Jianjun; Xiao, Ruijuan; Cui, Guanglei; Chen, Liquan

2017-11-29

Density functional theory simulations and experimental studies were performed to investigate the interfacial properties, including lithium ion migration kinetics, between lithium metal anode and solid electrolyte Li 10 GeP 2 S 12 (LGPS). The LGPS[001] plane was chosen as the studied surface because the easiest Li + migration pathway is along this direction. The electronic structure of the surface states indicated that the electrochemical stability was reduced at both the PS 4 - and GeS 4 -teminated surfaces. For the interface cases, the equilibrium interfacial structures of lithium metal against the PS 4 -terminated LGPS[001] surface (Li/PS 4 -LGPS) and the GeS 4 -terminated LGPS[001] surface (Li/GeS 4 -LGPS) were revealed based on the structural relaxation and adhesion energy analysis. Solid electrolyte interphases were expected to be formed at both Li/PS 4 -LGPS and Li/GeS 4 -LGPS interfaces, resulting in an unstable state of interface and large interfacial resistance, which was verified by the EIS results of the Li/LGPS/Li cell. In addition, the simulations of the migration kinetics show that the energy barriers for Li + crossing the Li/GeS 4 -LGPS interface were relatively low compared with the Li/PS 4 -LGPS interface. This may contribute to the formation of Ge-rich phases at the Li/LGPS interface, which can tune the interfacial structures to improve the ionic conductivity for future all-solid-state batteries. This work will offer a thorough understanding of the Li/LGPS interface, including local structures, electronic states and Li + diffusion behaviors in all-solid-state batteries.

Decision-Based Design Integrating Consumer Preferences into Engineering Design

CERN Document Server

Chen, Wei; Wassenaar, Henk Jan

2013-01-01

Building upon the fundamental principles of decision theory, Decision-Based Design: Integrating Consumer Preferences into Engineering Design presents an analytical approach to enterprise-driven Decision-Based Design (DBD) as a rigorous framework for decision making in engineering design.  Once the related fundamentals of decision theory, economic analysis, and econometrics modelling are established, the remaining chapters describe the entire process, the associated analytical techniques, and the design case studies for integrating consumer preference modeling into the enterprise-driven DBD framework. Methods for identifying key attributes, optimal design of human appraisal experiments, data collection, data analysis, and demand model estimation are presented and illustrated using engineering design case studies. The scope of the chapters also provides: •A rigorous framework of integrating the interests from both producer and consumers in engineering design, •Analytical techniques of consumer choice model...

Influence of branding on preference-based decision making.

Science.gov (United States)

Philiastides, Marios G; Ratcliff, Roger

2013-07-01

Branding has become one of the most important determinants of consumer choices. Intriguingly, the psychological mechanisms of how branding influences decision making remain elusive. In the research reported here, we used a preference-based decision-making task and computational modeling to identify which internal components of processing are affected by branding. We found that a process of noisy temporal integration of subjective value information can model preference-based choices reliably and that branding biases are explained by changes in the rate of the integration process itself. This result suggests that branding information and subjective preference are integrated into a single source of evidence in the decision-making process, thereby altering choice behavior.

Evidence-based decision making in health care settings: from theory to practice.

Science.gov (United States)

Kohn, Melanie Kazman; Berta, Whitney; Langley, Ann; Davis, David

2011-01-01

The relatively recent attention that evidence-based decision making has received in health care management has been at least in part due to the profound influence of evidence-based medicine. The result has been several comparisons in the literature between the use of evidence in health care management decisions and the use of evidence in medical decision making. Direct comparison, however, may be problematic, given the differences between medicine and management as they relate to (1) the nature of evidence that is brought to bear on decision making; (2) the maturity of empirical research in each field (in particular, studies that have substantiated whether or not and how evidence-based decision making is enacted); and (3) the context within which evidence-based decisions are made. By simultaneously reviewing evidence-based medicine and management, this chapter aims to inform future theorizing and empirical research on evidence-based decision making in health care settings.

Validating the predictions of case-based decision theory

OpenAIRE

Radoc, Benjamin

2015-01-01

Real-life decision-makers typically do not know all possible outcomes arising from alternative courses of action. Instead, when people face a problem, they may rely on the recollection of their past personal experience: the situation, the action taken, and the accompanying consequence. In addition, the applicability of a past experience in decision-making may depend on how similar the current problem is to situations encountered previously. Case-based decision theory (CBDT), proposed by Itzha...

An efficient communication strategy for mobile agent based distributed spatial data mining application

Science.gov (United States)

Han, Guodong; Wang, Jiazhen

2005-11-01

An efficient communication strategy is proposed in this paper, which aims to improve the response time and availability of mobile agent based distributed spatial data mining applications. When dealing with decomposed complex data mining tasks or On-Line Analytical Processing (OLAP), mobile agents authorized by the specified user need to coordinate and cooperate with each other by employing given communication method to fulfill the subtasks delegated to them. Agent interactive behavior, e.g. messages passing, intermediate results exchanging and final results merging, must happen after the specified path is determined by executing given routing selection algorithm. Most of algorithms exploited currently run in time that grows approximately quadratic with the size of the input nodes where mobile agents migrate between. In order to gain enhanced communication performance by reducing the execution time of the decision algorithm, we propose an approach to reduce the number of nodes involved in the computation. In practice, hosts in the system are reorganized into groups in terms of the bandwidth between adjacent nodes. Then, we find an optimal node for each group with high bandwidth and powerful computing resources, which is managed by an agent dispatched by agent home node. With that, the communication pattern can be implemented at a higher level of abstraction and contribute to improving the overall performance of mobile agent based distributed spatial data mining applications.

Decision Tree-Based Contextual Location Prediction from Mobile Device Logs

Directory of Open Access Journals (Sweden)

Linyuan Xia

2018-01-01

Full Text Available Contextual location prediction is an important topic in the field of personalized location recommendation in LBS (location-based services. With the advancement of mobile positioning techniques and various sensors embedded in smartphones, it is convenient to obtain massive human mobile trajectories and to derive a large amount of valuable information from geospatial big data. Extracting and recognizing personally interesting places and predicting next semantic location become a research hot spot in LBS. In this paper, we proposed an approach to predict next personally semantic place with historical visiting patterns derived from mobile device logs. To address the problems of location imprecision and lack of semantic information, a modified trip-identify method is employed to extract key visit points from GPS trajectories to a more accurate extent while semantic information are added through stay point detection and semantic places recognition. At last, a decision tree model is adopted to explore the spatial, temporal, and sequential features in contextual location prediction. To validate the effectiveness of our approach, experiments were conducted based on a trajectory collection in Guangzhou downtown area. The results verified the feasibility of our approach on contextual location prediction from continuous mobile devices logs.

Agent-Based Modeling of Consumer Decision making Process Based on Power Distance and Personality

NARCIS (Netherlands)

Roozmand, O.; Ghasem-Aghaee, N.; Hofstede, G.J.; Nematbakhsh, M.A.; Baraani, A.; Verwaart, T.

2011-01-01

Simulating consumer decision making processes involves different disciplines such as: sociology, social psychology, marketing, and computer science. In this paper, we propose an agent-based conceptual and computational model of consumer decision-making based on culture, personality and human needs.

Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

Directory of Open Access Journals (Sweden)

Rajesh P N Rao

2010-11-01

Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application

Directory of Open Access Journals (Sweden)

Gosselin Pierre

2009-04-01

Full Text Available Abstract Background Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP is central to the field known as BI (Business Intelligence, a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Results Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at

Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application.

Science.gov (United States)

Bernier, Eveline; Gosselin, Pierre; Badard, Thierry; Bédard, Yvan

2009-04-03

Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS) and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing) systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP) is central to the field known as BI (Business Intelligence), a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP) and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at integrating an initial collection of geo

Fundamentals of the fuzzy logic-based generalized theory of decisions

CERN Document Server

Aliev, Rafik Aziz

2013-01-01

Every day decision making and decision making in complex human-centric systems are characterized by imperfect decision-relevant information. Main drawback of the existing decision theories is namely incapability to deal with imperfect information and modeling vague preferences. Actually, a paradigm of non-numerical probabilities in decision making has a long history and arose also in Keynes’s analysis of uncertainty. There is a need for further generalization – a move to decision theories with perception-based imperfect information described in NL. The languages of new decision models for human-centric systems should be not languages based on binary logic but human-centric computational schemes able to operate on NL-described information. Development of new theories is now possible due to an increased computational power of information processing systems which allows for computations with imperfect information, particularly, imprecise and partially true information, which are much more complex than comput...

Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran

International Nuclear Information System (INIS)

Sharifi, Mozafar; Hadidi, Mosslem; Vessali, Elahe; Mosstafakhani, Parasto; Taheri, Kamal; Shahoie, Saber; Khodamoradpour, Mehran

2009-01-01

The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.

Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

KAUST Repository

Delimata, Paweł

2010-01-01

We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality. © 2010 Springer-Verlag.

A comparison of web-based versus print-based decision AIDS for prostate cancer screening: participants' evaluation and utilization.

Science.gov (United States)

Tomko, Catherine; Davis, Kimberly M; Luta, George; Krist, Alexander H; Woolf, Steven H; Taylor, Kathryn L

2015-01-01

Patient decision aids facilitate informed decision making for medical tests and procedures that have uncertain benefits. To describe participants' evaluation and utilization of print-based and web-based prostate cancer screening decision aids that were found to improve decisional outcomes in a prior randomized controlled trial. Men completed brief telephone interviews at baseline, one month, and 13 months post-randomization. Participants were primary care patients, 45-70 years old, who received the print-based (N = 628) or web-based decision aid (N = 625) and completed the follow-up assessments. We assessed men's baseline preference for web-based or print-based materials, time spent using the decision aids, comprehension of the overall message, and ratings of the content. Decision aid use was self-reported by 64.3 % (web) and 81.8 % (print) of participants. Significant predictors of decision aid use were race (white vs. non-white, OR = 2.43, 95 % CI: 1.77, 3.35), higher education (OR = 1.68, 95 % CI: 1.06, 2.70) and trial arm (print vs. web, OR = 2.78, 95 % CI: 2.03, 3.83). Multivariable analyses indicated that web-arm participants were more likely to use the website when they preferred web-based materials (OR: 1.91, CI: 1.17, 3.12), whereas use of the print materials was not significantly impacted by a preference for print-based materials (OR: 0.69, CI: 0.38, 1.25). Comprehension of the decision aid message (i.e., screening is an individual decision) did not significantly differ between arms in adjusted analyses (print: 61.9 % and web: 68.2 %, p = 0.42). Decision aid use was independently influenced by race, education, and the decision aid medium, findings consistent with the 'digital divide.' These results suggest that when it is not possible to provide this age cohort with their preferred decision aid medium, print materials will be more highly used than web-based materials. Although there are many advantages to web-based decision aids, providing an option for

Accuracy and impact of spatial aids based upon satellite enumeration to improve indoor residual spraying spatial coverage.

Science.gov (United States)

Bridges, Daniel J; Pollard, Derek; Winters, Anna M; Winters, Benjamin; Sikaala, Chadwick; Renn, Silvia; Larsen, David A

2018-02-23

Indoor residual spraying (IRS) is a key tool in the fight to control, eliminate and ultimately eradicate malaria. IRS protection is based on a communal effect such that an individual's protection primarily relies on the community-level coverage of IRS with limited protection being provided by household-level coverage. To ensure a communal effect is achieved through IRS, achieving high and uniform community-level coverage should be the ultimate priority of an IRS campaign. Ensuring high community-level coverage of IRS in malaria-endemic areas is challenging given the lack of information available about both the location and number of households needing IRS in any given area. A process termed 'mSpray' has been developed and implemented and involves use of satellite imagery for enumeration for planning IRS and a mobile application to guide IRS implementation. This study assessed (1) the accuracy of the satellite enumeration and (2) how various degrees of spatial aid provided through the mSpray process affected community-level IRS coverage during the 2015 spray campaign in Zambia. A 2-stage sampling process was applied to assess accuracy of satellite enumeration to determine number and location of sprayable structures. Results indicated an overall sensitivity of 94% for satellite enumeration compared to finding structures on the ground. After adjusting for structure size, roof, and wall type, households in Nchelenge District where all types of satellite-based spatial aids (paper-based maps plus use of the mobile mSpray application) were used were more likely to have received IRS than Kasama district where maps used were not based on satellite enumeration. The probability of a household being sprayed in Nchelenge district where tablet-based maps were used, did not differ statistically from that of a household in Samfya District, where detailed paper-based spatial aids based on satellite enumeration were provided. IRS coverage from the 2015 spray season benefited from

Spatial Outlier Detection of CO2 Monitoring Data Based on Spatial Local Outlier Factor

Directory of Open Access Journals (Sweden)

Liu Xin

2015-12-01

Full Text Available Spatial local outlier factor (SLOF algorithm was adopted in this study for spatial outlier detection because of the limitations of the traditional static threshold detection. Based on the spatial characteristics of CO2 monitoring data obtained in the carbon capture and storage (CCS project, the K-Nearest Neighbour (KNN graph was constructed using the latitude and longitude information of the monitoring points to identify the spatial neighbourhood of the monitoring points. Then SLOF was adopted to calculate the outlier degrees of the monitoring points and the 3σ rule was employed to identify the spatial outlier. Finally, the selection of K value was analysed and the optimal one was selected. The results show that, compared with the static threshold method, the proposed algorithm has a higher detection precision. It can overcome the shortcomings of the static threshold method and improve the accuracy and diversity of local outlier detection, which provides a reliable reference for the safety assessment and warning of CCS monitoring.

Landscape Modelling and Simulation Using Spatial Data

Directory of Open Access Journals (Sweden)

Amjed Naser Mohsin AL-Hameedawi

2017-08-01

Full Text Available In this paper a procedure was performed for engendering spatial model of landscape acclimated to reality simulation. This procedure based on combining spatial data and field measurements with computer graphics reproduced using Blender software. Thereafter that we are possible to form a 3D simulation based on VIS ALL packages. The objective was to make a model utilising GIS, including inputs to the feature attribute data. The objective of these efforts concentrated on coordinating a tolerable spatial prototype, circumscribing facilitation scheme and outlining the intended framework. Thus; the eventual result was utilized in simulation form. The performed procedure contains not only data gathering, fieldwork and paradigm providing, but extended to supply a new method necessary to provide the respective 3D simulation mapping production, which authorises the decision makers as well as investors to achieve permanent acceptance an independent navigation system for Geoscience applications.

Genomic Testing and Therapies for Breast Cancer in Clinical Practice

Science.gov (United States)

Haas, Jennifer S.; Phillips, Kathryn A.; Liang, Su-Ying; Hassett, Michael J.; Keohane, Carol; Elkin, Elena B.; Armstrong, Joanne; Toscano, Michele

2011-01-01

Purpose: Given the likely proliferation of targeted testing and treatment strategies for cancer, a better understanding of the utilization patterns of human epidermal growth factor receptor 2 (HER2) testing and trastuzumab and newer gene expression profiling (GEP) for risk stratification and chemotherapy decision making are important. Study Design: Cross-sectional. Methods: We performed a medical record review of women age 35 to 65 years diagnosed between 2006 and 2007 with invasive localized breast cancer, identified using claims from a large national health plan (N = 775). Results: Almost all women received HER2 testing (96.9%), and 24.9% of women with an accepted indication received GEP. Unexplained socioeconomic differences in GEP use were apparent after adjusting for age and clinical characteristics; specifically, GEP use increased with income. For example, those in the lowest income category (< $40,000) were less likely than those with an income of $125,000 or more to receive GEP (odds ratio, 0.34; 95% CI, 0.16 to 0.73). A majority of women (57.7%) with HER2-positive disease received trastuzumab; among these women, differences in age and clinical characteristics were not apparent, although surprisingly, those in the lowest income category were more likely than those in the high-income category to receive trastuzumab (P = .02). Among women who did not have a positive HER2 test, 3.9% still received trastuzumab. Receipt of adjuvant chemotherapy increased as GEP score indicated greater risk of recurrence. Conclusion: Identifying and eliminating unnecessary variation in the use of these expensive tests and treatments should be part of quality improvement and efficiency programs. PMID:21886507

Geospatial decision support systems for societal decision making

Science.gov (United States)

Bernknopf, R.L.

2005-01-01

While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the

Expression of p53 protein in high-grade gastroenteropancreatic neuroendocrine carcinoma

DEFF Research Database (Denmark)

Ali, Abir Salwa; Grönberg, Malin; Federspiel, Birgitte

2017-01-01

of immunoreactive p53 protein in GEP-NEC. Materials and methods Tumor tissues from 124 GEP-NEC patients with locally advanced or metastatic disease treated with platinum-based chemotherapy were collected from Nordic centers and clinical data were obtained from the Nordic NEC register. Tumor proliferation rate...... In this cohort of GEP-NEC patients, p53 expression could not be correlated with clinical outcome. However, in patients with colorectal NECs, p53 expression was correlated with shorter PFS and OS. Further studies are needed to establish the role of immunoreactive p53 as a prognostic marker for GEP-NEC patients.......Background Gastroenteropancreatic neuroendocrine carcinomas (GEP-NECs) are aggressive, rapidly proliferating tumors. Therapeutic response to current chemotherapy regimens is usually short lasting. The aim of this study was to examine the expression and potential clinical importance...

Vicarious Effort-Based Decision-Making in Autism Spectrum Disorders.

Science.gov (United States)

Mosner, Maya G; Kinard, Jessica L; McWeeny, Sean; Shah, Jasmine S; Markiewitz, Nathan D; Damiano-Goodwin, Cara R; Burchinal, Margaret R; Rutherford, Helena J V; Greene, Rachel K; Treadway, Michael T; Dichter, Gabriel S

2017-10-01

This study investigated vicarious effort-based decision-making in 50 adolescents with autism spectrum disorders (ASD) compared to 32 controls using the Effort Expenditure for Rewards Task. Participants made choices to win money for themselves or for another person. When choosing for themselves, the ASD group exhibited relatively similar patterns of effort-based decision-making across reward parameters. However, when choosing for another person, the ASD group demonstrated relatively decreased sensitivity to reward magnitude, particularly in the high magnitude condition. Finally, patterns of responding in the ASD group were related to individual differences in consummatory pleasure capacity. These findings indicate atypical vicarious effort-based decision-making in ASD and more broadly add to the growing body of literature addressing social reward processing deficits in ASD.

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

Science.gov (United States)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods

Improving the Slum Planning Through Geospatial Decision Support System

Science.gov (United States)

Shekhar, S.

2014-11-01

In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

Visual Information Processing Based on Spatial Filters Constrained by Biological Data.

Science.gov (United States)

1978-12-01

was provided by Pantie and Sekuler ( 19681. They found that the detection (if gratings was affected most by adapting isee Section 6.1. 11 to square...evidence for certain eye scans being directed by spatial information in filtered images is given. Eye scan paths of a portrait of a young girl I Figure 08...multistable objects to more complex objects such as the man- girl figure of Fisher 119681, decision boundaries that are a natural concomitant to any pattern

The impact of I(C)T in spatial planning education, 25 years of blended e-learning

NARCIS (Netherlands)

Knaap, van der W.G.M.

2014-01-01

The Wageningen spatial planning education curriculum is based on a mix of decision-oriented and design-oriented approaches. It is also intertwined with a wide range of E-learning options. The Elearning environment consists of a spectrum of applications such as model studies, spatial analysis using

The Research of Spatial-Temporal Analysis and Decision-Making Assistant System for Disabled Person Affairs Based on Mapworld

Science.gov (United States)

Zhang, J. H.; Yang, J.; Sun, Y. S.

2015-06-01

This system combines the Mapworld platform and informationization of disabled person affairs, uses the basic information of disabled person as center frame. Based on the disabled person population database, the affairs management system and the statistical account system, the data were effectively integrated and the united information resource database was built. Though the data analysis and mining, the system provides powerful data support to the decision making, the affairs managing and the public serving. It finally realizes the rationalization, normalization and scientization of disabled person affairs management. It also makes significant contributions to the great-leap-forward development of the informationization of China Disabled Person's Federation.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.

Science.gov (United States)

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Spatial quality, location theory and spatial planning

NARCIS (Netherlands)

Assink, Mathijs; Groenendijk, Nico

2009-01-01

This paper deals with spatial quality as a possible factor in location choices made by companies. Actual location decisions as well as location theory have changed over time. In the industrial era primary “hard” cost factors were dominant, to be supplemented by agglomeration factors ever since the

Flow of cortical activity underlying a tactile decision in mice

OpenAIRE

Guo, Zengcai V.; Li, Nuo; Huber, Daniel; Ophir, Eran; Gutnisky, Diego; Ting, Jonathan T.; Feng, Guoping; Svoboda, Karel

2013-01-01

Perceptual decisions involve distributed cortical activity. Does information flow sequentially from one cortical area to another, or do networks of interconnected areas contribute at the same time? Here we delineate when and how activity in specific areas drives a whisker-based decision in mice. A short-term memory component temporally separated tactile “sensation” and “action” (licking). Using optogenetic inhibition (spatial resolution, 2 mm; temporal resolution, 100 ms), we surveyed the neo...

Simulation-based decision support for evaluating operational plans

Directory of Open Access Journals (Sweden)

Johan Schubert

2015-12-01

Full Text Available In this article, we describe simulation-based decision support techniques for evaluation of operational plans within effects-based planning. Using a decision support tool, developers of operational plans are able to evaluate thousands of alternative plans against possible courses of events and decide which of these plans are capable of achieving a desired end state. The objective of this study is to examine the potential of a decision support system that helps operational analysts understand the consequences of numerous alternative plans through simulation and evaluation. Operational plans are described in the effects-based approach to operations concept as a set of actions and effects. For each action, we examine several different alternative ways to perform the action. We use a representation where a plan consists of several actions that should be performed. Each action may be performed in one of several different alternative ways. Together these action alternatives make up all possible plan instances, which are represented as a tree of action alternatives that may be searched for the most effective sequence of alternative actions. As a test case, we use an expeditionary operation with a plan of 43 actions and several alternatives for these actions, as well as a scenario of 40 group actors. Decision support for planners is provided by several methods that analyze the impact of a plan on the 40 actors, e.g., by visualizing time series of plan performance. Detailed decision support for finding the most influential actions of a plan is presented by using sensitivity analysis and regression tree analysis. Finally, a decision maker may use the tool to determine the boundaries of an operation that it must not move beyond without risk of drastic failure. The significant contribution of this study is the presentation of an integrated approach for evaluation of operational plans.

Probabilistic Decision Based Block Partitioning for Future Video Coding

KAUST Repository

Wang, Zhao; Wang, Shiqi; Zhang, Jian; Wang, Shanshe; Ma, Siwei

2017-01-01

, the mode decision problem is casted into a probabilistic framework to select the final partition based on the confidence interval decision strategy. Experimental results show that the proposed CIET algorithm can speed up QTBT block partitioning structure

Energy efficiency resource modeling in generation expansion planning

International Nuclear Information System (INIS)

Ghaderi, A.; Parsa Moghaddam, M.; Sheikh-El-Eslami, M.K.

2014-01-01

Energy efficiency plays an important role in mitigating energy security risks and emission problems. In this paper, energy efficiency resources are modeled as efficiency power plants (EPP) to evaluate their impacts on generation expansion planning (GEP). The supply curve of EPP is proposed using the production function of electricity consumption. A decision making framework is also presented to include EPP in GEP problem from an investor's point of view. The revenue of EPP investor is obtained from energy cost reduction of consumers and does not earn any income from electricity market. In each stage of GEP, a bi-level model for operation problem is suggested: the upper-level represents profit maximization of EPP investor and the lower-level corresponds to maximize the social welfare. To solve the bi-level problem, a fixed-point iteration algorithm is used known as diagonalization method. Energy efficiency feed-in tariff is investigated as a regulatory support scheme to encourage the investor. Results pertaining to a case study are simulated and discussed. - Highlights: • An economic model for energy efficiency programs is presented. • A framework is provided to model energy efficiency resources in GEP problem. • FIT is investigated as a regulatory support scheme to encourage the EPP investor. • The capacity expansion is delayed and reduced with considering EPP in GEP. • FIT-II can more effectively increase the energy saving compared to FIT-I

A physically based analytical spatial air temperature and humidity model

Science.gov (United States)

Yang Yang; Theodore A. Endreny; David J. Nowak

2013-01-01

Spatial variation of urban surface air temperature and humidity influences human thermal comfort, the settling rate of atmospheric pollutants, and plant physiology and growth. Given the lack of observations, we developed a Physically based Analytical Spatial Air Temperature and Humidity (PASATH) model. The PASATH model calculates spatial solar radiation and heat...

Modular Architecture for Integrated Model-Based Decision Support.

Science.gov (United States)

Gaebel, Jan; Schreiber, Erik; Oeser, Alexander; Oeltze-Jafra, Steffen

2018-01-01

Model-based decision support systems promise to be a valuable addition to oncological treatments and the implementation of personalized therapies. For the integration and sharing of decision models, the involved systems must be able to communicate with each other. In this paper, we propose a modularized architecture of dedicated systems for the integration of probabilistic decision models into existing hospital environments. These systems interconnect via web services and provide model sharing and processing capabilities for clinical information systems. Along the lines of IHE integration profiles from other disciplines and the meaningful reuse of routinely recorded patient data, our approach aims for the seamless integration of decision models into hospital infrastructure and the physicians' daily work.

Episodic memories predict adaptive value-based decision-making

Science.gov (United States)

Murty, Vishnu; FeldmanHall, Oriel; Hunter, Lindsay E.; Phelps, Elizabeth A; Davachi, Lila

2016-01-01

Prior research illustrates that memory can guide value-based decision-making. For example, previous work has implicated both working memory and procedural memory (i.e., reinforcement learning) in guiding choice. However, other types of memories, such as episodic memory, may also influence decision-making. Here we test the role for episodic memory—specifically item versus associative memory—in supporting value-based choice. Participants completed a task where they first learned the value associated with trial unique lotteries. After a short delay, they completed a decision-making task where they could choose to re-engage with previously encountered lotteries, or new never before seen lotteries. Finally, participants completed a surprise memory test for the lotteries and their associated values. Results indicate that participants chose to re-engage more often with lotteries that resulted in high versus low rewards. Critically, participants not only formed detailed, associative memories for the reward values coupled with individual lotteries, but also exhibited adaptive decision-making only when they had intact associative memory. We further found that the relationship between adaptive choice and associative memory generalized to more complex, ecologically valid choice behavior, such as social decision-making. However, individuals more strongly encode experiences of social violations—such as being treated unfairly, suggesting a bias for how individuals form associative memories within social contexts. Together, these findings provide an important integration of episodic memory and decision-making literatures to better understand key mechanisms supporting adaptive behavior. PMID:26999046

System and method for integrating hazard-based decision making tools and processes

Science.gov (United States)

Hodgin, C Reed [Westminster, CO

2012-03-20

A system and method for inputting, analyzing, and disseminating information necessary for identified decision-makers to respond to emergency situations. This system and method provides consistency and integration among multiple groups, and may be used for both initial consequence-based decisions and follow-on consequence-based decisions. The system and method in a preferred embodiment also provides tools for accessing and manipulating information that are appropriate for each decision-maker, in order to achieve more reasoned and timely consequence-based decisions. The invention includes processes for designing and implementing a system or method for responding to emergency situations.

Evidence-Based Medicine in judicial decisions concerning right to healthcare

Science.gov (United States)

Dias, Eduardo Rocha; da Silva, Geraldo Bezerra

2016-01-01

ABSTRACT Objective To analyze, from the examination of decisions issued by Brazilian courts, how Evidence-Based Medicine was applied and if it led to well-founded decisions, searching the best scientific knowledge. Methods The decisions made by the Federal Courts were searched, with no time limits, at the website of the Federal Court Council, using the expression “Evidence-Based Medicine”. With regard to decisions issued by the court of the State of São Paulo, the search was done at the webpage and applying the same terms and criterion as to time. Next, a qualitative analysis of the decisions was conducted for each action, to verify if the patient/plaintiff’s situation, as well as the efficacy or inefficacy of treatments or drugs addressed in existing protocols were considered before the court granted the provision claimed by the plaintiff. Results In less than one-third of the decisions there was an appropriate discussion about efficacy of the procedure sought in court, in comparison to other procedures available in clinical guidelines adopted by the Brazilian Unified Health System (Sistema Único de Saúde) or by private health insurance plans, considering the individual situation. The majority of the decisions involved private health insurance plans (n=13, 68%). Conclusion The number of decisions that did consider scientific evidence and the peculiarities of each patient was a concern. Further discussion on Evidence-Based Medicine in judgments involving public healthcare are required. PMID:27074226

Complex neural codes in rat prelimbic cortex are stable across days on a spatial decision task

Directory of Open Access Journals (Sweden)

Nathaniel J. Powell

2014-04-01

Full Text Available The rodent prelimbic cortex has been shown to play an important role in cognitive processing, and has been implicated in encoding many different parameters relevant to solving decision-making tasks. However, it is not known how the prelimbic cortex represents all these disparate variables, and if they are simultaneously represented when the task requires it. In order to investigate this question, we trained rats to run the Multiple-T Left Right Alternate (MT-LRA task and recorded multi-unit ensembles from their prelimbic regions. Significant populations of cells in the prelimbic cortex represented the strategy controlling reward receipt on a given lap, whether the animal chose to go right or left on a given lap, and whether the animal made a correct decision or an error on a given lap. These populations overlapped in the cells recorded, with several cells demonstrating differential firing to all three variables. The spatial and strategic firing patterns of individual prelimbic cells were highly conserved across several days of running this task, indicating that each cell encoded the same information across days.

Bayesian Spatial NBDA for Diffusion Data with Home-Base Coordinates.

Directory of Open Access Journals (Sweden)

Glenna F Nightingale

Full Text Available Network-based diffusion analysis (NBDA is a statistical method that allows the researcher to identify and quantify a social influence on the spread of behaviour through a population. Hitherto, NBDA analyses have not directly modelled spatial population structure. Here we present a spatial extension of NBDA, applicable to diffusion data where the spatial locations of individuals in the population, or of their home bases or nest sites, are available. The method is based on the estimation of inter-individual associations (for association matrix construction from the mean inter-point distances as represented on a spatial point pattern of individuals, nests or home bases. We illustrate the method using a simulated dataset, and show how environmental covariates (such as that obtained from a satellite image, or from direct observations in the study area can also be included in the analysis. The analysis is conducted in a Bayesian framework, which has the advantage that prior knowledge of the rate at which the individuals acquire a given task can be incorporated into the analysis. This method is especially valuable for studies for which detailed spatially structured data, but no other association data, is available. Technological advances are making the collection of such data in the wild more feasible: for example, bio-logging facilitates the collection of a wide range of variables from animal populations in the wild. We provide an R package, spatialnbda, which is hosted on the Comprehensive R Archive Network (CRAN. This package facilitates the construction of association matrices with the spatial x and y coordinates as the input arguments, and spatial NBDA analyses.

Grey situation group decision-making method based on prospect theory.

Science.gov (United States)

Zhang, Na; Fang, Zhigeng; Liu, Xiaqing

2014-01-01

This paper puts forward a grey situation group decision-making method on the basis of prospect theory, in view of the grey situation group decision-making problems that decisions are often made by multiple decision experts and those experts have risk preferences. The method takes the positive and negative ideal situation distance as reference points, defines positive and negative prospect value function, and introduces decision experts' risk preference into grey situation decision-making to make the final decision be more in line with decision experts' psychological behavior. Based on TOPSIS method, this paper determines the weight of each decision expert, sets up comprehensive prospect value matrix for decision experts' evaluation, and finally determines the optimal situation. At last, this paper verifies the effectiveness and feasibility of the method by means of a specific example.

Automated Vectorization of Decision-Based Algorithms

Science.gov (United States)

James, Mark

2006-01-01

Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

Cognitive schema and naturalistic decision making in evidence-based practices.

Science.gov (United States)

Falzer, Paul R

2004-04-01

A recent article in this journal proposed a naturalistic approach to decision making that overcomes problems intrinsic to classical decision theory. The approach emphasizes cognitive and multi-level processes, the development of expert reasoning, and the role of decision support in individual and organizational decision making. The current paper builds on this effort by suggesting a naturalistic, multi-level, theory that can facilitate the dissemination of evidence-based practices (EBPs). The paper presents "Image Theory," a theory that has been extensively investigated in other disciplines, but has yet to be utilized in medical decision research. It is suggested that its rich, empirically tested, distinctions among kinds of cognitive and organizational processes and types of decisions and tasks make Image Theory especially valuable in describing impediments to implementing EBPs. The paper discusses how naturalistic theory can assist clinicians, administrators, researchers, and policy makers in achieving a balance between evidence-based medicine and patient-centered practice.

Big-Data Based Decision-Support Systems to Improve Clinicians’ Cognition

Science.gov (United States)

Roosan, Don; Samore, Matthew; Jones, Makoto; Livnat, Yarden; Clutter, Justin

2016-01-01

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians’ cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems. PMID:27990498

Enabling Participatory Decision Making Through Web-Based GIS

International Nuclear Information System (INIS)

Sheng, Grant; Yam, Kevin; Hassas, Aranak

2001-01-01

The concept of 'Sustainable Communities' is taking an increasingly strong hold in discourses on civil society and sustainability. A basic tenet of the sustainability paradigm is that a community should be empowered to participate in the decision making process on issues that affect the well-being and continual development of the community. Meaningful participation in such a process requires that stakeholders have unrestricted and easy access to all relevant information regarding the issue at hand and that they have an effective means for communicating with one another without the barriers often posed by spatial, temporal, skill and financial constraints. The controversial nature of, and the intense emotion associated with nuclear waste disposal make it especially important that the principles of 'right-to-know' and 'participatory decision making' be upheld for communities engaged in any aspect of, or during any phase of, a site selection process. Whether a community is being considered as a potential host site, located along the route for transport of the waste material, or simply within a general region in which the siting may affect the economic and environmental well-being of the community, they all share, to varying degrees, a common concern: 'how will it affect me, my family, and my community?' Answering this question to the satisfaction of all stakeholders is one of the most challenging tasks in a site selection process. More than three decades of research has clearly demonstrated that addressing this concern goes far beyond simply 'supplying enough information' or even the 'appropriate information'. Experience has shown that no amount of public information programs, education programs, public hearing etc., will satisfy all parties involved. There are at least two major reasons for this: The different values held by people affect how they perceive even fundamental issues such as fairness, justice, morals, ethical behaviour, our relationship with, and

Proposal optimization in nuclear accident emergency decision based on IAHP

International Nuclear Information System (INIS)

Xin Jing

2007-01-01

On the basis of establishing the multi-layer structure of nuclear accident emergency decision, several decision objectives are synthetically analyzed, and an optimization model of decision proposals for nuclear accident emergency based on interval analytic hierarchy process is proposed in the paper. The model makes comparisons among several emergency decision proposals quantified, and the optimum proposal is selected out, which solved the uncertain and fuzzy decision problem of judgments by experts' experiences in nuclear accidents emergency decision. Case study shows that the optimization result is much more reasonable, objective and reliable than subjective judgments, and it could be decision references for nuclear accident emergency. (authors)

Framework for mapping the drivers of coastal vulnerability and spatial decision making for climate-change adaptation: A case study from Maharashtra, India.

Science.gov (United States)

Krishnan, Pandian; Ananthan, Pachampalayam Shanmugam; Purvaja, Ramachandran; Joyson Joe Jeevamani, Jeyapaul; Amali Infantina, John; Srinivasa Rao, Cherukumalli; Anand, Arur; Mahendra, Ranganalli Somashekharappa; Sekar, Iyyapa; Kareemulla, Kalakada; Biswas, Amit; Kalpana Sastry, Regulagedda; Ramesh, Ramachandran

2018-05-31

The impacts of climate change are of particular concern to the coastal region of tropical countries like India, which are exposed to cyclones, floods, tsunami, seawater intrusion, etc. Climate-change adaptation presupposes comprehensive assessment of vulnerability status. Studies so far relied either on remote sensing-based spatial mapping of physical vulnerability or on certain socio-economic aspects with limited scope for upscaling or replication. The current study is an attempt to develop a holistic and robust framework to assess the vulnerability of coastal India at different levels. We propose and estimate cumulative vulnerability index (CVI) as a function of exposure, sensitivity and adaptive capacity, at the village level, using nationally comparable and credible datasets. The exposure index (EI) was determined at the village level by decomposing the spatial multi-hazard maps, while sensitivity (SI) and adaptive capacity indices (ACI) were estimated using 23 indicators, covering social and economic aspects. The indicators were identified through the literature review, expert consultations, opinion survey, and were further validated through statistical tests. The socio-economic vulnerability index (SEVI) was constructed as a function of sensitivity and adaptive capacity for planning grassroot-level interventions and adaptation strategies. The framework was piloted in Sindhudurg, a coastal district in Maharashtra, India. It comprises 317 villages, spread across three taluks viz., Devgad, Malvan and Vengurla. The villages in Sindhudurg were ranked based on this multi-criteria approach. Based on CVI values, 92 villages (30%) in Sindhudurg were identified as highly vulnerable. We propose a decision tool for identifying villages vulnerable to changing climate, based on their level of sensitivity and adaptive capacity in a two-dimensional matrix, thus aiding in planning location-specific interventions. Here, vulnerability indicators are classified and designated as

Bayesian risk-based decision method for model validation under uncertainty

International Nuclear Information System (INIS)

Jiang Xiaomo; Mahadevan, Sankaran

2007-01-01

This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

Science.gov (United States)

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

The Relative Success of Recognition-Based Inference in Multichoice Decisions

Science.gov (United States)

McCloy, Rachel; Beaman, C. Philip; Smith, Philip T.

2008-01-01

The utility of an "ecologically rational" recognition-based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition-based judgment (the "less-is-more effect") is identified for a range of cue…

Evaluation of the NMC regional ensemble prediction system during the Beijing 2008 Olympic Games

Science.gov (United States)

Li, Xiaoli; Tian, Hua; Deng, Guo

2011-10-01

Based on the B08RDP (Beijing 2008 Olympic Games Mesoscale Ensemble Prediction Research and Development Project) that was launched by the World Weather Research Programme (WWRP) in 2004, a regional ensemble prediction system (REPS) at a 15-km horizontal resolution was developed at the National Meteorological Center (NMC) of the China Meteorological Administration (CMA). Supplementing to the forecasters' subjective affirmation on the promising performance of the REPS during the 2008 Beijing Olympic Games (BOG), this paper focuses on the objective verification of the REPS for precipitation forecasts during the BOG period. By use of a set of advanced probabilistic verification scores, the value of the REPS compared to the quasi-operational global ensemble prediction system (GEPS) is assessed for a 36-day period (21 July-24 August 2008). The evaluation here involves different aspects of the REPS and GEPS, including their general forecast skills, specific attributes (reliability and resolution), and related economic values. The results indicate that the REPS generally performs significantly better for the short-range precipitation forecasts than the GEPS, and for light to heavy rainfall events, the REPS provides more skillful forecasts for accumulated 6- and 24-h precipitation. By further identifying the performance of the REPS through the attribute-focused measures, it is found that the advantages of the REPS over the GEPS come from better reliability (smaller biases and better dispersion) and increased resolution. Also, evaluation of a decision-making score reveals that a much larger group of users benefits from using the REPS forecasts than using the single model (the control run) forecasts, especially for the heavy rainfall events.

Professional analysis in spatial planning

Directory of Open Access Journals (Sweden)

Andrej Černe

2005-12-01

Full Text Available Spatial analysis contributes to accomplishment of the three basic aims of spatial planning: it is basic element for setting spatial policies, concepts and strategies, gives basic information to inhabitants, land owners, investors, planners and helps in performing spatial policies, strategies, plans, programmes and projects. Analysis in planning are generally devoted to: understand current circumstances and emerging conditions within planning decisions; determine priorities of open questions and their solutions; formulate general principles for further development.

A vestibular sensation: probabilistic approaches to spatial perception.

Science.gov (United States)

Angelaki, Dora E; Klier, Eliana M; Snyder, Lawrence H

2009-11-25

The vestibular system helps maintain equilibrium and clear vision through reflexes, but it also contributes to spatial perception. In recent years, research in the vestibular field has expanded to higher-level processing involving the cortex. Vestibular contributions to spatial cognition have been difficult to study because the circuits involved are inherently multisensory. Computational methods and the application of Bayes theorem are used to form hypotheses about how information from different sensory modalities is combined together with expectations based on past experience in order to obtain optimal estimates of cognitive variables like current spatial orientation. To test these hypotheses, neuronal populations are being recorded during active tasks in which subjects make decisions based on vestibular and visual or somatosensory information. This review highlights what is currently known about the role of vestibular information in these processes, the computations necessary to obtain the appropriate signals, and the benefits that have emerged thus far.

Feasibility of web-based decision aids in neurological patients

NARCIS (Netherlands)

van Til, Janine Astrid; Drossaert, Constance H.C.; Renzenbrink, Gerbert J.; Snoek, Govert J.; Dijkstra, Evelien; Stiggelbout, Anne M.; IJzerman, Maarten Joost

2010-01-01

Decision aids (DAs) may be helpful in improving patients' participation in medical decision-making. We investigated the potential for web-based DAs in a rehabilitation population. Two self-administered DAs focused on the treatment of acquired ankle-foot impairment in stroke and the treatment of

Spatial pattern of diarrhea based on regional economic and environment by spatial autoregressive model

Science.gov (United States)

Bekti, Rokhana Dwi; Nurhadiyanti, Gita; Irwansyah, Edy

2014-10-01

The diarrhea case pattern information, especially for toddler, is very important. It is used to show the distribution of diarrhea in every region, relationship among that locations, and regional economic characteristic or environmental behavior. So, this research uses spatial pattern to perform them. This method includes: Moran's I, Spatial Autoregressive Models (SAR), and Local Indicator of Spatial Autocorrelation (LISA). It uses sample from 23 sub districts of Bekasi Regency, West Java, Indonesia. Diarrhea case, regional economic, and environmental behavior of households have a spatial relationship among sub district. SAR shows that the percentage of Regional Gross Domestic Product is significantly effect on diarrhea at α = 10%. Therefore illiteracy and health center facilities are significant at α = 5%. With LISA test, sub districts in southern Bekasi have high dependencies with Cikarang Selatan, Serang Baru, and Setu. This research also builds development application that is based on java and R to support data analysis.

A GIS-based decision support system for regional eco-security assessment and its application on the Tibetan Plateau.

Science.gov (United States)

Xiaodan, Wang; Xianghao, Zhong; Pan, Gao

2010-10-01

Regional eco-security assessment is an intricate, challenging task. In previous studies, the integration of eco-environmental models and geographical information systems (GIS) usually takes two approaches: loose coupling and tight coupling. However, the present study used a full coupling approach to develop a GIS-based regional eco-security assessment decision support system (ESDSS). This was achieved by merging the pressure-state-response (PSR) model and the analytic hierarchy process (AHP) into ArcGIS 9 as a dynamic link library (DLL) using ArcObjects in ArcGIS and Visual Basic for Applications. Such an approach makes it easy to capitalize on the GIS visualization and spatial analysis functions, thereby significantly supporting the dynamic estimation of regional eco-security. A case study is presented for the Tibetan Plateau, known as the world's "third pole" after the Arctic and Antarctic. Results verified the usefulness and feasibility of the developed method. As a useful tool, the ESDSS can also help local managers to make scientifically-based and effective decisions about Tibetan eco-environmental protection and land use. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Accrual based accounting implementation: An approach for modelling major decisions

OpenAIRE

Ratno Agriyanto; Abdul Rohman; Dwi Ratmono; Imam Ghozali

2016-01-01

Over the last three decades the main issues of implementation of accrual based accounting government institutions in Indonesia. Implementation of accrual based accounting in government institutions amid debate about the usefulness of accounting information for decision-making. Empirical study shows that the accrual based of accounting information on a government institution is not used for decision making. The research objective was to determine the impact of the implementation of the accrual...

Factors influencing the surgical decision for the treatment of degenerative lumbar stenosis in a preference-based shared decision-making process.

Science.gov (United States)

Kim, Ho-Joong; Park, Jae-Young; Kang, Kyoung-Tak; Chang, Bong-Soon; Lee, Choon-Ki; Yeom, Jin S

2015-02-01

In a preference-based shared decision-making system, several subjective and/or objective factors such as pain severity, degree of disability, and the radiological severity of canal stenosis may influence the final surgical decision for the treatment of lumbar spinal stenosis (LSS). However, our understanding of the shared decision-making process and the significance of each factor remain primitive. In the present study, we aimed to investigate which factors influence the surgical decision for the treatment of LSS when using a preference-based, shared decision-making process. We included 555 patients, aged 45-80 years, who used a preference-based shared decision-making process and were treated conservatively or surgically for chronic leg and/or back pain caused by LSS from April 2012 to December 2012. Univariate and multivariable-adjusted logistic regression analyses were used to assess the association of surgical decision making with age, sex, body mass index, symptom duration, radiologic stenotic grade, Oswestry Disability Index (ODI), visual analog scale (VAS) scores for back and leg pain, Short Form-36 (SF-36) subscales, and motor weakness. In univariate analysis, the following variables were associated with a higher odds of a surgical decision for LSS: male sex; the VAS score for leg pain; ODI; morphological stenotic grades B, C, and D; motor weakness; and the physical function, physical role, bodily pain, social function, and emotional role of the SF-36 subscales. Multivariate analysis revealed that male sex, ODI, morphological stenotic grades C and D, and motor weakness were significantly associated with a higher possibility of a surgical decision. Motor weakness, male sex, morphological stenotic grade, and the amount of disability are critical factors leading to a surgical decision for LSS when using a preference-based shared decision-making process.

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses

Science.gov (United States)

Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-01

Background Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. Objective The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Methods Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Results Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however

Features of Computer-Based Decision Aids: Systematic Review, Thematic Synthesis, and Meta-Analyses.

Science.gov (United States)

Syrowatka, Ania; Krömker, Dörthe; Meguerditchian, Ari N; Tamblyn, Robyn

2016-01-26

Patient information and education, such as decision aids, are gradually moving toward online, computer-based environments. Considerable research has been conducted to guide content and presentation of decision aids. However, given the relatively new shift to computer-based support, little attention has been given to how multimedia and interactivity can improve upon paper-based decision aids. The first objective of this review was to summarize published literature into a proposed classification of features that have been integrated into computer-based decision aids. Building on this classification, the second objective was to assess whether integration of specific features was associated with higher-quality decision making. Relevant studies were located by searching MEDLINE, Embase, CINAHL, and CENTRAL databases. The review identified studies that evaluated computer-based decision aids for adults faced with preference-sensitive medical decisions and reported quality of decision-making outcomes. A thematic synthesis was conducted to develop the classification of features. Subsequently, meta-analyses were conducted based on standardized mean differences (SMD) from randomized controlled trials (RCTs) that reported knowledge or decisional conflict. Further subgroup analyses compared pooled SMDs for decision aids that incorporated a specific feature to other computer-based decision aids that did not incorporate the feature, to assess whether specific features improved quality of decision making. Of 3541 unique publications, 58 studies met the target criteria and were included in the thematic synthesis. The synthesis identified six features: content control, tailoring, patient narratives, explicit values clarification, feedback, and social support. A subset of 26 RCTs from the thematic synthesis was used to conduct the meta-analyses. As expected, computer-based decision aids performed better than usual care or alternative aids; however, some features performed better than

Design and implementation of distributed spatial computing node based on WPS

International Nuclear Information System (INIS)

Liu, Liping; Li, Guoqing; Xie, Jibo

2014-01-01

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Modelling and simulation-based acquisition decision support: present & future

CSIR Research Space (South Africa)

Naidoo, S

2009-10-01

Full Text Available stream_source_info Naidoo1_2009.pdf.txt stream_content_type text/plain stream_size 24551 Content-Encoding UTF-8 stream_name Naidoo1_2009.pdf.txt Content-Type text/plain; charset=UTF-8 1 Modelling & Simulation...-Based Acquisition Decision Support: Present & Future Shahen Naidoo Abstract The Ground Based Air Defence System (GBADS) Programme, of the South African Army has been applying modelling and simulation (M&S) to provide acquisition decision and doctrine...

Promotion of technical harmonisation on risk-based decision making

International Nuclear Information System (INIS)

Kirchsteiger, Christian; Cojazzi, Giacomo

2000-01-01

The EC-JRC International Workshop on Promotion of Technical Harmonisation on Risk-Based Decision Making, held at Stresa and Ispra, Italy, 22-25 May 2000, was an experts meeting to discuss the possible need of developing an internationally accepted generic 'standard' for risk-based decision making.This paper briefly describes the workshop background, its organisation and summarises its main results and conclusions; it reflects the personal opinions of the authors and in no way commits the European Commission. (author)

Value-based attentional capture influences context-dependent decision-making

Science.gov (United States)

Cha, Kexin; Rangsipat, Napat; Serences, John T.

2015-01-01

Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making. PMID:25995350

Predicting the activity of drugs for a group of imidazopyridine anticoccidial compounds.

Science.gov (United States)

Si, Hongzong; Lian, Ning; Yuan, Shuping; Fu, Aiping; Duan, Yun-Bo; Zhang, Kejun; Yao, Xiaojun

2009-10-01

Gene expression programming (GEP) is a novel machine learning technique. The GEP is used to build nonlinear quantitative structure-activity relationship model for the prediction of the IC(50) for the imidazopyridine anticoccidial compounds. This model is based on descriptors which are calculated from the molecular structure. Four descriptors are selected from the descriptors' pool by heuristic method (HM) to build multivariable linear model. The GEP method produced a nonlinear quantitative model with a correlation coefficient and a mean error of 0.96 and 0.24 for the training set, 0.91 and 0.52 for the test set, respectively. It is shown that the GEP predicted results are in good agreement with experimental ones.

The Influence Of Planning Decisions Regarding Land Evaluation Based On A Selected Local Real Estate Market

Directory of Open Access Journals (Sweden)

Foryś Iwona

2015-12-01

Full Text Available The article analyzes the influence of planning decisions on changes taking place on the local real estate market. Three stages of the planning process are studied in particular, i.e.: the passing of the study of conditions and directions of spatial development, the Commune Council Resolution on initiating the formulation of a local spatial development plan, and finally the Resolution on accepting the local plan, as well as the effects of these activities on the land value in a given real estate market in Stargard Szczeciński, in the West-Pomeranian (Zachodniopomorskie Province of Poland. The object of the research is to identify the indicated relationships on a given real estate market, on which respective spatial planning stages can be distinguished, as well as the strength and course of the analyzed relationships. The study will verify the research hypothesis regarding the strength and directions of the effects of planning decisions as the direct and indirect reasons behind price changes on the real estate market. The analysis uses data from the Price Register and the District Starosty Values, along with statistical and public information data and the authors' own studies.

Risk-based decision making for terrorism applications.

Science.gov (United States)

Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

2009-03-01

This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.

FEMA's Earthquake Incident Journal: A Web-Based Data Integration and Decision Support Tool for Emergency Management

Science.gov (United States)

Jones, M.; Pitts, R.

2017-12-01

For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that

Developing shape analysis tools to assist complex spatial decision making

Energy Technology Data Exchange (ETDEWEB)

Mackey, H.E. [Westinghouse Savannah River Company, AIKEN, SC (United States); Ehler, G.B.; Cowen, D. [South Carolina Univ., Columbia, SC (United States)

1996-05-31

The objective of this research was to develop and implement a shape identification measure within a geographic information system, specifically one that incorporates analytical modeling for site location planning. The application that was developed incorporated a location model within a raster-based GIS, which helped address critical performance issues for the decision support system. Binary matrices, which approximate the object`s geometrical form, are passed over the grided data structure and allow identification of irregular and regularly shaped objects. Lastly, the issue of shape rotation is addressed and is resolved by constructing unique matrices corresponding to the object`s orientation

Developing shape analysis tools to assist complex spatial decision making

International Nuclear Information System (INIS)

Mackey, H.E.; Ehler, G.B.; Cowen, D.

1996-01-01

The objective of this research was to develop and implement a shape identification measure within a geographic information system, specifically one that incorporates analytical modeling for site location planning. The application that was developed incorporated a location model within a raster-based GIS, which helped address critical performance issues for the decision support system. Binary matrices, which approximate the object's geometrical form, are passed over the grided data structure and allow identification of irregular and regularly shaped objects. Lastly, the issue of shape rotation is addressed and is resolved by constructing unique matrices corresponding to the object's orientation

Semantic Metadata for Heterogeneous Spatial Planning Documents

Science.gov (United States)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

Science.gov (United States)

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Supporting decision-making processes for evidence-based mental health promotion.

Science.gov (United States)

Jané-Llopis, Eva; Katschnig, Heinz; McDaid, David; Wahlbeck, Kristian

2011-12-01

The use of evidence is critical in guiding decision-making, but evidence from effect studies will be only one of a number of factors that will need to be taken into account in the decision-making processes. Equally important for policymakers will be the use of different types of evidence including implementation essentials and other decision-making principles such as social justice, political, ethical, equity issues, reflecting public attitudes and the level of resources available, rather than be based on health outcomes alone. This paper, aimed to support decision-makers, highlights the importance of commissioning high-quality evaluations, the key aspects to assess levels of evidence, the importance of supporting evidence-based implementation and what to look out for before, during and after implementation of mental health promotion and mental disorder prevention programmes.

Using basic geographic information systems functionality to support sustainable forest management decision making and post-decision assessments

Science.gov (United States)

Ronald E. McRoberts; R. James Barbour; Krista M. Gebert; Greg C. Liknes; Mark D. Nelson; Dacia M. Meneguzzo; et al.

2006-01-01

Sustainable management of natural resources requires informed decision making and post-decision assessments of the results of those decisions. Increasingly, both activities rely on analyses of spatial data in the forms of maps and digital data layers. Fortunately, a variety of supporting maps and data layers rapidly are becoming available. Unfortunately, however, user-...

Detailed Sponge City Planning Based on Hierarchical Fuzzy Decision-Making: A Case Study on Yangchen Lake

Directory of Open Access Journals (Sweden)

Junyu Zhang

2017-11-01

Full Text Available We proposed a Hierarchical Fuzzy Inference System (HFIS framework to offer better decision supports with fewer user-defined data (uncertainty. The framework consists two parts: a fuzzified Geographic Information System (GIS and a HFIS system. The former provides comprehensive information on the criterion unit and the latter helps in making more robust decisions. The HFIS and the traditional Multi-Criteria Decision Making (MCDM method were applied to a case study and compared. The fuzzified GIS maps maintained a majority of the dominant characteristics of the criterion unit but also revealed some non-significant information according to the surrounding environment. The urban planning map generated by the two methods shares similar strategy choices (6% difference, while the spatial distribution of strategies shares 69.7% in common. The HFIS required fewer subjective decisions than the MCDM (34 user-defined decision rules vs. 141 manual evaluations.

Data Clustering and Evolving Fuzzy Decision Tree for Data Base Classification Problems

Science.gov (United States)

Chang, Pei-Chann; Fan, Chin-Yuan; Wang, Yen-Wen

Data base classification suffers from two well known difficulties, i.e., the high dimensionality and non-stationary variations within the large historic data. This paper presents a hybrid classification model by integrating a case based reasoning technique, a Fuzzy Decision Tree (FDT), and Genetic Algorithms (GA) to construct a decision-making system for data classification in various data base applications. The model is major based on the idea that the historic data base can be transformed into a smaller case-base together with a group of fuzzy decision rules. As a result, the model can be more accurately respond to the current data under classifying from the inductions by these smaller cases based fuzzy decision trees. Hit rate is applied as a performance measure and the effectiveness of our proposed model is demonstrated by experimentally compared with other approaches on different data base classification applications. The average hit rate of our proposed model is the highest among others.

Rationality versus reality: the challenges of evidence-based decision making for health policy makers.

Science.gov (United States)

McCaughey, Deirdre; Bruning, Nealia S

2010-05-26

Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the EBDM/EBPM process can be

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

Directory of Open Access Journals (Sweden)

Bruning Nealia S

2010-05-01

Full Text Available Abstract Background Current healthcare systems have extended the evidence-based medicine (EBM approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM and evidence-based policy making (EBPM because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial

Rationality versus reality: the challenges of evidence-based decision making for health policy makers

Science.gov (United States)

2010-01-01

Background Current healthcare systems have extended the evidence-based medicine (EBM) approach to health policy and delivery decisions, such as access-to-care, healthcare funding and health program continuance, through attempts to integrate valid and reliable evidence into the decision making process. These policy decisions have major impacts on society and have high personal and financial costs associated with those decisions. Decision models such as these function under a shared assumption of rational choice and utility maximization in the decision-making process. Discussion We contend that health policy decision makers are generally unable to attain the basic goals of evidence-based decision making (EBDM) and evidence-based policy making (EBPM) because humans make decisions with their naturally limited, faulty, and biased decision-making processes. A cognitive information processing framework is presented to support this argument, and subtle cognitive processing mechanisms are introduced to support the focal thesis: health policy makers' decisions are influenced by the subjective manner in which they individually process decision-relevant information rather than on the objective merits of the evidence alone. As such, subsequent health policy decisions do not necessarily achieve the goals of evidence-based policy making, such as maximizing health outcomes for society based on valid and reliable research evidence. Summary In this era of increasing adoption of evidence-based healthcare models, the rational choice, utility maximizing assumptions in EBDM and EBPM, must be critically evaluated to ensure effective and high-quality health policy decisions. The cognitive information processing framework presented here will aid health policy decision makers by identifying how their decisions might be subtly influenced by non-rational factors. In this paper, we identify some of the biases and potential intervention points and provide some initial suggestions about how the

Power generation capacity planning under budget constraint in developing countries

International Nuclear Information System (INIS)

Afful-Dadzie, Anthony; Afful-Dadzie, Eric; Awudu, Iddrisu; Banuro, Joseph Kwaku

2017-01-01

Highlights: • A long term stochastic GEP model with budget constraint is developed. • Model suitable for analyzing GEP problems in developing countries. • Model determines optimal mix, size and timing of future generation capacity needs. • A real case study of the Ghana GEP problem was employed. • Insufficient budget leads to costly generation capacity expansion plans. - Abstract: This paper presents a novel multi-period stochastic optimization model for studying long-term power generation capacity planning in developing countries. A stylized model is developed to achieve three objectives: (1) to serve as a tool for determining optimal mix, size and timing of power generation types in the face of budget constraint, (2) to help decision makers appreciate the consequences of capacity expansion decisions on level of unserved electricity demand and its attendant impact on the national economy, and (3) to encourage the habit of periodic savings towards new generation capacity financing. The problem is modeled using a stochastic mixed-integer linear programming (MILP) technique under demand uncertainty. The effectiveness of the model, together with valuable insights derived from considering different levels of budget constraints are demonstrated using Ghana as a case study. The results indicate that at an annual savings equivalent to 0.75% of GDP, Ghana could finance the needed generation capacity to meet approximately 95% of its annual electricity demand between 2016 and 2035. Additionally, it is observed that as financial constraint becomes tighter, decisions on the mix of new generation capacities tend to be more costly compared to when sufficient funds are available.

Research on presentation and query service of geo-spatial data based on ontology

Science.gov (United States)

Li, Hong-wei; Li, Qin-chao; Cai, Chang

2008-10-01

The paper analyzed the deficiency on presentation and query of geo-spatial data existed in current GIS, discussed the advantages that ontology possessed in formalization of geo-spatial data and the presentation of semantic granularity, taken land-use classification system as an example to construct domain ontology, and described it by OWL; realized the grade level and category presentation of land-use data benefited from the thoughts of vertical and horizontal navigation; and then discussed query mode of geo-spatial data based on ontology, including data query based on types and grade levels, instances and spatial relation, and synthetic query based on types and instances; these methods enriched query mode of current GIS, and is a useful attempt; point out that the key point of the presentation and query of spatial data based on ontology is to construct domain ontology that can correctly reflect geo-concept and its spatial relation and realize its fine formalization description.

Assessing the Development of Kenya National Spatial Data ...

African Journals Online (AJOL)

Spatial data plays a vital role in developmental activities, whether natural resource management or socio-economic development. Spatial Data Infrastructures (SDIs) facilitate access, sharing and dissemination of spatial data necessary for complex decision-making processes of the future. Thus, conducting SDI assessment ...

Value-based attentional capture influences context-dependent decision-making.

Science.gov (United States)

Itthipuripat, Sirawaj; Cha, Kexin; Rangsipat, Napat; Serences, John T

2015-07-01

Normative theories posit that value-based decision-making is context independent. However, decisions between two high-value options can be suboptimally biased by the introduction of a third low-value option. This context-dependent modulation is consistent with the divisive normalization of the value of each stimulus by the total value of all stimuli. In addition, an independent line of research demonstrates that pairing a stimulus with a high-value outcome can lead to attentional capture that can mediate the efficiency of visual information processing. Here we tested the hypothesis that value-based attentional capture interacts with value-based normalization to influence the optimality of decision-making. We used a binary-choice paradigm in which observers selected between two targets and the color of each target indicated the magnitude of their reward potential. Observers also had to simultaneously ignore a task-irrelevant distractor rendered in a color that was previously associated with a specific reward magnitude. When the color of the task-irrelevant distractor was previously associated with a high reward, observers responded more slowly and less optimally. Moreover, as the learned value of the distractor increased, electrophysiological data revealed an attenuation of the lateralized N1 and N2Pc responses evoked by the relevant choice stimuli and an attenuation of the late positive deflection (LPD). Collectively, these behavioral and electrophysiological data suggest that value-based attentional capture and value-based normalization jointly mediate the influence of context on free-choice decision-making. Copyright © 2015 the American Physiological Society.

Enabling Participatory Decision Making Through Web-Based GIS

Energy Technology Data Exchange (ETDEWEB)

Sheng, Grant; Yam, Kevin; Hassas, Aranak [York Univ., Toronto, ON (Canada). Faculty of Environmental Studies

2001-07-01

The concept of 'Sustainable Communities' is taking an increasingly strong hold in discourses on civil society and sustainability. A basic tenet of the sustainability paradigm is that a community should be empowered to participate in the decision making process on issues that affect the well-being and continual development of the community. Meaningful participation in such a process requires that stakeholders have unrestricted and easy access to all relevant information regarding the issue at hand and that they have an effective means for communicating with one another without the barriers often posed by spatial, temporal, skill and financial constraints. The controversial nature of, and the intense emotion associated with nuclear waste disposal make it especially important that the principles of 'right-to-know' and 'participatory decision making' be upheld for communities engaged in any aspect of, or during any phase of, a site selection process. Whether a community is being considered as a potential host site, located along the route for transport of the waste material, or simply within a general region in which the siting may affect the economic and environmental well-being of the community, they all share, to varying degrees, a common concern: 'how will it affect me, my family, and my community?' Answering this question to the satisfaction of all stakeholders is one of the most challenging tasks in a site selection process. More than three decades of research has clearly demonstrated that addressing this concern goes far beyond simply 'supplying enough information' or even the 'appropriate information'. Experience has shown that no amount of public information programs, education programs, public hearing etc., will satisfy all parties involved. There are at least two major reasons for this: The different values held by people affect how they perceive even fundamental issues such as fairness, justice

The impact of design-based modeling instruction on seventh graders' spatial abilities and model-based argumentation

Science.gov (United States)

McConnell, William J.

Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students' spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal's form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students' arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed

onlineDeCISion.org: a web-based decision aid for DCIS treatment.

Science.gov (United States)

Ozanne, Elissa M; Schneider, Katharine H; Soeteman, Djøra; Stout, Natasha; Schrag, Deborah; Fordis, Michael; Punglia, Rinaa S

2015-11-01

Women diagnosed with DCIS face complex treatment decisions and often do so with inaccurate and incomplete understanding of the risks and benefits involved. Our objective was to create a tool to guide these decisions for both providers and patients. We developed a web-based decision aid designed to provide clinicians with tailored information about a patient’s recurrence risks and survival outcomes following different treatment strategies for DCIS. A theoretical framework, microsimulation model (Soeteman et al., J Natl Cancer 105:774–781, 2013) and best practices for web-based decision tools guided the development of the decision aid. The development process used semi-structured interviews and usability testing with key stakeholders, including a diverse group of multidisciplinary clinicians and a patient advocate. We developed onlineDeCISion.​org to include the following features that were rated as important by the stakeholders: (1) descriptions of each of the standard treatment options available; (2) visual projections of the likelihood of time-specific (10-year and lifetime) breast-preservation, recurrence, and survival outcomes; and (3) side-by-side comparisons of down-stream effects of each treatment choice. All clinicians reviewing the decision aid in usability testing were interested in using it in their clinical practice. The decision aid is available in a web-based format and is planned to be publicly available. To improve treatment decision making in patients with DCIS, we have developed a web-based decision aid onlineDeCISion.​org that conforms to best practices and that clinicians are interested in using in their clinics with patients to better inform treatment decisions.

A Design Pattern for Decentralised Decision Making

Science.gov (United States)

Valentini, Gabriele; Fernández-Oto, Cristian; Dorigo, Marco

2015-01-01

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling. PMID:26496359

SPATIAL VARIETY AND DISTRIBUTION OF TRADITIONAL MARKETS IN SURAKARTA AS POTENTIAL FACTORS IN IMPROVING SPATIAL-BASED MANAGEMENT

Directory of Open Access Journals (Sweden)

Istijabatul Aliyah

2017-02-01

Full Text Available Traditional markets function as trading place, socio-culture interaction, and recreation facility either in regional or urban scope. Distribution and variety of spatial condition influence traditional markets’ planning both physically and non-physically. Therefore, this research aimed to conduct a mapping of traditional markets’ spatial distribution and variety as potential factors to improve spatial-based management. Analysis methods including: (1 Mapping by employing Geographic Information System, (2 Category Based Analysis (CBA, and (3 Interactive Analysis were applied in Surakarta City as the research location. The result of this research signifies that spatial variety and distribution of traditional markets in Surakarta had similar pattern between one market to others; overlapping service function; specific commodity types in accordance with the market’s characteristics; diverse operating hours. Spatial variety and distribution could be potential factors to improve traditional market management as shopping service. This result was contrasted with Central Place Theory by Christaller and NÆss & Jensen’s research finding stating that distance became a key factor influencing accessibility to a number of activity facilities. Therefore, distance toward the service center is not considered as the main factor in traditional market management. The main factor in managing and controlling traditional markets’ development includes service function, commodity specification, and operating hour’s flexibility.

Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks

Science.gov (United States)

Horita, Flávio E. A.; Albuquerque, João Porto de; Degrossi, Lívia C.; Mendiondo, Eduardo M.; Ueyama, Jó

2015-07-01

Effective flood risk management requires updated information to ensure that the correct decisions can be made. This can be provided by Wireless Sensor Networks (WSN) which are a low-cost means of collecting updated information about rivers. Another valuable resource is Volunteered Geographic Information (VGI) which is a comparatively new means of improving the coverage of monitored areas because it is able to supply supplementary information to the WSN and thus support decision-making in flood risk management. However, there still remains the problem of how to combine WSN data with VGI. In this paper, an attempt is made to investigate AGORA-DS, which is a Spatial Decision Support System (SDSS) that is able to make flood risk management more effective by combining these data sources, i.e. WSN with VGI. This approach is built over a conceptual model that complies with the interoperable standards laid down by the Open Geospatial Consortium (OGC) - e.g. Sensor Observation Service (SOS) and Web Feature Service (WFS) - and seeks to combine and present unified information in a web-based decision support tool. This work was deployed in a real scenario of flood risk management in the town of São Carlos in Brazil. The evidence obtained from this deployment confirmed that interoperable standards can support the integration of data from distinct data sources. In addition, they also show that VGI is able to provide information about areas of the river basin which lack data since there is no appropriate station in the area. Hence it provides a valuable support for the WSN data. It can thus be concluded that AGORA-DS is able to combine information provided by WSN and VGI, and provide useful information for supporting flood risk management.

Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming

Directory of Open Access Journals (Sweden)

I. Ilie

2017-09-01

Full Text Available Accurate model representation of land–atmosphere carbon fluxes is essential for climate projections. However, the exact responses of carbon cycle processes to climatic drivers often remain uncertain. Presently, knowledge derived from experiments, complemented by a steadily evolving body of mechanistic theory, provides the main basis for developing such models. The strongly increasing availability of measurements may facilitate new ways of identifying suitable model structures using machine learning. Here, we explore the potential of gene expression programming (GEP to derive relevant model formulations based solely on the signals present in data by automatically applying various mathematical transformations to potential predictors and repeatedly evolving the resulting model structures. In contrast to most other machine learning regression techniques, the GEP approach generates readable models that allow for prediction and possibly for interpretation. Our study is based on two cases: artificially generated data and real observations. Simulations based on artificial data show that GEP is successful in identifying prescribed functions, with the prediction capacity of the models comparable to four state-of-the-art machine learning methods (random forests, support vector machines, artificial neural networks, and kernel ridge regressions. Based on real observations we explore the responses of the different components of terrestrial respiration at an oak forest in south-eastern England. We find that the GEP-retrieved models are often better in prediction than some established respiration models. Based on their structures, we find previously unconsidered exponential dependencies of respiration on seasonal ecosystem carbon assimilation and water dynamics. We noticed that the GEP models are only partly portable across respiration components, the identification of a general terrestrial respiration model possibly prevented by equifinality issues. Overall

Reverse engineering model structures for soil and ecosystem respiration: the potential of gene expression programming

Science.gov (United States)

Ilie, Iulia; Dittrich, Peter; Carvalhais, Nuno; Jung, Martin; Heinemeyer, Andreas; Migliavacca, Mirco; Morison, James I. L.; Sippel, Sebastian; Subke, Jens-Arne; Wilkinson, Matthew; Mahecha, Miguel D.

2017-09-01

Accurate model representation of land-atmosphere carbon fluxes is essential for climate projections. However, the exact responses of carbon cycle processes to climatic drivers often remain uncertain. Presently, knowledge derived from experiments, complemented by a steadily evolving body of mechanistic theory, provides the main basis for developing such models. The strongly increasing availability of measurements may facilitate new ways of identifying suitable model structures using machine learning. Here, we explore the potential of gene expression programming (GEP) to derive relevant model formulations based solely on the signals present in data by automatically applying various mathematical transformations to potential predictors and repeatedly evolving the resulting model structures. In contrast to most other machine learning regression techniques, the GEP approach generates readable models that allow for prediction and possibly for interpretation. Our study is based on two cases: artificially generated data and real observations. Simulations based on artificial data show that GEP is successful in identifying prescribed functions, with the prediction capacity of the models comparable to four state-of-the-art machine learning methods (random forests, support vector machines, artificial neural networks, and kernel ridge regressions). Based on real observations we explore the responses of the different components of terrestrial respiration at an oak forest in south-eastern England. We find that the GEP-retrieved models are often better in prediction than some established respiration models. Based on their structures, we find previously unconsidered exponential dependencies of respiration on seasonal ecosystem carbon assimilation and water dynamics. We noticed that the GEP models are only partly portable across respiration components, the identification of a general terrestrial respiration model possibly prevented by equifinality issues. Overall, GEP is a promising

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

Science.gov (United States)

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

Science.gov (United States)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land

Applications of decision theory to computer-based adaptive instructional systems

NARCIS (Netherlands)

Vos, Hendrik J.

1988-01-01

This paper considers applications of decision theory to the problem of instructional decision-making in computer-based adaptive instructional systems, using the Minnesota Adaptive Instructional System (MAIS) as an example. The first section indicates how the problem of selecting the appropriate

Tactical decision games - developing scenario-based training for decision-making in distributed teams

NARCIS (Netherlands)

Lauche, K.; Crichton, M.; Bayerl, P.S.

2009-01-01

Team training should reflect the increasing complexity of decision-making environments. Guidelines for scenario-based training were adopted for a distributed setting and tested in a pilot training session with a distributed team in the offshore oil industry. Participants valued the scenario as

SEMANTIC METADATA FOR HETEROGENEOUS SPATIAL PLANNING DOCUMENTS

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A. Iwaniak

2016-09-01

Full Text Available Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa. The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

A precategorical spatial-data metamodel

OpenAIRE

Steven A Roberts; G Brent Hall; Paul H Calamai

2006-01-01

Increasing recognition of the extent and speed of habitat fragmentation and loss, particularly in the urban fringe, is driving the need to analyze qualitatively and quantitatively regional landscape structure for decision support in land-use planning and environmental-policy implementation. The spatial analysis required in this area is not well served by existing spatial-data models. In this paper a new theoretical spatial-data metamodel is introduced as a tool for addressing such needs and a...

Simulating Spatial Growth Patterns in Developing Countries: A Case of Shama in the Western Region of Ghana.

Science.gov (United States)

Inkoom, J. N.; Nyarko, B. K.

2014-12-01

The integration of geographic information systems (GIS) and agent-based modelling (ABM) can be an efficient tool to improve spatial planning practices. This paper utilizes GIS and ABM approaches to simulate spatial growth patterns of settlement structures in Shama. A preliminary household survey on residential location decision-making choice served as the behavioural rule for household agents in the model. Physical environment properties of the model were extracted from a 2005 image implemented in NetLogo. The resulting growth pattern model was compared with empirical growth patterns to ascertain the model's accuracy. The paper establishes that the development of unplanned structures and its evolving structural pattern are a function of land price, proximity to economic centres, household economic status and location decision-making patterns. The application of the proposed model underlines its potential for integration into urban planning policies and practices, and for understanding residential decision-making processes in emerging cities in developing countries. Key Words: GIS; Agent-based modelling; Growth patterns; NetLogo; Location decision making; Computational Intelligence.

Ontology-Based Retrieval of Spatially Related Objects for Location Based Services

Science.gov (United States)

Haav, Hele-Mai; Kaljuvee, Aivi; Luts, Martin; Vajakas, Toivo

Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.

Research-based-decision-making in Canadian health organizations: a behavioural approach.

Science.gov (United States)

Jbilou, Jalila; Amara, Nabil; Landry, Réjean

2007-06-01

Decision making in Health sector is affected by a several elements such as economic constraints, political agendas, epidemiologic events, managers' values and environment... These competing elements create a complex environment for decision making. Research-Based-Decision-Making (RBDM) offers an opportunity to reduce the generated uncertainty and to ensure efficacy and efficiency in health administrations. We assume that RBDM is dependant on decision makers' behaviour and the identification of the determinants of this behaviour can help to enhance research results utilization in health sector decision making. This paper explores the determinants of RBDM as a personal behaviour among managers and professionals in health administrations in Canada. From the behavioural theories and the existing literature, we build a model measuring "RBDM" as an index based on five items. These items refer to the steps accomplished by a decision maker while developing a decision which is based on evidence. The determinants of RBDM behaviour are identified using data collected from 942 health care decision makers in Canadian health organizations. Linear regression is used to model the behaviour RBDM. Determinants of this behaviour are derived from Triandis Theory and Bandura's construct "self-efficacy." The results suggest that to improve research use among managers in Canadian governmental health organizations, strategies should focus on enhancing exposition to evidence through facilitating communication networks, partnerships and links between researchers and decision makers, with the key long-term objective of developing a culture that supports and values the contribution that research can make to decision making in governmental health organizations. Nevertheless, depending on the organizational level, determinants of RBDM are different. This difference has to be taken into account if RBDM adoption is desired. Decision makers in Canadian health organizations (CHO) can help to build

Decision support tools : midterm review report Knowledge for Climate Theme 8

NARCIS (Netherlands)

Ierland, van E.C.

2012-01-01

The KfC program Decision Support Tools aims at improving tools for design and evaluation of adaptation strategies with a special focus on spatial planning and cross cutting issues. The program focuses on three core elements 1. tools for formulation of the adaptation task, based on climate scenarios

Ignorance- versus evidence-based decision making: a decision time analysis of the recognition heuristic.

Science.gov (United States)

Hilbig, Benjamin E; Pohl, Rüdiger F

2009-09-01

According to part of the adaptive toolbox notion of decision making known as the recognition heuristic (RH), the decision process in comparative judgments-and its duration-is determined by whether recognition discriminates between objects. By contrast, some recently proposed alternative models predict that choices largely depend on the amount of evidence speaking for each of the objects and that decision times thus depend on the evidential difference between objects, or the degree of conflict between options. This article presents 3 experiments that tested predictions derived from the RH against those from alternative models. All experiments used naturally recognized objects without teaching participants any information and thus provided optimal conditions for application of the RH. However, results supported the alternative, evidence-based models and often conflicted with the RH. Recognition was not the key determinant of decision times, whereas differences between objects with respect to (both positive and negative) evidence predicted effects well. In sum, alternative models that allow for the integration of different pieces of information may well provide a better account of comparative judgments. (c) 2009 APA, all rights reserved.

Spatial frequency information modulates response inhibition and decision-making processes.

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Sara Jahfari

Full Text Available We interact with the world through the assessment of available, but sometimes imperfect, sensory information. However, little is known about how variance in the quality of sensory information affects the regulation of controlled actions. In a series of three experiments, comprising a total of seven behavioral studies, we examined how different types of spatial frequency information affect underlying processes of response inhibition and selection. Participants underwent a stop-signal task, a two choice speed/accuracy balance experiment, and a variant of both these tasks where prior information was given about the nature of stimuli. In all experiments, stimuli were either intact, or contained only high-, or low- spatial frequencies. Overall, drift diffusion model analysis showed a decreased rate of information processing when spatial frequencies were removed, whereas the criterion for information accumulation was lowered. When spatial frequency information was intact, the cost of response inhibition increased (longer SSRT, while a correct response was produced faster (shorter reaction times and with more certainty (decreased errors. When we manipulated the motivation to respond with a deadline (i.e., be fast or accurate, removal of spatial frequency information slowed response times only when instructions emphasized accuracy. However, the slowing of response times did not improve error rates, when compared to fast instruction trials. These behavioral studies suggest that the removal of spatial frequency information differentially affects the speed of response initiation, inhibition, and the efficiency to balance fast or accurate responses. More generally, the present results indicate a task-independent influence of basic sensory information on strategic adjustments in action control.

Minimizing Erosion and Agro-Pollutants Transport from Furrow Irrigated Fields to the Nearby Water Body Using Spatially-Explicit Agent Based Model and Decision Optimization Platform

Science.gov (United States)

Ghoveisi, H.; Al Dughaishi, U.; Kiker, G.

2017-12-01

Maintaining water quality in agricultural watersheds is a worldwide challenge, especially where furrow irrigation is being practiced. The Yakima River Basin watershed in south central Washington State, (USA) is an example of these impacted areas with elevated load of sediments and other agricultural products due to runoff from furrow-irrigated fields. Within the Yakima basin, the Granger Drain watershed (area of 75 km2) is particularly challenged in this regard with more than 400 flood-irrigated individual parcels (area of 21 km2) growing a variety of crops from maize to grapes. Alternatives for improving water quality from furrow-irrigated parcels include vegetated filter strip (VFS) implementation, furrow water application efficiency, polyacrylamide (PAM) application and irrigation scheduling. These alternatives were simulated separately and in combinations to explore potential Best Management Practices (BMPs) for runoff-related-pollution reduction in a spatially explicit, agent based modeling system (QnD:GrangerDrain). Two regulatory scenarios were tested to BMP adoption within individual parcels. A blanket-style regulatory scenario simulated a total of 60 BMP combinations implemented in all 409 furrow-irrigated parcels. A second regulatory scenario simulated the BMPs in 119 furrow-irrigated parcels designated as "hotspots" based on a standard 12 Mg ha-1 seasonal sediment load. The simulated cumulative runoff and sediment loading from all BMP alternatives were ranked using Multiple Criteria Decision Analysis (MCDA), specifically the Stochastic Multi-Attribute Acceptability Analysis (SMAA) method. Several BMP combinations proved successful in reducing loads below a 25 NTU (91 mg L-1) regulatory sediment concentration. The QnD:GrangerDrain simulations and subsequent MCDA ranking revealed that the BMP combinations of 5 m-VFS and high furrow water efficiency were highly ranked alternatives for both the blanket and hotspot scenarios.

Opioid Modulation of Value-Based Decision-Making in Healthy Humans.

Science.gov (United States)

Eikemo, Marie; Biele, Guido; Willoch, Frode; Thomsen, Lotte; Leknes, Siri

2017-08-01

Modifying behavior to maximize reward is integral to adaptive decision-making. In rodents, the μ-opioid receptor (MOR) system encodes motivation and preference for high-value rewards. Yet it remains unclear whether and how human MORs contribute to value-based decision-making. We reasoned that if the human MOR system modulates value-based choice, this would be reflected by opposite effects of agonist and antagonist drugs. In a double-blind pharmacological cross-over study, 30 healthy men received morphine (10 mg), placebo, and the opioid antagonist naltrexone (50 mg). They completed a two-alternative decision-making task known to induce a considerable bias towards the most frequently rewarded response option. To quantify MOR involvement in this bias, we fitted accuracy and reaction time data with the drift-diffusion model (DDM) of decision-making. The DDM analysis revealed the expected bidirectional drug effects for two decision subprocesses. MOR stimulation with morphine increased the preference for the stimulus with high-reward probability (shift in starting point). Compared to placebo, morphine also increased, and naltrexone reduced, the efficiency of evidence accumulation. Since neither drug affected motor-coordination, speed-accuracy trade-off, or subjective state (indeed participants were still blinded after the third session), we interpret the MOR effects on evidence accumulation efficiency as a consequence of changes in effort exerted in the task. Together, these findings support a role for the human MOR system in value-based choice by tuning decision-making towards high-value rewards across stimulus domains.

Historical Roots of the Spatial, Temporal, and Diversity Scales of Agricultural Decision-Making in Sierra de Santa Marta, Los Tuxtlas

Science.gov (United States)

Negrete-Yankelevich, Simoneta; Porter-Bolland, Luciana; Blanco-Rosas, José Luis; Barois, Isabelle

2013-07-01

Land degradation is a serious problem in tropical mountainous areas. Market prices, technological development, and population growth are often invoked as the prime causes. Using historical agrarian documents, literature sources, and historical population data, we (1) provide quantitative and qualitative evidence that the land degradation present at Sierra de Santa Marta (Los Tuxtlas, Mexico) has involved a historical reduction in the temporal, spatial, and diversity scales, in which individual farmers make management decisions, and has resulted in decreased maize productivity; and (2) analyze how these three scalar changes can be linked to policy, population growth, and agrarian history. We conclude that the historical reduction in the scales of land use decision-making and practices constitutes a present threat to indigenous agricultural heritage. The long-term viability of agriculture requires that initiatives consider incentives for co-responsibility with an initial focus on self-sufficiency.

Hard Decision Fusion based Cooperative Spectrum Sensing in Cognitive Radio System

Directory of Open Access Journals (Sweden)

N. Armi N.M. Saad

2013-09-01

Full Text Available Cooperative spectrum sensing was proposed to combat fading, noise uncertainty, shadowing, and even hidden node problem due to primary users (PUs activity that is not spatially localized. It improves the probability of detection by collaborating to detect PUs signal in cognitive radio (CR system as well. This paper studies cooperative spectrum sensing and signal detection in CR system by implementing hard decision combining in data fusion centre. Through computer simulation, we evaluate the performances of cooperative spectrum sensing and signal detection by employing OR and AND rules as decision combining. Energy detector is used to observe the presence of primary user (PU signal. Those results are compared to non-cooperative signal detection for evaluation. They show that cooperative technique has better performance than non-cooperative. Moreover, signal to noise ratio (SNR with greater than or equal 10 dB and 15 collaborated users in CR system has optimal value for probability of detection.

The Interplay of Hippocampus and Ventromedial Prefrontal Cortex in Memory-Based Decision Making

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Regina A. Weilbächer

2016-12-01

Full Text Available Episodic memory and value-based decision making are two central and intensively studied research domains in cognitive neuroscience, but we are just beginning to understand how they interact to enable memory-based decisions. The two brain regions that have been associated with episodic memory and value-based decision making are the hippocampus and the ventromedial prefrontal cortex, respectively. In this review article, we first give an overview of these brain–behavior associations and then focus on the mechanisms of potential interactions between the hippocampus and ventromedial prefrontal cortex that have been proposed and tested in recent neuroimaging studies. Based on those possible interactions, we discuss several directions for future research on the neural and cognitive foundations of memory-based decision making.

Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping

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Dimitris G. Stavrakoudis

2014-07-01

Full Text Available This study investigates the effectiveness of combining multispectral very high resolution (VHR and hyperspectral satellite imagery through a decision fusion approach, for accurate forest species mapping. Initially, two fuzzy classifications are conducted, one for each satellite image, using a fuzzy output support vector machine (SVM. The classification result from the hyperspectral image is then resampled to the multispectral’s spatial resolution and the two sources are combined using a simple yet efficient fusion operator. Thus, the complementary information provided from the two sources is effectively exploited, without having to resort to computationally demanding and time-consuming typical data fusion or vector stacking approaches. The effectiveness of the proposed methodology is validated in a complex Mediterranean forest landscape, comprising spectrally similar and spatially intermingled species. The decision fusion scheme resulted in an accuracy increase of 8% compared to the classification using only the multispectral imagery, whereas the increase was even higher compared to the classification using only the hyperspectral satellite image. Perhaps most importantly, its accuracy was significantly higher than alternative multisource fusion approaches, although the latter are characterized by much higher computation, storage, and time requirements.

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha

2013-11-25

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Classifiers based on optimal decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

Analytical evaluation of computer-based decision aids

International Nuclear Information System (INIS)

Kisner, R.A.

1985-01-01

This paper introduces a method for evaluating decision aids for nuclear power plant operators. The method involves a two-stage process of classification and analytical evaluation of display form and content. The classification scheme relates each specific aid to one or more general decision-making tasks. Evaluation then proceeds using a normative top-down design process based on the classification scheme by determining or deducing how various design issues associated with this process were resolved by the designer. The result is an assessment of the ''understandability'' of the aid as well as identification of the training and display features necessary to ensure understandability. 7 refs., 4 figs., 1 tab

Perceptual decision neurosciences: a model-based review

NARCIS (Netherlands)

Mulder, M.J.; van Maanen, L.; Forstmann, B.U.

2014-01-01

In this review we summarize findings published over the past 10 years focusing on the neural correlates of perceptual decision-making. Importantly, this review highlights only studies that employ a model-based approach, i.e., they use quantitative cognitive models in combination with neuroscientific

Development of hybrid artificial intelligent based handover decision algorithm

Directory of Open Access Journals (Sweden)

A.M. Aibinu

2017-04-01

Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

Expected Utility Based Decision Making under Z-Information and Its Application.

Science.gov (United States)

Aliev, Rashad R; Mraiziq, Derar Atallah Talal; Huseynov, Oleg H

2015-01-01

Real-world decision relevant information is often partially reliable. The reasons are partial reliability of the source of information, misperceptions, psychological biases, incompetence, and so forth. Z-numbers based formalization of information (Z-information) represents a natural language (NL) based value of a variable of interest in line with the related NL based reliability. What is important is that Z-information not only is the most general representation of real-world imperfect information but also has the highest descriptive power from human perception point of view as compared to fuzzy number. In this study, we present an approach to decision making under Z-information based on direct computation over Z-numbers. This approach utilizes expected utility paradigm and is applied to a benchmark decision problem in the field of economics.

Application of Spatial Models in Making Location Decisions of Wind Power Plant in Poland

Science.gov (United States)

Płuciennik, Monika; Hełdak, Maria; Szczepański, Jakub; Patrzałek, Ciechosław

2017-10-01

In this paper,we explore the process of making decisions on the location of wind power plants in Poland in connection with a gradually increasing consumption of energy from renewable sources and the increase of impact problems of such facilities. The location of new wind power plants attracts much attention, and both positive and negative publicity. Visualisations can be of assistance when choosing the most advantageous location for a plant, as three-dimensional variants of the facility to be constructed can be prepared. This work involves terrestrial laser scanning of an existing wind power plant and 3D modelling followed by. The model could be subsequently used in visualisation of real terrain, with special purpose in local land development plan. This paper shows a spatial model of a wind power plant as a new element of a capital investment process in Poland. Next, we incorporate the model into an undeveloped site, intended for building a wind farm, subject to the requirements for location of power plants.

A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

Directory of Open Access Journals (Sweden)

Burhanuddin M. A.

2011-01-01

Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

OpenAIRE

Huaxiong Li; Xianzhong Zhou

2011-01-01

Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full description on such diverse decisions. In this article, a review of Pawlak rough set models and probabilistic rough set models is presented, and a ...

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

Science.gov (United States)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

The spatial resolution of silicon-based electron detectors in beta-autoradiography.

Science.gov (United States)

Cabello, Jorge; Wells, Kevin

2010-03-21

Thin tissue autoradiography is an imaging modality where ex-vivo tissue sections are placed in direct contact with autoradiographic film. These tissue sections contain a radiolabelled ligand bound to a specific biomolecule under study. This radioligand emits beta - or beta+ particles ionizing silver halide crystals in the film. High spatial resolution autoradiograms are obtained using low energy radioisotopes, such as (3)H where an intrinsic 0.1-1 microm spatial resolution can be achieved. Several digital alternatives have been presented over the past few years to replace conventional film but their spatial resolution has yet to equal film, although silicon-based imaging technologies have demonstrated higher sensitivity compared to conventional film. It will be shown in this work how pixel size is a critical parameter for achieving high spatial resolution for low energy uncollimated beta imaging. In this work we also examine the confounding factors impeding silicon-based technologies with respect to spatial resolution. The study considers charge diffusion in silicon and detector noise, and this is applied to a range of radioisotopes typically used in autoradiography. Finally an optimal detector geometry to obtain the best possible spatial resolution for a specific technology and a specific radioisotope is suggested.

Bases for Decisions on Final Disposal in Finland

International Nuclear Information System (INIS)

Avolahti, Jaana

2001-01-01

The disposal of the spent nuclear fuel is approaching one of the significant milestones in Finland. Social debate on the nuclear waste management is going on aiming at a decision of principle on future directions of spent fuel management. The research so far has required no political decision. This current situation is preceded by preparations for two decades carried out by Posiva Oy who took over the programme managed earlier by Teollisuuden Voinia Oy, one of the country's nuclear power companies. The preparations comprise site investigations, technical concept development, research into long-term safety and an environmental impact assessment. The work carried out by Posiva is under regular assessment by the authorities. Research programmes are drawn up every year and reports are published for open review. The preparations in the next years to come aim at starting the construction of the repository in 2010 and the disposal operations are planned to be started in 2020. Various stakeholders in Finland are involved in the decision-making process on the disposal of spent nuclear fuel. The process started when Posiva as an implementer applied for the Government's Decision in Principle in 1999. The Government made a favourable decision in December 2000 on the basis of different considerations. Among the important bases were the preceding favourable decisions made by the proposed siting municipality and the regulatory authority for radiation safety. At the moment the members of the Parliament are discussing the principles of the disposal in order to be able to vote on the Government's decision in the springtime. This paper discusses similarities and differences between the decisions made so far as regards the deep repository. The objective is to present the significance of the decisions from the point of view of an implementer of the repository. The Decision in Principle does not give any consent to start constructing the repository. Licenses for construction and

Spatial ability of slow learners based on Hubert Maier theory

Science.gov (United States)

Permatasari, I.; Pramudya, I.; Kusmayadi, T. A.

2018-03-01

Slow learners are children who have low learning achievement (under the average of normal children) in one or all of the academic field, but they are not classified as a mentally retarded children. Spatial ability developed according to age and level of knowledge possessed, both from the neighborhood and formal education. Analyzing the spatial ability of students is important for teachers, as an effort to improve the quality of learning for slow learners. Especially on the implementation of inclusion school which is developing in Indonesia. This research used a qualitative method and involved slow learner students as the subject. Based on the data analysis it was found the spatial ability of slow learners, there were: spatial perception, students were able to describe the other shape of object when its position changed; spatial visualisation, students were able to describe the materials that construct an object; mental rotation, students cannot describe the object being rotated; spatial relation, students cannot describe the relations of same objects; spatial orientation, students were able to describe object from the others perspective.

Decision rules for decision tables with many-valued decisions

KAUST Repository

Chikalov, Igor

2011-01-01

In the paper, authors presents a greedy algorithm for construction of exact and partial decision rules for decision tables with many-valued decisions. Exact decision rules can be \\'over-fitted\\', so instead of exact decision rules with many attributes, it is more appropriate to work with partial decision rules with smaller number of attributes. Based on results for set cover problem authors study bounds on accuracy of greedy algorithm for exact and partial decision rule construction, and complexity of the problem of minimization of decision rule length. © 2011 Springer-Verlag.

Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters

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Tao Ding

2016-01-01

Full Text Available Multiple attribute decision making (MADM problem is one of the most common and popular research fields in the theory of decision science. A variety of methods have been proposed to deal with such problems. Nevertheless, many of them assumed that attribute weights are determined by different types of additional preference information which will result in subjective decision making. In order to solve such problems, in this paper, we propose a novel MADM approach based on cross-evaluation with uncertain parameters. Specifically, the proposed approach assumes that all attribute weights are uncertain. It can overcome the drawback in prior research that the alternatives’ ranking may be determined by a single attribute with an overestimated weight. In addition, the proposed method can also balance the mean and deviation of each alternative’s cross-evaluation score to guarantee the stability of evaluation. Then, this method is extended to a more generalized situation where the attribute values are also uncertain. Finally, we illustrate the applicability of the proposed method by revisiting two reported studies and by a case study on the selection of community service companies in the city of Hefei in China.

Increased Reliance on Value-based Decision Processes Following Motor Cortex Disruption.

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Zénon, Alexandre; Klein, Pierre-Alexandre; Alamia, Andrea; Boursoit, François; Wilhelm, Emmanuelle; Duque, Julie

2015-01-01

During motor decision making, the neural activity in primary motor cortex (M1) encodes dynamically the competition occurring between potential action plans. A common view is that M1 represents the unfolding of the outcome of a decision process taking place upstream. Yet, M1 could also be directly involved in the decision process. Here we tested this hypothesis by assessing the effect of M1 disruption on a motor decision-making task. We applied continuous theta burst stimulation (cTBS) to inhibit either left or right M1 in different groups of subjects and included a third control group with no stimulation. Following cTBS, participants performed a task that required them to choose between two finger key-presses with the right hand according to both perceptual and value-based information. Effects were assessed by means of generalized linear mixed models and computational simulations. In all three groups, subjects relied both on perceptual (P < 0.0001) and value-based information (P = 0.003) to reach a decision. Yet, left M1 disruption led to an increased reliance on value-based information (P = 0.03). This result was confirmed by a computational model showing an increased weight of the valued-based process on the right hand finger choices following left M1 cTBS (P < 0.01). These results indicate that M1 is involved in motor decision making, possibly by weighting the final integration of multiple sources of evidence driving motor behaviors. Copyright © 2015 Elsevier Inc. All rights reserved.

Integrating Design Decision Management with Model-based Software Development

DEFF Research Database (Denmark)

Könemann, Patrick

Design decisions are continuously made during the development of software systems and are important artifacts for design documentation. Dedicated decision management systems are often used to capture such design knowledge. Most such systems are, however, separated from the design artifacts...... of the system. In model-based software development, where design models are used to develop a software system, outcomes of many design decisions have big impact on design models. The realization of design decisions is often manual and tedious work on design models. Moreover, keeping design models consistent......, or by ignoring the causes. This substitutes manual reviews to some extent. The concepts, implemented in a tool, have been validated with design patterns, refactorings, and domain level tests that comprise a replay of a real project. This proves the applicability of the solution to realistic examples...

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) andgene expression programming (GEP) models, which is a new hybrid method (SARIMA–GEP). To this end, a four-step process is employed. First, the monthly ...

Qualitative and quantitative image analysis of CT and MR imaging in patients with neuroendocrine liver metastases in comparison to 68Ga-DOTATOC PET

International Nuclear Information System (INIS)

Flechsig, Paul; Zechmann, Christian M.; Schreiweis, Julian; Kratochwil, Clemens; Rath, Daniel; Schwartz, Lawrence H.; Schlemmer, Heinz-Peter; Kauczor, Hans-Ulrich; Haberkorn, Uwe; Giesel, Frederik L.

2015-01-01

Highlights: • Qualitative analysis revealed significantly higher results for spatial lesion detectability of liver metastasis in CE-MRI as compared to DW-imaging (p < 0.05). • Primary visibility of liver metastases was scored equally in CE-MRI and DW-imaging. • Contrast-enhancement ratios in liver metastases reached highest values for DW-imaging (p < 0.05). • Staging of liver metastases in patients with GEP-NETs should rather be performed using a combination of PET and MRI than of PET and CT. • The combination of functional and morphologic native MR-sequences seems to be sufficient for follow-up imaging in clinical routine, especially in post-interventional follow-up. - Abstract: Purpose: To compare lesion conspicuity in patients with liver metastases arising from gastroenteropancreatic neuroendocrine tumors (GEP-NETs) using MRI, PET and CT. Materials and methods: 16 patients with GEP-NETs were evaluated using non-contrast MRI, contrast-enhanced (CE) MRI using Gd-EOB-DTPA and CE- 68 Ga-DOTATOC PET. Quantitative analyses were performed by two blinded readers using ROI-analyses quantifying contrast ratios (CR) between normal liver-tissue and GEP-NET-metastases. Qualitative analyses were performed evaluating primary visibility and spatial detectability of all lesions. Results: 103 of the same liver metastases were detected on all modalities. Qualitatively, lesion conspicuity was superior on CE-MRI imaging compared to non-contrast MR-sequences (T2, DWI, fl2D, fl3D), as well as arterial- and portal-venous phase CT. Concerning detectability of lesions, CE-MRI was superior to all other modalities. The quantitative ROI-analysis demonstrated improved CR for DWI compared to all other non-contrast MR-sequences (p < 0.001). CE-MRI presented with higher CR-values compared to CE- 68 Ga-DOTATOC PET/CT (p < 0.001). Conclusions: Anatomic imaging using non contrast MRI with fl2D-and fl3D-sequences in combination with the molecular imaging modality 68 Ga-DOTATOC PET is

Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi

Directory of Open Access Journals (Sweden)

Diego Montenegro

Full Text Available BACKGROUND Chagas disease (CD, caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. OBJECTIVES To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. METHODS Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE and geometrical analysis for interactive assistance (GAIA methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1 house indicator (HI; (2 triatominae indicator (TI; (3 host/reservoir indicator (Ho/RoI; (4 ecotope indicator (EI; and (5 socio-cultural indicator (S-CI. FINDINGS Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors’ setting (border areas on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector

Multi-criteria decision analysis and spatial statistic: an approach to determining human vulnerability to vector transmission of Trypanosoma cruzi.

Science.gov (United States)

Montenegro, Diego; Cunha, Ana Paula da; Ladeia-Andrade, Simone; Vera, Mauricio; Pedroso, Marcel; Junqueira, Angela

2017-10-01

Chagas disease (CD), caused by the protozoan Trypanosoma cruzi, is a neglected human disease. It is endemic to the Americas and is estimated to have an economic impact, including lost productivity and disability, of 7 billion dollars per year on average. To assess vulnerability to vector-borne transmission of T. cruzi in domiciliary environments within an area undergoing domiciliary vector interruption of T. cruzi in Colombia. Multi-criteria decision analysis [preference ranking method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive assistance (GAIA) methods] and spatial statistics were performed on data from a socio-environmental questionnaire and an entomological survey. In the construction of multi-criteria descriptors, decision-making processes and indicators of five determinants of the CD vector pathway were summarily defined, including: (1) house indicator (HI); (2) triatominae indicator (TI); (3) host/reservoir indicator (Ho/RoI); (4) ecotope indicator (EI); and (5) socio-cultural indicator (S-CI). Determination of vulnerability to CD is mostly influenced by TI, with 44.96% of the total weight in the model, while the lowest contribution was from S-CI, with 7.15%. The five indicators comprise 17 indices, and include 78 of the original 104 priority criteria and variables. The PROMETHEE and GAIA methods proved very efficient for prioritisation and quantitative categorisation of socio-environmental determinants and for better determining which criteria should be considered for interrupting the man-T. cruzi-vector relationship in endemic areas of the Americas. Through the analysis of spatial autocorrelation it is clear that there is a spatial dependence in establishing categories of vulnerability, therefore, the effect of neighbors' setting (border areas) on local values should be incorporated into disease management for establishing programs of surveillance and control of CD via vector. The study model proposed here is flexible and

Retrieving top-k prestige-based relevant spatial web objects

DEFF Research Database (Denmark)

Cao, Xin; Cong, Gao; Jensen, Christian S.

2010-01-01

The location-aware keyword query returns ranked objects that are near a query location and that have textual descriptions that match query keywords. This query occurs inherently in many types of mobile and traditional web services and applications, e.g., Yellow Pages and Maps services. Previous...... of prestige-based relevance to capture both the textual relevance of an object to a query and the effects of nearby objects. Based on this, a new type of query, the Location-aware top-k Prestige-based Text retrieval (LkPT) query, is proposed that retrieves the top-k spatial web objects ranked according...... to both prestige-based relevance and location proximity. We propose two algorithms that compute LkPT queries. Empirical studies with real-world spatial data demonstrate that LkPT queries are more effective in retrieving web objects than a previous approach that does not consider the effects of nearby...

An Adaptive Sweep-Circle Spatial Clustering Algorithm Based on Gestalt

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Qingming Zhan

2017-08-01

Full Text Available An adaptive spatial clustering (ASC algorithm is proposed in this present study, which employs sweep-circle techniques and a dynamic threshold setting based on the Gestalt theory to detect spatial clusters. The proposed algorithm can automatically discover clusters in one pass, rather than through the modification of the initial model (for example, a minimal spanning tree, Delaunay triangulation, or Voronoi diagram. It can quickly identify arbitrarily-shaped clusters while adapting efficiently to non-homogeneous density characteristics of spatial data, without the need for prior knowledge or parameters. The proposed algorithm is also ideal for use in data streaming technology with dynamic characteristics flowing in the form of spatial clustering in large data sets.

MRI-based decision tree model for diagnosis of biliary atresia.

Science.gov (United States)

Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung

2018-02-23

To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.

Decisions, dopamine, and degeneracy in complex biological systems

Directory of Open Access Journals (Sweden)

Regan CM

2014-01-01

Full Text Available Ciaran M Regan School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Belfield, Dublin, Ireland Abstract: The neurobiological and computational analysis of value-based decision-making rests within the domain of neuroeconomics which has the goal of providing a biological account of human behavior relevant to both natural and social sciences. This review proposes a framework to investigate different aspects of the theoretical and molecular neurobiology of decision-making. In order to learn how to make good decisions, the brain needs to compute a separate value signal that measures the desirability of the outcomes that were generated by its previous decisions. The framework presented here combines aspects of current ideas relating to information processing by the hippocampal formation and how these relate to the phasic midbrain dopaminergic firing that occurs in response to the spatial and motivational aspects of rewarding events in the environment. The activities of hippocampal ensembles are considered to reflect a continuous updating process for attended experiences, defining both regular and irregular stimuli, environments, and actions, that are rapidly encoded as schemas into pre-existing knowledge bases. Keywords: hippocampus, schemas, synapse assemblies, cell assemblies, synapse plasticity

Simulation of the Role of Government in Spatial Agent-Based Model

Directory of Open Access Journals (Sweden)

Viktor Ivanovich Suslov

2016-09-01

Full Text Available The paper describes the further development of an agent-based multiregional input-output model of the Russian economy. We consider the idea of incorporating the government into the model and analyze the results of experimental calculations for the conditional example of spatial economy. New agents are included into the model such as the federal and regional governments, pension fund and also the state enterprises producing public goods at the federal and regional levels. The government sets four types of taxes (personal and business income taxes, VAT and payroll taxes, ensures the provision of public goods and provides social, investment and interbudgetary transfers to households, firms and budgets. Social transfers consist of social assistance and unemployment benefits. The utility functions of households are expanded by the terms associated with national and regional public goods. The budget policy is designed in accordance with the maximization of isoelastic function of social welfare that formalizes the choice between the different concepts of social justice. The Gini index is used for the monitoring the inequality of income distribution. The results of experimental calculations present the convergence of the new version of the model to the state of quasi-equilibrium. The special attention is paid an optimal level of the taxation maximizing the social welfare function. Four variants of the optimal tax rates are defined: for three major taxes at a fixed proportion of rates and for each of the tax separately at zero rates of two other taxes. The further directions of modelling are identified, they allow to investigate the spatial development of the Russian economy taking into account the decision-making by private agents in responding to government policies.

Characterizing spatial uncertainty when integrating social data in conservation planning.

Science.gov (United States)

Lechner, A M; Raymond, C M; Adams, V M; Polyakov, M; Gordon, A; Rhodes, J R; Mills, M; Stein, A; Ives, C D; Lefroy, E C

2014-12-01

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches. © 2014 Society for Conservation Biology.

Augmentation of Explicit Spatial Configurations by Knowledge-Based Inference on Geometric Fields

Directory of Open Access Journals (Sweden)

Dan Tappan

2009-04-01

Full Text Available A spatial configuration of a rudimentary, static, realworld scene with known objects (animals and properties (positions and orientations contains a wealth of syntactic and semantic spatial information that can contribute to a computational understanding far beyond what its quantitative details alone convey. This work presents an approach that (1 quantitatively represents what a configuration explicitly states, (2 integrates this information with implicit, commonsense background knowledge of its objects and properties, (3 infers additional, contextually appropriate, commonsense spatial information from and about their interrelationships, and (4 augments the original representation with this combined information. A semantic network represents explicit, quantitative information in a configuration. An inheritance-based knowledge base of relevant concepts supplies implicit, qualitative background knowledge to support semantic interpretation. Together, these structures provide a simple, nondeductive, constraint-based, geometric logical formalism to infer substantial implicit knowledge for intrinsic and deictic frames of spatial reference.

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

Science.gov (United States)

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratiodecisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

The dynamic and indirect spatial effects of neighborhood conditions on land value, spatial panel dynamic econometrics model

Science.gov (United States)

Fitriani, Rahma; Sumarminingsih, Eni; Astutik, Suci

2017-05-01

Land value is the product of past decision of its use leading to its value, as well as the value of the surrounded land. It is also affected by the local characteristic and the spillover development demand of the previous time period. The effect of each factor on land value will have dynamic and spatial virtues. Thus, a spatial panel dynamic model is used to estimate the particular effects. The model will be useful for predicting the future land value or the effect of implemented policy on land value. The objective of this paper is to derive the dynamic and indirect spatial marginal effects of the land characteristic and the spillover development demand on land value. Each effect is the partial derivative of the expected land value based on the spatial dynamic model with respect to each variable, by considering different time period and different location. The results indicate that the instant change of local or neighborhood characteristics on land value affect the local and the immediate neighborhood land value. However, the longer the change take place, the effect will spread further, not only on the immediate neighborhood.

Spatial analysis based on variance of moving window averages

OpenAIRE

Wu, B M; Subbarao, K V; Ferrandino, F J; Hao, J J

2006-01-01

A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease survey data encompassing both a...

Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

Science.gov (United States)

Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

2017-03-01

Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

Arriba-lib: association of an evidence-based electronic library of decision aids with communication and decision-making in patients and primary care physicians.

Science.gov (United States)

Hirsch, Oliver; Keller, Heidemarie; Krones, Tanja; Donner-Banzhoff, Norbert

2012-03-01

In shared decision-making, patients are empowered to actively ask questions and participate in decisions about their healthcare based on their preferences and values. Decision aids should help patients make informed choices among diagnostic or treatment options by delivering evidence-based information on options and outcomes; however, they have rarely been field tested, especially in the primary care context. We therefore evaluated associations between the use of an interactive, transactional and evidence-based library of decision aids (arriba-lib) and communication and decision-making in patients and physicians in the primary care context. Our electronic library of decision aids ('arriba-lib') includes evidence-based modules for cardiovascular prevention, diabetes, coronary heart disease, atrial fibrillation and depression. Twenty-nine primary care physicians recruited 192 patients. We used questionnaires to ask patients and physicians about their experiences with and attitudes towards the programme. Patients were interviewed via telephone 2 months after the consultation. Data were analysed by general estimation equations, cross tab analyses and by using effect sizes. Only a minority (8.9%) of the consultations were felt to be too long because physicians said consultations were unacceptably extended by arriba-lib. We found a negative association between the detailedness of the discussion of the clinical problem's definition and the age of the patients. Physicians discuss therapeutic options in less detail with patients who have a formal education of less than 8 years. Patients who were counselled by a physician with no experience in using a decision aid more often reported that they do not remember being counselled with the help of a decision aid or do not wish to be counselled again with a decision aid. Arriba-lib has positive associations to the decision-making process in patients and physicians. It can also be used with older age groups and patients with less

Maintenance planning support method for nuclear power plants based on collective decision making

International Nuclear Information System (INIS)

Shimizu, Shunichi; Sakurai, Shoji; Takaoka, Kazushi; Kanemoto, Shigeru; Fukutomi, Shigeki

1992-01-01

Inspection and maintenance planning in nuclear power plants is conducted by decision making based on experts' collective consensus. However, since a great deal of time and effort is required to reach a consensus among expert judgments, the establishment of effective decision making methods is necessary. Therefore, the authors developed a method for supporting collective decision making, based on a combination of three types of decision making methods; the Characteristic Diagram method, Interpretative Structural Modeling method, and the Analytic Hierarchy Process method. The proposed method enables us to determine the evaluation criteria systematically for collective decision making, and also allows extracting collective decisions using simplified questionnaires. The proposed method can support reaching a consensus of groups effectively through the evaluation of collective decision structural models and their characteristics. In this paper, the effectiveness of the proposed method was demonstrated through its application to the decision making problem concerning whether or not the improved ultrasonic testing equipment should be adopted at nuclear power plants. (author)

Efficient Enhancement for Spatial Scalable Video Coding Transmission

Directory of Open Access Journals (Sweden)

Mayada Khairy

2017-01-01

Full Text Available Scalable Video Coding (SVC is an international standard technique for video compression. It is an extension of H.264 Advanced Video Coding (AVC. In the encoding of video streams by SVC, it is suitable to employ the macroblock (MB mode because it affords superior coding efficiency. However, the exhaustive mode decision technique that is usually used for SVC increases the computational complexity, resulting in a longer encoding time (ET. Many other algorithms were proposed to solve this problem with imperfection of increasing transmission time (TT across the network. To minimize the ET and TT, this paper introduces four efficient algorithms based on spatial scalability. The algorithms utilize the mode-distribution correlation between the base layer (BL and enhancement layers (ELs and interpolation between the EL frames. The proposed algorithms are of two categories. Those of the first category are based on interlayer residual SVC spatial scalability. They employ two methods, namely, interlayer interpolation (ILIP and the interlayer base mode (ILBM method, and enable ET and TT savings of up to 69.3% and 83.6%, respectively. The algorithms of the second category are based on full-search SVC spatial scalability. They utilize two methods, namely, full interpolation (FIP and the full-base mode (FBM method, and enable ET and TT savings of up to 55.3% and 76.6%, respectively.

Data Warehousing and Data Quality for a Spatial Decision Support System

National Research Council Canada - National Science Library

Dill, Robert

1997-01-01

.... The Army Reserve Installation Evaluation System (ARIES) integrates a GIS mapping engine and a decision model solver in a flexible environment that leverages operational legacy database information for decision-making...

Teaching advance care planning to medical students with a computer-based decision aid.

Science.gov (United States)

Green, Michael J; Levi, Benjamin H

2011-03-01

Discussing end-of-life decisions with cancer patients is a crucial skill for physicians. This article reports findings from a pilot study evaluating the effectiveness of a computer-based decision aid for teaching medical students about advance care planning. Second-year medical students at a single medical school were randomized to use a standard advance directive or a computer-based decision aid to help patients with advance care planning. Students' knowledge, skills, and satisfaction were measured by self-report; their performance was rated by patients. 121/133 (91%) of students participated. The Decision-Aid Group (n = 60) outperformed the Standard Group (n = 61) in terms of students' knowledge (p satisfaction with their learning experience (p student performance. Use of a computer-based decision aid may be an effective way to teach medical students how to discuss advance care planning with cancer patients.

VIDEO DENOISING USING SWITCHING ADAPTIVE DECISION BASED ALGORITHM WITH ROBUST MOTION ESTIMATION TECHNIQUE

Directory of Open Access Journals (Sweden)

V. Jayaraj

2010-08-01

Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.

An object-oriented approach to site characterization decision support

International Nuclear Information System (INIS)

Johnson, R.

1995-01-01

Effective decision support for site characterization is key to determining the nature and extent of contamination and the associated human and environmental risks. Site characterization data, however, present particular problems to technical analysts and decision-makers. Such data are four dimensional, incorporating temporal and spatial components. Their sheer volume can be daunting -- sites with hundreds of monitoring wells and thousands of samples sent for laboratory analyses are not uncommon. Data are derived from a variety of sources including laboratory analyses, non-intrusive geophysical surveys, historical information, bore logs, in-field estimates of key physical parameters such as aquifer transmissivity, soil moisture content, depth-to-water table, etc. Ultimately, decisions have to be made based on data that are always incomplete, often confusing, inaccurate, or inappropriate, and occasionally wrong. In response to this challenge, two approaches to environmental decision support have arisen, Data Quality Objectives (DQOS) and the Observational Approach (OA). DQOs establish criteria for data collection by clearly defining the decisions that need to be made, the uncertainty that can be tolerated, and the type and amount of data that needs to be collected to satisfy the uncertainty requirements. In practice, DQOs are typically based on statistical measures. The OA accepts the fact that the process of characterizing and remediating contaminated sites is always uncertain. Decision-making with the OA is based on what is known about a site, with contingencies developed for potential future deviations from the original assumptions about contamination nature, extent, and risks posed

Knowledge-Based Information Management in Decision Support for Ecosystem Management

Science.gov (United States)

Keith Reynolds; Micahel Saunders; Richard Olson; Daniel Schmoldt; Michael Foster; Donald Latham; Bruce Miller; John Steffenson; Lawrence Bednar; Patrick Cunningham

1995-01-01

The Pacific Northwest Research Station (USDA Forest Service) is developing a knowledge-based information management system to provide decision support for watershed analysis in the Pacific Northwest region of the U.S. The decision support system includes: (1) a GIS interface that allows users to graphically navigate to specific provinces and watersheds and display a...

Assessing the development of Kenya National Spatial Data Infrastructure (KNSDI)

NARCIS (Netherlands)

Okuku, J.; Bregt, A.K.; Grus, L.

2014-01-01

Spatial data plays a vital role in developmental activities, whether natural resource management or socio-economic development. Spatial Data Infrastructures (SDIs) facilitate access, sharing and dissemination of spatial data necessary for complex decision-making processes of the future. Thus,

Nicotine replacement therapy decision based on fuzzy multi-criteria analysis

Science.gov (United States)

Tarmudi, Zamali; Matmali, Norfazillah; Abdullah, Mohd Lazim

2017-08-01

It has been observed that Nicotine Replacement Therapy (NRT) is one of the alternatives to control and reduce smoking addiction among smokers. Since the decision to choose the best NRT alternative involves uncertainty, ambiguity factors and diverse input datasets, thus, this paper proposes a fuzzy multi-criteria analysis (FMA) to overcome these issues. It focuses on how the fuzzy approach can unify the diversity of datasets based on NRT's decision-making problem. The analysis done employed the advantage of the cost-benefit criterion to unify the mixture of dataset input. The performance matrix was utilised to derive the performance scores. An empirical example regarding the NRT's decision-making problem was employed to illustrate the proposed approach. Based on the calculations, this analytical approach was found to be highly beneficial in terms of usability. It was also very applicable and efficient in dealing with the mixture of input datasets. Hence, the decision-making process can easily be used by experts and patients who are interested to join the therapy/cessation program.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

Science.gov (United States)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

Permutation based decision making under fuzzy environment using Tabu search

Directory of Open Access Journals (Sweden)

Mahdi Bashiri

2012-04-01

Full Text Available One of the techniques, which are used for Multiple Criteria Decision Making (MCDM is the permutation. In the classical form of permutation, it is assumed that weights and decision matrix components are crisp. However, when group decision making is under consideration and decision makers could not agree on a crisp value for weights and decision matrix components, fuzzy numbers should be used. In this article, the fuzzy permutation technique for MCDM problems has been explained. The main deficiency of permutation is its big computational time, so a Tabu Search (TS based algorithm has been proposed to reduce the computational time. A numerical example has illustrated the proposed approach clearly. Then, some benchmark instances extracted from literature are solved by proposed TS. The analyses of the results show the proper performance of the proposed method.

Examining Preservice Teachers' Decision Behaviors and Individual Differences in Three Online Case-Based Approaches

Science.gov (United States)

Cevik, Yasemin Demiraslan; Andre, Thomas

2013-01-01

This study compared the impact of three types of case-based methods (case-based reasoning, worked example, and faded worked example) on preservice teachers' (n = 71) interaction with decision tasks and whether decision related measures (task difficulty, mental effort, decision making performance) were associated with the differences in student…

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

Science.gov (United States)

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.

Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

International Nuclear Information System (INIS)

Ohdaira, Tetsushi

2014-01-01

Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision. (paper)

Randomness in the network inhibits cooperation based on the bounded rational collective altruistic decision

Science.gov (United States)

Ohdaira, Tetsushi

2014-07-01

Previous studies discussing cooperation employ the best decision that every player knows all information regarding the payoff matrix and selects the strategy of the highest payoff. Therefore, they do not discuss cooperation based on the altruistic decision with limited information (bounded rational altruistic decision). In addition, they do not cover the case where every player can submit his/her strategy several times in a match of the game. This paper is based on Ohdaira's reconsideration of the bounded rational altruistic decision, and also employs the framework of the prisoner's dilemma game (PDG) with sequential strategy. The distinction between this study and the Ohdaira's reconsideration is that the former covers the model of multiple groups, but the latter deals with the model of only two groups. Ohdaira's reconsideration shows that the bounded rational altruistic decision facilitates much more cooperation in the PDG with sequential strategy than Ohdaira and Terano's bounded rational second-best decision does. However, the detail of cooperation of multiple groups based on the bounded rational altruistic decision has not been resolved yet. This study, therefore, shows how randomness in the network composed of multiple groups affects the increase of the average frequency of mutual cooperation (cooperation between groups) based on the bounded rational altruistic decision of multiple groups. We also discuss the results of the model in comparison with related studies which employ the best decision.

Support System Model for Value based Group Decision on Roof System Selection

Directory of Open Access Journals (Sweden)

Christiono Utomo

2011-02-01

Full Text Available A group decision support system is required on a value-based decision because there are different concern caused by differing preferences, experiences, and background. It is to enable each decision-maker to evaluate and rank the solution alternatives before engaging into negotiation with other decision-makers. Stakeholder of multi-criteria decision making problems usually evaluates the alternative solution from different perspective, making it possible to have a dominant solution among the alternatives. Each stakeholder needs to identify the goals that can be optimized and those that can be compromised in order to reach an agreement with other stakeholders. This paper presents group decision model involving three decision-makers on the selection of suitable system for a building’s roof. The objective of the research is to find an agreement options model and coalition algorithms for multi person decision with two main preferences of value which are function and cost. The methodology combines value analysis method using Function Analysis System Technique (FAST; Life Cycle Cost analysis, group decision analysis method based on Analytical Hierarchy Process (AHP in a satisfying options, and Game theory-based agent system to develop agreement option and coalition formation for the support system. The support system bridges theoretical gap between automated design in construction domain and automated negotiation in information technology domain by providing a structured methodology which can lead to systematic support system and automated negotiation. It will contribute to value management body of knowledge as an advanced method for creativity and analysis phase, since the practice of this knowledge is teamwork based. In the case of roof system selection, it reveals the start of the first negotiation round. Some of the solutions are not an option because no individual stakeholder or coalition of stakeholders desires to select it. The result indicates

Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral

Directory of Open Access Journals (Sweden)

Chunqiao Tan

2013-01-01

Full Text Available An effective decision making approach based on VIKOR and Choquet integral is developed to solve multicriteria group decision making problem with conflicting criteria and interdependent subjective preference of decision makers in a fuzzy environment where preferences of decision makers with respect to criteria are represented by interval-valued intuitionistic fuzzy sets. First, an interval-valued intuitionistic fuzzy Choquet integral operator is given. Some of its properties are investigated in detail. The extended VIKOR decision procedure based on the proposed operator is developed for solving the multicriteria group decision making problem where the interactive criteria weight is measured by Shapley value. An illustrative example is given for demonstrating the applicability of the proposed decision procedure for solving the multi-criteria group decision making problem in interval-valued intuitionistic fuzzy environment.

Multi-objective decision-making model based on CBM for an aircraft fleet

Science.gov (United States)

Luo, Bin; Lin, Lin

2018-04-01

Modern production management patterns, in which multi-unit (e.g., a fleet of aircrafts) are managed in a holistic manner, have brought new challenges for multi-unit maintenance decision making. To schedule a good maintenance plan, not only does the individual machine maintenance have to be considered, but also the maintenance of the other individuals have to be taken into account. Since most condition-based maintenance researches for aircraft focused on solely reducing maintenance cost or maximizing the availability of single aircraft, as well as considering that seldom researches concentrated on both the two objectives: minimizing cost and maximizing the availability of a fleet (total number of available aircraft in fleet), a multi-objective decision-making model based on condition-based maintenance concentrated both on the above two objectives is established. Furthermore, in consideration of the decision maker may prefer providing the final optimal result in the form of discrete intervals instead of a set of points (non-dominated solutions) in real decision-making problem, a novel multi-objective optimization method based on support vector regression is proposed to solve the above multi-objective decision-making model. Finally, a case study regarding a fleet is conducted, with the results proving that the approach efficiently generates outcomes that meet the schedule requirements.

Agent-based Decision Support System for the Third Generation Distributed Dynamic Decision-making (DDD-III) Simulator