WorldWideScience

Sample records for belief network bbn

  1. Using Bayesian Belief Network (BBN) modelling for rapid source term prediction. Final report

    International Nuclear Information System (INIS)

    Knochenhauer, M.; Swaling, V.H.; Dedda, F.D.; Hansson, F.; Sjoekvist, S.; Sunnegaerd, K.

    2013-10-01

    The project presented in this report deals with a number of complex issues related to the development of a tool for rapid source term prediction (RASTEP), based on a plant model represented as a Bayesian belief network (BBN) and a source term module which is used for assigning relevant source terms to BBN end states. Thus, RASTEP uses a BBN to model severe accident progression in a nuclear power plant in combination with pre-calculated source terms (i.e., amount, composition, timing, and release path of released radio-nuclides). The output is a set of possible source terms with associated probabilities. One major issue has been associated with the integration of probabilistic and deterministic analyses are addressed, dealing with the challenge of making the source term determination flexible enough to give reliable and valid output throughout the accident scenario. The potential for connecting RASTEP to a fast running source term prediction code has been explored, as well as alternative ways of improving the deterministic connections of the tool. As part of the investigation, a comparison of two deterministic severe accident analysis codes has been performed. A second important task has been to develop a general method where experts' beliefs can be included in a systematic way when defining the conditional probability tables (CPTs) in the BBN. The proposed method includes expert judgement in a systematic way when defining the CPTs of a BBN. Using this iterative method results in a reliable BBN even though expert judgements, with their associated uncertainties, have been used. It also simplifies verification and validation of the considerable amounts of quantitative data included in a BBN. (Author)

  2. Using Bayesian Belief Network (BBN) modelling for rapid source term prediction. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Knochenhauer, M.; Swaling, V.H.; Dedda, F.D.; Hansson, F.; Sjoekvist, S.; Sunnegaerd, K. [Lloyd' s Register Consulting AB, Sundbyberg (Sweden)

    2013-10-15

    The project presented in this report deals with a number of complex issues related to the development of a tool for rapid source term prediction (RASTEP), based on a plant model represented as a Bayesian belief network (BBN) and a source term module which is used for assigning relevant source terms to BBN end states. Thus, RASTEP uses a BBN to model severe accident progression in a nuclear power plant in combination with pre-calculated source terms (i.e., amount, composition, timing, and release path of released radio-nuclides). The output is a set of possible source terms with associated probabilities. One major issue has been associated with the integration of probabilistic and deterministic analyses are addressed, dealing with the challenge of making the source term determination flexible enough to give reliable and valid output throughout the accident scenario. The potential for connecting RASTEP to a fast running source term prediction code has been explored, as well as alternative ways of improving the deterministic connections of the tool. As part of the investigation, a comparison of two deterministic severe accident analysis codes has been performed. A second important task has been to develop a general method where experts' beliefs can be included in a systematic way when defining the conditional probability tables (CPTs) in the BBN. The proposed method includes expert judgement in a systematic way when defining the CPTs of a BBN. Using this iterative method results in a reliable BBN even though expert judgements, with their associated uncertainties, have been used. It also simplifies verification and validation of the considerable amounts of quantitative data included in a BBN. (Author)

  3. Using Bayesian Belief Network (BBN) modelling for Rapid Source Term Prediction. RASTEP Phase 1

    International Nuclear Information System (INIS)

    Knochenhauer, M.; Swaling, V.H.; Alfheim, P.

    2012-09-01

    The project is connected to the development of RASTEP, a computerized source term prediction tool aimed at providing a basis for improving off-site emergency management. RASTEP uses Bayesian belief networks (BBN) to model severe accident progression in a nuclear power plant in combination with pre-calculated source terms (i.e., amount, timing, and pathway of released radio-nuclides). The output is a set of possible source terms with associated probabilities. In the NKS project, a number of complex issues associated with the integration of probabilistic and deterministic analyses are addressed. This includes issues related to the method for estimating source terms, signal validation, and sensitivity analysis. One major task within Phase 1 of the project addressed the problem of how to make the source term module flexible enough to give reliable and valid output throughout the accident scenario. Of the alternatives evaluated, it is recommended that RASTEP is connected to a fast running source term prediction code, e.g., MARS, with a possibility of updating source terms based on real-time observations. (Author)

  4. Using Bayesian Belief Network (BBN) modelling for Rapid Source Term Prediction. RASTEP Phase 1

    Energy Technology Data Exchange (ETDEWEB)

    Knochenhauer, M.; Swaling, V.H.; Alfheim, P. [Scandpower AB, Sundbyberg (Sweden)

    2012-09-15

    The project is connected to the development of RASTEP, a computerized source term prediction tool aimed at providing a basis for improving off-site emergency management. RASTEP uses Bayesian belief networks (BBN) to model severe accident progression in a nuclear power plant in combination with pre-calculated source terms (i.e., amount, timing, and pathway of released radio-nuclides). The output is a set of possible source terms with associated probabilities. In the NKS project, a number of complex issues associated with the integration of probabilistic and deterministic analyses are addressed. This includes issues related to the method for estimating source terms, signal validation, and sensitivity analysis. One major task within Phase 1 of the project addressed the problem of how to make the source term module flexible enough to give reliable and valid output throughout the accident scenario. Of the alternatives evaluated, it is recommended that RASTEP is connected to a fast running source term prediction code, e.g., MARS, with a possibility of updating source terms based on real-time observations. (Author)

  5. BBN technical memorandum W1310 hydroacoustic network capability studies

    Energy Technology Data Exchange (ETDEWEB)

    Angell, J., LLNL

    1997-12-01

    This report summarizes work performed under contract to Lawrence Livermore National Laboratory during the period 1 August to 30 November 1997. Four separate tasks were undertaken during this period which investigated various aspects of hydroacoustic network performance using the Hydroacoustic Coverage Assessment Model (HydroCAM). The purpose of this report is to document each of these tasks.

  6. BBN based Quantitative Assessment of Software Design Specification

    International Nuclear Information System (INIS)

    Eom, Heung-Seop; Park, Gee-Yong; Kang, Hyun-Gook; Kwon, Kee-Choon; Chang, Seung-Cheol

    2007-01-01

    Probabilistic Safety Assessment (PSA), which is one of the important methods in assessing the overall safety of a nuclear power plant (NPP), requires quantitative reliability information of safety-critical software, but the conventional reliability assessment methods can not provide enough information for PSA of a NPP. Therefore current PSA which includes safety-critical software does not usually consider the reliability of the software or uses arbitrary values for it. In order to solve this situation this paper proposes a method that can produce quantitative reliability information of safety-critical software for PSA by making use of Bayesian Belief Networks (BBN). BBN has generally been used to model an uncertain system in many research fields including the safety assessment of software. The proposed method was constructed by utilizing BBN which can combine the qualitative and the quantitative evidence relevant to the reliability of safety critical software. The constructed BBN model can infer a conclusion in a formal and a quantitative way. A case study was carried out with the proposed method to assess the quality of software design specification (SDS) of safety-critical software that will be embedded in a reactor protection system. The intermediate V and V results of the software design specification were used as inputs to the BBN model

  7. Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation.

    Science.gov (United States)

    B.G. Marcot; J.D. Steventon; G.D. Sutherland; R.K. McCann

    2006-01-01

    We provide practical guidelines for developing, testing, and revising Bayesian belief networks (BBNs). Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model...

  8. Bayesian belief networks for human reliability analysis: A review of applications and gaps

    International Nuclear Information System (INIS)

    Mkrtchyan, L.; Podofillini, L.; Dang, V.N.

    2015-01-01

    The use of Bayesian Belief Networks (BBNs) in risk analysis (and in particular Human Reliability Analysis, HRA) is fostered by a number of features, attractive in fields with shortage of data and consequent reliance on subjective judgments: the intuitive graphical representation, the possibility of combining diverse sources of information, the use the probabilistic framework to characterize uncertainties. In HRA, BBN applications are steadily increasing, each emphasizing a different BBN feature or a different HRA aspect to improve. This paper aims at a critical review of these features as well as at suggesting research needs. Five groups of BBN applications are analysed: modelling of organizational factors, analysis of the relationships among failure influencing factors, BBN-based extensions of existing HRA methods, dependency assessment among human failure events, assessment of situation awareness. Further, the paper analyses the process for building BBNs and in particular how expert judgment is used in the assessment of the BBN conditional probability distributions. The gaps identified in the review suggest the need for establishing more systematic frameworks to integrate the different sources of information relevant for HRA (cognitive models, empirical data, and expert judgment) and to investigate algorithms to avoid elicitation of many relationships via expert judgment. - Highlights: • We analyze BBN uses for HRA applications; but some conclusions can be generalized. • Special review focus on BBN building approaches, key for model acceptance. • Gaps relate to the transparency of the BBN building and quantification phases. • Need for more systematic framework to integrate different sources of information. • Need of ways to avoid elicitation of many relationships via expert judgment

  9. ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari

    2011-06-01

    Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

  10. Modeling Land-Use Decision Behavior with Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Inge Aalders

    2008-06-01

    Full Text Available The ability to incorporate and manage the different drivers of land-use change in a modeling process is one of the key challenges because they are complex and are both quantitative and qualitative in nature. This paper uses Bayesian belief networks (BBN to incorporate characteristics of land managers in the modeling process and to enhance our understanding of land-use change based on the limited and disparate sources of information. One of the two models based on spatial data represented land managers in the form of a quantitative variable, the area of individual holdings, whereas the other model included qualitative data from a survey of land managers. Random samples from the spatial data provided evidence of the relationship between the different variables, which I used to develop the BBN structure. The model was tested for four different posterior probability distributions, and results showed that the trained and learned models are better at predicting land use than the uniform and random models. The inference from the model demonstrated the constraints that biophysical characteristics impose on land managers; for older land managers without heirs, there is a higher probability of the land use being arable agriculture. The results show the benefits of incorporating a more complex notion of land managers in land-use models, and of using different empirical data sources in the modeling process. Future research should focus on incorporating more complex social processes into the modeling structure, as well as incorporating spatio-temporal dynamics in a BBN.

  11. A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites

    DEFF Research Database (Denmark)

    Thomsen, Nanna Isbak; Binning, Philip John; McKnight, Ursula S.

    2016-01-01

    the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found...... to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models...... that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert...

  12. A Study on Quantitative Assessment of Design Specification of Reactor Protection System Software Using Bayesian Belief Networks

    International Nuclear Information System (INIS)

    Eom, H. S.; Kang, H. G.; Chang, S. C.; Park, G. Y.; Kwon, K. C.

    2007-02-01

    This report propose a method that can produce quantitative reliability of safety-critical software for PSA by making use of Bayesian Belief Networks (BBN). BBN has generally been used to model the uncertain system in many research fields. The proposed method was constructed by utilizing BBN that can combine the qualitative and the quantitative evidence relevant to the reliability of safety-critical software, and then can infer a conclusion in a formal and a quantitative way. A case study was also carried out with the proposed method to assess the quality of software design specification of safety-critical software that will be embedded in reactor protection system. The V and V results of the software were used as inputs for the BBN model. The calculation results of the BBN model showed that its conclusion is mostly equivalent to those of the V and V expert for a given input data set. The method and the results of the case study will be utilized in PSA of NPP. The method also can support the V and V expert's decision making process in controlling further V and V activities

  13. BAYES-HEP: Bayesian belief networks for estimation of human error probability

    International Nuclear Information System (INIS)

    Karthick, M.; Senthil Kumar, C.; Paul, Robert T.

    2017-01-01

    Human errors contribute a significant portion of risk in safety critical applications and methods for estimation of human error probability have been a topic of research for over a decade. The scarce data available on human errors and large uncertainty involved in the prediction of human error probabilities make the task difficult. This paper presents a Bayesian belief network (BBN) model for human error probability estimation in safety critical functions of a nuclear power plant. The developed model using BBN would help to estimate HEP with limited human intervention. A step-by-step illustration of the application of the method and subsequent evaluation is provided with a relevant case study and the model is expected to provide useful insights into risk assessment studies

  14. The manual of strategic economic decision making using Bayesian belief networks to solve complex problems

    CERN Document Server

    Grover, Jeff

    2016-01-01

    This book is an extension of the author’s first book and serves as a guide and manual on how to specify and compute 2-, 3-, & 4-Event Bayesian Belief Networks (BBN). It walks the learner through the steps of fitting and solving fifty BBN numerically, using mathematical proof. The author wrote this book primarily for naïve learners and professionals, with a proof-based academic rigor. The author's first book on this topic, a primer introducing learners to the basic complexities and nuances associated with learning Bayes’ theory and inverse probability for the first time, was meant for non-statisticians unfamiliar with the theorem - as is this book. This new book expands upon that approach and is meant to be a prescriptive guide for building BBN and executive decision-making for students and professionals; intended so that decision-makers can invest their time and start using this inductive reasoning principle in their decision-making processes. It highlights the utility of an algorithm that served as ...

  15. Advancing Dose-Response Assessment Methods for Environmental Regulatory Impact Analysis: A Bayesian Belief Network Approach Applied to Inorganic Arsenic.

    Science.gov (United States)

    Zabinski, Joseph W; Garcia-Vargas, Gonzalo; Rubio-Andrade, Marisela; Fry, Rebecca C; Gibson, Jacqueline MacDonald

    2016-05-10

    Dose-response functions used in regulatory risk assessment are based on studies of whole organisms and fail to incorporate genetic and metabolomic data. Bayesian belief networks (BBNs) could provide a powerful framework for incorporating such data, but no prior research has examined this possibility. To address this gap, we develop a BBN-based model predicting birthweight at gestational age from arsenic exposure via drinking water and maternal metabolic indicators using a cohort of 200 pregnant women from an arsenic-endemic region of Mexico. We compare BBN predictions to those of prevailing slope-factor and reference-dose approaches. The BBN outperforms prevailing approaches in balancing false-positive and false-negative rates. Whereas the slope-factor approach had 2% sensitivity and 99% specificity and the reference-dose approach had 100% sensitivity and 0% specificity, the BBN's sensitivity and specificity were 71% and 30%, respectively. BBNs offer a promising opportunity to advance health risk assessment by incorporating modern genetic and metabolomic data.

  16. A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation

    International Nuclear Information System (INIS)

    Trucco, P.; Cagno, E.; Ruggeri, F.; Grande, O.

    2008-01-01

    The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation's (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts' judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC

  17. A Bayesian Belief Network framework to predict SOC stock change: the Veneto region (Italy) case study

    Science.gov (United States)

    Dal Ferro, Nicola; Quinn, Claire Helen; Morari, Francesco

    2017-04-01

    A key challenge for soil scientists is predicting agricultural management scenarios that combine crop productions with high standards of environmental quality. In this context, reversing the soil organic carbon (SOC) decline in croplands is required for maintaining soil fertility and contributing to mitigate GHGs emissions. Bayesian belief networks (BBN) are probabilistic models able to accommodate uncertainty and variability in the predictions of the impacts of management and environmental changes. By linking multiple qualitative and quantitative variables in a cause-and-effect relationships, BBNs can be used as a decision support system at different spatial scales to find best management strategies in the agroecosystems. In this work we built a BBN to model SOC dynamics (0-30 cm layer) in the low-lying plain of Veneto region, north-eastern Italy, and define best practices leading to SOC accumulation and GHGs (CO2-equivalent) emissions reduction. Regional pedo-climatic, land use and management information were combined with experimental and modelled data on soil C dynamics as natural and anthropic key drivers affecting SOC stock change. Moreover, utility nodes were introduced to determine optimal decisions for mitigating GHGs emissions from croplands considering also three different IPCC climate scenarios. The network was finally validated with real field data in terms of SOC stock change. Results showed that the BBN was able to model real SOC stock changes, since validation slightly overestimated SOC reduction (+5%) at the expenses of its accumulation. At regional level, probability distributions showed 50% of SOC loss, while only 17% of accumulation. However, the greatest losses (34%) were associated with low reduction rates (100-500 kg C ha-1 y-1), followed by 33% of stabilized conditions (-100 < SOC < 100 kg ha-1 y-1). Land use management (especially tillage operations and soil cover) played a primary role to affect SOC stock change, while climate conditions

  18. Using Bayesian belief networks in adaptive management.

    Science.gov (United States)

    J.B. Nyberg; B.G. Marcot; R. Sulyma

    2006-01-01

    Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to...

  19. BBN predictions for 4He

    International Nuclear Information System (INIS)

    Walker, T.P.

    1993-01-01

    The standard model of the hot big bang assumes a homogeneous and isotropic Universe with gravity described by General Relativity and strong and electroweak interactions described by the Standard Model of particle physics. The hot big bang model makes the unavoidable prediction that the production of primordial elements occurred about one minute after the big band (referred to as big bang or primordial nucleosynthesis BBN). This review concerns the range of the primordial abundance of 4 He as predicted by standard BBN (i.e., primordial nucleosynthesis assuming a homogeneous distribution of baryons). In it the author discusses: (1) Uncertainties in the calculation of Y p (the mass fraction of primordial 4 He), (2) The expected range of Y p , (3) How the predictions stack up against the latest observations, and (4) The latest BBN bounds on Ω B h 2 and N ν . 13 refs., 2 figs

  20. A Bayesian belief network approach for assessing uncertainty in conceptual site models at contaminated sites

    Science.gov (United States)

    Thomsen, Nanna I.; Binning, Philip J.; McKnight, Ursula S.; Tuxen, Nina; Bjerg, Poul L.; Troldborg, Mads

    2016-05-01

    A key component in risk assessment of contaminated sites is in the formulation of a conceptual site model (CSM). A CSM is a simplified representation of reality and forms the basis for the mathematical modeling of contaminant fate and transport at the site. The CSM should therefore identify the most important site-specific features and processes that may affect the contaminant transport behavior at the site. However, the development of a CSM will always be associated with uncertainties due to limited data and lack of understanding of the site conditions. CSM uncertainty is often found to be a major source of model error and it should therefore be accounted for when evaluating uncertainties in risk assessments. We present a Bayesian belief network (BBN) approach for constructing CSMs and assessing their uncertainty at contaminated sites. BBNs are graphical probabilistic models that are effective for integrating quantitative and qualitative information, and thus can strengthen decisions when empirical data are lacking. The proposed BBN approach facilitates a systematic construction of multiple CSMs, and then determines the belief in each CSM using a variety of data types and/or expert opinion at different knowledge levels. The developed BBNs combine data from desktop studies and initial site investigations with expert opinion to assess which of the CSMs are more likely to reflect the actual site conditions. The method is demonstrated on a Danish field site, contaminated with chlorinated ethenes. Four different CSMs are developed by combining two contaminant source zone interpretations (presence or absence of a separate phase contamination) and two geological interpretations (fractured or unfractured clay till). The beliefs in each of the CSMs are assessed sequentially based on data from three investigation stages (a screening investigation, a more detailed investigation, and an expert consultation) to demonstrate that the belief can be updated as more information

  1. A Study on the Quantitative Assessment Method of Software Requirement Documents Using Software Engineering Measures and Bayesian Belief Networks

    International Nuclear Information System (INIS)

    Eom, Heung Seop; Kang, Hyun Gook; Park, Ki Hong; Kwon, Kee Choon; Chang, Seung Cheol

    2005-01-01

    One of the major challenges in using the digital systems in a NPP is the reliability estimation of safety critical software embedded in the digital safety systems. Precise quantitative assessment of the reliability of safety critical software is nearly impossible, since many of the aspects to be considered are of qualitative nature and not directly measurable, but they have to be estimated for a practical use. Therefore an expert's judgment plays an important role in estimating the reliability of the software embedded in safety-critical systems in practice, because they can deal with all the diverse evidence relevant to the reliability and can perform an inference based on the evidence. But, in general, the experts' way of combining the diverse evidence and performing an inference is usually informal and qualitative, which is hard to discuss and will eventually lead to a debate about the conclusion. We have been carrying out research on a quantitative assessment of the reliability of safety critical software using Bayesian Belief Networks (BBN). BBN has been proven to be a useful modeling formalism because a user can represent a complex set of events and relationships in a fashion that can easily be interpreted by others. In the previous works we have assessed a software requirement specification of a reactor protection system by using our BBN-based assessment model. The BBN model mainly employed an expert's subjective probabilities as inputs. In the process of assessing the software requirement documents we found out that the BBN model was excessively dependent on experts' subjective judgments in a large part. Therefore, to overcome the weakness of our methodology we employed conventional software engineering measures into the BBN model as shown in this paper. The quantitative relationship between the conventional software measures and the reliability of software were not identified well in the past. Then recently there appeared a few researches on a ranking of

  2. Can Bayesian Belief Networks help tackling conceptual model uncertainties in contaminated site risk assessment?

    DEFF Research Database (Denmark)

    Troldborg, Mads; Thomsen, Nanna Isbak; McKnight, Ursula S.

    different conceptual models may describe the same contaminated site equally well. In many cases, conceptual model uncertainty has been shown to be one of the dominant sources for uncertainty and is therefore essential to account for when quantifying uncertainties in risk assessments. We present here......A key component in risk assessment of contaminated sites is the formulation of a conceptual site model. The conceptual model is a simplified representation of reality and forms the basis for the mathematical modelling of contaminant fate and transport at the site. A conceptual model should...... a Bayesian Belief Network (BBN) approach for evaluating the uncertainty in risk assessment of groundwater contamination from contaminated sites. The approach accounts for conceptual model uncertainty by considering multiple conceptual models, each of which represents an alternative interpretation of the site...

  3. Bayesian Belief Networks (BBN) and Expert Systems for supporting model based sensor fault detection analysis of smart building systems

    NARCIS (Netherlands)

    Schagen, J.D.; Taal, A.; Itard, L.C.M.; Heiselberg, Per Kvols

    2016-01-01

    The Hague University in Delft uses an advanced climate control system. All sensors and actuators are monitored and deviations from the sensor data are reported daily. The building manager will have to combine the information from the sensor data in order to draw the right conclusions. In this paper,

  4. Baryon density in alternative BBN models

    International Nuclear Information System (INIS)

    Kirilova, D.

    2002-10-01

    We present recent determinations of the cosmological baryon density ρ b , extracted from different kinds of observational data. The baryon density range is not very wide and is usually interpreted as an indication for consistency. It is interesting to note that all other determinations give higher baryon density than the standard big bang nucleosynthesis (BBN) model. The differences of the ρ b values from the BBN predicted one (the most precise today) may be due to the statistical and systematic errors in observations. However, they may be an indication of new physics. Hence, it is interesting to study alternative BBN models, and the possibility to resolve the discrepancies. We discuss alternative cosmological scenarios: a BBN model with decaying particles (m ∼ MeV, τ ∼ sec) and BBN with electron-sterile neutrino oscillations, which permit to relax BBN constraints on the baryon content of the Universe. (author)

  5. Deep Belief Networks for dimensionality reduction

    NARCIS (Netherlands)

    Noulas, A.K.; Kröse, B.J.A.

    2008-01-01

    Deep Belief Networks are probabilistic generative models which are composed by multiple layers of latent stochastic variables. The top two layers have symmetric undirected connections, while the lower layers receive directed top-down connections from the layer above. The current state-of-the-art

  6. [Development and Application of a Performance Prediction Model for Home Care Nursing Based on a Balanced Scorecard using the Bayesian Belief Network].

    Science.gov (United States)

    Noh, Wonjung; Seomun, Gyeongae

    2015-06-01

    This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

  7. Development and Execution of the RUNSAFE Runway Safety Bayesian Belief Network Model

    Science.gov (United States)

    Green, Lawrence L.

    2015-01-01

    One focus area of the National Aeronautics and Space Administration (NASA) is to improve aviation safety. Runway safety is one such thrust of investigation and research. The two primary components of this runway safety research are in runway incursion (RI) and runway excursion (RE) events. These are adverse ground-based aviation incidents that endanger crew, passengers, aircraft and perhaps other nearby people or property. A runway incursion is the incorrect presence of an aircraft, vehicle or person on the protected area of a surface designated for the landing and take-off of aircraft; one class of RI events simultaneously involves two aircraft, such as one aircraft incorrectly landing on a runway while another aircraft is taking off from the same runway. A runway excursion is an incident involving only a single aircraft defined as a veer-off or overrun off the runway surface. Within the scope of this effort at NASA Langley Research Center (LaRC), generic RI, RE and combined (RI plus RE, or RUNSAFE) event models have each been developed and implemented as a Bayesian Belief Network (BBN). Descriptions of runway safety issues from the literature searches have been used to develop the BBN models. Numerous considerations surrounding the process of developing the event models have been documented in this report. The event models were then thoroughly reviewed by a Subject Matter Expert (SME) panel through multiple knowledge elicitation sessions. Numerous improvements to the model structure (definitions, node names, node states and the connecting link topology) were made by the SME panel. Sample executions of the final RUNSAFE model have been presented herein for baseline and worst-case scenarios. Finally, a parameter sensitivity analysis for a given scenario was performed to show the risk drivers. The NASA and LaRC research in runway safety event modeling through the use of BBN technology is important for several reasons. These include: 1) providing a means to clearly

  8. Bayesian Belief Networks Approach for Modeling Irrigation Behavior

    Science.gov (United States)

    Andriyas, S.; McKee, M.

    2012-12-01

    Canal operators need information to manage water deliveries to irrigators. Short-term irrigation demand forecasts can potentially valuable information for a canal operator who must manage an on-demand system. Such forecasts could be generated by using information about the decision-making processes of irrigators. Bayesian models of irrigation behavior can provide insight into the likely criteria which farmers use to make irrigation decisions. This paper develops a Bayesian belief network (BBN) to learn irrigation decision-making behavior of farmers and utilizes the resulting model to make forecasts of future irrigation decisions based on factor interaction and posterior probabilities. Models for studying irrigation behavior have been rarely explored in the past. The model discussed here was built from a combination of data about biotic, climatic, and edaphic conditions under which observed irrigation decisions were made. The paper includes a case study using data collected from the Canal B region of the Sevier River, near Delta, Utah. Alfalfa, barley and corn are the main crops of the location. The model has been tested with a portion of the data to affirm the model predictive capabilities. Irrigation rules were deduced in the process of learning and verified in the testing phase. It was found that most of the farmers used consistent rules throughout all years and across different types of crops. Soil moisture stress, which indicates the level of water available to the plant in the soil profile, was found to be one of the most significant likely driving forces for irrigation. Irrigations appeared to be triggered by a farmer's perception of soil stress, or by a perception of combined factors such as information about a neighbor irrigating or an apparent preference to irrigate on a weekend. Soil stress resulted in irrigation probabilities of 94.4% for alfalfa. With additional factors like weekend and irrigating when a neighbor irrigates, alfalfa irrigation

  9. Estimation of Remained defects in a Safety-Critical Software using Bayesian Belief Network of Software Development Life Cycle

    International Nuclear Information System (INIS)

    Lee, Seung Jun; Jung, Wondea Jung

    2015-01-01

    Some researchers recognized Bayesian belief network (BBN) method to be a promising method of quantifying software reliability. Brookhaven National Laboratory (BNL) comprehensively reviewed various quantitative software reliability methods to identify the most promising methods for use in probabilistic safety assessments (PSAs) of digital systems of NPPs against a set of the most desirable characteristics developed therein. BBNs are recognized as a promising way of quantifying software reliability and are useful for integrating many aspects of software engineering and quality assurance. The method explicitly incorporates important factors relevant to reliability, such as the quality of the developer, the development process, problem complexity, testing effort, and the operation environment. In this work, a BBN model was developed to estimate the number of remained defects in a safety-critical software based on the quality evaluation of software development life cycle (SDLC). Even though a number of software reliability evaluation methods exist, none of them can be applicable to the safety-critical software in an NPP because software quality in terms of PDF is required for the PSA

  10. Bayesian Belief Networks for predicting drinking water distribution system pipe breaks

    International Nuclear Information System (INIS)

    Francis, Royce A.; Guikema, Seth D.; Henneman, Lucas

    2014-01-01

    In this paper, we use Bayesian Belief Networks (BBNs) to construct a knowledge model for pipe breaks in a water zone. To the authors’ knowledge, this is the first attempt to model drinking water distribution system pipe breaks using BBNs. Development of expert systems such as BBNs for analyzing drinking water distribution system data is not only important for pipe break prediction, but is also a first step in preventing water loss and water quality deterioration through the application of machine learning techniques to facilitate data-based distribution system monitoring and asset management. Due to the difficulties in collecting, preparing, and managing drinking water distribution system data, most pipe break models can be classified as “statistical–physical” or “hypothesis-generating.” We develop the BBN with the hope of contributing to the “hypothesis-generating” class of models, while demonstrating the possibility that BBNs might also be used as “statistical–physical” models. Our model is learned from pipe breaks and covariate data from a mid-Atlantic United States (U.S.) drinking water distribution system network. BBN models are learned using a constraint-based method, a score-based method, and a hybrid method. Model evaluation is based on log-likelihood scoring. Sensitivity analysis using mutual information criterion is also reported. While our results indicate general agreement with prior results reported in pipe break modeling studies, they also suggest that it may be difficult to select among model alternatives. This model uncertainty may mean that more research is needed for understanding whether additional pipe break risk factors beyond age, break history, pipe material, and pipe diameter might be important for asset management planning. - Highlights: • We show Bayesian Networks for predictive and diagnostic management of water distribution systems. • Our model may enable system operators and managers to prioritize system

  11. Coastal vulnerability assessment using Fuzzy Logic and Bayesian Belief Network approaches

    Science.gov (United States)

    Valentini, Emiliana; Nguyen Xuan, Alessandra; Filipponi, Federico; Taramelli, Andrea

    2017-04-01

    Natural hazards such as sea surge are threatening low-lying coastal plains. In order to deal with disturbances a deeper understanding of benefits deriving from ecosystem services assessment, management and planning can contribute to enhance the resilience of coastal systems. In this frame assessing current and future vulnerability is a key concern of many Systems Of Systems SOS (social, ecological, institutional) that deals with several challenges like the definition of Essential Variables (EVs) able to synthesize the required information, the assignment of different weight to be attributed to each considered variable, the selection of method for combining the relevant variables. It is widely recognized that ecosystems contribute to human wellbeing and then their conservation increases the resilience capacities and could play a key role in reducing climate related risk and thus physical and economic losses. A way to fully exploit ecosystems potential, i.e. their so called ecopotential (see H2020 EU funded project "ECOPOTENTIAL"), is the Ecosystem based Adaptation (EbA): the use of ecosystem services as part of an adaptation strategy. In order to provide insight in understanding regulating ecosystem services to surge and which variables influence them and to make the best use of available data and information (EO products, in situ data and modelling), we propose a multi-component surge vulnerability assessment, focusing on coastal sandy dunes as natural barriers. The aim is to combine together eco-geomorphological and socio-economic variables with the hazard component on the base of different approaches: 1) Fuzzy Logic; 2) Bayesian Belief Networks (BBN). The Fuzzy Logic approach is very useful to get a spatialized information and it can easily combine variables coming from different sources. It provides information on vulnerability moving along-shore and across-shore (beach-dune transect), highlighting the variability of vulnerability conditions in the spatial

  12. A Bayesian Belief Network Approach to Predict Damages Caused by Disturbance Agents

    Directory of Open Access Journals (Sweden)

    Alfred Radl

    2017-12-01

    Full Text Available In mountain forests of Central Europe, storm and snow breakage as well as bark beetles are the prevailing major disturbances. The complex interrelatedness between climate, disturbance agents, and forest management increases the need for an integrative approach explicitly addressing the multiple interactions between environmental changes, forest management, and disturbance agents to support forest resource managers in adaptive management. Empirical data with a comprehensive coverage for modelling the susceptibility of forests and the impact of disturbance agents are rare, thus making probabilistic models, based on expert knowledge, one of the few modelling approaches that are able to handle uncertainties due to the available information. Bayesian belief networks (BBNs are a kind of probabilistic graphical model that has become very popular to practitioners and scientists mainly due to considerations of risk and uncertainties. In this contribution, we present a development methodology to define and parameterize BBNs based on expert elicitation and approximation. We modelled storm and bark beetle disturbances agents, analyzed effects of the development methodology on model structure, and evaluated behavior with stand data from Norway spruce (Picea abies (L. Karst. forests in southern Austria. The high vulnerability of the case study area according to different disturbance agents makes it particularly suitable for testing the BBN model.

  13. [Terahertz Spectroscopic Identification with Deep Belief Network].

    Science.gov (United States)

    Ma, Shuai; Shen, Tao; Wang, Rui-qi; Lai, Hua; Yu, Zheng-tao

    2015-12-01

    Feature extraction and classification are the key issues of terahertz spectroscopy identification. Because many materials have no apparent absorption peaks in the terahertz band, it is difficult to extract theirs terahertz spectroscopy feature and identify. To this end, a novel of identify terahertz spectroscopy approach with Deep Belief Network (DBN) was studied in this paper, which combines the advantages of DBN and K-Nearest Neighbors (KNN) classifier. Firstly, cubic spline interpolation and S-G filter were used to normalize the eight kinds of substances (ATP, Acetylcholine Bromide, Bifenthrin, Buprofezin, Carbazole, Bleomycin, Buckminster and Cylotriphosphazene) terahertz transmission spectra in the range of 0.9-6 THz. Secondly, the DBN model was built by two restricted Boltzmann machine (RBM) and then trained layer by layer using unsupervised approach. Instead of using handmade features, the DBN was employed to learn suitable features automatically with raw input data. Finally, a KNN classifier was applied to identify the terahertz spectrum. Experimental results show that using the feature learned by DBN can identify the terahertz spectrum of different substances with the recognition rate of over 90%, which demonstrates that the proposed method can automatically extract the effective features of terahertz spectrum. Furthermore, this KNN classifier was compared with others (BP neural network, SOM neural network and RBF neural network). Comparisons showed that the recognition rate of KNN classifier is better than the other three classifiers. Using the approach that automatic extract terahertz spectrum features by DBN can greatly reduce the workload of feature extraction. This proposed method shows a promising future in the application of identifying the mass terahertz spectroscopy.

  14. Facial expression recognition based on improved deep belief networks

    Science.gov (United States)

    Wu, Yao; Qiu, Weigen

    2017-08-01

    In order to improve the robustness of facial expression recognition, a method of face expression recognition based on Local Binary Pattern (LBP) combined with improved deep belief networks (DBNs) is proposed. This method uses LBP to extract the feature, and then uses the improved deep belief networks as the detector and classifier to extract the LBP feature. The combination of LBP and improved deep belief networks is realized in facial expression recognition. In the JAFFE (Japanese Female Facial Expression) database on the recognition rate has improved significantly.

  15. BBN-Based Portfolio Risk Assessment for NASA Technology R&D Outcome

    Science.gov (United States)

    Geuther, Steven C.; Shih, Ann T.

    2016-01-01

    The NASA Aeronautics Research Mission Directorate (ARMD) vision falls into six strategic thrusts that are aimed to support the challenges of the Next Generation Air Transportation System (NextGen). In order to achieve the goals of the ARMD vision, the Airspace Operations and Safety Program (AOSP) is committed to developing and delivering new technologies. To meet the dual challenges of constrained resources and timely technology delivery, program portfolio risk assessment is critical for communication and decision-making. This paper describes how Bayesian Belief Network (BBN) is applied to assess the probability of a technology meeting the expected outcome. The network takes into account the different risk factors of technology development and implementation phases. The use of BBNs allows for all technologies of projects in a program portfolio to be separately examined and compared. In addition, the technology interaction effects are modeled through the application of object-oriented BBNs. The paper discusses the development of simplified project risk BBNs and presents various risk results. The results presented include the probability of project risks not meeting success criteria, the risk drivers under uncertainty via sensitivity analysis, and what-if analysis. Finally, the paper shows how program portfolio risk can be assessed using risk results from BBNs of projects in the portfolio.

  16. Some nuclear physics aspects of BBN

    Science.gov (United States)

    Coc, Alain

    2017-09-01

    Primordial or big bang nucleosynthesis (BBN) is now a parameter free theory whose predictions are in good overall agreement with observations. However, the 7 Li calculated abundance is significantly higher than the one deduced from spectroscopic observations. Nuclear physics solutions to this lithium problem have been investigated by experimental means. Other solutions which were considered involve exotic sources of extra neutrons which inevitably leads to an increase of the deuterium abundance, but this seems now excluded by recent deuterium observations.

  17. Characterizing Species at Risk II: Using Bayesian Belief Networks as Decision Support Tools to Determine Species Conservation Categories Under the Northwest Forest Plan

    Directory of Open Access Journals (Sweden)

    Bruce G. Marcot

    2006-12-01

    Full Text Available We developed a set of decision-aiding models as Bayesian belief networks (BBNs that represented a complex set of evaluation guidelines used to determine the appropriate conservation of hundreds of potentially rare species on federally-administered lands in the Pacific Northwest United States. The models were used in a structured assessment and paneling procedure as part of an adaptive management process that evaluated new scientific information under the Northwest Forest Plan. The models were not prescriptive but helped resource managers and specialists to evaluate complicated and at times conflicting conservation guidelines and to reduce bias and uncertainty in evaluating the scientific data. We concluded that applying the BBN modeling framework to complex and equivocal evaluation guidelines provided a set of clear, intuitive decision-aiding tools that greatly aided the species evaluation and conservation process.

  18. Stakeholder perceptions of soil managements in the Canyoles watershed. A Bayesian Belief Network approach

    Science.gov (United States)

    Burguet Marimón, Maria; Quinn, Claire; Stringer, Lindsay; Cerdà, Artemi

    2017-04-01

    The fate of the management and use of land is the result of economic, social and political factors (Tengberg et al., 2016). Stakeholder perceptions are relevant in understanding land management (Marques et al., 2015; Teshome et al., 2016) as perceptions can shape behaviours and actions. In the Canyoles River watershed (Eastern Spain), rainfed agriculture has been replaced by traditional irrigation systems at its valley bottom, and by drip irrigation on its slopes. The new irrigation systems in hilly citrus orchards, along with intensive farming, use of herbicides and high fertilization, are causing high erosion and land degradation rates due to the lack of vegetation cover, soil compaction and the loss of organic matter. Bayesian Belief Networks (BBN) are defined as a 'graphical tool for building decision support systems to help make decisions under uncertain conditions' (Cain, 2001). In this work, BBNs were used to incorporate the issues and objectives identified by stakeholders during interviews about their perceptions of different soil management practices in the Canyoles watershed. BBNs are appropriate for the modeling of geospatial data which can contain different kinds of uncertainties due to positional error, feature classification error, resolution, attribute error, data completeness, currency, and logical consistency, and can integrate qualitative and quantitative data. Our stakeholders were farmers, politicians (especially the mayors of the nearby towns), managers, farm employees and technicians. The questions asked to the stakeholders were related to their concern in keeping the farm active and profitable, the changes in the price of the farm products, the price of the fertilizers and tractors and if soil erosion is a key issue in their farms Preliminary results from the interviews performed with the stakeholders suggest that there is still a strong refusal to the use of different cover crops, as well as to the change in the tillage systems. Farmers do

  19. Application of Bayesian Belief networks to the human reliability analysis of an oil tanker operation focusing on collision accidents

    International Nuclear Information System (INIS)

    Martins, Marcelo Ramos; Maturana, Marcos Coelho

    2013-01-01

    During the last three decades, several techniques have been developed for the quantitative study of human reliability. In the 1980s, techniques were developed to model systems by means of binary trees, which did not allow for the representation of the context in which human actions occur. Thus, these techniques cannot model the representation of individuals, their interrelationships, and the dynamics of a system. These issues make the improvement of methods for Human Reliability Analysis (HRA) a pressing need. To eliminate or at least attenuate these limitations, some authors have proposed modeling systems using Bayesian Belief Networks (BBNs). The application of these tools is expected to address many of the deficiencies in current approaches to modeling human actions with binary trees. This paper presents a methodology based on BBN for analyzing human reliability and applies this method to the operation of an oil tanker, focusing on the risk of collision accidents. The obtained model was used to determine the most likely sequence of hazardous events and thus isolate critical activities in the operation of the ship to study Internal Factors (IFs), Skills, and Management and Organizational Factors (MOFs) that should receive more attention for risk reduction.

  20. A method for risk-informed safety significance categorization using the analytic hierarchy process and bayesian belief networks

    International Nuclear Information System (INIS)

    Ha, Jun Su; Seong, Poong Hyun

    2004-01-01

    A risk-informed safety significance categorization (RISSC) is to categorize structures, systems, or components (SSCs) of a nuclear power plant (NPP) into two or more groups, according to their safety significance using both probabilistic and deterministic insights. In the conventional methods for the RISSC, the SSCs are quantitatively categorized according to their importance measures for the initial categorization. The final decisions (categorizations) of SSCs, however, are qualitatively made by an expert panel through discussions and adjustments of opinions by using the probabilistic insights compiled in the initial categorization process and combining the probabilistic insights with the deterministic insights. Therefore, owing to the qualitative and linear decision-making process, the conventional methods have the demerits as follows: (1) they are very costly in terms of time and labor, (2) it is not easy to reach the final decision, when the opinions of the experts are in conflict and (3) they have an overlapping process due to the linear paradigm (the categorization is performed twice - first, by the engineers who propose the method, and second, by the expert panel). In this work, a method for RISSC using the analytic hierarchy process (AHP) and bayesian belief networks (BBN) is proposed to overcome the demerits of the conventional methods and to effectively arrive at a final decision (or categorization). By using the AHP and BBN, the expert panel takes part in the early stage of the categorization (that is, the quantification process) and the safety significance based on both probabilistic and deterministic insights is quantified. According to that safety significance, SSCs are quantitatively categorized into three categories such as high safety significant category (Hi), potentially safety significant category (Po), or low safety significant category (Lo). The proposed method was applied to the components such as CC-V073, CV-V530, and SI-V644 in Ulchin Unit

  1. Rational Irrationality: Modeling Climate Change Belief Polarization Using Bayesian Networks.

    Science.gov (United States)

    Cook, John; Lewandowsky, Stephan

    2016-01-01

    Belief polarization is said to occur when two people respond to the same evidence by updating their beliefs in opposite directions. This response is considered to be "irrational" because it involves contrary updating, a form of belief updating that appears to violate normatively optimal responding, as for example dictated by Bayes' theorem. In light of much evidence that people are capable of normatively optimal behavior, belief polarization presents a puzzling exception. We show that Bayesian networks, or Bayes nets, can simulate rational belief updating. When fit to experimental data, Bayes nets can help identify the factors that contribute to polarization. We present a study into belief updating concerning the reality of climate change in response to information about the scientific consensus on anthropogenic global warming (AGW). The study used representative samples of Australian and U.S. Among Australians, consensus information partially neutralized the influence of worldview, with free-market supporters showing a greater increase in acceptance of human-caused global warming relative to free-market opponents. In contrast, while consensus information overall had a positive effect on perceived consensus among U.S. participants, there was a reduction in perceived consensus and acceptance of human-caused global warming for strong supporters of unregulated free markets. Fitting a Bayes net model to the data indicated that under a Bayesian framework, free-market support is a significant driver of beliefs about climate change and trust in climate scientists. Further, active distrust of climate scientists among a small number of U.S. conservatives drives contrary updating in response to consensus information among this particular group. Copyright © 2016 Cognitive Science Society, Inc.

  2. Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

    Science.gov (United States)

    Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

    2017-01-01

    Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  3. Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Ira zulfa

    2017-07-01

    Full Text Available Sentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research. It aims to move machine learning closer to its main goal, artificial intelligence. The purpose of deep learning is to change the manual of engineering with learning. At its growth, deep learning has algorithms arrangement that focus on non-linear data representation. One of the machine learning methods is Deep Belief Network (DBN. Deep Belief Network (DBN, which is included in Deep Learning method, is a stack of several algorithms with some extraction features that optimally utilize all resources. This study has two points. First, it aims to classify positive, negative, and neutral sentiments towards the test data. Second, it determines the classification model accuracy by using Deep Belief Network method so it would be able to be applied into the tweet classification, to highlight the sentiment class of training data tweet in Bahasa Indonesia. Based on the experimental result, it can be concluded that the best method in managing tweet data is the DBN method with an accuracy of 93.31%, compared with  Naive Bayes method which has an accuracy of 79.10%, and SVM (Support Vector Machine method with an accuracy of 92.18%.

  4. Fuzzy knowledge base construction through belief networks based on Lukasiewicz logic

    Science.gov (United States)

    Lara-Rosano, Felipe

    1992-01-01

    In this paper, a procedure is proposed to build a fuzzy knowledge base founded on fuzzy belief networks and Lukasiewicz logic. Fuzzy procedures are developed to do the following: to assess the belief values of a consequent, in terms of the belief values of its logical antecedents and the belief value of the corresponding logical function; and to update belief values when new evidence is available.

  5. Using Bayesian Belief Networks and event trees for volcanic hazard assessment and decision support : reconstruction of past eruptions of La Soufrière volcano, Guadeloupe and retrospective analysis of 1975-77 unrest.

    Science.gov (United States)

    Komorowski, Jean-Christophe; Hincks, Thea; Sparks, Steve; Aspinall, Willy; Legendre, Yoann; Boudon, Georges

    2013-04-01

    Since 1992, mild but persistent seismic and fumarolic unrest at La Soufrière de Guadeloupe volcano has prompted renewed concern about hazards and risks, crisis response planning, and has rejuvenated interest in geological studies. Scientists monitoring active volcanoes frequently have to provide science-based decision support to civil authorities during such periods of unrest. In these circumstances, the Bayesian Belief Network (BBN) offers a formalized evidence analysis tool for making inferences about the state of the volcano from different strands of data, allowing associated uncertainties to be treated in a rational and auditable manner, to the extent warranted by the strength of the evidence. To illustrate the principles of the BBN approach, a retrospective analysis is undertaken of the 1975-77 crisis, providing an inferential assessment of the evolving state of the magmatic system and the probability of subsequent eruption. Conditional dependencies and parameters in the BBN are characterized quantitatively by structured expert elicitation. Revisiting data available in 1976 suggests the probability of magmatic intrusion would have been evaluated high at the time, according with subsequent thinking about the volcanological nature of the episode. The corresponding probability of a magmatic eruption therefore would have been elevated in July and August 1976; however, collective uncertainty about the future course of the crisis was great at the time, even if some individual opinions were certain. From this BBN analysis, while the more likely appraised outcome - based on observational trends at 31 August 1976 - might have been 'no eruption' (mean probability 0.5; 5-95 percentile range 0.8), an imminent magmatic eruption (or blast) could have had a probability of about 0.4, almost as substantial. Thus, there was no real scientific basis to assert one scenario was more likely than the other. This retrospective evaluation adds objective probabilistic expression to

  6. Approximation Methods for Inference and Learning in Belief Networks: Progress and Future Directions

    National Research Council Canada - National Science Library

    Pazzan, Michael

    1997-01-01

    .... In this research project, we have investigated methods and implemented algorithms for efficiently making certain classes of inference in belief networks, and for automatically learning certain...

  7. Predicting Software Suitability Using a Bayesian Belief Network

    Science.gov (United States)

    Beaver, Justin M.; Schiavone, Guy A.; Berrios, Joseph S.

    2005-01-01

    The ability to reliably predict the end quality of software under development presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This research proposes a model that captures the evolution of the quality of a software product, and provides reliable forecasts of the end quality of the software being developed in terms of product suitability. Development team skill, software process maturity, and software problem complexity are hypothesized as driving factors of software product quality. The cause-effect relationships between these factors and the elements of software suitability are modeled using Bayesian Belief Networks, a machine learning method. This research presents a Bayesian Network for software quality, and the techniques used to quantify the factors that influence and represent software quality. The developed model is found to be effective in predicting the end product quality of small-scale software development efforts.

  8. Random Deep Belief Networks for Recognizing Emotions from Speech Signals

    Directory of Open Access Journals (Sweden)

    Guihua Wen

    2017-01-01

    Full Text Available Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

  9. Probabilistic Volcanic Multi-Hazard Assessment at Somma-Vesuvius (Italy): coupling Bayesian Belief Networks with a physical model for lahar propagation

    Science.gov (United States)

    Tierz, Pablo; Woodhouse, Mark; Phillips, Jeremy; Sandri, Laura; Selva, Jacopo; Marzocchi, Warner; Odbert, Henry

    2017-04-01

    Volcanoes are extremely complex physico-chemical systems where magma formed at depth breaks into the planet's surface resulting in major hazards from local to global scales. Volcano physics are dominated by non-linearities, and complicated spatio-temporal interrelationships which make volcanic hazards stochastic (i.e. not deterministic) by nature. In this context, probabilistic assessments are required to quantify the large uncertainties related to volcanic hazards. Moreover, volcanoes are typically multi-hazard environments where different hazardous processes can occur whether simultaneously or in succession. In particular, explosive volcanoes are able to accumulate, through tephra fallout and Pyroclastic Density Currents (PDCs), large amounts of pyroclastic material into the drainage basins surrounding the volcano. This addition of fresh particulate material alters the local/regional hydrogeological equilibrium and increases the frequency and magnitude of sediment-rich aqueous flows, commonly known as lahars. The initiation and volume of rain-triggered lahars may depend on: rainfall intensity and duration; antecedent rainfall; terrain slope; thickness, permeability and hydraulic diffusivity of the tephra deposit; etc. Quantifying these complex interrelationships (and their uncertainties), in a tractable manner, requires a structured but flexible probabilistic approach. A Bayesian Belief Network (BBN) is a directed acyclic graph that allows the representation of the joint probability distribution for a set of uncertain variables in a compact and efficient way, by exploiting unconditional and conditional independences between these variables. Once constructed and parametrized, the BBN uses Bayesian inference to perform causal (e.g. forecast) and/or evidential reasoning (e.g. explanation) about query variables, given some evidence. In this work, we illustrate how BBNs can be used to model the influence of several variables on the generation of rain-triggered lahars

  10. Hypothesis Management Framework: a exible design pattern for belief networks in decision support systems

    NARCIS (Netherlands)

    Gosliga, S.P. van; Voorde, I. van de

    2008-01-01

    This article discusses a design pattern for building belief networks for application domains in which causal models are hard to construct. In this approach we pursue a modular belief network structure that is easily extended by the users themselves, while remaining reliable for decision support. The

  11. Single and combined fault diagnosis of reciprocating compressor valves using a hybrid deep belief network

    NARCIS (Netherlands)

    Tran, Van Tung; Thobiani, Faisal Al; Tinga, Tiedo; Ball, Andrew David; Niu, Gang

    2017-01-01

    In this paper, a hybrid deep belief network is proposed to diagnose single and combined faults of suction and discharge valves in a reciprocating compressor. This hybrid integrates the deep belief network structured by multiple stacked restricted Boltzmann machines for pre-training and simplified

  12. Causal inference in biology networks with integrated belief propagation.

    Science.gov (United States)

    Chang, Rui; Karr, Jonathan R; Schadt, Eric E

    2015-01-01

    Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

  13. Prediction of new bioactive molecules using a Bayesian belief network.

    Science.gov (United States)

    Abdo, Ammar; Leclère, Valérie; Jacques, Philippe; Salim, Naomie; Pupin, Maude

    2014-01-27

    Natural products and synthetic compounds are a valuable source of new small molecules leading to novel drugs to cure diseases. However identifying new biologically active small molecules is still a challenge. In this paper, we introduce a new activity prediction approach using Bayesian belief network for classification (BBNC). The roots of the network are the fragments composing a compound. The leaves are, on one side, the activities to predict and, on another side, the unknown compound. The activities are represented by sets of known compounds, and sets of inactive compounds are also used. We calculated a similarity between an unknown compound and each activity class. The more similar activity is assigned to the unknown compound. We applied this new approach on eight well-known data sets extracted from the literature and compared its performance to three classical machine learning algorithms. Experiments showed that BBNC provides interesting prediction rates (from 79% accuracy for high diverse data sets to 99% for low diverse ones) with a short time calculation. Experiments also showed that BBNC is particularly effective for homogeneous data sets but has been found to perform less well with structurally heterogeneous sets. However, it is important to stress that we believe that using several approaches whenever possible for activity prediction can often give a broader understanding of the data than using only one approach alone. Thus, BBNC is a useful addition to the computational chemist's toolbox.

  14. Gender differences in collaborative learning over online social networks: Epistemological beliefs and behaviors

    Directory of Open Access Journals (Sweden)

    Rosanna Y.-Y. Chan

    2013-09-01

    Full Text Available Online social networks are popular venues for computer-supported collaborative work and computer-supported collaborative learning. Professionals within the same discipline, such as software developers, often interact over various social network sites for knowledge updates and collective understandings. The current study aims at gathering empirical evidences concerning gender differences in online social network beliefs and behaviors. A total of 53 engineering postgraduate students were engaged in a blogging community for collaborative learning. Participants’ beliefs about collaboration and nature of knowledge and knowing (i.e. epistemological beliefs are investigated. More specifically, social network analysis metrics including in-degree, out-degree, closeness centrality, and betweenness centrality are obtained from an 8-interval longitudinal SNA. Methodologically speaking, the current work puts forward mixed methods of longitudinal SNA and quantitative beliefs survey to explore online social network participants’ beliefs and behaviors. The study’s findings demonstrate significant gender differences in collaborative learning through online social networks, including (1 female engineering postgraduate students engage significantly more actively in online communications, (2 male engineering postgraduate students are more likely to be the potential controllers of information flows, and (3 gender differences exist in belief gains related to social aspects, but not individual's epistemic aspects. Overall, participants in both genders demonstrated enhanced beliefs in collaboration as well as the nature of knowledge and knowing.

  15. A deep belief network with PLSR for nonlinear system modeling.

    Science.gov (United States)

    Qiao, Junfei; Wang, Gongming; Li, Wenjing; Li, Xiaoli

    2017-10-31

    Nonlinear system modeling plays an important role in practical engineering, and deep learning-based deep belief network (DBN) is now popular in nonlinear system modeling and identification because of the strong learning ability. However, the existing weights optimization for DBN is based on gradient, which always leads to a local optimum and a poor training result. In this paper, a DBN with partial least square regression (PLSR-DBN) is proposed for nonlinear system modeling, which focuses on the problem of weights optimization for DBN using PLSR. Firstly, unsupervised contrastive divergence (CD) algorithm is used in weights initialization. Secondly, initial weights derived from CD algorithm are optimized through layer-by-layer PLSR modeling from top layer to bottom layer. Instead of gradient method, PLSR-DBN can determine the optimal weights using several PLSR models, so that a better performance of PLSR-DBN is achieved. Then, the analysis of convergence is theoretically given to guarantee the effectiveness of the proposed PLSR-DBN model. Finally, the proposed PLSR-DBN is tested on two benchmark nonlinear systems and an actual wastewater treatment system as well as a handwritten digit recognition (nonlinear mapping and modeling) with high-dimension input data. The experiment results show that the proposed PLSR-DBN has better performances of time and accuracy on nonlinear system modeling than that of other methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Academic Activities Transaction Extraction Based on Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Xiangqian Wang

    2017-01-01

    Full Text Available Extracting information about academic activity transactions from unstructured documents is a key problem in the analysis of academic behaviors of researchers. The academic activities transaction includes five elements: person, activities, objects, attributes, and time phrases. The traditional method of information extraction is to extract shallow text features and then to recognize advanced features from text with supervision. Since the information processing of different levels is completed in steps, the error generated from various steps will be accumulated and affect the accuracy of final results. However, because Deep Belief Network (DBN model has the ability to automatically unsupervise learning of the advanced features from shallow text features, the model is employed to extract the academic activities transaction. In addition, we use character-based feature to describe the raw features of named entities of academic activity, so as to improve the accuracy of named entity recognition. In this paper, the accuracy of the academic activities extraction is compared by using character-based feature vector and word-based feature vector to express the text features, respectively, and with the traditional text information extraction based on Conditional Random Fields. The results show that DBN model is more effective for the extraction of academic activities transaction information.

  17. MODELING INFORMATION SYSTEM AVAILABILITY BY USING BAYESIAN BELIEF NETWORK APPROACH

    Directory of Open Access Journals (Sweden)

    Semir Ibrahimović

    2016-03-01

    Full Text Available Modern information systems are expected to be always-on by providing services to end-users, regardless of time and location. This is particularly important for organizations and industries where information systems support real-time operations and mission-critical applications that need to be available on 24  7  365 basis. Examples of such entities include process industries, telecommunications, healthcare, energy, banking, electronic commerce and a variety of cloud services. This article presents a modified Bayesian Belief Network model for predicting information system availability, introduced initially by Franke, U. and Johnson, P. (in article “Availability of enterprise IT systems – an expert based Bayesian model”. Software Quality Journal 20(2, 369-394, 2012 based on a thorough review of several dimensions of the information system availability, we proposed a modified set of determinants. The model is parameterized by using probability elicitation process with the participation of experts from the financial sector of Bosnia and Herzegovina. The model validation was performed using Monte Carlo simulation.

  18. A deep belief network approach using VDRAS data for nowcasting

    Science.gov (United States)

    Han, Lei; Dai, Jie; Zhang, Wei; Zhang, Changjiang; Feng, Hanlei

    2018-04-01

    Nowcasting or very short-term forecasting convective storms is still a challenging problem due to the high nonlinearity and insufficient observation of convective weather. As the understanding of the physical mechanism of convective weather is also insufficient, the numerical weather model cannot predict convective storms well. Machine learning approaches provide a potential way to nowcast convective storms using various meteorological data. In this study, a deep belief network (DBN) is proposed to nowcast convective storms using the real-time re-analysis meteorological data. The nowcasting problem is formulated as a classification problem. The 3D meteorological variables are fed directly to the DBN with dimension of input layer 6*6*80. Three hidden layers are used in the DBN and the dimension of output layer is two. A box-moving method is presented to provide the input features containing the temporal and spatial information. The results show that the DNB can generate reasonable prediction results of the movement and growth of convective storms.

  19. Isolated guitar transcription using a deep belief network

    Directory of Open Access Journals (Sweden)

    Gregory Burlet

    2017-03-01

    Full Text Available Music transcription involves the transformation of an audio recording to common music notation, colloquially referred to as sheet music. Manually transcribing audio recordings is a difficult and time-consuming process, even for experienced musicians. In response, several algorithms have been proposed to automatically analyze and transcribe the notes sounding in an audio recording; however, these algorithms are often general-purpose, attempting to process any number of instruments producing any number of notes sounding simultaneously. This paper presents a polyphonic transcription algorithm that is constrained to processing the audio output of a single instrument, specifically an acoustic guitar. The transcription system consists of a novel note pitch estimation algorithm that uses a deep belief network and multi-label learning techniques to generate multiple pitch estimates for each analysis frame of the input audio signal. Using a compiled dataset of synthesized guitar recordings for evaluation, the algorithm described in this work results in an 11% increase in the f-measure of note transcriptions relative to Zhou et al.’s (2009 transcription algorithm in the literature. This paper demonstrates the effectiveness of deep, multi-label learning for the task of polyphonic transcription.

  20. Peer beliefs and smoking in adolescence: a longitudinal social network analysis.

    Science.gov (United States)

    Ragan, Daniel T

    2016-03-01

    Peer smoking is one of the strongest predictors of adolescent cigarette use, but less is known about whether other peer characteristics also contribute to this behavior. This study examined the links between adolescent cigarette use and peer beliefs about smoking. It tested whether peer beliefs about smoking are associated with changes in cigarette use, whether this association is a result of changes in individual beliefs about smoking, and how beliefs inform friendship choices. Analyses drew on data collected from 29 school-based networks, each measured at five occasions as students moved from 6th through 9th grade, as part of the study of the PROSPER partnership model. Longitudinal social network models provided estimates of friendship selection and behavior for an average of 6,200 students at each measurement point and more than 9,000 students overall. Peer beliefs about smoking influenced cigarette use both directly and through their impact on individual beliefs. Respondents tended to name friends whose beliefs about smoking were similar to their own, and the likelihood of being named as a friend was higher for those who reported more positive beliefs about smoking. The results from this study suggest that peer beliefs about smoking, in addition to peer cigarette use itself, are associated with adolescent smoking through several mechanisms. Because beliefs favorable to cigarette use are present before adolescents actually smoke, these results underscore the importance of implementing smoking prevention programs in early adolescence.

  1. A Belief Network Decision Support Method Applied to Aerospace Surveillance and Battle Management Projects

    National Research Council Canada - National Science Library

    Staker, R

    2003-01-01

    This report demonstrates the application of a Bayesian Belief Network decision support method for Force Level Systems Engineering to a collection of projects related to Aerospace Surveillance and Battle Management...

  2. A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

    Science.gov (United States)

    2017-12-05

    A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

  3. Deep Belief Networks Based Toponym Recognition for Chinese Text

    Directory of Open Access Journals (Sweden)

    Shu Wang

    2018-06-01

    Full Text Available In Geographical Information Systems, geo-coding is used for the task of mapping from implicitly geo-referenced data to explicitly geo-referenced coordinates. At present, an enormous amount of implicitly geo-referenced information is hidden in unstructured text, e.g., Wikipedia, social data and news. Toponym recognition is the foundation of mining this useful geo-referenced information by identifying words as toponyms in text. In this paper, we propose an adapted toponym recognition approach based on deep belief network (DBN by exploring two key issues: word representation and model interpretation. A Skip-Gram model is used in the word representation process to represent words with contextual information that are ignored by current word representation models. We then determine the core hyper-parameters of the DBN model by illustrating the relationship between the performance and the hyper-parameters, e.g., vector dimensionality, DBN structures and probability thresholds. The experiments evaluate the performance of the Skip-Gram model implemented by the Word2Vec open-source tool, determine stable hyper-parameters and compare our approach with a conditional random field (CRF based approach. The experimental results show that the DBN model outperforms the CRF model with smaller corpus. When the corpus size is large enough, their statistical metrics become approaching. However, their recognition results express differences and complementarity on different kinds of toponyms. More importantly, combining their results can directly improve the performance of toponym recognition relative to their individual performances. It seems that the scale of the corpus has an obvious effect on the performance of toponym recognition. Generally, there is no adequate tagged corpus on specific toponym recognition tasks, especially in the era of Big Data. In conclusion, we believe that the DBN-based approach is a promising and powerful method to extract geo

  4. Network Traffic Prediction Based on Deep Belief Network and Spatiotemporal Compressive Sensing in Wireless Mesh Backbone Networks

    Directory of Open Access Journals (Sweden)

    Laisen Nie

    2018-01-01

    Full Text Available Wireless mesh network is prevalent for providing a decentralized access for users and other intelligent devices. Meanwhile, it can be employed as the infrastructure of the last few miles connectivity for various network applications, for example, Internet of Things (IoT and mobile networks. For a wireless mesh backbone network, it has obtained extensive attention because of its large capacity and low cost. Network traffic prediction is important for network planning and routing configurations that are implemented to improve the quality of service for users. This paper proposes a network traffic prediction method based on a deep learning architecture and the Spatiotemporal Compressive Sensing method. The proposed method first adopts discrete wavelet transform to extract the low-pass component of network traffic that describes the long-range dependence of itself. Then, a prediction model is built by learning a deep architecture based on the deep belief network from the extracted low-pass component. Otherwise, for the remaining high-pass component that expresses the gusty and irregular fluctuations of network traffic, the Spatiotemporal Compressive Sensing method is adopted to predict it. Based on the predictors of two components, we can obtain a predictor of network traffic. From the simulation, the proposed prediction method outperforms three existing methods.

  5. Continuous/discrete non parametric Bayesian belief nets with UNICORN and UNINET

    NARCIS (Netherlands)

    Cooke, R.M.; Kurowicka, D.; Hanea, A.M.; Morales Napoles, O.; Ababei, D.A.; Ale, B.J.M.; Roelen, A.

    2007-01-01

    Hanea et al. (2006) presented a method for quantifying and computing continuous/discrete non parametric Bayesian Belief Nets (BBN). Influences are represented as conditional rank correlations, and the joint normal copula enables rapid sampling and conditionalization. Further mathematical background

  6. A belief network approach for development of a nuclear power plant diagnosis system

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, I K; Kim, J T; Lee, D Y; Jung, C H; Kim, J Y; Lee, J S; Ham, C S [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1999-12-31

    Belief network (or Bayesian network) based on Bayes` rule in probabilistic theory can be applied to the reasoning of diagnostic system. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences. 6 refs., 3 figs. (Author)

  7. A belief network approach for development of a nuclear power plant diagnosis system

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, I. K.; Kim, J. T.; Lee, D. Y.; Jung, C. H.; Kim, J. Y.; Lee, J. S.; Ham, C. S. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    Belief network (or Bayesian network) based on Bayes` rule in probabilistic theory can be applied to the reasoning of diagnostic system. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences. 6 refs., 3 figs. (Author)

  8. Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks.

    Science.gov (United States)

    Movahedi, Faezeh; Coyle, James L; Sejdic, Ervin

    2018-05-01

    Deep learning, a relatively new branch of machine learning, has been investigated for use in a variety of biomedical applications. Deep learning algorithms have been used to analyze different physiological signals and gain a better understanding of human physiology for automated diagnosis of abnormal conditions. In this paper, we provide an overview of deep learning approaches with a focus on deep belief networks in electroencephalography applications. We investigate the state-of-the-art algorithms for deep belief networks and then cover the application of these algorithms and their performances in electroencephalographic applications. We covered various applications of electroencephalography in medicine, including emotion recognition, sleep stage classification, and seizure detection, in order to understand how deep learning algorithms could be modified to better suit the tasks desired. This review is intended to provide researchers with a broad overview of the currently existing deep belief network methodology for electroencephalography signals, as well as to highlight potential challenges for future research.

  9. Generating prior probabilities for classifiers of brain tumours using belief networks

    Directory of Open Access Journals (Sweden)

    Arvanitis Theodoros N

    2007-09-01

    Full Text Available Abstract Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET, germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.

  10. Cambodian Parental Involvement: The Role of Parental Beliefs, Social Networks, and Trust

    Science.gov (United States)

    Eng, Sothy; Szmodis, Whitney; Mulsow, Miriam

    2014-01-01

    The role of social capital (parental beliefs, social networks, and trust) as a predictor of parental involvement in Cambodian children's education was examined, controlling for human capital (family socioeconomic status). Parents of elementary students (n = 273) were interviewed face to face in Cambodia. Teacher contact scored highest, followed by…

  11. Geometry on the parameter space of the belief propagation algorithm on Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, Yodai [National Institute of Informatics, Research Organization of Information and Systems, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430 (Japan); Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako-shi, Saitama 351-0198 (Japan)

    2006-01-30

    This Letter considers a geometrical structure on the parameter space of the belief propagation algorithm on Bayesian networks. The statistical manifold of posterior distributions is introduced, and the expression for the information metric on the manifold is derived. The expression is used to construct a cost function which can be regarded as a measure of the distance in the parameter space.

  12. BELIEF dashboard - a web-based curation interface to support generation of BEL networks

    OpenAIRE

    Madan, Sumit; Hodapp, Sven; Fluck, Juliane

    2015-01-01

    The relevance of network-based approaches in systems biology to achieve a better understanding of biological mechanisms has increased enormously. The Biological Expression Language (BEL) is well designed to collate findings from scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a free and user-friendly web-based curation interface called BELIEF Dashboard has been developed. The interface incorporates an information extraction...

  13. Visible technologies, invisible organisations: An empirical study of public beliefs about electricity supply networks

    International Nuclear Information System (INIS)

    Devine-Wright, Patrick; Devine-Wright, Hannah; Sherry-Brennan, Fionnguala

    2010-01-01

    Reducing carbon emissions in the energy system poses significant challenges to electricity transmission and distribution networks. Whilst these challenges are as much social as economic or technical, to date few research studies have investigated public beliefs about electricity supply networks. This research aimed to address this gap by means of a nationally representative study of UK adults (n=1041), probing beliefs about how electricity reaches the home, responsibility for electricity supply, associations with the words 'National Grid', as well as beliefs about the planning of new infrastructure. Findings suggest that electricity networks are represented predominantly in terms of technologies rather than organisations, specifically in terms of familiar, visible components such as cables or wires, rather than more systemic concepts such as networks. Transmission and distribution network operators were largely invisible to members of the public. In terms of planning new lines, most respondents assumed that government ministers were involved in decision-making, while local residents were widely perceived to have little influence; moreover, there was strong public support for placing new power lines underground, regardless of the cost. In conclusion, organisational invisibility, coupled with low expectations of participatory involvement, could provoke public opposition and delay siting new network infrastructure.

  14. BBN: Description of the PLUM System as Used for MUC-4

    National Research Council Canada - National Science Library

    Ayuso, Damaris; Boisen, Sean; Fox, Heidi; Gish, Herb; Ingria, Robert; Weischedel, Ralph

    1992-01-01

    .... In contrast, BBN's PLUM system (Probabilistic Language Understanding Model) was developed as part of a DARPA-funded research effort on integrating probabilistic language models with more traditional linguistic techniques...

  15. Constraining f(T) teleparallel gravity by big bang nucleosynthesis. f(T) cosmology and BBN

    Energy Technology Data Exchange (ETDEWEB)

    Capozziello, S. [Universita di Napoli ' ' Federico II' ' , Complesso Universitario di Monte Sant' Angelo, Dipartimento di Fisica ' ' E. Pancini' ' , Napoli (Italy); Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Napoli (Italy); Gran Sasso Science Institute, L' Aquila (Italy); Lambiase, G. [University of Salerno, Dipartimento di Fisica E.R. Cainaiello, Fisciano (Italy); INFN, Gruppo Collegato di Salerno, Sezione di Napoli, Fisciano (Italy); Saridakis, E.N. [National Technical University of Athens, Department of Physics, Athens (Greece); Baylor University, CASPER, Physics Department, Waco, TX (United States)

    2017-09-15

    We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f(T) gravity. The three most studied viable f(T) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f(T) models can successfully satisfy the BBN constraints. (orig.)

  16. Constraining f(T) teleparallel gravity by big bang nucleosynthesis: f(T) cosmology and BBN.

    Science.gov (United States)

    Capozziello, S; Lambiase, G; Saridakis, E N

    2017-01-01

    We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f ( T ) gravity. The three most studied viable f ( T ) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f ( T ) models can successfully satisfy the BBN constraints.

  17. Constraining f(T) teleparallel gravity by big bang nucleosynthesis. f(T) cosmology and BBN

    International Nuclear Information System (INIS)

    Capozziello, S.; Lambiase, G.; Saridakis, E.N.

    2017-01-01

    We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f(T) gravity. The three most studied viable f(T) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f(T) models can successfully satisfy the BBN constraints. (orig.)

  18. Constraining f( T) teleparallel gravity by big bang nucleosynthesis. f(T) cosmology and BBN

    Science.gov (United States)

    Capozziello, S.; Lambiase, G.; Saridakis, E. N.

    2017-09-01

    We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f( T) gravity. The three most studied viable f( T) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f( T) models can successfully satisfy the BBN constraints.

  19. The BBN (Bolt Beranek and Newman) Knowledge Acquisition Project. Phase 1. Functional Description; Test Plan.

    Science.gov (United States)

    1987-05-01

    Computers . " Symbolics. Inc. 8. Carnegie Group. Inc KnoiledgeCraft Carnegie Group, Inc.. 1985. .- 9. Moser, Margaret, An Overviev of NIKL. Section of BBN...ORGANIZATION NAME AND ADDRESS I0. PROGRAM ELEMENT. PROJECT. TASK BBN Laboratories Inc. AREAAWoRIUNTNUMER_ 10 Moulton St. Cambridge, MA 02238 It...knowledge representation, expert systems; strategic computing , . A 20 ABSTRACT (Contnue an r rerse ide If neceaesary and Identify by block number) This

  20. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

    OpenAIRE

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of tra...

  1. Maritime Transportation Risk Assessment of Tianjin Port with Bayesian Belief Networks.

    Science.gov (United States)

    Zhang, Jinfen; Teixeira, Ângelo P; Guedes Soares, C; Yan, Xinping; Liu, Kezhong

    2016-06-01

    This article develops a Bayesian belief network model for the prediction of accident consequences in the Tianjin port. The study starts with a statistical analysis of historical accident data of six years from 2008 to 2013. Then a Bayesian belief network is constructed to express the dependencies between the indicator variables and accident consequences. The statistics and expert knowledge are synthesized in the Bayesian belief network model to obtain the probability distribution of the consequences. By a sensitivity analysis, several indicator variables that have influence on the consequences are identified, including navigational area, ship type and time of the day. The results indicate that the consequences are most sensitive to the position where the accidents occurred, followed by time of day and ship length. The results also reflect that the navigational risk of the Tianjin port is at the acceptable level, despite that there is more room of improvement. These results can be used by the Maritime Safety Administration to take effective measures to enhance maritime safety in the Tianjin port. © 2016 Society for Risk Analysis.

  2. DeepQA: improving the estimation of single protein model quality with deep belief networks.

    Science.gov (United States)

    Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

    2016-12-05

    Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

  3. Research on Improved Depth Belief Network-Based Prediction of Cardiovascular Diseases

    Directory of Open Access Journals (Sweden)

    Peng Lu

    2018-01-01

    Full Text Available Quantitative analysis and prediction can help to reduce the risk of cardiovascular disease. Quantitative prediction based on traditional model has low accuracy. The variance of model prediction based on shallow neural network is larger. In this paper, cardiovascular disease prediction model based on improved deep belief network (DBN is proposed. Using the reconstruction error, the network depth is determined independently, and unsupervised training and supervised optimization are combined. It ensures the accuracy of model prediction while guaranteeing stability. Thirty experiments were performed independently on the Statlog (Heart and Heart Disease Database data sets in the UCI database. Experimental results showed that the mean of prediction accuracy was 91.26% and 89.78%, respectively. The variance of prediction accuracy was 5.78 and 4.46, respectively.

  4. Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

    Science.gov (United States)

    Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

    2016-01-01

    In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

  5. Implementing particle-in-cell plasma simulation code on the BBN TC2000

    International Nuclear Information System (INIS)

    Sturtevant, J.E.; Maccabe, A.B.

    1990-01-01

    The BBN TC2000 is a multiple instruction, multiple data (MIMD) machine that combines a physically distributed memory with a logically shared memory programming environment using the unique Butterfly switch. Particle-In-Cell (PIC) plasma simulations model the interaction of charged particles with electric and magnetic fields. This paper describes the implementation of both a 1-D electrostatic and a 2 1/2-D electromagnetic PIC (particle-in-cell) plasma simulation code on a BBN TC2000. Performance is compared to implementations of the same code on the shared memory Sequent Balance and distributed memory Intel iPSC hypercube

  6. Evidence of social network influence on multiple HIV risk behaviors and normative beliefs among young Tanzanian men.

    Science.gov (United States)

    Mulawa, Marta; Yamanis, Thespina J; Hill, Lauren M; Balvanz, Peter; Kajula, Lusajo J; Maman, Suzanne

    2016-03-01

    Research on network-level influences on HIV risk behaviors among young men in sub-Saharan Africa is severely lacking. One significant gap in the literature that may provide direction for future research with this population is understanding the degree to which various HIV risk behaviors and normative beliefs cluster within men's social networks. Such research may help us understand which HIV-related norms and behaviors have the greatest potential to be changed through social influence. Additionally, few network-based studies have described the structure of social networks of young men in sub-Saharan Africa. Understanding the structure of men's peer networks may motivate future research examining the ways in which network structures shape the spread of information, adoption of norms, and diffusion of behaviors. We contribute to filling these gaps by using social network analysis and multilevel modeling to describe a unique dataset of mostly young men (n = 1249 men and 242 women) nested within 59 urban social networks in Dar es Salaam, Tanzania. We examine the means, ranges, and clustering of men's HIV-related normative beliefs and behaviors. Networks in this urban setting varied substantially in both composition and structure and a large proportion of men engaged in risky behaviors including inconsistent condom use, sexual partner concurrency, and intimate partner violence perpetration. We found significant clustering of normative beliefs and risk behaviors within these men's social networks. Specifically, network membership explained between 5.78 and 7.17% of variance in men's normative beliefs and between 1.93 and 15.79% of variance in risk behaviors. Our results suggest that social networks are important socialization sites for young men and may influence the adoption of norms and behaviors. We conclude by calling for more research on men's social networks in Sub-Saharan Africa and map out several areas of future inquiry. Copyright © 2016 Elsevier Ltd. All

  7. Classification of ECG beats using deep belief network and active learning.

    Science.gov (United States)

    G, Sayantan; T, Kien P; V, Kadambari K

    2018-04-12

    A new semi-supervised approach based on deep learning and active learning for classification of electrocardiogram signals (ECG) is proposed. The objective of the proposed work is to model a scientific method for classification of cardiac irregularities using electrocardiogram beats. The model follows the Association for the Advancement of medical instrumentation (AAMI) standards and consists of three phases. In phase I, feature representation of ECG is learnt using Gaussian-Bernoulli deep belief network followed by a linear support vector machine (SVM) training in the consecutive phase. It yields three deep models which are based on AAMI-defined classes, namely N, V, S, and F. In the last phase, a query generator is introduced to interact with the expert to label few beats to improve accuracy and sensitivity. The proposed approach depicts significant improvement in accuracy with minimal queries posed to the expert and fast online training as tested on the MIT-BIH Arrhythmia Database and the MIT-BIH Supra-ventricular Arrhythmia Database (SVDB). With 100 queries labeled by the expert in phase III, the method achieves an accuracy of 99.5% in "S" versus all classifications (SVEB) and 99.4% accuracy in "V " versus all classifications (VEB) on MIT-BIH Arrhythmia Database. In a similar manner, it is attributed that an accuracy of 97.5% for SVEB and 98.6% for VEB on SVDB database is achieved respectively. Graphical Abstract Reply- Deep belief network augmented by active learning for efficient prediction of arrhythmia.

  8. Understanding Migration as an Adaptation in Deltas Using a Bayesian Network Model

    Science.gov (United States)

    Lázár, A. N.; Adams, H.; de Campos, R. S.; Mortreux, C. C.; Clarke, D.; Nicholls, R. J.; Amisigo, B. A.

    2016-12-01

    Deltas are hotspots of high population density, fertile lands and dramatic environmental and anthropogenic pressures and changes. Amongst other environmental factors, sea level rise, soil salinization, water shortages and erosion threaten people's livelihoods and wellbeing. As a result, there is a growing concern that significant environmental change induced migration might occur from these areas. Migration, however, is already happening for economic, education and other reasons (e.g. livelihood change, marriage, planned relocation, etc.). Migration hence has multiple, interlinked drivers and depending on the perspective, can be considered as a positive or negative phenomenon. The DECCMA project (Deltas, Vulnerability & Climate Change: Migration & Adaptation) studies migration as part of a suite of adaptation options available to the coastal populations in the Ganges delta in Bangladesh, the Mahanadi delta in India and the Volta delta in Ghana. It aims to develop a holistic framework of analysis that assesses the impact of climate and environmental change on the migration patterns of these areas. This assessment framework will couple environmental, socio-economics and governance dimensions in an attempt to synthesise drivers and barriers and allow testing of plausible future scenarios. One of the integrative methods of DECCMA is a Bayesian Belief Network (BBN) model describing the decision-making of a coastal household. BBN models are built on qualitative and quantitative observations/expert knowledge and describe the probability of different events/responses etc. BBN models are especially useful to capture uncertainties of large systems and engaging with stakeholders. The DECCMA BBN model is based on household survey results from delta migrant sending areas. This presentation will describe model elements (livelihood sensitivity to climate change, local and national adaptation options, household characteristics/attitude, social networks, household decision) and

  9. Global Diversity and Local Consensus in Status Beliefs : The Role of Network Clustering and Resistance to Belief Change

    NARCIS (Netherlands)

    Grow, André; Flache, Andreas; Wittek, Rafael

    2017-01-01

    Formal models of status construction theory suggest that beliefs about the relative social worth and competence of members of different social groups can emerge from face-to-face interactions in task-focused groups and eventually become consensual in large populations. We propose two extensions of

  10. Influences of variables on ship collision probability in a Bayesian belief network model

    International Nuclear Information System (INIS)

    Hänninen, Maria; Kujala, Pentti

    2012-01-01

    The influences of the variables in a Bayesian belief network model for estimating the role of human factors on ship collision probability in the Gulf of Finland are studied for discovering the variables with the largest influences and for examining the validity of the network. The change in the so-called causation probability is examined while observing each state of the network variables and by utilizing sensitivity and mutual information analyses. Changing course in an encounter situation is the most influential variable in the model, followed by variables such as the Officer of the Watch's action, situation assessment, danger detection, personal condition and incapacitation. The least influential variables are the other distractions on bridge, the bridge view, maintenance routines and the officer's fatigue. In general, the methods are found to agree on the order of the model variables although some disagreements arise due to slightly dissimilar approaches to the concept of variable influence. The relative values and the ranking of variables based on the values are discovered to be more valuable than the actual numerical values themselves. Although the most influential variables seem to be plausible, there are some discrepancies between the indicated influences in the model and literature. Thus, improvements are suggested to the network.

  11. A guide on the elicitation of expert knowledge in constructing BBN for quantitative reliability assessment of safety critical software

    International Nuclear Information System (INIS)

    Eom, H. S.; Kang, H. G.; Chang, S. C.; Ha, J. J.

    2003-08-01

    This report describes the methodology which could elicit probabilistic representation from the experts' knowledge or qualitative data. It is necessary to elicit expert's knowledge while we quantitatively assess the reliability of safety critical software using Bayesian Belief Nets(BBNs). Especially in composing the node probability table and in making out the input data for BBN model, experts' qualitative judgment or qualitative data should be converted into probabilistic representation. This conversion process is vulnerable to bias or error. The purpose of the report is to provide the guideline to avoid the occurrence of this kinds of bias/error or to eliminate them which is included in the existing data prepared by experts. The contents of the report are: o The types and the explanation of bias and error The types of bias and error which might be occur in the process of eliciting the expert's knowledge. o The procedure of expert's judgment elicitation. The process and techniques to avoid bias and error in eliciting the expert's judgments. o The examples of expert's knowledge appeared in the BBNs The examples of expert's knowledge (probability values) appeared in the BBNs for assessing the safety of digital system

  12. On the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition

    Directory of Open Access Journals (Sweden)

    Marco Zennaro

    2010-12-01

    Full Text Available Achieving situation recognition in ubiquitous sensor networks (USNs is an important issue that has been poorly addressed by both the research and practitioner communities. This paper describes some steps taken to address this issue by effecting USN middleware intelligence using an emerging situation awareness (ESA technology. We propose a situation recognition framework where temporal probabilistic reasoning is used to derive and emerge situation awareness in ubiquitous sensor networks. Using data collected from an outdoor environment monitoring in the city of Cape Town, we illustrate the use of the ESA technology in terms of sensor system operating conditions and environmental situation recognition.

  13. Rolling bearing fault diagnosis using adaptive deep belief network with dual-tree complex wavelet packet.

    Science.gov (United States)

    Shao, Haidong; Jiang, Hongkai; Wang, Fuan; Wang, Yanan

    2017-07-01

    Automatic and accurate identification of rolling bearing fault categories, especially for the fault severities and compound faults, is a challenge in rotating machinery fault diagnosis. For this purpose, a novel method called adaptive deep belief network (DBN) with dual-tree complex wavelet packet (DTCWPT) is developed in this paper. DTCWPT is used to preprocess the vibration signals to refine the fault characteristics information, and an original feature set is designed from each frequency-band signal of DTCWPT. An adaptive DBN is constructed to improve the convergence rate and identification accuracy with multiple stacked adaptive restricted Boltzmann machines (RBMs). The proposed method is applied to the fault diagnosis of rolling bearings. The results confirm that the proposed method is more effective than the existing methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Rolling bearing fault feature learning using improved convolutional deep belief network with compressed sensing

    Science.gov (United States)

    Shao, Haidong; Jiang, Hongkai; Zhang, Haizhou; Duan, Wenjing; Liang, Tianchen; Wu, Shuaipeng

    2018-02-01

    The vibration signals collected from rolling bearing are usually complex and non-stationary with heavy background noise. Therefore, it is a great challenge to efficiently learn the representative fault features of the collected vibration signals. In this paper, a novel method called improved convolutional deep belief network (CDBN) with compressed sensing (CS) is developed for feature learning and fault diagnosis of rolling bearing. Firstly, CS is adopted for reducing the vibration data amount to improve analysis efficiency. Secondly, a new CDBN model is constructed with Gaussian visible units to enhance the feature learning ability for the compressed data. Finally, exponential moving average (EMA) technique is employed to improve the generalization performance of the constructed deep model. The developed method is applied to analyze the experimental rolling bearing vibration signals. The results confirm that the developed method is more effective than the traditional methods.

  15. Active semi-supervised learning method with hybrid deep belief networks.

    Science.gov (United States)

    Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

    2014-01-01

    In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

  16. Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Jun He

    2017-07-01

    Full Text Available Artificial intelligence (AI techniques, which can effectively analyze massive amounts of fault data and automatically provide accurate diagnosis results, have been widely applied to fault diagnosis of rotating machinery. Conventional AI methods are applied using features selected by a human operator, which are manually extracted based on diagnostic techniques and field expertise. However, developing robust features for each diagnostic purpose is often labour-intensive and time-consuming, and the features extracted for one specific task may be unsuitable for others. In this paper, a novel AI method based on a deep belief network (DBN is proposed for the unsupervised fault diagnosis of a gear transmission chain, and the genetic algorithm is used to optimize the structural parameters of the network. Compared to the conventional AI methods, the proposed method can adaptively exploit robust features related to the faults by unsupervised feature learning, thus requires less prior knowledge about signal processing techniques and diagnostic expertise. Besides, it is more powerful at modelling complex structured data. The effectiveness of the proposed method is validated using datasets from rolling bearings and gearbox. To show the superiority of the proposed method, its performance is compared with two well-known classifiers, i.e., back propagation neural network (BPNN and support vector machine (SVM. The fault classification accuracies are 99.26% for rolling bearings and 100% for gearbox when using the proposed method, which are much higher than that of the other two methods.

  17. Unsupervised Fault Diagnosis of a Gear Transmission Chain Using a Deep Belief Network.

    Science.gov (United States)

    He, Jun; Yang, Shixi; Gan, Chunbiao

    2017-07-04

    Artificial intelligence (AI) techniques, which can effectively analyze massive amounts of fault data and automatically provide accurate diagnosis results, have been widely applied to fault diagnosis of rotating machinery. Conventional AI methods are applied using features selected by a human operator, which are manually extracted based on diagnostic techniques and field expertise. However, developing robust features for each diagnostic purpose is often labour-intensive and time-consuming, and the features extracted for one specific task may be unsuitable for others. In this paper, a novel AI method based on a deep belief network (DBN) is proposed for the unsupervised fault diagnosis of a gear transmission chain, and the genetic algorithm is used to optimize the structural parameters of the network. Compared to the conventional AI methods, the proposed method can adaptively exploit robust features related to the faults by unsupervised feature learning, thus requires less prior knowledge about signal processing techniques and diagnostic expertise. Besides, it is more powerful at modelling complex structured data. The effectiveness of the proposed method is validated using datasets from rolling bearings and gearbox. To show the superiority of the proposed method, its performance is compared with two well-known classifiers, i.e., back propagation neural network (BPNN) and support vector machine (SVM). The fault classification accuracies are 99.26% for rolling bearings and 100% for gearbox when using the proposed method, which are much higher than that of the other two methods.

  18. Preparation and preliminary evaluation of 99Tcm-HYNIC-β-Ala-BBN(7-14)NH2

    International Nuclear Information System (INIS)

    Quan Xin; Zhang Yan; Jia Bing; Shi Jiyun; Wang Fan; Zhao Huiyun; Yu Zilin

    2007-01-01

    99 Tc m -HYNIC-β-Ala-BBN(7-14)NH 2 is prepared by choosing Tricine and EDDA as coligands, and the in vitro stability and biodistribution are compared for the two compounds. The results of ITLC and HPLC analyses show that the labeling yield of both compounds is >95%, and the radiochemical purity (RCP) after purification of Sep-Pak C-18 cartridge is >99%. Both of the compounds show pretty good stability in saline and fetal bovine serum, but cysteine challenge assay shows that the stability of 99 Tc m -HYNIC(EDDA)- β-Ala-BBN (7-14) NH 2 is much better than 99 Tc m -HYNIC (Tricine)-β-Ala-BBN (7-14) NH 2 , with the RCP is >95% and 99 Tc m HYNIC (EDDA)-βAla-BBN (7-14)NH 2 and 99 Tc m -HYNIC (Tricine)-β-Ala-BBN(7-14)NH 2 is defined as two-compartment model, with T 1/2α calculated to be 0.27 min and 1.55 min, and T 1/2β calculated to be 18.1 min and 29.7 min, respectively. Biodistribution reveals that the radio uptake of 99 Tc m -HYNIC(Tricine)-β-Ala-BBN(7-14)NH 2 is higher than that of 99 Tc m -HYNIC(EDDA)-β-Ala-BBN(7-14)NH 2 for all of tis- sues at all time points of the experiment. The uptake in kidneys for both compounds is relatively high, as the uptake in livers and intestines for 99 Tc m -HYNIC(Tricine)-β-Ala-BBN(7- 14)NH 2 is significantly higher than that for 99 Tc m -HYNIC(EDDA)-β-Ala-BBN(7-14)NH 2 , which means that 99 Tc m -HYNIC(EDDA)-β-Ala-BBN(7-14)NH 2 is mainly excreted through kidneys, while 99 Tc m -HYNIC(Tricine)-β-Ala-BBN(7-14)NH 2 is excreted through both kidneys and hepatobiliary system. The above data demonstrate that 99 Tc m -HYNIC(EDDA)-β- Ala-BBN(7-14)NH 2 possesses better chemical and biological properties. (authors)

  19. Research on Factors Influencing Municipal Household Solid Waste Separate Collection: Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Zhujie Chu

    2016-02-01

    Full Text Available Municipal household solid waste (MHSW has become a serious problem in China over the course of the last two decades, resulting in significant side effects to the environment. Therefore, effective management of MHSW has attracted wide attention from both researchers and practitioners. Separate collection, the first and crucial step to solve the MHSW problem, however, has not been thoroughly studied to date. An empirical survey has been conducted among 387 households in Harbin, China in this study. We use Bayesian Belief Networks model to determine the influencing factors on separate collection. Four types of factors are identified, including political, economic, social cultural and technological based on the PEST (political, economic, social and technological analytical method. In addition, we further analyze the influential power of different factors, based on the network structure and probability changes obtained by Netica software. Results indicate that technological dimension has the greatest impact on MHSW separate collection, followed by the political dimension and economic dimension; social cultural dimension impacts MHSW the least.

  20. Deep Belief Network Based Hybrid Model for Building Energy Consumption Prediction

    Directory of Open Access Journals (Sweden)

    Chengdong Li

    2018-01-01

    Full Text Available To enhance the prediction performance for building energy consumption, this paper presents a modified deep belief network (DBN based hybrid model. The proposed hybrid model combines the outputs from the DBN model with the energy-consuming pattern to yield the final prediction results. The energy-consuming pattern in this study represents the periodicity property of building energy consumption and can be extracted from the observed historical energy consumption data. The residual data generated by removing the energy-consuming pattern from the original data are utilized to train the modified DBN model. The training of the modified DBN includes two steps, the first one of which adopts the contrastive divergence (CD algorithm to optimize the hidden parameters in a pre-train way, while the second one determines the output weighting vector by the least squares method. The proposed hybrid model is applied to two kinds of building energy consumption data sets that have different energy-consuming patterns (daily-periodicity and weekly-periodicity. In order to examine the advantages of the proposed model, four popular artificial intelligence methods—the backward propagation neural network (BPNN, the generalized radial basis function neural network (GRBFNN, the extreme learning machine (ELM, and the support vector regressor (SVR are chosen as the comparative approaches. Experimental results demonstrate that the proposed DBN based hybrid model has the best performance compared with the comparative techniques. Another thing to be mentioned is that all the predictors constructed by utilizing the energy-consuming patterns perform better than those designed only by the original data. This verifies the usefulness of the incorporation of the energy-consuming patterns. The proposed approach can also be extended and applied to some other similar prediction problems that have periodicity patterns, e.g., the traffic flow forecasting and the electricity consumption

  1. Real-time classification and sensor fusion with a spiking deep belief network.

    Science.gov (United States)

    O'Connor, Peter; Neil, Daniel; Liu, Shih-Chii; Delbruck, Tobi; Pfeiffer, Michael

    2013-01-01

    Deep Belief Networks (DBNs) have recently shown impressive performance on a broad range of classification problems. Their generative properties allow better understanding of the performance, and provide a simpler solution for sensor fusion tasks. However, because of their inherent need for feedback and parallel update of large numbers of units, DBNs are expensive to implement on serial computers. This paper proposes a method based on the Siegert approximation for Integrate-and-Fire neurons to map an offline-trained DBN onto an efficient event-driven spiking neural network suitable for hardware implementation. The method is demonstrated in simulation and by a real-time implementation of a 3-layer network with 2694 neurons used for visual classification of MNIST handwritten digits with input from a 128 × 128 Dynamic Vision Sensor (DVS) silicon retina, and sensory-fusion using additional input from a 64-channel AER-EAR silicon cochlea. The system is implemented through the open-source software in the jAER project and runs in real-time on a laptop computer. It is demonstrated that the system can recognize digits in the presence of distractions, noise, scaling, translation and rotation, and that the degradation of recognition performance by using an event-based approach is less than 1%. Recognition is achieved in an average of 5.8 ms after the onset of the presentation of a digit. By cue integration from both silicon retina and cochlea outputs we show that the system can be biased to select the correct digit from otherwise ambiguous input.

  2. Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

    Science.gov (United States)

    Sadeghi, Zahra

    2016-09-01

    In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

  3. Strategic Belief Management

    DEFF Research Database (Denmark)

    Foss, Nicolai Juul

    While (managerial) beliefs are central to many aspects of strategic organization, interactive beliefs are almost entirely neglected, save for some game theory treatments. In an increasingly connected and networked economy, firms confront coordination problems that arise because of network effects....... The capability to manage beliefs will increasingly be a strategic one, a key source of wealth creation, and a key research area for strategic organization scholars.......While (managerial) beliefs are central to many aspects of strategic organization, interactive beliefs are almost entirely neglected, save for some game theory treatments. In an increasingly connected and networked economy, firms confront coordination problems that arise because of network effects...

  4. Experimental challenge to the big-bang nucleosynthesis - Cosmological 7Li problem in BBN

    Science.gov (United States)

    Kubono, S.; Kawabata, T.; Hou, S. Q.; He, J. J.

    2018-04-01

    The primordial nucleosynthesis(BBN) right after the big bang (BB) is one of the key elements that basically support the BB model. The BBN is well known that it produced primarily light elements, and explains reasonably most of the elemental abundances. However, there remains an interesting and serious question. That is so called the cosmological 7Li problem in BBN. The BBN simulations using nuclear data together with the recent detailed micro-wave background measurements explain most of the light elements including D, 4He, etc, but the 7Li abundance is over predicted roughly by a factor of three. Although this problem should be investigated in all the fields relevant including physics and astronomical observations, I will concentrate my discussion on the nuclear physics side, especially the recent progress for studying the last possible major destruction process of 7Be, the 7Be(n,α)4He reaction, which would reduce the overproduction if the cross section is large. There are several efforts recently made for the 7Be(n,α)4He reaction in the world. A new theoretical estimate was made compiling all available data of the mirror reaction 7Li(p,α)4He, suggesting about one order smaller reaction rate than the ones currently being used (Wagoner rate). The n-TOF group measured some part of the s-wave components of the reaction, suggesting that the s-wave contributions are much smaller than the Wagoner rate. The p-wave component was measured clearly at RCNP, Osaka using the time-reverse reaction 4He(α,n)7Be, indicating that the p-wave contribution dominates at the effective temperature region for the BBN. However, the sum of the s-wave and p-wave contributions is about one order of magnitude smaller than the Wagoner rate. It should be of great interest to confirm by the indirect method, Trojan-Horse method to deduce cross sections at the effective temperature region, and also see the cross sections for a wider energy range systematically, which is under way by the BELICOS

  5. Classification of Exacerbation Frequency in the COPDGene Cohort Using Deep Learning with Deep Belief Networks.

    Science.gov (United States)

    Ying, Jun; Dutta, Joyita; Guo, Ning; Hu, Chenhui; Zhou, Dan; Sitek, Arkadiusz; Li, Quanzheng

    2016-12-21

    This study aims to develop an automatic classifier based on deep learning for exacerbation frequency in patients with chronic obstructive pulmonary disease (COPD). A threelayer deep belief network (DBN) with two hidden layers and one visible layer was employed to develop classification models and the models' robustness to exacerbation was analyzed. Subjects from the COPDGene cohort were labeled with exacerbation frequency, defined as the number of exacerbation events per year. 10,300 subjects with 361 features each were included in the analysis. After feature selection and parameter optimization, the proposed classification method achieved an accuracy of 91.99%, using a 10-fold cross validation experiment. The analysis of DBN weights showed that there was a good visual spatial relationship between the underlying critical features of different layers. Our findings show that the most sensitive features obtained from the DBN weights are consistent with the consensus showed by clinical rules and standards for COPD diagnostics. We thus demonstrate that DBN is a competitive tool for exacerbation risk assessment for patients suffering from COPD.

  6. EMD-Based Predictive Deep Belief Network for Time Series Prediction: An Application to Drought Forecasting

    Directory of Open Access Journals (Sweden)

    Norbert A. Agana

    2018-02-01

    Full Text Available Drought is a stochastic natural feature that arises due to intense and persistent shortage of precipitation. Its impact is mostly manifested as agricultural and hydrological droughts following an initial meteorological phenomenon. Drought prediction is essential because it can aid in the preparedness and impact-related management of its effects. This study considers the drought forecasting problem by developing a hybrid predictive model using a denoised empirical mode decomposition (EMD and a deep belief network (DBN. The proposed method first decomposes the data into several intrinsic mode functions (IMFs using EMD, and a reconstruction of the original data is obtained by considering only relevant IMFs. Detrended fluctuation analysis (DFA was applied to each IMF to determine the threshold for robust denoising performance. Based on their scaling exponents, irrelevant intrinsic mode functions are identified and suppressed. The proposed method was applied to predict different time scale drought indices across the Colorado River basin using a standardized streamflow index (SSI as the drought index. The results obtained using the proposed method was compared with standard methods such as multilayer perceptron (MLP and support vector regression (SVR. The proposed hybrid model showed improvement in prediction accuracy, especially for multi-step ahead predictions.

  7. Convolutional deep belief network with feature encoding for classification of neuroblastoma histological images

    Directory of Open Access Journals (Sweden)

    Soheila Gheisari

    2018-01-01

    Full Text Available Background: Neuroblastoma is the most common extracranial solid tumor in children younger than 5 years old. Optimal management of neuroblastic tumors depends on many factors including histopathological classification. The gold standard for classification of neuroblastoma histological images is visual microscopic assessment. In this study, we propose and evaluate a deep learning approach to classify high-resolution digital images of neuroblastoma histology into five different classes determined by the Shimada classification. Subjects and Methods: We apply a combination of convolutional deep belief network (CDBN with feature encoding algorithm that automatically classifies digital images of neuroblastoma histology into five different classes. We design a three-layer CDBN to extract high-level features from neuroblastoma histological images and combine with a feature encoding model to extract features that are highly discriminative in the classification task. The extracted features are classified into five different classes using a support vector machine classifier. Data: We constructed a dataset of 1043 neuroblastoma histological images derived from Aperio scanner from 125 patients representing different classes of neuroblastoma tumors. Results: The weighted average F-measure of 86.01% was obtained from the selected high-level features, outperforming state-of-the-art methods. Conclusion: The proposed computer-aided classification system, which uses the combination of deep architecture and feature encoding to learn high-level features, is highly effective in the classification of neuroblastoma histological images.

  8. Deep learning architecture for iris recognition based on optimal Gabor filters and deep belief network

    Science.gov (United States)

    He, Fei; Han, Ye; Wang, Han; Ji, Jinchao; Liu, Yuanning; Ma, Zhiqiang

    2017-03-01

    Gabor filters are widely utilized to detect iris texture information in several state-of-the-art iris recognition systems. However, the proper Gabor kernels and the generative pattern of iris Gabor features need to be predetermined in application. The traditional empirical Gabor filters and shallow iris encoding ways are incapable of dealing with such complex variations in iris imaging including illumination, aging, deformation, and device variations. Thereby, an adaptive Gabor filter selection strategy and deep learning architecture are presented. We first employ particle swarm optimization approach and its binary version to define a set of data-driven Gabor kernels for fitting the most informative filtering bands, and then capture complex pattern from the optimal Gabor filtered coefficients by a trained deep belief network. A succession of comparative experiments validate that our optimal Gabor filters may produce more distinctive Gabor coefficients and our iris deep representations be more robust and stable than traditional iris Gabor codes. Furthermore, the depth and scales of the deep learning architecture are also discussed.

  9. Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

    Science.gov (United States)

    Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

    2017-05-01

    Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

  10. Estimating dependability of programmable systems using bayesian belief nets

    International Nuclear Information System (INIS)

    Gran, Bjoern Axel; Dahll, Gustav

    2000-05-01

    The research programme at the Halden Project on software safety assessment is augmented through a joint project with Kongsberg Defence and Aerospace AS and Det Norske Veritas. The objective of this project is to investigate the possibility to combine the Bayesian Belief Net (BBN) methodology with a software safety standard. The report discusses software safety standards in general, with respect to how they can be used to measure software safety. The possibility to transfer the requirements of a software safety standard into a BBN is also investigated. The aim is to utilise the BBN methodology and associated tools, by transferring the software safety measurement into a probabilistic quantity. In this way software can be included in a total probabilistic safety analysis. This project was performed by applying the method for an evaluation of a real, safety related programmable system which was developed according to the avionic standard DO-178B. The test case, the standard, and the BBN methodology are shortly described. This is followed by a description of the construction of the BBN used in this project. This includes the topology of the BBN, the elicitation of probabilities and the making of observations. Based on this a variety of computations are made using the SERENE methodology and the HUGIN tool. Observations and conclusions are made on the basis of the findings from this process. This report should be considered as a progress report in a more long-term activity on the use of BBNs as support for safety assessment of programmable systems. (Author). 23 refs., 9 figs., tabs

  11. Combining Volcano Monitoring Timeseries Analyses with Bayesian Belief Networks to Update Hazard Forecast Estimates

    Science.gov (United States)

    Odbert, Henry; Hincks, Thea; Aspinall, Willy

    2015-04-01

    Volcanic hazard assessments must combine information about the physical processes of hazardous phenomena with observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We show how our method

  12. Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application

    International Nuclear Information System (INIS)

    Baraldi, Piero; Podofillini, Luca; Mkrtchyan, Lusine; Zio, Enrico; Dang, Vinh N.

    2015-01-01

    The use of expert systems can be helpful to improve the transparency and repeatability of assessments in areas of risk analysis with limited data available. In this field, human reliability analysis (HRA) is no exception, and, in particular, dependence analysis is an HRA task strongly based on analyst judgement. The analysis of dependence among Human Failure Events refers to the assessment of the effect of an earlier human failure on the probability of the subsequent ones. This paper analyses and compares two expert systems, based on Bayesian Belief Networks and Fuzzy Logic (a Fuzzy Expert System, FES), respectively. The comparison shows that a BBN approach should be preferred in all the cases characterized by quantifiable uncertainty in the input (i.e. when probability distributions can be assigned to describe the input parameters uncertainty), since it provides a satisfactory representation of the uncertainty and its output is directly interpretable for use within PSA. On the other hand, in cases characterized by very limited knowledge, an analyst may feel constrained by the probabilistic framework, which requires assigning probability distributions for describing uncertainty. In these cases, the FES seems to lead to a more transparent representation of the input and output uncertainty. - Highlights: • We analyse treatment of uncertainty in two expert systems. • We compare a Bayesian Belief Network (BBN) and a Fuzzy Expert System (FES). • We focus on the input assessment, inference engines and output assessment. • We focus on an application problem of interest for human reliability analysis. • We emphasize the application rather than math to reach non-BBN or FES specialists

  13. Bayesian Belief Network to support conflict analysis for groundwater protection: the case of the Apulia region.

    Science.gov (United States)

    Giordano, Raffaele; D'Agostino, Daniela; Apollonio, Ciro; Lamaddalena, Nicola; Vurro, Michele

    2013-01-30

    Water resource management is often characterized by conflicts, as a result of the heterogeneity of interests associated with a shared resource. Many water conflicts arise on a global scale and, in particular, an increasing level of conflicts can be observed in the Mediterranean basin, characterized by water scarcity. In the present work, in order to assist the conflict analysis process, and thus outline a proper groundwater management, stakeholders were involved in the process and suitable tools were used in a Mediterranean area (the Apulia region, in Italy). In particular, this paper seeks to elicit and structure farmers' mental models influencing their decision over the main water source for irrigation. The more crucial groundwater is for farmers' objectives, the more controversial is the groundwater protection strategy. Bayesian Belief Networks were developed to simulate farmers' behavior with regard to groundwater management and to assess the impacts of protection strategy. These results have been used to calculate the conflict degree in the study area, derived from the introduction of policies for the reduction of groundwater exploitation for irrigation purposes. The less acceptable the policy is, the more likely it is that conflict will develop between farmers and the Regional Authority. The results of conflict analysis were also used to contribute to the debate concerning potential conflict mitigation measures. The approach adopted in this work has been discussed with a number of experts in groundwater management policies and irrigation management, and its main strengths and weaknesses have been identified. Increasing awareness of the existence of potential conflicts and the need to deal with them can be seen as an interesting initial shift in the Apulia region's water management regime, which is still grounded in merely technical approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

  14. [Research of electroencephalography representational emotion recognition based on deep belief networks].

    Science.gov (United States)

    Yang, Hao; Zhang, Junran; Jiang, Xiaomei; Liu, Fei

    2018-04-01

    In recent years, with the rapid development of machine learning techniques,the deep learning algorithm has been widely used in one-dimensional physiological signal processing. In this paper we used electroencephalography (EEG) signals based on deep belief network (DBN) model in open source frameworks of deep learning to identify emotional state (positive, negative and neutrals), then the results of DBN were compared with support vector machine (SVM). The EEG signals were collected from the subjects who were under different emotional stimuli, and DBN and SVM were adopted to identify the EEG signals with changes of different characteristics and different frequency bands. We found that the average accuracy of differential entropy (DE) feature by DBN is 89.12%±6.54%, which has a better performance than previous research based on the same data set. At the same time, the classification effects of DBN are better than the results from traditional SVM (the average classification accuracy of 84.2%±9.24%) and its accuracy and stability have a better trend. In three experiments with different time points, single subject can achieve the consistent results of classification by using DBN (the mean standard deviation is1.44%), and the experimental results show that the system has steady performance and good repeatability. According to our research, the characteristic of DE has a better classification result than other characteristics. Furthermore, the Beta band and the Gamma band in the emotional recognition model have higher classification accuracy. To sum up, the performances of classifiers have a promotion by using the deep learning algorithm, which has a reference for establishing a more accurate system of emotional recognition. Meanwhile, we can trace through the results of recognition to find out the brain regions and frequency band that are related to the emotions, which can help us to understand the emotional mechanism better. This study has a high academic value and

  15. Using Bayesian Belief Networks To Assess Volcano State from Multiple Monitoring Timeseries And Other Evidence

    Science.gov (United States)

    Odbert, Henry; Aspinall, Willy

    2013-04-01

    When volcanoes exhibit unrest or become eruptively active, science-based decision support invariably is sought by civil authorities. Evidence available to scientists about a volcano's internal state is usually indirect, secondary or very nebulous.Advancement of volcano monitoring technology in recent decades has increased the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Monitoring timeseries may be interpreted in real time by observatory staff and are often later subjected to further analytic scrutiny by the research community at large. With increasing variety and resolution of data, interpreting these multiple strands of parallel, partial evidence has become increasingly complex. In practice, interpretation of many timeseries involves familiarity with the idiosyncracies of the volcano, the monitoring techniques, the configuration of the recording instrumentation, observations from other datasets, and so on. Assimilation of this knowledge is necessary in order to select and apply the appropriate statistical techniques required to extract the required information. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple observations, model results and interpretations - and associated uncertainties - in a methodical manner. The formulation is usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic timeseries, the certainty with which inferences may be drawn, and how they can be updated dynamically. Such approaches provide a route to developing analytical interface(s) between volcano monitoring analyses and probabilistic hazard analysis. We discuss the use of BBNs in hazard

  16. You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites.

    Science.gov (United States)

    Leung, Angel N M; Wong, Natalie; Farver, JoAnn M

    2018-01-01

    The present study tested how exposure to two types of responses to a hypothetical simulated Facebook setting influenced cyber-bystanders' perceived control and normative beliefs using a 4 cyberbully-victim group (pure cyberbullies, non-involved, pure cyberbullied victims, and cyberbullied-victims) × 2 condition (offend vs. defend) experimental design. 203 Hong Kong Chinese secondary school and university students (132 females, 71 males; 12 to 28; M = 16.70; SD = 3.03 years old) were randomly assigned into one of two conditions. Results showed that participants' involvement in cyberbullying significantly related to their control beliefs about bully and victim assisting behaviors, while exposure to the two different conditions (offend vs. defend comments) was related to both their control and normative beliefs. In general, the defend condition promoted higher control beliefs to help the victims and promoted higher normative beliefs to help the victims. Regardless of their past involvement in cyberbullying and exposure to offend vs. defend conditions, both cyber-bullies and cyber-victims were more inclined to demonstrate normative beliefs to help victims than to assist bullies. These results have implications for examining environmental influences in predicting bystander behaviors in cyberbullying contexts, and for creating a positive environment to motivate adolescents to become "upstanders" in educational programs to combat cyberbullying.

  17. You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites

    Science.gov (United States)

    Leung, Angel N. M.; Wong, Natalie; Farver, JoAnn M.

    2018-01-01

    The present study tested how exposure to two types of responses to a hypothetical simulated Facebook setting influenced cyber-bystanders’ perceived control and normative beliefs using a 4 cyberbully-victim group (pure cyberbullies, non-involved, pure cyberbullied victims, and cyberbullied-victims) × 2 condition (offend vs. defend) experimental design. 203 Hong Kong Chinese secondary school and university students (132 females, 71 males; 12 to 28; M = 16.70; SD = 3.03 years old) were randomly assigned into one of two conditions. Results showed that participants’ involvement in cyberbullying significantly related to their control beliefs about bully and victim assisting behaviors, while exposure to the two different conditions (offend vs. defend comments) was related to both their control and normative beliefs. In general, the defend condition promoted higher control beliefs to help the victims and promoted higher normative beliefs to help the victims. Regardless of their past involvement in cyberbullying and exposure to offend vs. defend conditions, both cyber-bullies and cyber-victims were more inclined to demonstrate normative beliefs to help victims than to assist bullies. These results have implications for examining environmental influences in predicting bystander behaviors in cyberbullying contexts, and for creating a positive environment to motivate adolescents to become “upstanders” in educational programs to combat cyberbullying. PMID:29740362

  18. You Are What You Read: The Belief Systems of Cyber-Bystanders on Social Networking Sites

    Directory of Open Access Journals (Sweden)

    Angel N. M. Leung

    2018-04-01

    Full Text Available The present study tested how exposure to two types of responses to a hypothetical simulated Facebook setting influenced cyber-bystanders’ perceived control and normative beliefs using a 4 cyberbully-victim group (pure cyberbullies, non-involved, pure cyberbullied victims, and cyberbullied-victims × 2 condition (offend vs. defend experimental design. 203 Hong Kong Chinese secondary school and university students (132 females, 71 males; 12 to 28; M = 16.70; SD = 3.03 years old were randomly assigned into one of two conditions. Results showed that participants’ involvement in cyberbullying significantly related to their control beliefs about bully and victim assisting behaviors, while exposure to the two different conditions (offend vs. defend comments was related to both their control and normative beliefs. In general, the defend condition promoted higher control beliefs to help the victims and promoted higher normative beliefs to help the victims. Regardless of their past involvement in cyberbullying and exposure to offend vs. defend conditions, both cyber-bullies and cyber-victims were more inclined to demonstrate normative beliefs to help victims than to assist bullies. These results have implications for examining environmental influences in predicting bystander behaviors in cyberbullying contexts, and for creating a positive environment to motivate adolescents to become “upstanders” in educational programs to combat cyberbullying.

  19. Updated BBN bounds on the cosmological lepton asymmetry for non-zero θ13

    International Nuclear Information System (INIS)

    Mangano, Gianpiero; Miele, Gennaro; Pastor, Sergio; Pisanti, Ofelia; Sarikas, Srdjan

    2012-01-01

    We discuss the bounds on the cosmological lepton number from Big Bang Nucleosynthesis (BBN), in light of recent evidences for a large value of the neutrino mixing angle θ 13 , sin 2 θ 13 ≥0.01 at 2σ. The largest asymmetries for electron and μ, τ neutrinos compatible with 4 He and 2 H primordial yields are computed versus the neutrino mass hierarchy and mixing angles. The flavour oscillation dynamics is traced till the beginning of BBN and neutrino distributions after decoupling are numerically computed. The latter contains in general, non-thermal distortion due to the onset of flavour oscillations driven by solar squared mass difference in the temperature range where neutrino scatterings become inefficient to enforce thermodynamical equilibrium. Depending on the value of θ 13 , this translates into a larger value for the effective number of neutrinos, N eff . Upper bounds on this parameter are discussed for both neutrino mass hierarchies. Values for N eff which are large enough to be detectable by the Planck experiment are found only for the (presently disfavoured) range sin 2 θ 13 ≤0.01.

  20. SELENE - Self-Forming Extensible Lunar EVA Network, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The overall objective of this research effort (Phase I and Phase II) by Scientific Systems Company, Inc. and BBN Technologies is to develop the SELENE network --...

  1. Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

    Science.gov (United States)

    Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

    2012-01-01

    Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

  2. The DARPA quantum network

    International Nuclear Information System (INIS)

    Elliot, B.

    2005-01-01

    Full text: The DARPA quantum network is now in initial operational, with six nodes performing quantum cryptography 24x7 across the Boston metro area between our campuses at Harvard University, Boston University, and BBN Technologies. In this talk, we present our recent activities, including the deployment of this network, building our Mark 1 Entangled QKD system, porting BBN QKD protocol software to NIST and Qinetiq freespace systems, performing initial design of a superconducting single photon detector with U. Rochester and NIST Boulder, and implementing a novel Low-Density Parity Check (LDPC) protocol for QKD. (author)

  3. Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms.

    Science.gov (United States)

    Stromatias, Evangelos; Neil, Daniel; Pfeiffer, Michael; Galluppi, Francesco; Furber, Steve B; Liu, Shih-Chii

    2015-01-01

    Increasingly large deep learning architectures, such as Deep Belief Networks (DBNs) are the focus of current machine learning research and achieve state-of-the-art results in different domains. However, both training and execution of large-scale Deep Networks require vast computing resources, leading to high power requirements and communication overheads. The on-going work on design and construction of spike-based hardware platforms offers an alternative for running deep neural networks with significantly lower power consumption, but has to overcome hardware limitations in terms of noise and limited weight precision, as well as noise inherent in the sensor signal. This article investigates how such hardware constraints impact the performance of spiking neural network implementations of DBNs. In particular, the influence of limited bit precision during execution and training, and the impact of silicon mismatch in the synaptic weight parameters of custom hybrid VLSI implementations is studied. Furthermore, the network performance of spiking DBNs is characterized with regard to noise in the spiking input signal. Our results demonstrate that spiking DBNs can tolerate very low levels of hardware bit precision down to almost two bits, and show that their performance can be improved by at least 30% through an adapted training mechanism that takes the bit precision of the target platform into account. Spiking DBNs thus present an important use-case for large-scale hybrid analog-digital or digital neuromorphic platforms such as SpiNNaker, which can execute large but precision-constrained deep networks in real time.

  4. Social Networks and Parent Motivational Beliefs: Evidence from an Urban School District

    Science.gov (United States)

    Curry, Katherine A.; Jean-Marie, Gaëtane; Adams, Curt M.

    2016-01-01

    Background: Despite devotion of substantial resources and effort to increase parent/school partnerships, gaps remain between policy rhetoric and practice, especially in high-poverty communities. Current research focuses on parent involvement or effects of parent motivational beliefs on parent choice for behavior; however, it does not address the…

  5. A Cognitive Perspective on Policy Implementation : Reform Beliefs, Sensemaking, and Social Networks

    NARCIS (Netherlands)

    Siciliano, Michael D.; Moolenaar, Nienke M.; Daly, Alan J.; Liou, Yi Hwa

    2017-01-01

    Utilizing a cognitive perspective, this article examines the social processes through which teachers come to understand the Common Core State Standards. The authors begin by identifying three beliefs that have important implications for policy implementation: self-efficacy, resource adequacy, and

  6. A Bayesian Belief Network approach to assess the potential of non wood forest products for small scale forest owners

    Science.gov (United States)

    Vacik, Harald; Huber, Patrick; Hujala, Teppo; Kurtilla, Mikko; Wolfslehner, Bernhard

    2015-04-01

    It is an integral element of the European understanding of sustainable forest management to foster the design and marketing of forest products, non-wood forest products (NWFPs) and services that go beyond the production of timber. Despite the relevance of NWFPs in Europe, forest management and planning methods have been traditionally tailored towards wood and wood products, because most forest management models and silviculture techniques were developed to ensure a sustained production of timber. Although several approaches exist which explicitly consider NWFPs as management objectives in forest planning, specific models are needed for the assessment of their production potential in different environmental contexts and for different management regimes. Empirical data supporting a comprehensive assessment of the potential of NWFPs are rare, thus making development of statistical models particularly problematic. However, the complex causal relationships between the sustained production of NWFPs, the available ecological resources, as well as the organizational and the market potential of forest management regimes are well suited for knowledge-based expert models. Bayesian belief networks (BBNs) are a kind of probabilistic graphical model that have become very popular to practitioners and scientists mainly due to the powerful probability theory involved, which makes BBNs suitable to deal with a wide range of environmental problems. In this contribution we present the development of a Bayesian belief network to assess the potential of NWFPs for small scale forest owners. A three stage iterative process with stakeholder and expert participation was used to develop the Bayesian Network within the frame of the StarTree Project. The group of participants varied in the stages of the modelling process. A core team, consisting of one technical expert and two domain experts was responsible for the entire modelling process as well as for the first prototype of the network

  7. Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms

    Directory of Open Access Journals (Sweden)

    Evangelos eStromatias

    2015-07-01

    Full Text Available Increasingly large deep learning architectures, such as Deep Belief Networks (DBNs are the focus of current machine learning research and achieve state-of-the-art results in different domains. However, both training and execution of large-scale Deep Networks requires vast computing resources, leading to high power requirements and communication overheads. The on-going work on design and construction of spike-based hardware platforms offers an alternative for running deep neural networks with significantly lower power consumption, but has to overcome hardware limitations in terms of noise and limited weight precision, as well as noise inherent in the sensor signal. This article investigates how such hardware constraints impact the performance of spiking neural network implementations of DBNs. In particular, the influence of limited bit precision during execution and training, and the impact of silicon mismatch in the synaptic weight parameters of custom hybrid VLSI implementations is studied. Furthermore, the network performance of spiking DBNs is characterized with regard to noise in the spiking input signal. Our results demonstrate that spiking DBNs can tolerate very low levels of hardware bit precision down to almost 2 bits, and shows that their performance can be improved by at least 30% through an adapted training mechanism that takes the bit precision of the target platform into account. Spiking DBNs thus present an important use-case for large-scale hybrid analog-digital or digital neuromorphic platforms such as SpiNNaker, which can execute large but precision-constrained deep networks in real time.

  8. On the application of Hidden Markov Model and Bayesian Belief Network to seismic noise at Las Canadas Caldera, Tenerife, Spain

    Energy Technology Data Exchange (ETDEWEB)

    Quintero Oliveros, Anggi [Dipartimento di Georisorse e Territorio, Universita di Udine (Italy); Departamento de Ciencias de La Tierra, Universidad Simon Bolivar, Caracas (Venezuela); Carniel, Roberto [Dipartimento di Georisorse e Territorio, Universita di Udine (Italy)], E-mail: roberto.carniel@uniud.it; Tarraga, Marta [Departamento de Volcanologia, Museo Nacional de Ciencias Naturales, CSIC, Madrid (Spain); Aspinall, Willy [Aspinall and Associates, 5 Woodside Close, Beaconsfield, Bucks (United Kingdom)

    2008-08-15

    The Teide-Pico Viejo volcanic complex situated in Tenerife Island (Canary Islands, Spain) has recently shown signs of unrest, long after its last eruptive episode at Chinyero in 1909, and the last explosive episode which happened at Montana Blanca, 2000 years ago. In this paper we study the seismicity of the Teide-Pico Viejo complex recorded between May and December 2004, in order to show the applicability of tools such as Hidden Markov Models and Bayesian Belief Networks which can be used to build a structure for evaluating the probability of given eruptive or volcano-related scenarios. The results support the existence of a bidirectional relationship between volcano-tectonic events and the background seismic noise - in particular its frequency content. This in turn suggests that the two phenomena can be related to one unique process influencing their generation.

  9. On the application of Hidden Markov Model and Bayesian Belief Network to seismic noise at Las Canadas Caldera, Tenerife, Spain

    International Nuclear Information System (INIS)

    Quintero Oliveros, Anggi; Carniel, Roberto; Tarraga, Marta; Aspinall, Willy

    2008-01-01

    The Teide-Pico Viejo volcanic complex situated in Tenerife Island (Canary Islands, Spain) has recently shown signs of unrest, long after its last eruptive episode at Chinyero in 1909, and the last explosive episode which happened at Montana Blanca, 2000 years ago. In this paper we study the seismicity of the Teide-Pico Viejo complex recorded between May and December 2004, in order to show the applicability of tools such as Hidden Markov Models and Bayesian Belief Networks which can be used to build a structure for evaluating the probability of given eruptive or volcano-related scenarios. The results support the existence of a bidirectional relationship between volcano-tectonic events and the background seismic noise - in particular its frequency content. This in turn suggests that the two phenomena can be related to one unique process influencing their generation

  10. The cosmic {sup 6}Li and {sup 7}Li problems and BBN with long-lived charged massive particles

    Energy Technology Data Exchange (ETDEWEB)

    Karsten, Jedamzik [Montpellier-2 Univ., Lab. de Physique Mathemathique et Theorique, C.N.R.S., 34 - Montpellier (France)

    2007-07-01

    Charged massive particles (CHAMPs), when present during the Big Bang nucleosynthesis (BBN) era, may significantly alter the synthesis of light elements when compared to a standard BBN scenario. This is due to the formation of bound states with nuclei. This paper presents a detailed numerical and analytical analysis of such CHAMP BBN. All reactions important for predicting light-element yields are calculated within the Born approximation. Three prior neglected effects are treated in detail: (a) photo destruction of bound states due to electromagnetic cascades induced by the CHAMP decay, (b) late-time efficient destruction/production of H{sup 2}, Li{sup 6}, and Li{sup 7} due to reactions on charge Z = 1 nuclei bound to CHAMPs, and (c) CHAMP exchange between nuclei. Each of these effects may induce orders-of-magnitude changes in the final abundance yields. The study focusses on the impact of CHAMPs on a possible simultaneous solution of the Li{sup 6} and Li{sup 7} problems. It is shown that a prior suggested simultaneous solution of the Li{sup 6} and Li{sup 7} problems for a relic decaying at {tau}{sub x} {approx} 1000 s is only very weakly dependent on the relic being neutral or charged, unless its hadronic branching ratio is B{sub h} << 10{sup -4} very small. By use of a Monte-Carlo analysis it is shown that within CHAMP BBN the existence of further parameter space for a simultaneous solution of the Li{sup 6} and Li{sup 7} problem for long decay times {tau}{sub x} {>=} 10{sup 6} s seems possible but fairly unlikely. (author)

  11. The cosmic 6Li and 7Li problems and BBN with long-lived charged massive particles

    International Nuclear Information System (INIS)

    Karsten, Jedamzik

    2007-01-01

    Charged massive particles (CHAMPs), when present during the Big Bang nucleosynthesis (BBN) era, may significantly alter the synthesis of light elements when compared to a standard BBN scenario. This is due to the formation of bound states with nuclei. This paper presents a detailed numerical and analytical analysis of such CHAMP BBN. All reactions important for predicting light-element yields are calculated within the Born approximation. Three prior neglected effects are treated in detail: (a) photo destruction of bound states due to electromagnetic cascades induced by the CHAMP decay, (b) late-time efficient destruction/production of H 2 , Li 6 , and Li 7 due to reactions on charge Z = 1 nuclei bound to CHAMPs, and (c) CHAMP exchange between nuclei. Each of these effects may induce orders-of-magnitude changes in the final abundance yields. The study focusses on the impact of CHAMPs on a possible simultaneous solution of the Li 6 and Li 7 problems. It is shown that a prior suggested simultaneous solution of the Li 6 and Li 7 problems for a relic decaying at τ x ∼ 1000 s is only very weakly dependent on the relic being neutral or charged, unless its hadronic branching ratio is B h -4 very small. By use of a Monte-Carlo analysis it is shown that within CHAMP BBN the existence of further parameter space for a simultaneous solution of the Li 6 and Li 7 problem for long decay times τ x ≥ 10 6 s seems possible but fairly unlikely. (author)

  12. Dynamical 3-Space Predicts Hotter Early Universe: Resolves CMB-BBN 7-Li and 4-He Abundance Anomalies

    Directory of Open Access Journals (Sweden)

    Cahill R. T.

    2010-01-01

    Full Text Available The observed abundances of 7-Li and 4-He are significantly inconsistent with the predictions from Big Bang Nucleosynthesis (BBN when using the $Lambda$CDM cosmological model together with the value for $Omega_B h^2 = 0.0224pm0.0009$ from WMAP CMB fluctuations, with the value from BBN required to fit observed abundances being $0.009 < Omega_B h^2 < 0.013$. The dynamical 3-space theory is shown to predict a 20% hotter universe in the radiation-dominated epoch, which then results in a remarkable parameter-free agreement between the BBN and the WMAP value for $Omega_B h^2$. The dynamical 3-space also gives a parameter-free fit to the supernova redshift data, and predicts that the flawed $Lambda$CDM model would require $Omega_Lambda = 0.73$ and $Omega_M = 0.27$ to fit the 3-space dynamics Hubble expansion, and independently of the supernova data. These results amount to the discovery of new physics for the early universe that is matched by numerous other successful observational and experimental tests.

  13. Dynamical 3-Space Predicts Hotter Early Universe: Resolves CMB-BBN 7-Li and 4-He Abundance Anomalies

    Directory of Open Access Journals (Sweden)

    Cahill R. T.

    2010-01-01

    Full Text Available The observed abundances of 7 Li and 4 He are significantly inconsistent with the pre- dictions from Big Bang Nucleosynthesis (BBN when using the CDM cosmolog- ical model together with the value for B h 2 = 0 : 0224 0 : 0009 from WMAP CMB fluctuations, with the value from BBN required to fit observed abundances being 0 : 009 < B h 2 < 0 : 013. The dynamical 3-space theory is shown to predict a 20% hot- ter universe in the radiation-dominated epoch, which then results in a remarkable parameter-free agreement between the BBN and the WMAP value for B h 2 . The dy- namical 3-space also gives a parameter-free fit to the supernova redshift data, and pre- dicts that the flawed CDM model would require = 0 : 73 and M = 0 : 27 to fit the 3-space dynamics Hubble expansion, and independently of the supernova data. These results amount to the discovery of new physics for the early universe that is matched by numerous other successful observational and experimental tests.

  14. Multiple roles for executive control in belief-desire reasoning: distinct neural networks are recruited for self perspective inhibition and complexity of reasoning.

    Science.gov (United States)

    Hartwright, Charlotte E; Apperly, Ian A; Hansen, Peter C

    2012-07-16

    Belief-desire reasoning is a core component of 'Theory of Mind' (ToM), which can be used to explain and predict the behaviour of agents. Neuroimaging studies reliably identify a network of brain regions comprising a 'standard' network for ToM, including temporoparietal junction and medial prefrontal cortex. Whilst considerable experimental evidence suggests that executive control (EC) may support a functioning ToM, co-ordination of neural systems for ToM and EC is poorly understood. We report here use of a novel task in which psychologically relevant ToM parameters (true versus false belief; approach versus avoidance desire) were manipulated orthogonally. The valence of these parameters not only modulated brain activity in the 'standard' ToM network but also in EC regions. Varying the valence of both beliefs and desires recruits anterior cingulate cortex, suggesting a shared inhibitory component associated with negatively valenced mental state concepts. Varying the valence of beliefs additionally draws on ventrolateral prefrontal cortex, reflecting the need to inhibit self perspective. These data provide the first evidence that separate functional and neural systems for EC may be recruited in the service of different aspects of ToM. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Uncertainty measurement with belief entropy on interference effect in Quantum-Like Bayesian Networks

    OpenAIRE

    Huang, Zhiming; Yang, Lin; Jiang, Wen

    2017-01-01

    Social dilemmas have been regarded as the essence of evolution game theory, in which the prisoner's dilemma game is the most famous metaphor for the problem of cooperation. Recent findings revealed people's behavior violated the Sure Thing Principle in such games. Classic probability methodologies have difficulty explaining the underlying mechanisms of people's behavior. In this paper, a novel quantum-like Bayesian Network was proposed to accommodate the paradoxical phenomenon. The special ne...

  16. Improved Deep Belief Networks (IDBN Dynamic Model-Based Detection and Mitigation for Targeted Attacks on Heavy-Duty Robots

    Directory of Open Access Journals (Sweden)

    Lianpeng Li

    2018-04-01

    Full Text Available In recent years, the robots, especially heavy-duty robots, have become the hardest-hit areas for targeted attacks. These attacks come from both the cyber-domain and the physical-domain. In order to improve the security of heavy-duty robots, this paper proposes a detection and mitigation mechanism which based on improved deep belief networks (IDBN and dynamic model. The detection mechanism consists of two parts: (1 IDBN security checks, which can detect targeted attacks from the cyber-domain; (2 Dynamic model and security detection, used to detect the targeted attacks which can possibly lead to a physical-domain damage. The mitigation mechanism was established on the base of the detection mechanism and could mitigate transient and discontinuous attacks. Moreover, a test platform was established to carry out the performance evaluation test for the proposed mechanism. The results show that, the detection accuracy for the attack of the cyber-domain of IDBN reaches 96.2%, and the detection accuracy for the attack of physical-domain control commands reaches 94%. The performance evaluation test has verified the reliability and high efficiency of the proposed detection and mitigation mechanism for heavy-duty robots.

  17. Estimation of total Effort and Effort Elapsed in Each Step of Software Development Using Optimal Bayesian Belief Network

    Directory of Open Access Journals (Sweden)

    Fatemeh Zare Baghiabad

    2017-09-01

    Full Text Available Accuracy in estimating the needed effort for software development caused software effort estimation to be a challenging issue. Beside estimation of total effort, determining the effort elapsed in each software development step is very important because any mistakes in enterprise resource planning can lead to project failure. In this paper, a Bayesian belief network was proposed based on effective components and software development process. In this model, the feedback loops are considered between development steps provided that the return rates are different for each project. Different return rates help us determine the percentages of the elapsed effort in each software development step, distinctively. Moreover, the error measurement resulted from optimized effort estimation and the optimal coefficients to modify the model are sought. The results of the comparison between the proposed model and other models showed that the model has the capability to highly accurately estimate the total effort (with the marginal error of about 0.114 and to estimate the effort elapsed in each software development step.

  18. COmmunications and Networking with QUantum Operationally-Secure Technology for Maritime Deployment (CONQUEST)

    Science.gov (United States)

    2017-03-06

    15 minutes 48 Efficient post -processing for CV QKD Saikat Guha BBN Review Meeting Feb 17, 2017 Communications and Networking with Quantum Operationally...Raytheon BBN Technologies; Dr. Saikat Guha Contractor Address: 10 Moulton Street, Cambridge, MA 02138 Title of the Project: COmmunications and...Equipment Purchased No equipment has been purchased or constructed at this time. Section D. Key Personnel There have been no changes in

  19. Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

    Science.gov (United States)

    Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan

    2017-01-15

    Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the

  20. Updating Parameters for Volcanic Hazard Assessment Using Multi-parameter Monitoring Data Streams And Bayesian Belief Networks

    Science.gov (United States)

    Odbert, Henry; Aspinall, Willy

    2014-05-01

    Evidence-based hazard assessment at volcanoes assimilates knowledge about the physical processes of hazardous phenomena and observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We discuss

  1. Study of the 2H(p,γ)3He reaction in the BBN energy range at LUNA

    Science.gov (United States)

    Trezzi, Davide; LUNA Collaboration

    2018-01-01

    Using Big Bang Nucleosynthesis with the recent cosmological parameters obtained by the Planck collaboration, a primordial deuterium abundance value D/H = (2.65 ± 0.07) × 10-5 is obtained. This one is a little bit in tension with astronomical observations on metal- poor damped Lyman alpha systems where D/H = (2.53 ± 0.04) × 105. In order to reduce the BBN calculation uncertainty, a measurement of the 2H(p,γ)3He cross section in the energy range 10-300 keV with a 3% accuracy is thus desirable. Thanks to the low background of the underground Gran Sasso Laboratories, and to the experience accumulated in more than twenty years of scientific activity, LUNA (Laboratory for Underground Nuclear Astrophysics) planned to measure the 2H(p,γ)3He fusion cross section at the BBN energy range in 2015-2016. A feasibility test of the measurement has been recently performed at LUNA. In this paper, the results obtained will be shown. Possible cosmological outcomes from the future LUNA data will be also discussed.

  2. Suppressed Belief

    Directory of Open Access Journals (Sweden)

    Komarine Romdenh-Romluc

    2009-12-01

    Full Text Available Moran’s revised conception of conscious belief requires us to reconceptualise suppressed belief. The work of Merleau-Ponty offers a way to do this. His account of motor-skills allows us to understand suppressed beliefs as pre-reflective ways of dealing with the world.

  3. A Framework for Probabilistic Multi-Hazard Assessment of Rain-Triggered Lahars Using Bayesian Belief Networks

    Directory of Open Access Journals (Sweden)

    Pablo Tierz

    2017-09-01

    Full Text Available Volcanic water-sediment flows, commonly known as lahars, can often pose a higher threat to population and infrastructure than primary volcanic hazardous processes such as tephra fallout and Pyroclastic Density Currents (PDCs. Lahars are volcaniclastic flows of water, volcanic debris and entrained sediments that can travel long distances from their source, causing severe damage by impact and burial. Lahars are frequently triggered by intense or prolonged rainfall occurring after explosive eruptions, and their occurrence depends on numerous factors including the spatio-temporal rainfall characteristics, the spatial distribution and hydraulic properties of the tephra deposit, and the pre- and post-eruption topography. Modeling (and forecasting such a complex system requires the quantification of aleatory variability in the lahar triggering and propagation. To fulfill this goal, we develop a novel framework for probabilistic hazard assessment of lahars within a multi-hazard environment, based on coupling a versatile probabilistic model for lahar triggering (a Bayesian Belief Network: Multihaz with a dynamic physical model for lahar propagation (LaharFlow. Multihaz allows us to estimate the probability of lahars of different volumes occurring by merging varied information about regional rainfall, scientific knowledge on lahar triggering mechanisms and, crucially, probabilistic assessment of available pyroclastic material from tephra fallout and PDCs. LaharFlow propagates the aleatory variability modeled by Multihaz into hazard footprints of lahars. We apply our framework to Somma-Vesuvius (Italy because: (1 the volcano is strongly lahar-prone based on its previous activity, (2 there are many possible source areas for lahars, and (3 there is high density of population nearby. Our results indicate that the size of the eruption preceding the lahar occurrence and the spatial distribution of tephra accumulation have a paramount role in the lahar

  4. An ecosystem service approach to support integrated pond management: a case study using Bayesian belief networks--highlighting opportunities and risks.

    Science.gov (United States)

    Landuyt, Dries; Lemmens, Pieter; D'hondt, Rob; Broekx, Steven; Liekens, Inge; De Bie, Tom; Declerck, Steven A J; De Meester, Luc; Goethals, Peter L M

    2014-12-01

    Freshwater ponds deliver a broad range of ecosystem services (ESS). Taking into account this broad range of services to attain cost-effective ESS delivery is an important challenge facing integrated pond management. To assess the strengths and weaknesses of an ESS approach to support decisions in integrated pond management, we applied it on a small case study in Flanders, Belgium. A Bayesian belief network model was developed to assess ESS delivery under three alternative pond management scenarios: intensive fish farming (IFF), extensive fish farming (EFF) and nature conservation management (NCM). A probabilistic cost-benefit analysis was performed that includes both costs associated with pond management practices and benefits associated with ESS delivery. Whether or not a particular ESS is included in the analysis affects the identification of the most preferable management scenario by the model. Assessing the delivery of a more complete set of ecosystem services tends to shift the results away from intensive management to more biodiversity-oriented management scenarios. The proposed methodology illustrates the potential of Bayesian belief networks. BBNs facilitate knowledge integration and their modular nature encourages future model expansion to more encompassing sets of services. Yet, we also illustrate the key weaknesses of such exercises, being that the choice whether or not to include a particular ecosystem service may determine the suggested optimal management practice. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagation.

    Directory of Open Access Journals (Sweden)

    Salvador Dura-Bernal

    Full Text Available Hierarchical generative models, such as Bayesian networks, and belief propagation have been shown to provide a theoretical framework that can account for perceptual processes, including feedforward recognition and feedback modulation. The framework explains both psychophysical and physiological experimental data and maps well onto the hierarchical distributed cortical anatomy. However, the complexity required to model cortical processes makes inference, even using approximate methods, very computationally expensive. Thus, existing object perception models based on this approach are typically limited to tree-structured networks with no loops, use small toy examples or fail to account for certain perceptual aspects such as invariance to transformations or feedback reconstruction. In this study we develop a Bayesian network with an architecture similar to that of HMAX, a biologically-inspired hierarchical model of object recognition, and use loopy belief propagation to approximate the model operations (selectivity and invariance. Crucially, the resulting Bayesian network extends the functionality of HMAX by including top-down recursive feedback. Thus, the proposed model not only achieves successful feedforward recognition invariant to noise, occlusions, and changes in position and size, but is also able to reproduce modulatory effects such as illusory contour completion and attention. Our novel and rigorous methodology covers key aspects such as learning using a layerwise greedy algorithm, combining feedback information from multiple parents and reducing the number of operations required. Overall, this work extends an established model of object recognition to include high-level feedback modulation, based on state-of-the-art probabilistic approaches. The methodology employed, consistent with evidence from the visual cortex, can be potentially generalized to build models of hierarchical perceptual organization that include top-down and bottom

  6. Conscious Belief

    Directory of Open Access Journals (Sweden)

    David Pitt

    2016-04-01

    Full Text Available Tim Crane maintains that beliefs cannot be conscious because they persist in the absence of consciousness. Conscious judgments can share their contents with beliefs, and their occurrence can be evidence for what one believes; but they cannot be beliefs, because they don’t persist. I challenge Crane’s premise that belief attributions to the temporarily unconscious are literally true. To say of an unconscious agent that she believes that p is like saying that she sings well. To say she sings well is to say that when she sings, her singing is good. To say that she believes that p is (roughly to say that when she consciously considers the content that p she consciously affirms (believes it. I also argue that the phenomenal view of intentional content Crane appears to endorse prima facie commits him to the view, at least controversial, perhaps incoherent, that there is unconscious phenomenology (the intentional contents of unconscious beliefs.

  7. Integration of biological, economic and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon

    DEFF Research Database (Denmark)

    Levontin, Polina; Kulmala, Soile; Haapasaari, Päivi Elisabet

    2011-01-01

    There is a growing need to evaluate fisheries management plans in a comprehensive interdisciplinary context involving stakeholders. The use of a probabilistic management model to evaluate potential management plans for Baltic salmon fisheries is demonstrated. The analysis draws on several scientific...... studies: a biological stock assessment with integrated economic analysis of the commercial fisheries, an evaluation of recreational fisheries, and a sociological study aimed at understanding stakeholder perspectives and potential commitment to alternative management plans. A Bayesian belief network is used...... is highlighted by modelling the link between commitment and implementation success. Such analyses, relying on prior knowledge, can forewarn of the consequences of management choices before they are implemented...

  8. arXiv AlterBBN v2: A public code for calculating Big-Bang nucleosynthesis constraints in alternative cosmologies

    CERN Document Server

    Arbey, A.; Hickerson, K.P.; Jenssen, E.S.

    We present the version 2 of AlterBBN, an open public code for the calculation of the abundance of the elements from Big-Bang nucleosynthesis. It does not rely on any closed external library or program, aims at being user-friendly and allowing easy modifications, and provides a fast and reliable calculation of the Big-Bang nucleosynthesis constraints in the standard and alternative cosmologies.

  9. Low-energy cross sections of the BBN reaction d({alpha},{gamma}){sup 6}Li by Coulomb dissociation of {sup 6}Li

    Energy Technology Data Exchange (ETDEWEB)

    Heil, Michael; Suemmerer, Klaus [GSI Darmstadt (Germany); Hammache, Fairouz [IPN Orsay (France); Galaviz, Daniel [TU Darmstadt (Germany); Typel, Stefan [GANIL Caen (France)

    2008-07-01

    The primordial abundances of D, ({sup 3}He), {sup 4}He, and {sup 7}Li can be used to infer the baryon density of the Universe based on the framework of Big-Bang Nucleosynthesis (BBN). By precision measurements of the cosmic microwave background (CMB) an independent method became available recently. This lead to a renewed interest for BBN. Together with the recent observation of {sup 6}Li in old stars and the problems to reconcile calculated primordial {sup 7}Li abundances with those predicted on the basis of CMB results, the production of both, {sup 6}Li and {sup 7}Li in BBN has been reinvestigated. One important ingredient is the low-energy S-factor of the d-alpha radiative-capture reaction. Up to now, the only available experimental result by Kiener et al. (1991) introduced an uncertainty of about a factor of 20 in the {sup 6}Li yield. We have therefore reinvestigated the d-alpha reaction with the help of Coulomb dissociation (CD) of {sup 6}Li at 150 MeV/nucleon at GSI. CD is the only practical way to study the low-energy S-factor (which involves l=2 multipolarity) due to the large number of E2 photons contained in the equivalent-photon flux. Preliminary results indicate a drop of the S-factor as predicted by theory, contrary to the constant low-energy S-factor resulting from the previous study.

  10. Application of a Bayesian belief network for assessing the vulnerability of permafrost to thaw and implications for greenhouse gas production and climate feedback

    International Nuclear Information System (INIS)

    Webster, K.L.; McLaughlin, J.W.

    2014-01-01

    Highlights: • Permafrost areas are subject to accelerated rates of climate change leading to thaw. • Thaw will increase decomposition rates, exacerbating climate feedback. • We present a Bayesian belief network as a tool to examine interacting factors. • Organic soil (Hudson Plain region) and mineral soil (Arctic region) are contrasted. • Hudson Plain has contributed more to climate feedback than Arctic, but gap closing. - Abstract: Permafrost affected soils are an important component of the Boreal, Subarctic, and Arctic ecosystems of Canada. These areas are undergoing accelerated rates of climate change and have been identified as being at high risk for thaw. Thaw will expose soil to warmer conditions that support increased decomposition rates, which in turn will affect short- and long-term carbon storage capacity and result in feedback to global climate. We present a tool in the form of a Bayesian belief network influence diagram that will allow policymakers and managers to understand how interacting factors contribute to permafrost thaw and resulting effects on greenhouse gas (GHG) production and climate feedback. A theoretical example of expected responses from an organic soil typical of the Hudson Plain region and a mineral soil typical in the Arctic region demonstrate variability in responses across different combinations of climate and soil conditions within Canada. Based on the network results, the Arctic has historically had higher probability of thaw, but the Hudson Plain has had higher probability of producing carbon dioxide (CO 2 ) and methane (CH 4 ). Under past and current climate conditions, the Hudson Plain has, on a per unit area basis, contributed more to climate feedback than the Arctic. However, the gap in contribution between the two regions is likely to decrease as thaw progresses more rapidly in the Arctic than Hudson Plain region, resulting in strong positive feedback to climate warming from both regions. The flexible framework

  11. Measurement of the Constructs of Health Belief Model related to Self-care during Pregnancy in Women Referred to South Tehran Health Network

    Directory of Open Access Journals (Sweden)

    Yalda Soleiman Ekhtiari

    2016-03-01

    Full Text Available Background and Objective: Self-care activities during pregnancy can be effective in reducing adverse pregnancy outcomes. Health Belief Model (HBM is one of the most applicable models in educational need assessment for planning and implementation of educational interventions. The purpose of this study was to measurement of the constructs of HBM related to self-care during pregnancy in women referred to South Tehran health network.Materials and Methods: In this cross-sectional study 270 pregnant women who referred to health centers of South Tehran Health Networks participated. Demographic, knowledge and attitude questionnaires based on constructs of HBM was used to measure the status of knowledge and attitude of women. Data were analyzed using statistical software SPSS18.Results: Results showed that 92.2% of women had the knowledge scores in good level. The scores of perceived severity, perceived self-efficacy and cues to action were in good level in almost of women but almost of women obtained weak point in perceived susceptibility, perceived benefits and barriersConclusion: HBM can be used as an appropriate tool for assessment the status of pregnant women in the field of self-care behaviors during pregnancy and planning and implementation of educational interventions.

  12. Family physician's knowledge, beliefs, and self-reported practice patterns regarding hyperlipidemia: a National Research Network (NRN) survey.

    Science.gov (United States)

    Eaton, Charles B; Galliher, James M; McBride, Patrick E; Bonham, Aaron J; Kappus, Jennifer A; Hickner, John

    2006-01-01

    Family physicians have the potential to make a major impact on reducing the burden of cardiovascular disease through the optimal assessment and management of hyperlipidemia. We were interested in assessing the knowledge, beliefs, and self-reported practice patterns of a representative sample of family physicians regarding the assessment and management of hyperlipidemia 2 years after the release of the evidence-based National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP) III guidelines. A 33-item survey was mailed to a random sample (N = 1200) of members of the American Academy of Family Physicians in April of 2004, with 2 follow-up mailings to nonresponders. Physicians were queried about sociodemographic characteristics, their knowledge, attitudes, and self-reported practice patterns regarding the assessment and management of hyperlipidemia. Four case scenarios also were presented. Response rate was 58%. Over 90% of surveyed family physicians screened adults for hyperlipidemia as part of a cardiovascular disease prevention strategy. Most (89%) did this screening by themselves without the support of office staff, and 36% reported routine use of a flow sheet. Most had heard of the ATP III guidelines (85%), but only 13% had read them carefully. Only 17% of respondents used a coronary heart disease (CHD) risk calculator usually or always. Over 90% of those responding reported using low-density lipoprotein (LDL) as the treatment goal but only 76% reported using non-high-density lipoprotein (HDL) cholesterol as a secondary goal of therapy. We found a large variability in knowledge, beliefs, and practice patterns among practicing family physicians. We found general agreement on universal screening of adults for hyperlipidemia as part of cardiovascular disease prevention strategy and use of LDL cholesterol as a treatment goal. Many other aspects of the NCEP ATP III guidelines, such as use of a systematic, multidisciplinary approach, using non

  13. A study on the quantitative evaluation of the reliability for safety critical software using Bayesian belief nets

    International Nuclear Information System (INIS)

    Eom, H. S.; Jang, S. C.; Ha, J. J.

    2003-01-01

    Despite the efforts to avoid undesirable risks, or at least to bring them under control in the world, new risks that are highly difficult to manage continue to emerge from the use of new technologies, such as the use of digital instrumentation and control (I and C) components in nuclear power plant. Whenever new risk issues came out by now, we have endeavored to find the most effective ways to reduce risks, or to allocate limited resources to do this. One of the major challenges is the reliability analysis of safety-critical software associated with digital safety systems. Though many activities such as testing, verification and validation (V and V) techniques have been carried out in the design stage of software, however, the process of quantitatively evaluating the reliability of safety-critical software has not yet been developed because of the irrelevance of the conventional software reliability techniques to apply for the digital safety systems. This paper focuses on the applicability of Bayesian Belief Net (BBN) techniques to quantitatively estimate the reliability of safety-critical software adopted in digital safety system. In this paper, a typical BBN model was constructed using the dedication process of the Commercial-Off-The-Shelf (COTS) installed by KAERI. In conclusion, the adoption of BBN technique can facilitate the process of evaluating the safety-critical software reliability in nuclear power plant, as well as provide very useful information (e.g., 'what if' analysis) associated with software reliability in the viewpoint of practicality

  14. Belief change

    CSIR Research Space (South Africa)

    Booth, R

    2012-07-01

    Full Text Available In this paper the authors present a brief overview of belief change, a research area concerned with the question of how a rational agent ought to change its mind in the face of new, possibly conflicting, information. The authors limit themselves...

  15. Dual integrin and gastrin-releasing peptide receptor targeted tumor imaging using 18F-labeled PEGylated RGD-bombesin heterodimer 18F-FB-PEG3-Glu-RGD-BBN.

    Science.gov (United States)

    Liu, Zhaofei; Yan, Yongjun; Chin, Frederic T; Wang, Fan; Chen, Xiaoyuan

    2009-01-22

    Radiolabeled RGD and bombesin peptides have been extensively investigated for tumor integrin alpha(v)beta(3) and GRPR imaging, respectively. Due to the fact that many tumors are both integrin and GRPR positive, we designed and synthesized a heterodimeric peptide Glu-RGD-BBN, which is expected to be advantageous over the monomeric peptides for dual-receptor targeting. A PEG(3) spacer was attached to the glutamate alpha-amino group of Glu-RGD-BBN to enhance the (18)F labeling yield and to improve the in vivo kinetics. PEG(3)-Glu-RGD-BBN possesses the comparable GRPR and integrin alpha(v)beta(3) receptor-binding affinities as the corresponding monomers, respectively. The dual-receptor targeting properties of (18)F-FB-PEG(3)-Glu-RGD-BBN were observed in PC-3 tumor model. (18)F-FB-PEG(3)-Glu-RGD-BBN with high tumor contrast and favorable pharmacokinetics is a promising PET tracer for dual integrin and GRPR positive tumor imaging. This heterodimer strategy may also be an applicable method to develop other molecules with improved in vitro and in vivo characterizations for tumor diagnosis and therapy.

  16. Analysis of regional scale risk to whirling disease in populations of Colorado and Rio Grande cutthroat trout using Bayesian belief network model

    Science.gov (United States)

    Kolb Ayre, Kimberley; Caldwell, Colleen A.; Stinson, Jonah; Landis, Wayne G.

    2014-01-01

    Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.

  17. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  18. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

    Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  19. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  20. Up-conversion emission of Er{sup 3+}/Yb{sup 3+}co-doped BaBi{sub 2}Nb{sub 2}O{sub 9} (BBN) phosphors

    Energy Technology Data Exchange (ETDEWEB)

    Façanha, M.X., E-mail: marcello.facanha@uece.br [Departamento de Química, Centro de Ciências, Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Faculdade de Educação de Crateús (FAEC), Universidade Estadual do Ceará (UECE), Fortaleza, Ceará (Brazil); Laboratório de Telecomunicações e Ciências e Engenharia de Materiais (LOCEM), Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Nascimento, J.P.C. do [Departamento de Química, Centro de Ciências, Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Laboratório de Telecomunicações e Ciências e Engenharia de Materiais (LOCEM), Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); Silva, M.A.S., E-mail: marceloassilva@yahoo.com.br [Laboratório de Telecomunicações e Ciências e Engenharia de Materiais (LOCEM), Universidade Federal do Ceará (UFC), Fortaleza, Ceará (Brazil); and others

    2017-03-15

    On this paper, polycrystalline samples of the tetragonal systems BaBi{sub 2}Nb{sub 2}O{sub 9} (BBN) and BBN co-doped with Er{sup 3+}/Yb{sup 3+} (BBN: 0.04Er{sup 3+}yYb{sup 3+}, where y=0.02, 0.04, 0.06 and 0.08 mol%) were synthesized by the solid state method. The crystalline structure and photoluminescent properties of the ceramic phosphors were investigated by powder X-ray diffraction (PXRD), Raman spectroscopy and spectral analysis of up-conversion (UC) emission. The results reveal that all compositions crystallize in the I4/mmm space group at room temperature, and show UC green emissions (centered at 525 nm and 550 nm) and red (around 660 nm) coming from ({sup 2}H{sub 11/2}, {sup 4}S{sub 3/2}→{sup 4}I{sub 15/2}) and ({sup 4}F{sub 9/2}→{sup 4}I{sub 15/2}) transitions, respectively, under excitation at 980 nm. Increasing variations of the Yb{sup 3+} sensitizer concentration in the host BBN, lead to a significant intensity increase in both UC emissions due to the efficiency of the energy-transfer process. The BBN: 0.04 mol%Er{sup 3+}0.08 mol%Yb{sup 3+} composition showed the higher intensity bands, thus establishing the BBN as an alternative host material for luminescent centers.

  1. Belief change

    CSIR Research Space (South Africa)

    Booth, R

    2011-08-01

    Full Text Available in the presence of Vacuity. 3.2 Partial meet theory contraction The preceding construction works equally well when B is taken to be a theory K. But in this case, since the input to contraction is a theory, we should expect the output to be a theory too... that is analogous to that of a belief set K in theory change. Intuitively, E is the ?current? set of expectations of the agent, and the plausible consequences of a sentence ? are those sentences ? for which ? |?? holds. The set of expectations E is not explicitly...

  2. An exploratory study on 99mTc-RGD-BBN peptide scintimammography in the assessment of breast malignant lesions compared to 99mTc-3P4-RGD2.

    Directory of Open Access Journals (Sweden)

    Qianqian Chen

    Full Text Available This study aimed to explore the diagnostic performance of single photon emission computed tomography / computerized tomography (SPECT/CT using a new radiotracer 99mTc-RGD-BBN for breast malignant tumor compared with 99mTc-3P4-RGD2.6 female patients with breast malignant tumors diagnosed by fine needle aspiration cytology biopsy (FNAB who were scheduled to undergo surgery were included in the study. 99mTc-3P4-RGD2 and 99mTc-RGD-BBN were performed with single photon emission computed tomography (SPECT at 1 hour after intravenous injection of 299 ± 30 MBq and 293 ± 32 MBq of radiotracers respectively at separate day. The results were evaluated by the Tumor to non-Tumor ratios (T/NT. 99mTc-RGD-BBN and 99mTc-3P4-RGD2 SPECT/CT images were interpreted independently by 3 experienced nuclear medicine physicians using a 3-point scale system. All of the samples were analyzed immunohistochemically to evaluate the integrin αvβ3 and gastrin-releasing peptide receptor (GRPR expression. The safety, biodistribution and radiation dosimetry of 99mTc-RGD-BBN were also evaluated in the healthy volunteers.No serious adverse events were reported in any of the patients during the study. The effective radiation dose entirely conformed to the relevant standards. A total of 6 palpable malignant lesions were detected using 99mTc-RGD-BBN SPECT/CT with clear uptake. All malignant lesions were also detected using 99mTc-3P4-RGD2 SPECT/CT. The results showed that five malignant lesions were with clear uptake and the other one with barely an uptake. 4 malignant cases were found with both αvβ3 and GRPR expression, 1 case with only GRPR positive expression (integrin αvβ3 negative and 1 case with only integrin αvβ3 positive expression (GRPR negative.99mTc-RGD-BBN is a safe agent for detecting breast cancer. 99mTc-RGD-BBN may have the potential to make up for the deficiency of 99mTc-3P4-RGD2 in the detection of breast cancer with only GRPR positive expression (integrin

  3. Optimization, biological evaluation and microPET imaging of copper-64-labeled bombesin agonists, [64Cu-NO2A-(X)-BBN(7-14)NH2], in a prostate tumor xenografted mouse model

    International Nuclear Information System (INIS)

    Lane, Stephanie R.; Nanda, Prasanta; Rold, Tammy L.; Sieckman, Gary L.; Figueroa, Said D.; Hoffman, Timothy J.; Jurisson, Silvia S.; Smith, Charles J.

    2010-01-01

    Gastrin-releasing peptide receptors (GRPr) are a member of the bombesin (BBN) receptor family. GRPr are expressed in high numbers on specific human cancers, including human prostate cancer. Therefore, copper-64 ( 64 Cu) radiolabeled BBN(7-14)NH 2 conjugates could have potential for diagnosis of human prostate cancer via positron-emission tomography (PET). The aim of this study was to produce [ 64 Cu-NO2A-(X)-BBN(7-14)NH 2 ] conjugates for prostate cancer imaging, where X=pharmacokinetic modifier (beta-alanine, 5-aminovaleric acid, 6-aminohexanoic acid, 8-aminooctanoic acid, 9-aminonanoic acid or para-aminobenzoic acid) and NO2A=1,4,7-triazacyclononane-1,4-diacetic acid [a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)]. Methods: [(X)-BBN(7-14)NH 2 ] Conjugates were synthesized by solid-phase peptide synthesis (SPPS), after which NOTA was added via manual conjugation. The new peptide conjugates were radiolabeled with 64 Cu radionuclide. The receptor-binding affinity was determined in human prostate PC-3 cells, and tumor-targeting efficacy was determined in PC-3 tumor-bearing severely combined immunodeficient (SCID) mice. Whole-body maximum intensity microPET/CT images of PC-3 tumor-bearing SCID mice were obtained 18 h postinjection (pi). Results: Competitive binding assays in PC-3 cells indicated high receptor-binding affinity for the [NO2A-(X)-BBN(7-14)NH 2 ] and [ nat Cu-NO2A-(X)-BBN(7-14)NH 2 ] conjugates. In vivo biodistribution studies of the [ 64 Cu-NO2A-(X)-BBN(7-14)NH 2 ] conjugates at 1, 4 and 24 h pi showed very high uptake of the tracer in GRPr-positive tissue with little accumulation and retention in nontarget tissues. High-quality, high-contrast microPET images were obtained, with xenografted tumors being clearly visible at 18 h pi. Conclusions: NO2A chelator sufficiently stabilizes copper(II) radiometal under in vivo conditions, producing conjugates with very high uptake and retention in targeted GRPr. Preclinical evaluation of these

  4. A Bayesian belief nets based quantitative software reliability assessment for PSA: COTS case study

    International Nuclear Information System (INIS)

    Eom, H. S.; Sung, T. Y.; Jeong, H. S.; Park, J. H.; Kang, H. G.; Lee, K. Y.; Park, J. K

    2002-03-01

    Current reliability assessments of safety critical software embedded in the digital systems in nuclear power plants are based on the rule-based qualitative assessment methods. Then recently practical needs require the quantitative features of software reliability for Probabilistic Safety Assessment (PSA) that is one of important methods being used in assessing the whole safety of nuclear power plant. But conventional quantitative software reliability assessment methods are not enough to get the necessary results in assessing the safety critical software used in nuclear power plants. Thus, current reliability assessment methods for these digital systems exclude the software part or use arbitrary values for the software reliability in the assessment. This reports discusses a Bayesian Belief Nets (BBN) based quantification method that models current qualitative software assessment in formal way and produces quantitative results required for PSA. Commercial Off-The-Shelf (COTS) software dedication process that KAERI developed was applied to the discussed BBN based method for evaluating the plausibility of the proposed method in PSA

  5. Chemoprevention with green propolis green propolis extracted in L-lysine versus carcinogenesis promotion with L-lysine in N-Butyl-N-[4-hydroxybutyl] nitrosamine (BBN induced rat bladder cancer Quimioprevenção com própolis verde extraído em L-Lisina versus promoção da carcinogênese como L-Lisina em ratos induzidos ao câncer de bexiga pelo N-Butyl-N-[4-hydroxybutyl] nitrosamine (BBN

    Directory of Open Access Journals (Sweden)

    Conceição Aparecida Dornelas

    2012-02-01

    Full Text Available PURPOSE: To determine the effects of green propolis extracted in L-lysine (WSDP and of L- lysine for 40 weeks on induced rat bladder carcinogenesis. METHODS: The animals (groups I, II, III, IV, V and VI received BBN during 14 weeks. Group I was treated with propolis 30 days prior received BBN, and then these animals were treated daily with propolis; Groups II and III was treated with subcutaneous and oral propolis (respectively concurrently with BBN. The animals of Group IV were treated L-lysine; Group V received water subcutaneous; and Group VI received only to BBN. Among the animals not submitted to carcinogenesis induction, Group VII received propolis, Group VIII received L-lysine and Group IX received water. RESULTS: The carcinoma incidence in Group I was lower than that of control (Group VI. The carcinoma multiplicity in Group IV was greater than in Group VI. All animals treated with L-lysine developed carcinomas, and they were also more invasive in Group IV than in controls. On the other hand, Group VIII showed no bladder lesions. CONCLUSION: The WSDP is chemopreventive against rat bladder carcinogenesis, if administered 30 days prior to BBN , and that L-lysine causes promotion of bladder carcinogenesis.OBJETIVO: Determinar os efeitos da própolis verde extraída em L - Lisina (WSDP e da L-Lisina por 40 semanas em ratos induzidos a carcinogênese de bexiga. MÉTODOS: Os animais (grupos I, II, III, IV, V e VI receberam BBN por 14 semanas. O grupo I foi tratado com própolis 30 dias antes de receber BBN e em seguida estes animais foram tratados diariamente com própolis; Os grupos II e III foram tratados com própolis subcutânea e oral (respectivamente e concorretemente com BBN. Os animais do grupo IV foram tratados com L- Lisina; o grupo V recebeu água subcutânea; o grupo VI recebeu apenas BBN. Entre os animais não submetidos a indução de carcinogênese, Grupo VII, receberam própolis, Grupo VIII, receberam L-Lisina e Grupo IX

  6. Belief Elicitation in Experiments

    DEFF Research Database (Denmark)

    Blanco, Mariana; Engelmann, Dirk; Koch, Alexander

    Belief elicitation in economics experiments usually relies on paying subjects according to the accuracy of stated beliefs in addition to payments for other decisions. Such incentives, however, allow risk-averse subjects to hedge with their stated beliefs against adverse outcomes of other decisions......-belief elicitation treatment using a financial investment frame, where hedging arguably would be most natural....

  7. Evolution of Religious Beliefs

    CERN Multimedia

    CERN. Geneva

    2009-01-01

    Humans may be distinguished from all other animals in having beliefs about the causal interaction of physical objects. Causal beliefs are a developmental primitive in human children; animals, by contrast, have very few causal beliefs. The origin of human causal beliefs comes from the evolutionary advantage it gave in relation to complex tool making and use. Causal beliefs gave rise religion and mystical thinking as our ancestors wanted to know the causes of events that affected their lives.

  8. First-in-human study of PET and optical dual-modality image-guided surgery in glioblastoma using 68Ga-IRDye800CW-BBN.

    Science.gov (United States)

    Li, Deling; Zhang, Jingjing; Chi, Chongwei; Xiao, Xiong; Wang, Junmei; Lang, Lixin; Ali, Iqbal; Niu, Gang; Zhang, Liwei; Tian, Jie; Ji, Nan; Zhu, Zhaohui; Chen, Xiaoyuan

    2018-01-01

    Purpose : Despite the use of fluorescence-guided surgery (FGS), maximum safe resection of glioblastoma multiforme (GBM) remains a major challenge. It has restricted surgeons between preoperative diagnosis and intraoperative treatment. Currently, an integrated approach combining preoperative assessment with intraoperative guidance would be a significant step in this direction. Experimental design : We developed a novel 68 Ga-IRDye800CW-BBN PET/near-infrared fluorescence (NIRF) dual-modality imaging probe targeting gastrin-releasing peptide receptor (GRPR) in GBM. The preclinical in vivo tumor imaging and FGS were first evaluated using an orthotopic U87MG glioma xenograft model. Subsequently, the first-in-human prospective cohort study (NCT 02910804) of GBM patients were conducted with preoperative PET assessment and intraoperative FGS. Results : The orthotopic tumors in mice could be precisely resected using the near-infrared intraoperative system. Translational cohort research in 14 GBM patients demonstrated an excellent correlation between preoperative positive PET uptake and intraoperative NIRF signal. The tumor fluorescence signals were significantly higher than those from adjacent brain tissue in vivo and ex vivo (p dual-modality imaging technique is feasible for integrated pre- and intraoperative targeted imaging via the same molecular receptor and improved intraoperative GBM visualization and maximum safe resection.

  9. Quantum Graphical Models and Belief Propagation

    International Nuclear Information System (INIS)

    Leifer, M.S.; Poulin, D.

    2008-01-01

    Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences amongst large numbers of random variables. This paper presents a generalization of these concepts and methods to the quantum case, based on the idea that quantum theory can be thought of as a noncommutative, operator-valued, generalization of classical probability theory. Some novel characterizations of quantum conditional independence are derived, and definitions of Quantum n-Bifactor Networks, Markov Networks, Factor Graphs and Bayesian Networks are proposed. The structure of Quantum Markov Networks is investigated and some partial characterization results are obtained, along the lines of the Hammersley-Clifford theorem. A Quantum Belief Propagation algorithm is presented and is shown to converge on 1-Bifactor Networks and Markov Networks when the underlying graph is a tree. The use of Quantum Belief Propagation as a heuristic algorithm in cases where it is not known to converge is discussed. Applications to decoding quantum error correcting codes and to the simulation of many-body quantum systems are described

  10. Intention and Normative Belief

    OpenAIRE

    Chislenko, Eugene

    2016-01-01

    I defend the view that we act “under the guise of the good.” More specifically, I argue that an intention to do something is a belief that one ought to do it. I show how conflicts in intention and belief, as well as more complex impairments in these states, account for the central problem cases: akrasia in belief and intention, apparently unintelligible choices, and lack of motivation or accidie.

  11. Conditional Belief Types

    Science.gov (United States)

    2016-04-19

    Rationality of a player is determined by comparing her actual expected payoff to her expected payoff when her strategy is changed , while her beliefs —and...reduced strategies, and it is possible that under such conditions, beliefs about other players’ reduced strategies change as well. Thus, independence...assumptions, whether they concern observability of moves or subjective beliefs of any other kind, can be all accommodated by changing the informational

  12. Connecting to young adults: an online social network survey of beliefs and attitudes associated with prescription opioid misuse among college students.

    Science.gov (United States)

    Lord, Sarah; Brevard, Julie; Budman, Simon

    2011-01-01

    A survey of motives and attitudes associated with patterns of nonmedical prescription opioid medication use among college students was conducted on Facebook, a popular online social networking Web site. Response metrics for a 2-week random advertisement post, targeting students who had misused prescription medications, surpassed typical benchmarks for online marketing campaigns and yielded 527 valid surveys. Respondent characteristics, substance use patterns, and use motives were consistent with other surveys of prescription opioid use among college populations. Results support the potential of online social networks to serve as powerful vehicles to connect with college-aged populations about their drug use. Limitations of the study are noted.

  13. Synthesis and biological evaluation of copper-64 radiolabeled [DUPA-6-Ahx-(NODAGA)-5-Ava-BBN(7-14)NH2], a novel bivalent targeting vector having affinity for two distinct biomarkers (GRPr/PSMA) of prostate cancer

    International Nuclear Information System (INIS)

    Bandari, Rajendra Prasad; Jiang, Zongrun; Reynolds, Tamila Stott; Bernskoetter, Nicole E.; Szczodroski, Ashley F.; Bassuner, Kurt J.; Kirkpatrick, Daniel L.; Rold, Tammy L.; Sieckman, Gary L.; Hoffman, Timothy J.; Connors, James P.; Smith, Charles J.

    2014-01-01

    Gastrin-releasing peptide receptors (GRPr) and prostate-specific membrane antigen (PSMA) are two identifying biomarkers expressed in very high numbers on prostate cancer cells and could serve as a useful tool for molecular targeting and diagnosis of disease via positron-emission tomography (PET). The aim of this study was to produce the multipurpose, bivalent [DUPA-6-Ahx-( 64 Cu-NODAGA)-5-Ava-BBN(7-14)NH 2 ] radioligand for prostate cancer imaging, where DUPA = (2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid), a small-molecule, PSMA-targeting probe, 6Ahx = 6-aminohexanoic acid, 5-Ava = 5-aminovaleric acid, NODAGA = [2-(4,7-biscarboxymethyl)-1,4,7-(triazonan-1-yl)pentanedioic acid] (a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)), and BBN(7-14)NH 2 = bombesin, a GRPr-specific peptide targeting probe. Methods: The PSMA/GRPr dual targeting ligand precursor [DUPA-6-Ahx-K-5-Ava-BBN(7-14)NH 2 ], was synthesized by solid-phase and manual peptide synthesis, after which NODAGA was added via manual conjugation to the ε-amine of lysine (K). The new bivalent GRPr/PSMA targeting vector was purified by reversed-phase high performance liquid chromatography (RP-HPLC), characterized by electrospray-ionization mass spectrometry (ESI-MS), and metallated with 64 CuCl 2 and nat CuCl 2 . The receptor binding affinity was evaluated in human, prostate, PC-3 (GRPr-positive) and LNCaP (PSMA-positive) cells and the tumor-targeting efficacy determined in severe combined immunodeficient (SCID) and athymic nude mice bearing PC-3 and LNCaP tumors. Whole-body maximum intensity microPET/CT images of PC-3/LNCaP tumor-bearing mice were obtained 18 h post-injection (p.i.). Results: Competitive binding assays in PC-3 and LNCaP cells indicated high receptor binding affinity for the [DUPA-6-Ahx-( nat Cu-NODAGA)-5-Ava-BBN(7-14)NH 2 ] conjugate. MicroPET scintigraphy in PC-3/LNCaP tumor-bearing mice indicated that xenografted tumors were visible at 18 h p.i. with collateral

  14. Synthesis and biological evaluation of copper-64 radiolabeled [DUPA-6-Ahx-(NODAGA)-5-Ava-BBN(7-14)NH2], a novel bivalent targeting vector having affinity for two distinct biomarkers (GRPr/PSMA) of prostate cancer.

    Science.gov (United States)

    Bandari, Rajendra Prasad; Jiang, Zongrun; Reynolds, Tamila Stott; Bernskoetter, Nicole E; Szczodroski, Ashley F; Bassuner, Kurt J; Kirkpatrick, Daniel L; Rold, Tammy L; Sieckman, Gary L; Hoffman, Timothy J; Connors, James P; Smith, Charles J

    2014-04-01

    Gastrin-releasing peptide receptors (GRPr) and prostate-specific membrane antigen (PSMA) are two identifying biomarkers expressed in very high numbers on prostate cancer cells and could serve as a useful tool for molecular targeting and diagnosis of disease via positron-emission tomography (PET). The aim of this study was to produce the multipurpose, bivalent [DUPA-6-Ahx-((64)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] radioligand for prostate cancer imaging, where DUPA = (2-[3-(1,3-dicarboxypropyl)-ureido]pentanedioic acid), a small-molecule, PSMA-targeting probe, 6Ahx = 6-aminohexanoic acid, 5-Ava = 5-aminovaleric acid, NODAGA = [2-(4,7-biscarboxymethyl)-1,4,7-(triazonan-1-yl)pentanedioic acid] (a derivative of NOTA (1,4,7-triazacyclononane-1,4,7-triacetic acid)), and BBN(7-14)NH2 = bombesin, a GRPr-specific peptide targeting probe. The PSMA/GRPr dual targeting ligand precursor [DUPA-6-Ahx-K-5-Ava-BBN(7-14)NH2], was synthesized by solid-phase and manual peptide synthesis, after which NODAGA was added via manual conjugation to the ε-amine of lysine (K). The new bivalent GRPr/PSMA targeting vector was purified by reversed-phase high performance liquid chromatography (RP-HPLC), characterized by electrospray-ionization mass spectrometry (ESI-MS), and metallated with (64)CuCl2 and (nat)CuCl2. The receptor binding affinity was evaluated in human, prostate, PC-3 (GRPr-positive) and LNCaP (PSMA-positive) cells and the tumor-targeting efficacy determined in severe combined immunodeficient (SCID) and athymic nude mice bearing PC-3 and LNCaP tumors. Whole-body maximum intensity microPET/CT images of PC-3/LNCaP tumor-bearing mice were obtained 18 h post-injection (p.i.). Competitive binding assays in PC-3 and LNCaP cells indicated high receptor binding affinity for the [DUPA-6-Ahx-((nat)Cu-NODAGA)-5-Ava-BBN(7-14)NH2] conjugate. MicroPET scintigraphy in PC-3/LNCaP tumor-bearing mice indicated that xenografted tumors were visible at 18h p.i. with collateral, background radiation also

  15. Constructivism, Factoring, and Beliefs.

    Science.gov (United States)

    Rauff, James V.

    1994-01-01

    Discusses errors made by remedial intermediate algebra students in factoring polynomials in light of student definitions of factoring. Found certain beliefs about factoring to logically imply many of the errors made. Suggests that belief-based teaching can be successful in teaching factoring. (16 references) (Author/MKR)

  16. Scandinavian belief in fate

    Directory of Open Access Journals (Sweden)

    Åke Ström

    1967-02-01

    Full Text Available In point of principle, Christianity does not give room for any belief in fate. Astrology, horoscopes, divination, etc., are strictly rejected. Belief in fate never disappeared in Christian countries, nor did it in Scandinavia in Christian times. Especially in folklore we can find it at any period: People believed in an implacable fate. All folklore is filled up with this belief in destiny. Nobody can escape his fate. The future lies in the hands of fate, and the time to come takes its form according to inscrutable laws. The pre-Christian period in Scandinavia, dominated by pagan Norse religion, and the secularized epoch of the 20th century, however, show more distinctive and more widespread beliefs in fate than does the Christian period. The present paper makes a comparison between these forms of belief.

  17. The BBN Knowledge Acquisition Project

    Science.gov (United States)

    1988-09-01

    bmawt’s most ban for it w be comdmed a member of toe darn definted by dta concept. A slot consists of ’@A WMa dm@@Wg as W O*Jin do aw sudL 61 a role ne, a...When staking a new concept. KR&IE will prompt for t name of the new concept sod then a pop-up form will app an dt looks shdo Descriti !n Heme you may

  18. Belief Change in Reasoning Agents

    OpenAIRE

    Jin, Yi

    2007-01-01

    The capability of changing beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. Belief change therefore is one of the central research fields in Artificial Intelligence (AI) for over two decades. In the AI literature, two different kinds of belief change operations have been intensively investigated: belief update, which deal with situations where the new information describes changes of the world; and belief revision, which assumes the world is st...

  19. Belief, hope and faith.

    Science.gov (United States)

    Figueiredo, Luis Claudio

    2004-12-01

    A case of hysteria is presented in order to create a frame of reference for the author's approach to the concepts of hope, belief and faith. A difference between hope as a 'sad passion' (which is here called regressive hope) and hope as a principle of mental functioning is established. The concept of hope will at first always be based on beliefs--either beliefs organised in the paranoid-schizoid position (called here fragmented and delusional beliefs)--or those organised from the depressive position (complex systems of beliefs, which end up being dogmatic); the latter typically occur in neurotics. It is suggested here that there is another possibility for hope, which is based on faith. The meaning of faith is considered here externally to the religious sense. The solid establishment of hope as a principle--based on faith--can be viewed as responsible for the opening up of creative potentials and as one of the main aims of analysis. Such an aim, however requires the establishment of a deep relationship, both in theory and in clinical practice, between the Kleinian question of the depressive position and the Freudian question of the Oedipus complex.

  20. The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track

    OpenAIRE

    Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

    2016-01-01

    Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboa...

  1. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  2. Islamic Beliefs and Practices.

    Science.gov (United States)

    Sefein, Naim A.

    1981-01-01

    To help social studies classroom teachers present a realistic picture of the Middle Eastern religion of Islam, this article presents an overview of major beliefs and religious practices of Moslems. Information is presented on religious fundamentals, Islam's relationship to Judaism and Christianity, the development of Islam, the role of women, and…

  3. Teacher Beliefs and Technology Integration

    Science.gov (United States)

    Kim, ChanMin; Kim, Min Kyu; Lee, Chiajung; Spector, J. Michael; DeMeester, Karen

    2013-01-01

    The purpose of this exploratory mixed methods study was to investigate how teacher beliefs were related to technology integration practices. We were interested in how and to what extent teachers' (a) beliefs about the nature of knowledge and learning, (b) beliefs about effective ways of teaching, and (c) technology integration practices were…

  4. Underestimating belief in climate change

    Science.gov (United States)

    Jost, John T.

    2018-03-01

    People are influenced by second-order beliefsbeliefs about the beliefs of others. New research finds that citizens in the US and China systematically underestimate popular support for taking action to curb climate change. Fortunately, they seem willing and able to correct their misperceptions.

  5. Collective Dynamics of Belief Evolution under Cognitive Coherence and Social Conformity.

    Science.gov (United States)

    Rodriguez, Nathaniel; Bollen, Johan; Ahn, Yong-Yeol

    2016-01-01

    Human history has been marked by social instability and conflict, often driven by the irreconcilability of opposing sets of beliefs, ideologies, and religious dogmas. The dynamics of belief systems has been studied mainly from two distinct perspectives, namely how cognitive biases lead to individual belief rigidity and how social influence leads to social conformity. Here we propose a unifying framework that connects cognitive and social forces together in order to study the dynamics of societal belief evolution. Each individual is endowed with a network of interacting beliefs that evolves through interaction with other individuals in a social network. The adoption of beliefs is affected by both internal coherence and social conformity. Our framework may offer explanations for how social transitions can arise in otherwise homogeneous populations, how small numbers of zealots with highly coherent beliefs can overturn societal consensus, and how belief rigidity protects fringe groups and cults against invasion from mainstream beliefs, allowing them to persist and even thrive in larger societies. Our results suggest that strong consensus may be insufficient to guarantee social stability, that the cognitive coherence of belief-systems is vital in determining their ability to spread, and that coherent belief-systems may pose a serious problem for resolving social polarization, due to their ability to prevent consensus even under high levels of social exposure. We argue that the inclusion of cognitive factors into a social model could provide a more complete picture of collective human dynamics.

  6. Implicit false-belief processing in the human brain.

    Science.gov (United States)

    Schneider, Dana; Slaughter, Virginia P; Becker, Stefanie I; Dux, Paul E

    2014-11-01

    Eye-movement patterns in 'Sally-Anne' tasks reflect humans' ability to implicitly process the mental states of others, particularly false-beliefs - a key theory of mind (ToM) operation. It has recently been proposed that an efficient ToM system, which operates in the absence of awareness (implicit ToM, iToM), subserves the analysis of belief-like states. This contrasts to consciously available belief processing, performed by the explicit ToM system (eToM). The frontal, temporal and parietal cortices are engaged when humans explicitly 'mentalize' about others' beliefs. However, the neural underpinnings of implicit false-belief processing and the extent to which they draw on networks involved in explicit general-belief processing are unknown. Here, participants watched 'Sally-Anne' movies while fMRI and eye-tracking measures were acquired simultaneously. Participants displayed eye-movements consistent with implicit false-belief processing. After independently localizing the brain areas involved in explicit general-belief processing, only the left anterior superior temporal sulcus and precuneus revealed greater blood-oxygen-level-dependent activity for false- relative to true-belief trials in our iToM paradigm. No such difference was found for the right temporal-parietal junction despite significant activity in this area. These findings fractionate brain regions that are associated with explicit general ToM reasoning and false-belief processing in the absence of awareness. Copyright © 2014 Elsevier Inc. All rights reserved.

  7. Information and Heterogeneous Beliefs

    DEFF Research Database (Denmark)

    Christensen, Peter Ove; Qin, Zhenjiang

    2014-01-01

    In an incomplete market with heterogeneous prior beliefs, we show public information can have a substantial impact on the ex ante cost of capital, trading volume, and investor welfare. The Pareto effcient public information system is the system enjoying the maximum ex ante cost of capital...... and the maximum expected abnormal trading volume. Imperfect public information increases the gains-to-trade based on heterogeneously updated posterior beliefs. In an exchange economy, this leads to higher growth in the investors' certainty equivalents and, thus, a higher equilibrium interest rate, whereas the ex...... ante risk premium is unaffected by the informativeness of the public information system. Similar results are obtained in a production economy, but the impact on the ex ante cost of capital is dampened compared to the exchange economy due to welfare improving reductions in real investments to smooth...

  8. Mixmaster: fact and belief

    International Nuclear Information System (INIS)

    Heinzle, J Mark; Uggla, Claes

    2009-01-01

    We consider the dynamics towards the initial singularity of Bianchi type IX vacuum and orthogonal perfect fluid models with a linear equation of state. Surprisingly few facts are known about the 'Mixmaster' dynamics of these models, while at the same time most of the commonly held beliefs are rather vague. In this paper, we use Mixmaster facts as a base to build an infrastructure that makes it possible to sharpen the main Mixmaster beliefs. We formulate explicit conjectures concerning (i) the past asymptotic states of type IX solutions and (ii) the relevance of the Mixmaster/Kasner map for generic past asymptotic dynamics. The evidence for the conjectures is based on a study of the stochastic properties of this map in conjunction with dynamical systems techniques. We use a dynamical systems formulation, since this approach has so far been the only successful path to obtain theorems, but we also make comparisons with the 'metric' and Hamiltonian 'billiard' approaches.

  9. [French validation of the Revised Paranormal Belief Scale].

    Science.gov (United States)

    Bouvet, R; Djeriouat, H; Goutaudier, N; Py, J; Chabrol, H

    2014-09-01

    For the last decades, many researchers have focused on paranormal beliefs. Beliefs in the existence of paranormal phenomena would be common and studies conducted in westernized countries have highlighted a high prevalence of individuals believing in the existence of such phenomena. Tobacyk and Milford (1984) developed the Revised Paranormal Belief Scale (RPBS) for assessing beliefs in paranormal phenomena. This 26-item self-reported questionnaire, measuring beliefs in phenomena such as witchcraft or superstition, is one of the most widely used questionnaires to assess such beliefs. While studies focusing on paranormal beliefs tend to develop, there is no French self-report instrument to assess this construct. Researchers have tried to identify specific variables that might be linked to such beliefs, and some have focused on personalities of individuals who believe in the paranormal. Schizotypy has been reported to be significantly and positively correlated with paranormal beliefs. The aim of this study was a) to validate the French version of the RPBS and b) to explore the relationship between Schizotypal Personality Disorder traits and paranormal beliefs. After being recruited using the Internet and social networks (e.g. facebook), a sample of 313 participants (mean [SD] age=31.12 [11.62]; range 18-58years) completed the Schizotypal Personality Questionnaire (SPQ-B), assessing Schizotypal Personality Disorder traits and the Revised Paranormal Belief Scale assessing paranormal beliefs. Confirmatory factor analysis (CFA) was conducted to test the proposed 7-factor structure of the RPB developed by Tobacyk. Several adjustment indices were used to evaluate the model. As the first model did not fit the original one, others models were tested. Our findings indicated that a seven-factor solution, excluding 2 items, best described the item structure: (1) spiritualism, (2) superstition, (3) witchcraft, (4) precognition, (5) traditional religious belief, (6) psi, (7) and

  10. Ontological confusions but not mentalizing abilities predict religious belief, paranormal belief, and belief in supernatural purpose.

    Science.gov (United States)

    Lindeman, Marjaana; Svedholm-Häkkinen, Annika M; Lipsanen, Jari

    2015-01-01

    The current research tested the hypothesis that the abilities for understanding other people's minds give rise to the cognitive biases that underlie supernatural beliefs. We used structural equation modeling (N=2789) to determine the roles of various mentalizing tendencies, namely self-reported affective and cognitive empathy (i.e., mind reading), actual cognitive and affective empathic abilities, hyper-empathizing, and two cognitive biases (core ontological confusions and promiscuous teleology) in giving rise to supernatural beliefs. Support for a path from mentalizing abilities through cognitive biases to supernatural beliefs was weak. The relationships of mentalizing abilities with supernatural beliefs were also weak, and these relationships were not substantially mediated by cognitive biases. Core ontological confusions emerged as the best predictor, while promiscuous teleology predicted only a small proportion of variance. The results were similar for religious beliefs, paranormal beliefs, and for belief in supernatural purpose. Copyright © 2014 Elsevier B.V. All rights reserved.

  11. The neural basis of testable and non-testable beliefs.

    Directory of Open Access Journals (Sweden)

    Jonathon R Howlett

    Full Text Available Beliefs about the state of the world are an important influence on both normal behavior and psychopathology. However, understanding of the neural basis of belief processing remains incomplete, and several aspects of belief processing have only recently been explored. Specifically, different types of beliefs may involve fundamentally different inferential processes and thus recruit distinct brain regions. Additionally, neural processing of truth and falsity may differ from processing of certainty and uncertainty. The purpose of this study was to investigate the neural underpinnings of assessment of testable and non-testable propositions in terms of truth or falsity and the level of certainty in a belief. Functional magnetic resonance imaging (fMRI was used to study 14 adults while they rated propositions as true or false and also rated the level of certainty in their judgments. Each proposition was classified as testable or non-testable. Testable propositions activated the DLPFC and posterior cingulate cortex, while non-testable statements activated areas including inferior frontal gyrus, superior temporal gyrus, and an anterior region of the superior frontal gyrus. No areas were more active when a proposition was accepted, while the dorsal anterior cingulate was activated when a proposition was rejected. Regardless of whether a proposition was testable or not, certainty that the proposition was true or false activated a common network of regions including the medial prefrontal cortex, caudate, posterior cingulate, and a region of middle temporal gyrus near the temporo-parietal junction. Certainty in the truth or falsity of a non-testable proposition (a strong belief without empirical evidence activated the insula. The results suggest that different brain regions contribute to the assessment of propositions based on the type of content, while a common network may mediate the influence of beliefs on motivation and behavior based on the level of

  12. Promoting Enjoyment in Girls' Physical Education: The Impact of Goals, Beliefs, and Self-Determination

    Science.gov (United States)

    Wang, C. K. John; Liu, W. C.

    2007-01-01

    This study examined the network of relationships between sport ability beliefs, achievement goals, self-determination and female students' enjoyment in school physical education (PE). Female secondary students (n = 343) from a single-sex secondary school in Singapore participated in the survey. They were assessed on sport ability beliefs, goal…

  13. Economic Beliefs and Party Preference

    OpenAIRE

    Michael W.M. Roos; Andreas Orland

    2014-01-01

    This paper reports the results of a questionnaire study used to explore the economic understanding, normative positions along the egalitarian-libertarian spectrum, and the party preferences of a large student sample. The aim of the study is both to find socio-economic determinants of normative and positive beliefs and to explore how beliefs about the economy influence party support. We find that positive beliefs of lay people differ systematically from those of economic experts. Positive beli...

  14. Homo economicus belief inhibits trust.

    Directory of Open Access Journals (Sweden)

    Ziqiang Xin

    Full Text Available As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners' benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals' homo economicus belief and inhibit their trust. It seems that people's increasing homo economicus belief may serve as one cause of the worldwide decline of trust.

  15. Homo Economicus Belief Inhibits Trust

    Science.gov (United States)

    Xin, Ziqiang; Liu, Guofang

    2013-01-01

    As a foundational concept in economics, the homo economicus assumption regards humans as rational and self-interested actors. In contrast, trust requires individuals to believe partners’ benevolence and unselfishness. Thus, the homo economicus belief may inhibit trust. The present three experiments demonstrated that the direct exposure to homo economicus belief can weaken trust. And economic situations like profit calculation can also activate individuals’ homo economicus belief and inhibit their trust. It seems that people’s increasing homo economicus belief may serve as one cause of the worldwide decline of trust. PMID:24146907

  16. Generalized belief propagation on tree robust structured region graphs

    NARCIS (Netherlands)

    Gelfand, A.E.; Welling, M.; Murphy, K.; de Freitas, N.

    2012-01-01

    This paper provides some new guidance in the construction of region graphs for Generalized Belief Propagation (GBP). We connect the problem of choosing the outer regions of a LoopStructured Region Graph (SRG) to that of finding a fundamental cycle basis of the corresponding Markov network. We also

  17. Belief update as social choice

    NARCIS (Netherlands)

    van Benthem, J.; Girard, P.; Roy, O.; Marion, M.

    2011-01-01

    Dynamic epistemic-doxastic logics describe the new knowledge or new beliefs indexBelief of agents after some informational event has happened. Technically, this requires an update rule that turns a doxastic-epistemic modelM(recording the current information state of the agents) and a dynamic ‘event

  18. Free will and paranormal beliefs.

    Science.gov (United States)

    Mogi, Ken

    2014-01-01

    Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions) constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi). Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders) were conducted, which revealed significant positive correlations between belief in free will (theory and practice) and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker) difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs.

  19. Assessment of Religious Beliefs Form.

    Science.gov (United States)

    Faiver, Christopher M.; O'Brien, Eugene M.

    1993-01-01

    Notes that religion may be source of spiritual strength or source of conflict and guilt. Outlines importance of assessing religious beliefs of clients for treatment purposes and provides format for counselor to use. Says that, because counselors may be unaware of clients' individual perspectives, it is important to evaluate client's belief system…

  20. Playing with knowledge and belief

    NARCIS (Netherlands)

    Fiutek, V.

    2013-01-01

    This thesis contributes to the development of Soft Dynamic Epistemic Logic (Soft DEL). Soft DEL has been introduced to deal with a number of informational phenomena, including belief revision. The work in this thesis extends the scope of Soft DEL to belief contraction, providing as such a framework

  1. Free will and paranormal beliefs

    Science.gov (United States)

    Mogi, Ken

    2014-01-01

    Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions) constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi). Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders) were conducted, which revealed significant positive correlations between belief in free will (theory and practice) and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker) difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs. PMID:24765084

  2. Comparing strengths of beliefs explicitly

    NARCIS (Netherlands)

    Ghosh, S.; de Jongh, D.

    2013-01-01

    Inspired by a similar use in provability logic, formulas p > B q and p ≥ B q are introduced in the existing logical framework for discussing beliefs to express that the strength of belief in p is greater than (or equal to) that in q. Besides its usefulness in studying the properties of the concept

  3. Free will and paranormal beliefs

    Directory of Open Access Journals (Sweden)

    Ken eMogi

    2014-04-01

    Full Text Available Free will is one of the fundamental aspects of human cognition. In the context of cognitive neuroscience, various experiments on time perception, sensorimotor coordination, and agency suggest the possibility that it is a robust illusion (a feeling independent of actual causal relationship with actions constructed by neural mechanisms. Humans are known to suffer from various cognitive biases and failures, and the sense of free will might be one of them. Here I report a positive correlation between the belief in free will and paranormal beliefs (UFO, reincarnation, astrology, and psi. Web questionnaires involving 2076 subjects (978 males, 1087 females, and 11 other genders were conducted, which revealed significant positive correlations between belief in free will (theory and practice and paranormal beliefs. There was no significant correlation between belief in free will and knowledge in paranormal phenomena. Paranormal belief scores for females were significantly higher than those for males, with corresponding significant (albeit weaker difference in belief in free will. These results are consistent with the view that free will is an illusion which shares common cognitive elements with paranormal beliefs.

  4. Equilibria in social belief removal

    CSIR Research Space (South Africa)

    Booth, R

    2008-09-01

    Full Text Available In studies of multi-agent interaction, especially in game theory, the notion of equilibrium often plays a prominent role. A typical scenario for the belief merging problem is one in which several agents pool their beliefs together to form a...

  5. Politics of climate change belief

    Science.gov (United States)

    2017-01-01

    Donald Trump's actions during the election and his first weeks as US president-elect send a strong message about his belief in climate change, or lack thereof. However, these actions may reflect polarization of climate change beliefs, not climate mitigation behaviour.

  6. LIGO: The strong belief

    CERN Multimedia

    Antonella Del Rosso

    2016-01-01

    Twenty years of designing, building and testing a number of innovative technologies, with the strong belief that the endeavour would lead to a historic breakthrough. The Bulletin publishes an abstract of the Courier’s interview with Barry Barish, one of the founding fathers of LIGO.   The plots show the signals of gravitational waves detected by the twin LIGO observatories at Livingston, Louisiana, and Hanford, Washington. (Image: Caltech/MIT/LIGO Lab) On 11 February, the Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo collaborations published a historic paper in which they showed a gravitational signal emitted by the merger of two black holes. These results come after 20 years of hard work by a large collaboration of scientists operating the two LIGO observatories in the US. Barry Barish, Linde Professor of Physics, Emeritus at the California Institute of Technology and former Director of the Global Design Effort for the Internat...

  7. Against Motivational Efficacy of Beliefs

    Directory of Open Access Journals (Sweden)

    Seungbae Park

    2015-07-01

    Full Text Available Danielle Bromwich (2010 argues that a belief is motivationally efficacious in that, other things being equal, it disposes an agent to answer a question in accordance with that belief. I reply that what we are disposed to do is largely determined by our genes, whereas what we believe is largely determined by stimuli from the environment. We have a standing and default disposition to answer questions honestly, ceteris paribus, even before we are exposed to environmental stimuli. Since this standing and default disposition is innate, and our beliefs have their source in environmental stimuli, our beliefs cannot be the source of the disposition. Moreover, a recent finding in neuroscience suggests that motivation is extrinsic to belief.

  8. Sociospatial Knowledge Networks: Appraising Community as Place.

    Science.gov (United States)

    Skelly, Anne H.; Arcury, Thomas A.; Gesler, Wilbert M.; Cravey, Altha J.; Dougherty, Molly C.; Washburn, Sarah A.; Nash, Sally

    2002-01-01

    A new theory of geographical analysis--sociospatial knowledge networks--provides a framework for understanding the social and spatial locations of a community's health knowledge and beliefs. This theory is guiding an ethnographic study of health beliefs, knowledge, and knowledge networks in a diverse rural community at high risk for type-2…

  9. Cognitive biases explain religious belief, paranormal belief, and belief in life's purpose.

    Science.gov (United States)

    Willard, Aiyana K; Norenzayan, Ara

    2013-11-01

    Cognitive theories of religion have postulated several cognitive biases that predispose human minds towards religious belief. However, to date, these hypotheses have not been tested simultaneously and in relation to each other, using an individual difference approach. We used a path model to assess the extent to which several interacting cognitive tendencies, namely mentalizing, mind body dualism, teleological thinking, and anthropomorphism, as well as cultural exposure to religion, predict belief in God, paranormal beliefs and belief in life's purpose. Our model, based on two independent samples (N=492 and N=920) found that the previously known relationship between mentalizing and belief is mediated by individual differences in dualism, and to a lesser extent by teleological thinking. Anthropomorphism was unrelated to religious belief, but was related to paranormal belief. Cultural exposure to religion (mostly Christianity) was negatively related to anthropomorphism, and was unrelated to any of the other cognitive tendencies. These patterns were robust for both men and women, and across at least two ethnic identifications. The data were most consistent with a path model suggesting that mentalizing comes first, which leads to dualism and teleology, which in turn lead to religious, paranormal, and life's-purpose beliefs. Alternative theoretical models were tested but did not find empirical support. Copyright © 2013 Elsevier B.V. All rights reserved.

  10. Recursive belief manipulation and second-order false-beliefs

    DEFF Research Database (Denmark)

    Braüner, Torben; Blackburn, Patrick Rowan; Polyanskaya, Irina

    2016-01-01

    it indicate that a more fundamental *conceptual change* has taken place? In this paper we extend Braüner's hybrid-logical analysis of first-order false-belief tasks to the second-order case, and argue that our analysis supports a version of the conceptual change position.......The literature on first-order false-belief is extensive, but less is known about the second-order case. The ability to handle second-order false-beliefs correctly seems to mark a cognitively significant step, but what is its status? Is it an example of *complexity only* development, or does...

  11. Moral Beliefs and Cognitive Homogeneity

    Directory of Open Access Journals (Sweden)

    Nevia Dolcini

    2018-04-01

    Full Text Available The Emotional Perception Model of moral judgment intends to account for experientialism about morality and moral reasoning. In explaining how moral beliefs are formed and applied in practical reasoning, the model attempts to overcome the mismatch between reason and action/desire: morality isn’t about reason for actions, yet moral beliefs, if caused by desires, may play a motivational role in (moral agency. The account allows for two kinds of moral beliefs: genuine moral beliefs, which enjoy a relation to desire, and motivationally inert moral beliefs acquired in ways other than experience. Such etiology-based dichotomy of concepts, I will argue, leads to the undesirable view of cognition as a non-homogeneous phenomenon. Moreover, the distinction between moral beliefs and moral beliefs would entail a further dichotomy encompassing the domain of moral agency: one and the same action might possibly be either genuine moral, or not moral, if acted by individuals lacking the capacity for moral feelings, such as psychopaths.

  12. Belief attribution despite verbal interference.

    Science.gov (United States)

    Forgeot d'Arc, Baudouin; Ramus, Franck

    2011-05-01

    False-belief (FB) tasks have been widely used to study the ability of individuals to represent the content of their conspecifics' mental states (theory of mind). However, the cognitive processes involved are still poorly understood, and it remains particularly debated whether language and inner speech are necessary for the attribution of beliefs to other agents. We present a completely nonverbal paradigm consisting of silent animated cartoons in five closely related conditions, systematically teasing apart different aspects of scene analysis and allowing the assessment of the attribution of beliefs, goals, and physical causation. In order to test the role of language in belief attribution, we used verbal shadowing as a dual task to inhibit inner speech. Data on 58 healthy adults indicate that verbal interference decreases overall performance, but has no specific effect on belief attribution. Participants remained able to attribute beliefs despite heavy concurrent demands on their verbal abilities. Our results are most consistent with the hypothesis that belief attribution is independent from inner speech.

  13. Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become "Normalized".

    Science.gov (United States)

    Rahman, Tahir

    2018-01-12

    Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People's Temple, Heaven's Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.

  14. The Relationship among Pre-Service EFL Teachers' Beliefs about Language Learning, Pedagogical Beliefs, and Beliefs about ICT Integration

    Science.gov (United States)

    Inayati, Dian; Emaliana, Ive

    2017-01-01

    This paper elucidates the relationship among pre-service teachers' beliefs about language learning, pedagogical beliefs, and beliefs about ICT Integration through survey methodology. This study employed a quantitative approach, particularly a correlational relationship to investigate the relationships among beliefs about language learning,…

  15. Paranormal belief and attributional style.

    Science.gov (United States)

    Dudley, R T; Whisnand, E A

    2000-06-01

    52 college students completed Tobacyk's 1988 Revised Paranormal Belief Scale and Peterson, Semmel, von Baeyer, Abramson, Metalsky, and Seligman's 1982 Attributional Style Questionnaire. Analysis showed significantly higher depressive attributional styles among high scorers on paranormal phenomena than low scorers.

  16. Breast Health Belief Systems Study

    National Research Council Canada - National Science Library

    Williams, Mary

    1999-01-01

    .... The hypothesis underlying this research is that a breast health promotion approach that is based in specific belief systems among three disparate African American rural populations of low socioeconomic status (SES...

  17. Young Adolescents' Beliefs Concerning Menstruation

    Science.gov (United States)

    Clarke, Anne E.; Ruble, Diane N.

    1978-01-01

    A sample of 54 young adolescent girls (both pre- and postmenarcheal) and boys responded to a questionnaire assessing evaluative attitudes toward menstruation, expected symptomatology, perceived effects on moods and activities, and sources of information for these beliefs. (Author/JMB)

  18. Decision scenario analysis for addressing sediment accumulation in Lago Lucchetti, Puerto Rico

    Science.gov (United States)

    A Bayesian belief network (BBN) was used to characterize the effects of sediment accumulation on water storage capacity of a reservoir (Lago Lucchetti) in southwest Puerto Rico and the potential of different management options to increase reservoir life expectancy. Water and sedi...

  19. Children's beliefs about parental divorce

    OpenAIRE

    Dovydaitienė, Miglė

    2001-01-01

    This article investigates children's beliefs about parental divorce and attitudes toward environment and people. Children's believes about parental divorce is evaluated in a sample 8 through 10-year children whose parents had been separated for about 3 years. Attitudes toward environment and people between children of separated as well as intact families are compared. We also examined the relation of children's beliefs about parental divorce and attitudes toward environment and people. The me...

  20. A Mixed Methods Approach to Code Stakeholder Beliefs in Urban Water Governance

    Science.gov (United States)

    Bell, E. V.; Henry, A.; Pivo, G.

    2017-12-01

    What is a reliable way to code policies to represent belief systems? The Advocacy Coalition Framework posits that public policy may be viewed as manifestations of belief systems. Belief systems include both ontological beliefs about cause-and-effect relationships and policy effectiveness, as well as normative beliefs about appropriate policy instruments and the relative value of different outcomes. The idea that belief systems are embodied in public policy is important for urban water governance because it trains our focus on belief conflict; this can help us understand why many water-scarce cities do not adopt innovative technology despite available scientific information. To date, there has been very little research on systematic, rigorous methods to measure the belief system content of public policies. We address this by testing the relationship between beliefs and policy participation to develop an innovative coding framework. With a focus on urban water governance in Tucson, Arizona, we analyze grey literature on local water management. Mentioned policies are coded into a typology of common approaches identified in urban water governance literature, which include regulation, education, price and non-price incentives, green infrastructure and other types of technology. We then survey local water stakeholders about their perceptions of these policies. Urban water governance requires coordination of organizations from multiple sectors, and we cannot assume that belief development and policy participation occur in a vacuum. Thus, we use a generalized exponential random graph model to test the relationship between perceptions and policy participation in the Tucson water governance network. We measure policy perceptions for organizations by averaging across their respective, affiliated respondents and generating a belief distance matrix of coordinating network participants. Similarly, we generate a distance matrix of these actors based on the frequency of their

  1. Modeling the Evolution of Beliefs Using an Attentional Focus Mechanism.

    Directory of Open Access Journals (Sweden)

    Dimitrije Marković

    2015-10-01

    Full Text Available For making decisions in everyday life we often have first to infer the set of environmental features that are relevant for the current task. Here we investigated the computational mechanisms underlying the evolution of beliefs about the relevance of environmental features in a dynamical and noisy environment. For this purpose we designed a probabilistic Wisconsin card sorting task (WCST with belief solicitation, in which subjects were presented with stimuli composed of multiple visual features. At each moment in time a particular feature was relevant for obtaining reward, and participants had to infer which feature was relevant and report their beliefs accordingly. To test the hypothesis that attentional focus modulates the belief update process, we derived and fitted several probabilistic and non-probabilistic behavioral models, which either incorporate a dynamical model of attentional focus, in the form of a hierarchical winner-take-all neuronal network, or a diffusive model, without attention-like features. We used Bayesian model selection to identify the most likely generative model of subjects' behavior and found that attention-like features in the behavioral model are essential for explaining subjects' responses. Furthermore, we demonstrate a method for integrating both connectionist and Bayesian models of decision making within a single framework that allowed us to infer hidden belief processes of human subjects.

  2. Vehicle detection from very-high-resolution (VHR) aerial imagery using attribute belief propagation (ABP)

    Science.gov (United States)

    Wang, Yanli; Li, Ying; Zhang, Li; Huang, Yuchun

    2016-10-01

    With the popularity of very-high-resolution (VHR) aerial imagery, the shape, color, and context attribute of vehicles are better characterized. Due to the various road surroundings and imaging conditions, vehicle attributes could be adversely affected so that vehicle is mistakenly detected or missed. This paper is motivated to robustly extract the rich attribute feature for detecting the vehicles of VHR imagery under different scenarios. Based on the hierarchical component tree of vehicle context, attribute belief propagation (ABP) is proposed to detect salient vehicles from the statistical perspective. With the Max-tree data structure, the multi-level component tree around the road network is efficiently created. The spatial relationship between vehicle and its belonging context is established with the belief definition of vehicle attribute. To effectively correct single-level belief error, the inter-level belief linkages enforce consistency of belief assignment between corresponding components at different levels. ABP starts from an initial set of vehicle belief calculated by vehicle attribute, and then iterates through each component by applying inter-level belief passing until convergence. The optimal value of vehicle belief of each component is obtained via minimizing its belief function iteratively. The proposed algorithm is tested on a diverse set of VHR imagery acquired in the city and inter-city areas of the West and South China. Experimental results show that the proposed algorithm can detect vehicle efficiently and suppress the erroneous effectively. The proposed ABP framework is promising to robustly classify the vehicles from VHR Aerial imagery.

  3. Attitudes and beliefs as verbal behavior

    OpenAIRE

    Guerin, Bernard

    1994-01-01

    Attitudes and beliefs are analyzed as verbal behavior. It is argued that shaping by a verbal community is an essential part of the formation and maintenance of both attitudes and beliefs, and it is suggested that verbal communities mediate the important shift in control from events in the environment (attitudes and beliefs as tacts) to control by other words (attitudes and beliefs as intraverbals). It appears that both attitudes and beliefs are constantly being socially negotiated through aut...

  4. The BEL information extraction workflow (BELIEF): evaluation in the BioCreative V BEL and IAT track.

    Science.gov (United States)

    Madan, Sumit; Hodapp, Sven; Senger, Philipp; Ansari, Sam; Szostak, Justyna; Hoeng, Julia; Peitsch, Manuel; Fluck, Juliane

    2016-01-01

    Network-based approaches have become extremely important in systems biology to achieve a better understanding of biological mechanisms. For network representation, the Biological Expression Language (BEL) is well designed to collate findings from the scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a BEL Information Extraction Workflow (BELIEF) was developed. BELIEF provides a web-based curation interface, the BELIEF Dashboard, that incorporates text mining techniques to support the biocurator in the generation of BEL networks. The underlying UIMA-based text mining pipeline (BELIEF Pipeline) uses several named entity recognition processes and relationship extraction methods to detect concepts and BEL relationships in literature. The BELIEF Dashboard allows easy curation of the automatically generated BEL statements and their context annotations. Resulting BEL statements and their context annotations can be syntactically and semantically verified to ensure consistency in the BEL network. In summary, the workflow supports experts in different stages of systems biology network building. Based on the BioCreative V BEL track evaluation, we show that the BELIEF Pipeline automatically extracts relationships with an F-score of 36.4% and fully correct statements can be obtained with an F-score of 30.8%. Participation in the BioCreative V Interactive task (IAT) track with BELIEF revealed a systems usability scale (SUS) of 67. Considering the complexity of the task for new users-learning BEL, working with a completely new interface, and performing complex curation-a score so close to the overall SUS average highlights the usability of BELIEF.Database URL: BELIEF is available at http://www.scaiview.com/belief/. © The Author(s) 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Beliefs about chelation among thalassemia patients

    Directory of Open Access Journals (Sweden)

    Trachtenberg Felicia L

    2012-12-01

    Full Text Available Abstract Background Understanding patients’ views about medication is crucial to maximize adherence. Thalassemia is a congenital blood disorder requiring chronic blood transfusions and daily iron chelation therapy. Methods The Beliefs in Medicine Questionnaire (BMQ was used to assess beliefs in chelation in thalassemia patients from North America and London in the Thalassemia Longitudinal Cohort (TLC of the Thalassemia Clinical Research Network (TCRN. Chelation adherence was based on patient report of doses administered out of those prescribed in the last four weeks. Results Of 371 patients (ages 5-58y, mean 24y, 93% were transfused and 92% receiving chelation (26% deferoxamine (DFO; a slow subcutaneous infusion via portable pump, 63% oral, 11% combination. Patients expressed high “necessity” for transfusion (96%, DFO chelation (92% and oral chelation (89%, with lower “concern” about treatment (48%, 39%, 19% respectively. Concern about oral chelation was significantly lower than that of DFO (p Conclusions Despite their requirement for multimodal therapy, thalassemia patients have positive views about medicine, more so than in other disease populations. Patients may benefit from education about the tolerability of chelation and strategies to effectively cope with side effects, both of which might be beneficial in lowering body iron burden. Clinicaltrials.gov identifier NCT00661804

  6. Indoor Positioning Using Nonparametric Belief Propagation Based on Spanning Trees

    Directory of Open Access Journals (Sweden)

    Savic Vladimir

    2010-01-01

    Full Text Available Nonparametric belief propagation (NBP is one of the best-known methods for cooperative localization in sensor networks. It is capable of providing information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST created by breadth first search (BFS method. In addition, we propose a reliable indoor model based on obtained measurements in our lab. According to our simulation results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks. Furthermore, the computational and communication costs are nearly constant with respect to the transmission radius. However, the drawbacks of proposed method are a little bit higher computational cost and poor performance in low-connected networks.

  7. Scaling Irrational Beliefs in the General Attitude and Belief Scale

    Directory of Open Access Journals (Sweden)

    Lindsay R. Owings

    2013-04-01

    Full Text Available Accurate measurement of key constructs is essential to the continued development of Rational-Emotive Behavior Therapy (REBT. The General Attitude and Belief Scale (GABS, a contemporary inventory of rational and irrational beliefs based on current REBT theory, is one of the most valid and widely used instruments available, and recent research has continued to improve its psychometric standing. In this study of 544 students, item response theory (IRT methods were used (a to identify the most informative item in each irrational subscale of the GABS, (b to determine the level of irrationality represented by each of those items, and (c to suggest a condensed form of the GABS for further study with clinical populations. Administering only the most psychometrically informative items to clients could result in economies of time and effort. Further research based on the scaling of items could clarify the specific patterns of irrational beliefs associated with particular clinical syndromes.

  8. The ecology of religious beliefs

    Science.gov (United States)

    Botero, Carlos A.; Gardner, Beth; Kirby, Kathryn R.; Bulbulia, Joseph; Gavin, Michael C.; Gray, Russell D.

    2014-01-01

    Although ecological forces are known to shape the expression of sociality across a broad range of biological taxa, their role in shaping human behavior is currently disputed. Both comparative and experimental evidence indicate that beliefs in moralizing high gods promote cooperation among humans, a behavioral attribute known to correlate with environmental harshness in nonhuman animals. Here we combine fine-grained bioclimatic data with the latest statistical tools from ecology and the social sciences to evaluate the potential effects of environmental forces, language history, and culture on the global distribution of belief in moralizing high gods (n = 583 societies). After simultaneously accounting for potential nonindependence among societies because of shared ancestry and cultural diffusion, we find that these beliefs are more prevalent among societies that inhabit poorer environments and are more prone to ecological duress. In addition, we find that these beliefs are more likely in politically complex societies that recognize rights to movable property. Overall, our multimodel inference approach predicts the global distribution of beliefs in moralizing high gods with an accuracy of 91%, and estimates the relative importance of different potential mechanisms by which this spatial pattern may have arisen. The emerging picture is neither one of pure cultural transmission nor of simple ecological determinism, but rather a complex mixture of social, cultural, and environmental influences. Our methods and findings provide a blueprint for how the increasing wealth of ecological, linguistic, and historical data can be leveraged to understand the forces that have shaped the behavior of our own species. PMID:25385605

  9. Aggregation of Information and Beliefs

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    In a binary prediction market in which risk-neutral traders have heterogeneous prior beliefs and are allowed to invest a limited amount of money, the static rational expectations equilibrium price is demonstrated to underreact to information. This effect is consistent with a favorite-longshot bias......, and is more pronounced when prior beliefs are more heterogeneous. Relaxing the assumptions of risk neutrality and bounded budget, underreaction to information also holds in a more general asset market with heterogeneous priors, provided traders have decreasing absolute risk aversion. In a dynamic asset market...

  10. Teachers’ Beliefs and Their Belief Change in an Intercultural Context

    DEFF Research Database (Denmark)

    Wang, Li

    of teaching in a new context and in their early years of the teaching careers of CFL teachers in the Danish context. It has been shown that the multifaceted beliefs that CFL teachers hold are based on their personal experience, shaped by context, and mediated by their classroom practices. The educational...

  11. Peer Smoking and Smoking-related Beliefs Among College Students in Bangladesh

    Directory of Open Access Journals (Sweden)

    Akiko Kamimura

    2018-01-01

    Full Text Available Objectives Smoking is a significant public health issue in Bangladesh. The purpose of this study was to examine peer smoking and smoking-related beliefs among college students in Bangladesh. Methods College students at two universities in Dhaka, Bangladesh participated in a self-administered survey in May and June 2017. Results First, being a current or former smoker is associated with lower levels of beliefs among respondents that they would not smoke even with smoker friends or nervousness, and lower levels of intentions that they would not smoke, while current smokers and former smokers have different smoking-related beliefs. Second, having smoker friends is associated with lower levels of intentions that they would not smoke. Third, higher levels of normative beliefs that it is important not to smoke are associated with higher levels of beliefs that they would not smoke even with smoker friends or nervousness, higher levels of intentions that they would not smoke, and higher levels of avoidance of smoking. Conclusions Smoking-related beliefs and perceived norms in individuals’ social networks are important components in promoting tobacco cessation in Bangladesh. But it is challenging to prevent or intervene in smoking because of the high rates of smoking in this country and the high prevalence of smokers in individuals’ social networks. Future studies should examine the most effective interventions to combat smoking in high-smoking social networks, such as using mobile apps or social media, and evaluate the effectiveness of such interventions.

  12. Peer Smoking and Smoking-related Beliefs Among College Students in Bangladesh.

    Science.gov (United States)

    Kamimura, Akiko; Ahmmad, Zobayer; Pye, Mu; Gull, Bethany

    2018-01-01

    Smoking is a significant public health issue in Bangladesh. The purpose of this study was to examine peer smoking and smoking-related beliefs among college students in Bangladesh. College students at two universities in Dhaka, Bangladesh participated in a self-administered survey in May and June 2017. First, being a current or former smoker is associated with lower levels of beliefs among respondents that they would not smoke even with smoker friends or nervousness, and lower levels of intentions that they would not smoke, while current smokers and former smokers have different smoking-related beliefs. Second, having smoker friends is associated with lower levels of intentions that they would not smoke. Third, higher levels of normative beliefs that it is important not to smoke are associated with higher levels of beliefs that they would not smoke even with smoker friends or nervousness, higher levels of intentions that they would not smoke, and higher levels of avoidance of smoking. Smoking-related beliefs and perceived norms in individuals' social networks are important components in promoting tobacco cessation in Bangladesh. But it is challenging to prevent or intervene in smoking because of the high rates of smoking in this country and the high prevalence of smokers in individuals' social networks. Future studies should examine the most effective interventions to combat smoking in high-smoking social networks, such as using mobile apps or social media, and evaluate the effectiveness of such interventions.

  13. The Relationships among Chinese Practicing Teachers' Epistemic Beliefs, Pedagogical Beliefs and Their Beliefs about the Use of ICT

    Science.gov (United States)

    Deng, Feng; Chai, Ching Sing; Tsai, Chin-Chung; Lee, Min-Hsien

    2014-01-01

    This study aimed to investigate the relationships among practicing teachers' epistemic beliefs, pedagogical beliefs and their beliefs about the use of ICT through survey methodology. Participants were 396 high school practicing teachers from mainland China. The path analysis results analyzed via structural equation modelling technique indicated…

  14. Illness beliefs and the sociocultural context of diabetes self-management in British South Asians: a mixed methods study.

    Science.gov (United States)

    Patel, Neesha R; Chew-Graham, Carolyn; Bundy, Christine; Kennedy, Anne; Blickem, Christian; Reeves, David

    2015-05-10

    British South Asians have a higher incidence of diabetes and poorer health outcomes compared to the general UK population. Beliefs about diabetes are known to play an important role in self-management, yet little is known about the sociocultural context in shaping beliefs. This study aimed to explore the influence of sociocultural context on illness beliefs and diabetes self-management in British South Asians. A mixed methods approach was used. 67 participants recruited using random and purposive sampling, completed a questionnaire measuring illness beliefs, fatalism, health outcomes and demographics; 37 participants completed a social network survey interview and semi-structured interviews. Results were analysed using SPSS and thematic analysis. Quantitative data found certain social network characteristics (emotional and illness work) were related to perceived concern, emotional distress and health outcomes (p work remained a significant predictor of perceived concern and emotional distress related to diabetes (p culturally appropriate interventions to modify beliefs and support self-management in this population.

  15. Witchcraft Beliefs and Witch Hunts

    NARCIS (Netherlands)

    Koning, N.B.J.

    2013-01-01

    This paper proposes an interdisciplinary explanation of the cross-cultural similarities and evolutionary patterns of witchcraft beliefs. It argues that human social dilemmas have led to the evolution of a fear system that is sensitive to signs of deceit and envy. This was adapted in the evolutionary

  16. Heterogeneous Beliefs and Climate Catastrophes

    NARCIS (Netherlands)

    Kiseleva, T.

    2016-01-01

    We study how heterogeneous beliefs about the causes and extent of global warming affect local mitigation and adaptation strategies and therefore global climate dynamics. Local policies are determined by expectations of policy makers about future climate. There are three types of expectations: strong

  17. Resilience: It Begins with Beliefs

    Science.gov (United States)

    Truebridge, Sara

    2016-01-01

    Educators' beliefs are powerful, affecting not only their pedagogical practices, but also student efficacy and success. The academic achievement of any particular student may rely greatly on whether the teacher believes that student has the ability to succeed. This article affirms the imperative for administrators and educators to spend time…

  18. Astrology Beliefs among Undergraduate Students

    Science.gov (United States)

    Sugarman, Hannah; Impey, Chris; Buxner, Sanlyn; Antonellis, Jessie

    2011-01-01

    A survey of the science knowledge and attitudes toward science of nearly 10000 undergraduates at a large public university over a 20-year period included several questions addressing student beliefs in astrology and other forms of pseudoscience. The results from our data reveal that a large majority of students (78%) considered astrology "very" or…

  19. Negligent Rape and Reasonable Beliefs

    DEFF Research Database (Denmark)

    Hansen, Pelle Guldborg

    2008-01-01

    practice such defences are often acknowledged if the belief is reasonable by some general standard, even when this standard does not pertain to the rules currently governing the practice of intercourse in Denmark. As a result it has often been argued that the notion of negligent rape should be introduced...

  20. Machiavellian Beliefs and Social Influence.

    Science.gov (United States)

    O'Hair, Dan; Cody, Michael J.

    1987-01-01

    Replicates previous findings of separate Machiavellian belief constructs (Deceit, Flatter, Immorality, and Cynicism). Indicates that different constructs predict selection of compliance-gaining strategies; for example, actors who scored high on Immorality used more referent influence on superiors. Discusses implications of this study concerning a…

  1. Changing Conspiracy Beliefs through Rationality and Ridiculing.

    Science.gov (United States)

    Orosz, Gábor; Krekó, Péter; Paskuj, Benedek; Tóth-Király, István; Bőthe, Beáta; Roland-Lévy, Christine

    2016-01-01

    Conspiracy theory (CT) beliefs can be harmful. How is it possible to reduce them effectively? Three reduction strategies were tested in an online experiment using general and well-known CT beliefs on a comprehensive randomly assigned Hungarian sample ( N = 813): exposing rational counter CT arguments, ridiculing those who hold CT beliefs, and empathizing with the targets of CT beliefs. Several relevant individual differences were measured. Rational and ridiculing arguments were effective in reducing CT, whereas empathizing with the targets of CTs had no effect. Individual differences played no role in CT reduction, but the perceived intelligence and competence of the individual who conveyed the CT belief-reduction information contributed to the success of the CT belief reduction. Rational arguments targeting the link between the object of belief and its characteristics appear to be an effective tool in fighting conspiracy theory beliefs.

  2. Illness causal beliefs in Turkish immigrants

    Directory of Open Access Journals (Sweden)

    Klimidis Steven

    2007-07-01

    Full Text Available Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes

  3. Illness causal beliefs in Turkish immigrants.

    Science.gov (United States)

    Minas, Harry; Klimidis, Steven; Tuncer, Can

    2007-07-24

    People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different

  4. Order effects in research on paranormal belief.

    Science.gov (United States)

    Dudley, R Thomas

    2002-04-01

    Measures of paranormal belief and emotional intelligence were given a group of 72 college students using Tobacyk's Revised Paranormal Belief Scale and Schutte, Malouff, Hall, Haggerty, Cooper, Golden, and Dornheim's Emotional Intelligence Scale. Order effects indicated that participants who took the Paranormal Belief Scale first had lower emotional intelligence scores than those who took the Emotional Intelligence Scale first. The study demonstrates the importance of taking order effects into account when conducting research on paranormal belief.

  5. Folk beliefs of cultural changes in China

    OpenAIRE

    Xu, Yi; Hamamura, Takeshi

    2014-01-01

    For the last several decades, Chinese society has experienced transformative changes. How are these changes understood among Chinese people? To examine this question, Part 1 in this research solicited folk beliefs of cultural change from a group of Chinese participants in an open-ended format, and the generated folk beliefs were rated by another group of participants in Part 2 to gage each belief's level of agreement. Part 3 plotted the folk beliefs retained in Part 2 using the Google Ngram V...

  6. Changing Conspiracy Beliefs through Rationality and Ridiculing

    OpenAIRE

    Orosz, Gábor; Krekó, Péter; Paskuj, Benedek; Tóth-Király, István; Bőthe, Beáta; Roland-Lévy, Christine

    2016-01-01

    Conspiracy theory (CT) beliefs can be harmful. How is it possible to reduce them effectively? Three reduction strategies were tested in an online experiment using general and well-known CT beliefs on a comprehensive randomly assigned Hungarian sample (N = 813): exposing rational counter CT arguments, ridiculing those who hold CT beliefs, and empathizing with the targets of CT beliefs. Several relevant individual differences were measured. Rational and ridiculing arguments were effective in re...

  7. The moderating role of rational beliefs in the relationship between irrational beliefs and posttraumatic stress symptomology.

    Science.gov (United States)

    Hyland, Philip; Shevlin, Mark; Adamson, Gary; Boduszek, Daniel

    2014-05-01

    Rational Emotive Behaviour Therapy (REBT) assumes that rational beliefs act as cognitive protective factors against the development of psychopathology; however little empirical evidence exists regarding the nature of the possible protective effects that they offer. The current study investigates whether rational beliefs moderate the impact of irrational beliefs on posttraumatic stress symptomology (PTS). Three hundred and thirteen active law enforcement, military, and related emergency service personnel took part in the current study. Sequential moderated multiple regression analysis was employed to investigate: (i) the direct impact of irrational beliefs on PTS; (ii) the direct impact of rational beliefs on PTS; (iii) the moderating effects of rational beliefs in the relationship between irrational beliefs and PTS. The irrational beliefs predicted by REBT theory emerged as critical predictors of PTS symptomology, in particular Depreciation beliefs. Rational beliefs (Preferences, and Acceptance beliefs) had a direct, negative impact on levels of PTS, and Acceptance beliefs moderated the impact of Catastrophizing beliefs on PTS. Irrational beliefs are important cognitive vulnerability factors in symptoms of PTS, while rational beliefs (Acceptance) appear to have a protective role in the emergence of PTS symptoms, both directly and by moderating the impact of Catastrophizing beliefs.

  8. Korean Americans' Beliefs about Colorectal Cancer Screening

    Directory of Open Access Journals (Sweden)

    Shin-Young Lee, PhD, RN

    2013-06-01

    Conclusion: Results show the critical need for in-depth understanding of unique health and cultural beliefs about CRC screening in KAs. These beliefs could be useful for future intervention strategies to change health and cultural beliefs in order to increase CRC screening participation in KAs.

  9. Losing Belief, While Keeping Up the Attitudes

    DEFF Research Database (Denmark)

    Klausen, Søren Harnow

    2013-01-01

    While arguing that many cognitive states do indeed have a characteristic phenomenology, I find reasons for exempting beliefs from the program of cognitive phenomenology. Examining the complex relationship between beliefs and various kinds of conscious experience shows that belief is a messy conce...

  10. Well-Founded Belief and Perceptual Justification

    DEFF Research Database (Denmark)

    Broncano-Berrocal, Fernando

    2016-01-01

    According to Alan Millar, justified beliefs are well-founded beliefs. Millar cashes out the notion of well-foundedness in terms of having an adequate reason to believe something and believing it for that reason. To make his account of justified belief compatible with perceptual justification he...

  11. Forward induction reasoning and correct beliefs

    NARCIS (Netherlands)

    Perea y Monsuwé, Andrés

    2017-01-01

    All equilibrium concepts implicitly make a correct beliefs assumption, stating that a player believes that his opponents are correct about his first-order beliefs. In this paper we show that in many dynamic games of interest, this correct beliefs assumption may be incompatible with a very basic form

  12. Islamic Cultures: Health Care Beliefs and Practices.

    Science.gov (United States)

    Kemp, Charles

    1996-01-01

    Presents an overview of Islamic health care beliefs and practices, noting health-related social and spiritual issues, fundamental beliefs and themes in Islam, health care beliefs and practices common among Muslims, and health-affecting social roles among Muslims. Cultural, religious, and social barriers to health care and ways to reduce them are…

  13. Changing Preservice Teachers' Beliefs about Motivating Students

    Science.gov (United States)

    Peterson, Sarah; Schreiber, Jim; Moss, Connie

    2011-01-01

    We examined the effects of an educational psychology course on students' beliefs about motivating students. After providing opportunities to engage in systematic intentional inquiry of their beliefs about teaching and learning, we expected that students' beliefs would become more soundly based in theory and research. Following several classes on…

  14. Beliefs about work and beliefs about groupwork: Exploring the relationship

    OpenAIRE

    Cullen, John G.

    2013-01-01

    Smrt & Karau’s (2011) finding that the Protestant Work Ethic (PWE) influences individual behaviour towards groups, emphasized that individuals who have a stronger PWE are less likely to socially loaf. This note aims to contribute to this research by exploring the influence which a key component of the PWE, the vocation, has on individual beliefs about groupwork. An online questionnaire based on Wrzesniewski et al.’s (1997) research on personal relationships to work and Karau & Elsaid’s (200...

  15. Introducing the modified paranormal belief scale: distinguishing between classic paranormal beliefs, religious paranormal beliefs and conventional religiosity among undergraduates in Northern Ireland and Wales

    OpenAIRE

    Williams, Emyr; Francis, Leslie J.; Lewis, Christopher Alan

    2009-01-01

    Previous empirical studies concerned with the association between paranormal beliefs and conventional religiosity have produced conflicting evidence. Drawing on Rice's (2003) distinction between classic paranormal beliefs and religious paranormal beliefs, the present study proposed a modified form of the Tobacyk Revised Paranormal Belief Scale to produce separate scores for these two forms of paranormal belief, styled 'religious paranormal beliefs' and 'classic paranormal beliefs'. Data provi...

  16. Narcissism and belief in the paranormal.

    Science.gov (United States)

    Roe, Chris A; Morgan, Claire L

    2002-04-01

    The present study was designed to assess whether the relationship between narcissistic personality and paranormal belief identified by Tobacyk and Mitchell earlier could be replicated with a general population and to see whether the effect could be found with a narrower definition of paranormal beliefs that focuses only on belief in psychic phenomena. 75 participants completed the Narcissistic Personality Inventory and two measures of paranormal belief, the Paranormal Belief Scale and the Australian Sheep-Goat Scale. There was no correlation between narcissism and Paranormal Belief Scale scores, but narcissism and Australian Sheep-Goat Scale scores were significantly positively correlated. Of the three subscales to the Australian Sheep-Goat measure, scores for narcissism correlated with belief in ESP and PK but not in Life after death. These relationships were interpreted in terms of need for control.

  17. Belief in reciprocity in a Chinese sample.

    Science.gov (United States)

    Zhang, Zhen; Zhang, Jianxin

    2012-08-01

    Belief in reciprocity refers to a personally internalized faith in the reciprocity norm: that people will return positive and negative interactions or favors in kind. The current study aims to examine the relationship between belief in reciprocity and altruism among a Chinese sample. The Personal Norm of Reciprocity Scale, Trait Forgiveness Scale, Prosocial Tendency Measure, and Altruism Scale were used to assess extent of belief in reciprocity, forgiveness, and prosocial motivation, respectively, among 204 Chinese undergraduates. The results indicated that belief in reciprocity was a partially negative, but not neutral, reciprocity norm for Chinese people. Specifically, belief in reciprocity was positively related to negative reciprocity, but not significantly related to positive reciprocity. Moreover, belief in reciprocity was negatively related to both prosocial tendency and altruistic motivation. The results also indicated that forgiveness largely mediated the effect of belief in reciprocity on altruism. Finally, the implications and limitations of the current study were discussed.

  18. Can Cultural Worldviews Influence Network Composition?

    Science.gov (United States)

    Vaisey, Stephen; Lizardo, Omar

    2010-01-01

    Most sociological research assumes that social network composition shapes individual beliefs. Network theory and research has not adequately considered that internalized cultural worldviews might affect network composition. Drawing on a synthetic, dual-process theory of culture and two waves of nationally-representative panel data, this article…

  19. The neural correlates of religious and nonreligious belief.

    Directory of Open Access Journals (Sweden)

    Sam Harris

    2009-10-01

    Full Text Available While religious faith remains one of the most significant features of human life, little is known about its relationship to ordinary belief at the level of the brain. Nor is it known whether religious believers and nonbelievers differ in how they evaluate statements of fact. Our lab previously has used functional neuroimaging to study belief as a general mode of cognition [1], and others have looked specifically at religious belief [2]. However, no research has compared these two states of mind directly.We used functional magnetic resonance imaging (fMRI to measure signal changes in the brains of thirty subjects-fifteen committed Christians and fifteen nonbelievers-as they evaluated the truth and falsity of religious and nonreligious propositions. For both groups, and in both categories of stimuli, belief (judgments of "true" vs judgments of "false" was associated with greater signal in the ventromedial prefrontal cortex, an area important for self-representation [3], [4], [5], [6], emotional associations [7], reward [8], [9], [10], and goal-driven behavior [11]. This region showed greater signal whether subjects believed statements about God, the Virgin Birth, etc. or statements about ordinary facts. A comparison of both stimulus categories suggests that religious thinking is more associated with brain regions that govern emotion, self-representation, and cognitive conflict, while thinking about ordinary facts is more reliant upon memory retrieval networks.While religious and nonreligious thinking differentially engage broad regions of the frontal, parietal, and medial temporal lobes, the difference between belief and disbelief appears to be content-independent. Our study compares religious thinking with ordinary cognition and, as such, constitutes a step toward developing a neuropsychology of religion. However, these findings may also further our understanding of how the brain accepts statements of all kinds to be valid descriptions of the

  20. A Bayesian Framework for False Belief Reasoning in Children: A Rational Integration of Theory-Theory and Simulation Theory.

    Science.gov (United States)

    Asakura, Nobuhiko; Inui, Toshio

    2016-01-01

    Two apparently contrasting theories have been proposed to account for the development of children's theory of mind (ToM): theory-theory and simulation theory. We present a Bayesian framework that rationally integrates both theories for false belief reasoning. This framework exploits two internal models for predicting the belief states of others: one of self and one of others. These internal models are responsible for simulation-based and theory-based reasoning, respectively. The framework further takes into account empirical studies of a developmental ToM scale (e.g., Wellman and Liu, 2004): developmental progressions of various mental state understandings leading up to false belief understanding. By representing the internal models and their interactions as a causal Bayesian network, we formalize the model of children's false belief reasoning as probabilistic computations on the Bayesian network. This model probabilistically weighs and combines the two internal models and predicts children's false belief ability as a multiplicative effect of their early-developed abilities to understand the mental concepts of diverse beliefs and knowledge access. Specifically, the model predicts that children's proportion of correct responses on a false belief task can be closely approximated as the product of their proportions correct on the diverse belief and knowledge access tasks. To validate this prediction, we illustrate that our model provides good fits to a variety of ToM scale data for preschool children. We discuss the implications and extensions of our model for a deeper understanding of developmental progressions of children's ToM abilities.

  1. Association of health professional leadership behaviors on health promotion practice beliefs.

    Science.gov (United States)

    Stone, Jacqueline D; Belcher, Harolyn M E; Attoh, Prince; D'Abundo, Michelle; Gong, Tao

    2017-04-01

    Leadership is a process by which an individual influences a group or individual to achieve a common goal, in this case health promotion for individuals with disabilities. (1) To examine the association between the transformational leadership behaviors of the Association of University Centers on Disabilities (AUCD) network professionals and their practice beliefs about health promotion activities, specifically cardiovascular fitness and healthy weight, for people with disabilities. (2) To determine if discipline and/or years of practice moderate the association between transformational leadership behaviors and practice beliefs regarding health promotion. There is a positive association between transformational leadership behaviors and health professionals practice beliefs regarding health promotion activities for persons with disabilities. A quantitative cross-sectional web-based survey design was used to determine the association between leadership behaviors and practices beliefs regarding health promotion for people with disabilities. The Multifactor Leadership Questionnaire and an adapted version of the Role of Health Promotion in Physical Therapy Survey were used to measure leadership and practice beliefs, respectively. Multiple regression analysis was applied to determine the association of leadership behaviors with health promotion practice beliefs variables. Transformational leadership behaviors of the AUCD network professionals were positively associated with health promotion practice beliefs about cardiovascular fitness for people with disabilities. Years post licensure and discipline did not moderate the association between transformational leadership and practice beliefs regarding health promotion. Transformational leadership may facilitate health professionals' health promotion practices for people with disabilities. Further research and training in leadership is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Attitudes, beliefs, uncertainty and risk

    Energy Technology Data Exchange (ETDEWEB)

    Greenhalgh, Geoffrey [Down Park Place, Crawley Down (United Kingdom)

    2001-07-01

    There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course chosen will be more favourable

  3. Attitudes, beliefs, uncertainty and risk

    Energy Technology Data Exchange (ETDEWEB)

    Greenhalgh, Geoffrey [Down Park Place, Crawley Down (United Kingdom)

    2001-07-01

    There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course

  4. Attitudes, beliefs, uncertainty and risk

    International Nuclear Information System (INIS)

    Greenhalgh, Geoffrey

    2001-01-01

    There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course chosen will be more favourable

  5. Lateralized direct and indirect semantic priming effects in subjects with paranormal experiences and beliefs.

    Science.gov (United States)

    Pizzagalli, D; Lehmann, D; Brugger, P

    2001-01-01

    The present investigation tested the hypothesis that, as an aspect of schizotypal thinking, the formation of paranormal beliefs was related to spreading activation characteristics within semantic networks. From a larger student population (n = 117) prescreened for paranormal belief, 12 strong believers and 12 strong disbelievers (all women) were invited for a lateralized semantic priming task with directly and indirectly related prime-target pairs. Believers showed stronger indirect (but not direct) semantic priming effects than disbelievers after left (but not right) visual field stimulation, indicating faster appreciation of distant semantic relations specifically by the right hemisphere, reportedly specialized in coarse rather than focused semantic processing. These results are discussed in the light of recent findings in schizophrenic patients with thought disorders. They suggest that a disinhibition with semantic networks may underlie the formation of paranormal belief. The potential usefulness of work with healthy subjects for neuropsychiatric research is stressed. Copyright 2001 S. Karger AG, Basel

  6. Race Research and the Ethics of Belief.

    Science.gov (United States)

    Anomaly, Jonathan

    2017-06-01

    On most accounts, beliefs are supposed to fit the world rather than change it. But believing can have social consequences, since the beliefs we form underwrite our actions and impact our character. Because our beliefs affect how we live our lives and how we treat other people, it is surprising how little attention is usually given to the moral status of believing apart from its epistemic justification. In what follows, I develop a version of the harm principle that applies to beliefs as well as actions. In doing so, I challenge the often exaggerated distinction between forming beliefs and acting on them. 1 After developing this view, I consider what it might imply about controversial research the goal of which is to yield true beliefs but the outcome of which might include negative social consequences. In particular, I focus on the implications of research into biological differences between racial groups.

  7. Public beliefs about and attitudes towards bipolar disorder: testing theory based models of stigma.

    Science.gov (United States)

    Ellison, Nell; Mason, Oliver; Scior, Katrina

    2015-04-01

    Given the vast literature into public beliefs and attitudes towards schizophrenia and depression, there is paucity of research on attitudes towards bipolar disorder despite its similar prevalence to schizophrenia. This study explored public beliefs and attitudes towards bipolar disorder and examined the relationship between these different components of stigma. Using an online questionnaire distributed via email, social networking sites and public institutions, 753 members of the UK population were presented with a vignette depicting someone who met DSM-IV criteria for bipolar disorder. Causal beliefs, beliefs about prognosis, emotional reactions, stereotypes, and social distance were assessed in response to the vignette. Preacher and Hayes procedure for estimating direct and indirect effects of multiple mediators was used to examine the relationship between these components of stigma. Bipolar disorder was primarily associated with positive beliefs and attitudes and elicited a relatively low desire for social distance. Fear partially mediated the relationship between stereotypes and social distance. Biomedical causal beliefs reduced desire for social distance by increasing compassion, whereas fate causal beliefs increased it through eliciting fear. Psychosocial causal beliefs had mixed effects. The measurement of stigma using vignettes and self-report questionnaires has implications for ecological validity and participants may have been reluctant to reveal the true extent of their negative attitudes. Dissemination of these findings to people with bipolar disorder has implications for the reduction of internalised stigma in this population. Anti-stigma campaigns should attend to causal beliefs, stereotypes and emotional reactions as these all play a vital role in discriminatory behaviour towards people with bipolar disorder. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Journalism as Justified True Belief

    OpenAIRE

    Lisboa, Sílvia; Benetti, Marcia

    2015-01-01

    If it is important to think of journalism as a form of knowledge, then how does it become knowledge? How does this process work? In order to answer this question, this article proposes a new understanding of journalism as a subject; presenting it as a justified true belief. We think of journalism being based on pillars of truth and justification, conditions necessary in order for Epistemology to grant it the status of knowledge. We address the concept of truth and show how journalistic report...

  9. Graduates beliefs about career management

    Directory of Open Access Journals (Sweden)

    Babić Lepa

    2012-06-01

    Full Text Available Career management is increasingly becoming an individuals' matter, despite the various activities organized by the different institutions to support career development and planning. An exploratory survey was conducted to determine what kind of beliefs graduates have about career management. Results indicate that graduates are aware of the importance of university knowledge for getting a job, the importance of knowledge and investment in education for positioning in the labor market, so they give priority to development opportunities that business brings opposed to the material rewards.

  10. Equilibria in social belief removal [Journal article

    CSIR Research Space (South Africa)

    Booth, R

    2010-08-01

    Full Text Available removal function >i, which tells it how to remove any given sentence from its belief set. In this paper we view >i as a unary function on the set L of non- tautologous sentences, i.e., agents are never required to remove >. The result of removing 2 L... from i?s belief set is denoted by >i( ). We assume i?s initial belief set can always be recaptured from >i alone by just removing the (b) (1) (A) contradiction, i.e., i?s initial belief set is >i(?). We call any n-tuple (>i)i2A of removal functions a...

  11. When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias

    OpenAIRE

    Trippas, Dries; Thompson, Valerie A.; Handley, Simon J.

    2016-01-01

    Two experiments pitted the default-interventionist account of belief bias against a parallel-processing model. According to the former, belief bias occurs because a fast, belief-based evaluation of the conclusion pre-empts a working-memory demanding logical analysis. In contrast, according to the latter both belief-based and logic-based responding occur in parallel. Participants were given deductive reasoning problems of variable complexity and instructed to decide whether the conclusion was ...

  12. Associative processing and paranormal belief.

    Science.gov (United States)

    Gianotti, L R; Mohr, C; Pizzagalli, D; Lehmann, D; Brugger, P

    2001-12-01

    In the present study we introduce a novel task for the quantitative assessment of both originality and speed of individual associations. This 'BAG' (Bridge-the-Associative-Gap) task was used to investigate the relationships between creativity and paranormal belief. Twelve strong 'believers' and 12 strong 'skeptics' in paranormal phenomena were selected from a large student population (n > 350). Subjects were asked to produce single-word associations to word pairs. In 40 trials the two stimulus words were semantically indirectly related and in 40 other trials the words were semantically unrelated. Separately for these two stimulus types, response commonalities and association latencies were calculated. The main finding was that for unrelated stimuli, believers produced associations that were more original (had a lower frequency of occurrence in the group as a whole) than those of the skeptics. For the interpretation of the result we propose a model of association behavior that captures both 'positive' psychological aspects (i.e., verbal creativity) and 'negative' aspects (susceptibility to unfounded inferences), and outline its relevance for psychiatry. This model suggests that believers adopt a looser response criterion than skeptics when confronted with 'semantic noise'. Such a signal detection view of the presence/absence of judgments for loose semantic relations may help to elucidate the commonalities between creative thinking, paranormal belief and delusional ideation.

  13. BELIEF Project: the Portal and the Digital Library

    International Nuclear Information System (INIS)

    Zoppi, F.; Calabro, G.

    2007-01-01

    BELIEF (Bringing Europes eLectronic Infrastructures to Expanding Frontiers) Project aim to create a platform where eInfrastructures providers and users can collaborate and exchange knowledge, which will help ensure that eInfrastructures are developed and used effectively worldwide, filling the gap separating the Research Infrastructure providers from the users, and thus contribute to the emergence of a competitive knowledge-based economy. To create this synergy of multi-disciplinary Research Infrastructure communities, BELIEF created a one-stop-shop for eInfrastructures communities providing online a Digital Library (DL) and a Portal with a search and contact facility, case studies, a discussion forum, eInfrastructures publications. Offline, it has organised events including brainstorming, networking workshops and international conferences and publications, since BELIEFs values are firmly rooted in international cooperation to the emerging economies, particularly of Latin America and India. The Portal and the DL are key parts of this project. There was an opportunity to provide a ready and common source of information on eInfrastructures, both for the users wanting to find out the supply, and for the providers wanting to extend user base and develop their systems. The Portal and the DL respond to this demand by supplying to researchers documentation that matches their search criteria precisely, according to their interest and professional profile. (Author)

  14. Exploring the beliefs of Australian prefabricated house builders

    Directory of Open Access Journals (Sweden)

    Dale A Steinhardt

    2016-06-01

    Full Text Available The housing sector accounts for a majority of newly constructed buildings. Prefabrication, defined as the factory construction of houses or significant components, is widely promoted as a means to improve efficiency. This paper focuses on the research questions: RQ1. What are the attitudes of builders towards prefabrication adoption? RQ2. What types of stakeholders do builders believe influence their adoption decisions? RQ3. What types of contextual influences do builders believe impact their adoption decisions? Current prefabrication research has focused on the advantages and disadvantages of prefabrication, without further unpacking the beliefs of stakeholders that underpin them. This paper addresses this gap and increases the understanding of beliefs that can frame interventions to increase the market penetration of prefabrication. Fourteen interviews with Australian prefabricators were undertaken as a Belief Elicitation Study. This qualitative methodology is framed by the Theory of Planned Behaviour (TPB and the Technology Acceptance Model (TAM. Results show that modern high-quality prefabricated housing has struggled to overcome historical stigma; improved construction speed has not and is not likely to translate to reduced totals costs for a majority of firms; and prefabrication adoption has been hindered by an almost completely unsupportive industry infrastructure. Recommendations are made to frame arguments in improving short-term outcomes for an industry driven by practical considerations. Future discourse must focus on cost impacts, financial security and risk reduction. Establishing networks of prefabricators that can build a strong, unified voice for the industry should be prioritised.

  15. Belief in complementary and alternative medicine is related to age and paranormal beliefs in adults.

    Science.gov (United States)

    Van den Bulck, Jan; Custers, Kathleen

    2010-04-01

    The use of complementary and alternative medicine (CAM) is widespread, even among people who use conventional medicine. Positive beliefs about CAM are common among physicians and medical students. Little is known about the beliefs regarding CAM among the general public. Among science students, belief in CAM was predicted by belief in the paranormal. In a cross-sectional study, 712 randomly selected adults (>18 years old) responded to the CAM Health Belief Questionnaire (CHBQ) and a paranormal beliefs scale. CAM beliefs were very prevalent in this sample of adult Flemish men and women. Zero-order correlations indicated that belief in CAM was associated with age (r = 0.173 P paranormal belief (r = 0.365 P paranormal. Paranormal beliefs accounted for 14% of the variance of the CAM beliefs (regression coefficient: 0.376; 95%: CI 0.30-0.44). The level of education (regression coefficient: 0.06; 95% CI: -0.014-0.129) and social desirability (regression coefficient: -0.023; 95% CI: -0.048-0.026) did not make a significant contribution to the explained variance (paranormal beliefs.

  16. Posttraumatic Maladaptive Beliefs Scale: Evolution of the Personal Beliefs and Reactions Scale

    Science.gov (United States)

    Vogt, Dawne S.; Shipherd, Jillian C.; Resick, Patricia A.

    2012-01-01

    The Posttraumatic Maladaptive Beliefs Scale (PMBS) was developed to measure maladaptive beliefs about current life circumstances that may occur following trauma exposure. This scale assesses maladaptive beliefs within three domains: (a) Threat of Harm, (b) Self-Worth and Judgment, and (c) Reliability and Trustworthiness of Others. Items for the…

  17. Do Humans Have Two Systems to Track Beliefs and Belief-Like States?

    Science.gov (United States)

    Apperly, Ian A.; Butterfill, Stephen A.

    2009-01-01

    The lack of consensus on how to characterize humans' capacity for belief reasoning has been brought into sharp focus by recent research. Children fail critical tests of belief reasoning before 3 to 4 years of age (H. Wellman, D. Cross, & J. Watson, 2001; H. Wimmer & J. Perner, 1983), yet infants apparently pass false-belief tasks at 13 or 15…

  18. Negatively-Biased Credulity and the Cultural Evolution of Beliefs

    Science.gov (United States)

    Fessler, Daniel M. T.; Pisor, Anne C.; Navarrete, Carlos David

    2014-01-01

    The functions of cultural beliefs are often opaque to those who hold them. Accordingly, to benefit from cultural evolution’s ability to solve complex adaptive problems, learners must be credulous. However, credulity entails costs, including susceptibility to exploitation, and effort wasted due to false beliefs. One determinant of the optimal level of credulity is the ratio between the costs of two types of errors: erroneous incredulity (failing to believe information that is true) and erroneous credulity (believing information that is false). This ratio can be expected to be asymmetric when information concerns hazards, as the costs of erroneous incredulity will, on average, exceed the costs of erroneous credulity; no equivalent asymmetry characterizes information concerning benefits. Natural selection can therefore be expected to have crafted learners’ minds so as to be more credulous toward information concerning hazards. This negatively-biased credulity extends general negativity bias, the adaptive tendency for negative events to be more salient than positive events. Together, these biases constitute attractors that should shape cultural evolution via the aggregated effects of learners’ differential retention and transmission of information. In two studies in the U.S., we demonstrate the existence of negatively-biased credulity, and show that it is most pronounced in those who believe the world to be dangerous, individuals who may constitute important nodes in cultural transmission networks. We then document the predicted imbalance in cultural content using a sample of urban legends collected from the Internet and a sample of supernatural beliefs obtained from ethnographies of a representative collection of the world’s cultures, showing that beliefs about hazards predominate in both. PMID:24736596

  19. Negatively-biased credulity and the cultural evolution of beliefs.

    Directory of Open Access Journals (Sweden)

    Daniel M T Fessler

    Full Text Available The functions of cultural beliefs are often opaque to those who hold them. Accordingly, to benefit from cultural evolution's ability to solve complex adaptive problems, learners must be credulous. However, credulity entails costs, including susceptibility to exploitation, and effort wasted due to false beliefs. One determinant of the optimal level of credulity is the ratio between the costs of two types of errors: erroneous incredulity (failing to believe information that is true and erroneous credulity (believing information that is false. This ratio can be expected to be asymmetric when information concerns hazards, as the costs of erroneous incredulity will, on average, exceed the costs of erroneous credulity; no equivalent asymmetry characterizes information concerning benefits. Natural selection can therefore be expected to have crafted learners' minds so as to be more credulous toward information concerning hazards. This negatively-biased credulity extends general negativity bias, the adaptive tendency for negative events to be more salient than positive events. Together, these biases constitute attractors that should shape cultural evolution via the aggregated effects of learners' differential retention and transmission of information. In two studies in the U.S., we demonstrate the existence of negatively-biased credulity, and show that it is most pronounced in those who believe the world to be dangerous, individuals who may constitute important nodes in cultural transmission networks. We then document the predicted imbalance in cultural content using a sample of urban legends collected from the Internet and a sample of supernatural beliefs obtained from ethnographies of a representative collection of the world's cultures, showing that beliefs about hazards predominate in both.

  20. Negatively-biased credulity and the cultural evolution of beliefs.

    Science.gov (United States)

    Fessler, Daniel M T; Pisor, Anne C; Navarrete, Carlos David

    2014-01-01

    The functions of cultural beliefs are often opaque to those who hold them. Accordingly, to benefit from cultural evolution's ability to solve complex adaptive problems, learners must be credulous. However, credulity entails costs, including susceptibility to exploitation, and effort wasted due to false beliefs. One determinant of the optimal level of credulity is the ratio between the costs of two types of errors: erroneous incredulity (failing to believe information that is true) and erroneous credulity (believing information that is false). This ratio can be expected to be asymmetric when information concerns hazards, as the costs of erroneous incredulity will, on average, exceed the costs of erroneous credulity; no equivalent asymmetry characterizes information concerning benefits. Natural selection can therefore be expected to have crafted learners' minds so as to be more credulous toward information concerning hazards. This negatively-biased credulity extends general negativity bias, the adaptive tendency for negative events to be more salient than positive events. Together, these biases constitute attractors that should shape cultural evolution via the aggregated effects of learners' differential retention and transmission of information. In two studies in the U.S., we demonstrate the existence of negatively-biased credulity, and show that it is most pronounced in those who believe the world to be dangerous, individuals who may constitute important nodes in cultural transmission networks. We then document the predicted imbalance in cultural content using a sample of urban legends collected from the Internet and a sample of supernatural beliefs obtained from ethnographies of a representative collection of the world's cultures, showing that beliefs about hazards predominate in both.

  1. Tunable Sparse Network Coding for Multicast Networks

    DEFF Research Database (Denmark)

    Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant

    2014-01-01

    This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity...... a mechanism to perform efficient Gaussian elimination over sparse matrices going beyond belief propagation but maintaining low decoding complexity. Supporting simulation results are provided showing the trade-off between decoding complexity and completion time....

  2. Breast Health Belief Systems Study

    National Research Council Canada - National Science Library

    Williams, Mary

    1998-01-01

    ... (200 at each of 3 sites) who have not received a diagnosis of breast cancer, and (3) quantitatively test the effectiveness of an educational approach that utilizes an existing network of lay workers who are indigenous to the target communities...

  3. A new approach to probabilistic belief change

    CSIR Research Space (South Africa)

    Rens, G

    2015-05-01

    Full Text Available One way for an agent to deal with uncertainty about its beliefs is to maintain a probability distribution over the worlds it believes are possible. A belief change operation may recommend some previously believed worlds to become impossible and some...

  4. How psychotic-like are paranormal beliefs?

    Science.gov (United States)

    Cella, Matteo; Vellante, Marcello; Preti, Antonio

    2012-09-01

    Paranormal beliefs and Psychotic-like Experiences (PLE) are phenotypically similar and can occur in individuals with psychosis but also in the general population; however the relationship of these experiences for psychosis risk is largely unclear. This study investigates the association of PLE and paranormal beliefs with psychological distress. Five hundred and three young adults completed measures of paranormal beliefs (Beliefs in the Paranormal Scale), psychological distress (General Health Questionnaire), delusion (Peters et al. Delusions Inventory), and hallucination (Launay-Slade Hallucination Scale) proneness. The frequency and intensity of PLE was higher in believers in the paranormal compared to non-believers, however psychological distress levels were comparable. Regression findings confirmed that paranormal beliefs were predicted by delusion and hallucination-proneness but not psychological distress. The use of a cross-sectional design in a specific young adult population makes the findings exploratory and in need of replication with longitudinal studies. The predictive value of paranormal beliefs and experiences for psychosis may be limited; appraisal or the belief emotional salience rather than the belief per se may be more relevant risk factors to predict psychotic risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. Criminalising defamation of religion and belief

    NARCIS (Netherlands)

    van Noorloos, L.A.

    2014-01-01

    This article deals with the role of criminal law in dealing with defamatory expressions about religion or belief. Defamation of religion and belief is a form of indirect defamation ‘via identification’ which, as the discussion about the Dutch group defamation law shows, stretches up the notion of

  6. relationship between patients' beliefs about their antihypertensives ...

    African Journals Online (AJOL)

    userpc

    effects of their medication, suggesting a high counter-balancing effect of this belief on their ... patients have positive belief regarding the efficacy of their ... Divorced. Widow. 11. 100. 5. 11. 9. 79. 4. 8. Religion. Muslim. Christian. 108. 19. 85. 15.

  7. Investigating Teachers' Personal Visions and Beliefs: Implications ...

    African Journals Online (AJOL)

    Investigating Teachers' Personal Visions and Beliefs: Implications for Quality in Language Teacher Education. ... attitude, focus and performance. The growing influence of constructivism in teacher education and the increase in the amount of research into teacher cognition has put the notion of beliefs and vision into central ...

  8. The product of capacities and belief functions

    DEFF Research Database (Denmark)

    Hendon, Ebbe; Whitta-Jacobsen, Hans Jørgen; Sloth, Birgitte

    1996-01-01

    Capacities (monotone, non-additive set functions) have been suggested to describe situations of uncertainty. We examine the question of how to define the product of two independent capacities. In particular, for the product of two belief functions (totally monotone capacities), there is a unique...... minimal product belief function. This is characterized in several ways...

  9. 116 THE IGALA TRADITIONAL RELIGIOUS BELIEF SYSTEM ...

    African Journals Online (AJOL)

    Ike Odimegwu

    supreme God called Ọjọ, but that it is a function of intercourse between ..... other deities at the same time; implicit monotheism,. i.e. a belief in a supreme deity yet no definite denial of other gods; and lastly, explicit monotheism, a belief in a ...

  10. Teachers' Beliefs about Neuroscience and Education

    Science.gov (United States)

    Zambo, Debby; Zambo, Ron

    2011-01-01

    Information from neuroscience is readily available to educators, yet instructors of educational psychology and related fields have not investigated teachers' beliefs regarding this information. The purpose of this survey study was to uncover the beliefs 62 teachers held about neuroscience and education. Results indicate there were three types of…

  11. The product of capacities and belief functions

    DEFF Research Database (Denmark)

    Hendon, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

    1996-01-01

    Capacities (monotone, non-additive set functions) have been suggested to describe situations of uncertainty. We examine the question of how to define the product of two independent capacities. In particular, for the product of two belief functions (totally monotone capacities), there is a unique...... minimal product belief function. This is characterized in several ways....

  12. The Hot Hand Belief and Framing Effects

    Science.gov (United States)

    MacMahon, Clare; Köppen, Jörn; Raab, Markus

    2014-01-01

    Purpose: Recent evidence of the hot hand in sport--where success breeds success in a positive recency of successful shots, for instance--indicates that this pattern does not actually exist. Yet the belief persists. We used 2 studies to explore the effects of framing on the hot hand belief in sport. We looked at the effect of sport experience and…

  13. Academic Optimism: An Individual Teacher Belief

    Science.gov (United States)

    Ngidi, David P.

    2012-01-01

    In this study, academic optimism as an individual teacher belief was investigated. Teachers' self-efficacy beliefs were measured using the short form of the Teacher Sense of Efficacy Scale. One subtest from the Omnibus T-Scale, the faculty trust in clients subtest, was used to measure teachers' trust in students and parents. One subtest from the…

  14. Are Teacher Beliefs Gender-Related?

    NARCIS (Netherlands)

    Kraker - de Pauw, Emmy; van Wesel, F.; Verwijmeren, Thijs; Denessen, Eddie; Krabbendam, Lydia

    2016-01-01

    Teacher beliefs influence student behaviour and learning outcomes. Little is known about the role of specific teacher characteristics (e.g., gender and teaching domain) in the formation of these beliefs. In the current study, three versions of the Implicit Association Test (IAT) were used to assess

  15. Are teacher beliefs gender-related?

    NARCIS (Netherlands)

    Kraker-Pauw, E. de; Wesel, F. van; Verwijmeren, T.; Denessen, E.J.P.G.; Krabbendam, L.

    2016-01-01

    Teacher beliefs influence student behaviour and learning outcomes. Little is known about the role of specific teacher characteristics (e.g., gender and teaching domain) in the formation of these beliefs. In the current study, three versions of the Implicit Association Test (IAT) were used to assess

  16. Total Evidence, Uncertainty and A Priori Beliefs

    NARCIS (Netherlands)

    Bewersdorf, Benjamin; Felline, Laura; Ledda, Antonio; Paoli, Francesco; Rossanese, Emanuele

    2016-01-01

    Defining the rational belief state of an agent in terms of her initial or a priori belief state as well as her total evidence can help to address a number of important philosophical problems. In this paper, I discuss how this strategy can be applied to cases in which evidence is uncertain. I argue

  17. SPORT SCIENCE STUDENTS‟ BELIEFS ABOUT LANGUAGE LEARNING

    Directory of Open Access Journals (Sweden)

    Suvi Akhiriyah

    2017-04-01

    Full Text Available There are many reasons for students of Sport Science to use English. Yet, knowing the importance of learning English is sometimes not enough to encourage them to learn English well. Based on the experience in teaching them, erroneous belief seems to be held by many of them. It arouses curiosity about the beliefs which might be revealed to help the students to be successful in language learning. By investigating sport science students‘ beliefs about language learning, it is expected that types of the beliefs which they hold can be revealed. Understanding students‘ beliefs about language learning is essential because these beliefs can have possible consequences for second language learning and instruction. This study is expected to provide empirical evidence. The subjects of this study were 1st semester students majoring in Sport Science of Sport Science Faculty. There were 4 classes with 38 students in each class. There were approximately 152 students as the population of the study. The sample was taken by using random sampling. All members of the population received the questionnaire. The questionnaire which was later handed back to the researcher is considered as the sample. The instrument in this study is the newest version of Beliefs About Language Learning Inventory (BALLI, version 2.0, developed by Horwitz to asses the beliefs about learning a foreign language.

  18. Cultural Beliefs about Autism in Indonesia

    Science.gov (United States)

    Riany, Yulina Eva; Cuskelly, Monica; Meredith, Pamela

    2016-01-01

    Cultural beliefs about parenting have an important influence on parenting behaviours, including considerations about appropriate ways to parent children with autism. Although Indonesia has one of the largest and most ethnically diverse populations in the world, little is known about cultural beliefs regarding children with autism within Indonesian…

  19. Lay belief in biopolitics and political prejudice

    NARCIS (Netherlands)

    Suhay, E; Brandt, M.J.; Proulx, T.

    2017-01-01

    Building on psychological research linking essentialist beliefs about human differences with prejudice, we test whether lay belief in the biological basis of political ideology is associated with political intolerance and social avoidance. In two studies of American adults (Study 1: N = 288, Study

  20. Changing Professional Practice Requires Changing Beliefs

    Science.gov (United States)

    Guerra, Patricia L.; Nelson, Sarah W.

    2009-01-01

    Creating schools that are culturally responsive and successful with all students requires doing basic work with educators to uncover their beliefs about children. If school leaders believe, like many people do, that changed behavior will result in changed beliefs, they are mistaken. Leaders must be proactive in identifying what teachers believe…

  1. Double preference relations for generalised belief change

    CSIR Research Space (South Africa)

    Booth, R

    2010-11-01

    Full Text Available Many belief change formalisms employ plausibility orderings over the set of possible worlds to determine how the beliefs of an agent ought to be modified after the receipt of a new epistemic input. While most such possible world semantics rely on a...

  2. Journalism as Justified True Belief

    Directory of Open Access Journals (Sweden)

    Sílvia Lisboa

    2015-12-01

    Full Text Available If it is important to think of journalism as a form of knowledge, then how does it become knowledge? How does this process work? In order to answer this question, this article proposes a new understanding of journalism as a subject; presenting it as a justified true belief. We think of journalism being based on pillars of truth and justification, conditions necessary in order for Epistemology to grant it the status of knowledge. We address the concept of truth and show how journalistic reports are justified to the public as well as consider the central role of credibility in this process. We add to the epistemic conception by using concepts of discourse that help to understand how journalism provides evidence through its intentions, its authority and its ability. This evidence acts like a guide for the reader towards forming opinions on journalistic reports and recognizing journalism as a form of knowledge.

  3. Motivational beliefs, values, and goals.

    Science.gov (United States)

    Eccles, Jacquelynne S; Wigfield, Allan

    2002-01-01

    This chapter reviews the recent research on motivation, beliefs, values, and goals, focusing on developmental and educational psychology. The authors divide the chapter into four major sections: theories focused on expectancies for success (self-efficacy theory and control theory), theories focused on task value (theories focused on intrinsic motivation, self-determination, flow, interest, and goals), theories that integrate expectancies and values (attribution theory, the expectancy-value models of Eccles et al., Feather, and Heckhausen, and self-worth theory), and theories integrating motivation and cognition (social cognitive theories of self-regulation and motivation, the work by Winne & Marx, Borkowski et al., Pintrich et al., and theories of motivation and volition). The authors end the chapter with a discussion of how to integrate theories of self-regulation and expectancy-value models of motivation and suggest new directions for future research.

  4. Paranormal belief, schizotypy, and Body Mass Index.

    Science.gov (United States)

    Hergovich, Andreas; Willinger, Ulrike; Arendasy, Martin

    2005-06-01

    There are indications that subjects with schizotypal personality have a lower Body Mass Index. Also schizotypal personality is linked to a higher incidence of paranormal belief. In this study we examined whether low Body Mass Index is also linked to paranormal belief. In a pilot study 48 students of psychology (85.4% women) between the ages of 20 and 27 years were administered a questionnaire assessing weight, height, and paranormal belief. Analysis suggested an association between belief in paranormal phenomena and low Body Mass Index. In a follow-up study with 300 subjects and equal sex distribution, the relationship was examined under control of schizotypy. The results for Body Mass Index could not be confirmed; however, paranormal belief was heavily associated with the cognitive-perceptual component of schizotypy.

  5. Normative beliefs and sexual risk in China.

    Science.gov (United States)

    Li, Li; Ding, Ying Ying; Wu, Zunyou; Rotheram-Borus, Mary Jane; Guo, Sam

    2011-08-01

    We examined normative beliefs about multiple sexual partners and social status in China and their association with risky sexual behaviors and sexually transmitted infections (STIs). Self-reported and biological markers of sexual risk were examined among 3,716 market vendors from a city in eastern China. Men who were older or with less education believed having multiple sexual partners was linked to higher social status. Adjusting for demographic characteristics, normative beliefs were significantly associated with having multiple sexual partners, while having multiple sexual partners was significantly associated with STIs. Normative beliefs regarding sexual behaviors may play an important role in individual risk behaviors. Future HIV/STI interventions must address community beliefs about the positive meaning of sexual risks, particularly among men with traditional beliefs about gender roles.

  6. Indonesian teachers' epistemological beliefs and inclusive education.

    Science.gov (United States)

    Sheehy, Kieron; Budiyanto; Kaye, Helen; Rofiah, Khofidotur

    2017-01-01

    A growing number of children with intellectual disabilities attend inclusive schools in Indonesia. Previous research has suggested that teachers' type of school and experience influences their beliefs about inclusive education. This research collected questionnaire data from 267 Indonesian teachers and compared the responses from those working in inclusive, special and regular schools regarding their epistemological and pedagogical beliefs. The results showed that teachers in inclusive schools expressed stronger social constructivist beliefs than those in other schools. However, it was teachers' epistemological beliefs, rather than their type of school or experience, which were the significant predictor of their beliefs about inclusive education. The findings suggest that international epistemological research needs to have a more nuanced view of constructivist models of learning to better understand and inform how inclusive pedagogy is being enacted in different contexts.

  7. A belief-based evolutionarily stable strategy.

    Science.gov (United States)

    Deng, Xinyang; Wang, Zhen; Liu, Qi; Deng, Yong; Mahadevan, Sankaran

    2014-11-21

    As an equilibrium refinement of the Nash equilibrium, evolutionarily stable strategy (ESS) is a key concept in evolutionary game theory and has attracted growing interest. An ESS can be either a pure strategy or a mixed strategy. Even though the randomness is allowed in mixed strategy, the selection probability of pure strategy in a mixed strategy may fluctuate due to the impact of many factors. The fluctuation can lead to more uncertainty. In this paper, such uncertainty involved in mixed strategy has been further taken into consideration: a belief strategy is proposed in terms of Dempster-Shafer evidence theory. Furthermore, based on the proposed belief strategy, a belief-based ESS has been developed. The belief strategy and belief-based ESS can reduce to the mixed strategy and mixed ESS, which provide more realistic and powerful tools to describe interactions among agents. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Test Performance Related Dysfunctional Beliefs

    Directory of Open Access Journals (Sweden)

    Recep TÜTÜNCÜ

    2012-11-01

    Full Text Available Objective: Examinations by using tests are very frequently used in educational settings and successful studying before the examinations is a complex matter to deal with. In order to understand the determinants of success in exams better, we need to take into account not only emotional and motivational, but also cognitive aspects of the participants such as dysfunctional beliefs. Our aim is to present the relationship between candidates’ characteristics and distorted beliefs/schemata just before an examination. Method: The subjects of the study were 30 female and 30 male physicians who were about to take the medical specialization exam (MSE in Turkey. Dysfunctional Attitude Scale (DAS and Young Schema Questionnaire Short Form (YSQ-SF were applied to the subjects. The statistical analysis was done using the F test, Mann-Whitney, Kruskal-Wallis, chi-square test and spearman’s correlation test. Results: It was shown that some of the DAS and YSQ-SF scores were significantly higher in female gender, in the group who could not pass the exam, who had repetitive examinations, who had their first try taking an examination and who were unemployed at the time of the examination. Conclusion: Our findings indicate that candidates seeking help before MSE examination could be referred for cognitive therapy or counseling even they do not have any psychiatric diagnosis due to clinically significant cognitive distortion. Measurement and treatment of cognitive distortions that have negative impact on MSE performance may improve the cost-effectiveness and mental well being of the young doctors.

  9. A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment.

    Science.gov (United States)

    Nicol, Sam; Chadès, Iadine

    2017-01-01

    Environmental impact assessment (EIA) is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN) to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.

  10. A preliminary approach to quantifying the overall environmental risks posed by development projects during environmental impact assessment.

    Directory of Open Access Journals (Sweden)

    Sam Nicol

    Full Text Available Environmental impact assessment (EIA is used globally to manage the impacts of development projects on the environment, so there is an imperative to demonstrate that it can effectively identify risky projects. However, despite the widespread use of quantitative predictive risk models in areas such as toxicology, ecosystem modelling and water quality, the use of predictive risk tools to assess the overall expected environmental impacts of major construction and development proposals is comparatively rare. A risk-based approach has many potential advantages, including improved prediction and attribution of cause and effect; sensitivity analysis; continual learning; and optimal resource allocation. In this paper we investigate the feasibility of using a Bayesian belief network (BBN to quantify the likelihood and consequence of non-compliance of new projects based on the occurrence probabilities of a set of expert-defined features. The BBN incorporates expert knowledge and continually improves its predictions based on new data as it is collected. We use simulation to explore the trade-off between the number of data points and the prediction accuracy of the BBN, and find that the BBN could predict risk with 90% accuracy using approximately 1000 data points. Although a further pilot test with real project data is required, our results suggest that a BBN is a promising method to monitor overall risks posed by development within an existing EIA process given a modest investment in data collection.

  11. Religious beliefs are factual beliefs: Content does not correlate with context sensitivity.

    Science.gov (United States)

    Levy, Neil

    2017-04-01

    Neil Van Leeuwen argues that religious beliefs are not factual beliefs: typically, at least, they are attitudes of a different type. He argues that they exhibit much more sensitivity to context than factual beliefs: outside of contexts in which they are salient, they do not govern behaviour or inference, or provide background assumptions for cognition. This article surveys a large range of data to show that the kind of context sensitivity that Van Leeuwen thinks is the province of religious beliefs does not correlate with belief content. Beliefs about matters of fact beyond the theological realm exhibit this kind of sensitivity too. Conversely, theological and supernatural beliefs often guide behaviour across contexts. It is the intuitiveness of representations across contexts that predicts context (in)sensitivity, and intuitiveness is powerfully influenced by processing fluency. Fluency, in turn, is sensitive to cues that vary across contexts. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Processing of false belief passages during natural story comprehension: An fMRI study.

    Science.gov (United States)

    Kandylaki, Katerina D; Nagels, Arne; Tune, Sarah; Wiese, Richard; Bornkessel-Schlesewsky, Ina; Kircher, Tilo

    2015-11-01

    The neural correlates of theory of mind (ToM) are typically studied using paradigms which require participants to draw explicit, task-related inferences (e.g., in the false belief task). In a natural setup, such as listening to stories, false belief mentalizing occurs incidentally as part of narrative processing. In our experiment, participants listened to auditorily presented stories with false belief passages (implicit false belief processing) and immediately after each story answered comprehension questions (explicit false belief processing), while neural responses were measured with functional magnetic resonance imaging (fMRI). All stories included (among other situations) one false belief condition and one closely matched control condition. For the implicit ToM processing, we modeled the hemodynamic response during the false belief passages in the story and compared it to the hemodynamic response during the closely matched control passages. For implicit mentalizing, we found activation in typical ToM processing regions, that is the angular gyrus (AG), superior medial frontal gyrus (SmFG), precuneus (PCUN), middle temporal gyrus (MTG) as well as in the inferior frontal gyrus (IFG) billaterally. For explicit ToM, we only found AG activation. The conjunction analysis highlighted the left AG and MTG as well as the bilateral IFG as overlapping ToM processing regions for both implicit and explicit modes. Implicit ToM processing during listening to false belief passages, recruits the left SmFG and billateral PCUN in addition to the "mentalizing network" known form explicit processing tasks. © 2015 Wiley Periodicals, Inc.

  13. The Origins of Belief Representation: Monkeys Fail to Automatically Represent Others’ Beliefs

    Science.gov (United States)

    Martin, Alia; Santos, Laurie R.

    2014-01-01

    Young infants’ successful performance on false belief tasks has led several researchers to argue that there may be a core knowledge system for representing the beliefs of other agents, emerging early in human development and constraining automatic belief processing into adulthood. One way to investigate this purported core belief representation system is to examine whether non-human primates share such a system. Although non-human primates have historically performed poorly on false belief tasks that require executive function capacities, little work has explored how primates perform on more automatic measures of belief processing. To get at this issue, we modified Kovács et al. (2010)’s test of automatic belief representation to examine whether one non-human primate species—the rhesus macaque (Macaca mulatta)—is automatically influenced by another agent’s beliefs when tracking an object’s location. Monkeys saw an event in which a human agent watched an apple move back and forth between two boxes and an outcome in which one box was revealed to be empty. By occluding segments of the apple’s movement from either the monkey or the agent, we manipulated both the monkeys’ belief (true or false) and agent’s belief (true or false) about the final location of the apple. We found that monkeys looked longer at events that violated their own beliefs than at events that were consistent with their beliefs. In contrast to human infants, however, monkeys’ expectations were not influenced by another agent’s beliefs, suggesting that belief representation may be an aspect of core knowledge unique to humans. PMID:24374209

  14. Anders Breivik: Extreme Beliefs Mistaken for Psychosis.

    Science.gov (United States)

    Rahman, Tahir; Resnick, Phillip J; Harry, Bruce

    2016-03-01

    The case of Anders Breivik, who committed mass murder in Norway in 2011, stirred controversy among forensic mental health experts. His bizarrely composed compendium and references to himself as the "Knights Templar" raised concerns that he had a psychotic mental illness. Beliefs such as Mr. Breivik's that precede odd, unusual, or extremely violent behavior present a unique challenge to the forensic evaluator, who sometimes struggles to understand those beliefs. Psychotic disorder frequently is invoked to characterize odd, unusual, or extreme beliefs, with a classification that has evolved over time. However, the important concept of overvalued idea, largely ignored in American psychiatry, may better characterize these beliefs in some cases. We discuss the definitions of delusion and overvalued ideas in the context of Anders Breivik's rigidly held extreme beliefs. We also review the British definition of overvalued idea and discuss McHugh's construct, to introduce the term "extreme overvalued belief" as an aid in sharpening the forensic evaluator's conceptualization of these and similar beliefs. © 2016 American Academy of Psychiatry and the Law.

  15. The hot hand belief and framing effects.

    Science.gov (United States)

    MacMahon, Clare; Köppen, Jörn; Raab, Markus

    2014-09-01

    Recent evidence of the hot hand in sport-where success breeds success in a positive recency of successful shots, for instance-indicates that this pattern does not actually exist. Yet the belief persists. We used 2 studies to explore the effects of framing on the hot hand belief in sport. We looked at the effect of sport experience and task on the perception of baseball pitch behavior as well as the hot hand belief and free-throw behavior in basketball. Study 1 asked participants to designate outcomes with different alternation rates as the result of baseball pitches or coin tosses. Study 2 examined basketball free-throw behavior and measured predicted success before each shot as well as general belief in the hot hand pattern. The results of Study 1 illustrate that experience and stimulus alternation rates influence the perception of chance in human performance tasks. Study 2 shows that physically performing an act and making judgments are related. Specifically, beliefs were related to overall performance, with more successful shooters showing greater belief in the hot hand and greater predicted success for upcoming shots. Both of these studies highlight that the hot hand belief is influenced by framing, which leads to instability and situational contingencies. We show the specific effects of framing using accumulated experience of the individual with the sport and knowledge of its structure and specific experience with sport actions (basketball shots) prior to judgments.

  16. Analytic thinking reduces belief in conspiracy theories.

    Science.gov (United States)

    Swami, Viren; Voracek, Martin; Stieger, Stefan; Tran, Ulrich S; Furnham, Adrian

    2014-12-01

    Belief in conspiracy theories has been associated with a range of negative health, civic, and social outcomes, requiring reliable methods of reducing such belief. Thinking dispositions have been highlighted as one possible factor associated with belief in conspiracy theories, but actual relationships have only been infrequently studied. In Study 1, we examined associations between belief in conspiracy theories and a range of measures of thinking dispositions in a British sample (N=990). Results indicated that a stronger belief in conspiracy theories was significantly associated with lower analytic thinking and open-mindedness and greater intuitive thinking. In Studies 2-4, we examined the causational role played by analytic thinking in relation to conspiracist ideation. In Study 2 (N=112), we showed that a verbal fluency task that elicited analytic thinking reduced belief in conspiracy theories. In Study 3 (N=189), we found that an alternative method of eliciting analytic thinking, which related to cognitive disfluency, was effective at reducing conspiracist ideation in a student sample. In Study 4, we replicated the results of Study 3 among a general population sample (N=140) in relation to generic conspiracist ideation and belief in conspiracy theories about the July 7, 2005, bombings in London. Our results highlight the potential utility of supporting attempts to promote analytic thinking as a means of countering the widespread acceptance of conspiracy theories. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. How do Epistemological Beliefs Affect Training Motivation?

    Directory of Open Access Journals (Sweden)

    Ingrid Molan

    2014-05-01

    Full Text Available Studies show that human resources development through workplace training is one of the major investments in the workforce in today’s globalized and challenging market. As training motivation influences employees’ preparation for the workplace training, their respond to the programme, their learning outcome, their performance levels, and use of acquired knowledge and skills in their workplace it seems logical to investigate and determine antecedents of training motivation. The aim of this study was to examine the relationship between the concepts of epistemological beliefs, training motivation and the actual participation in the workplace training. We predicted that epistemological beliefs would have an effect on training motivation and actual participation on the workplace training and that there would be a positive relationship between the concepts, meaning that the more sophisticated epistemological beliefs would lead to higher motivation and participation. To test the epistemological beliefs, the Epistemic Belief Inventory (Schraw, Bendixen & Dunkle, 2002 was used and adjusted to the workplace setting. Then the results were compared to employees’ training motivation, which was measured with a questionnaire made by authors of the present study, and employees’ actual number of training hours annually. The results confirmed the relationship between the concepts as well as a significant predicting value of epistemological beliefs on motivation and actual participation. Epistemic Belief Inventory did not yield expected results reported by the authors of the instrument therefore the limitations, possible other interpretations and suggested further exploration are discussed.

  18. Are essentialist beliefs associated with prejudice?

    Science.gov (United States)

    Haslam, Nick; Rothschild, Louis; Ernst, Donald

    2002-03-01

    Gordon Allport (1954) proposed that belief in group essences is one aspect of the prejudiced personality, alongside a rigid, dichotomous and ambiguity-intolerant cognitive style. We examined whether essentialist beliefs-beliefs that a social category has a fixed, inherent, identity-defining nature-are indeed associated in this fashion with prejudice towards black people, women and gay men. Allport's claim, which is mirrored by many contemporary social theorists, received partial support but had to be qualified in important respects. Essence-related beliefs were associated strongly with anti-gay attitudes but only weakly with sexism and racism, and they did not reflect a cognitive style that was consistent across stigmatized categories. When associations with prejudice were obtained, only a few specific beliefs were involved, and some anti-essentialist beliefs were associated with anti-gay attitudes. Nevertheless, the powerful association that essence-related beliefs had with anti-gay attitudes was independent of established prejudice-related traits, indicating that they have a significant role to play in the psychology of prejudice.

  19. Lucky Belief in Science Education - Gettier Cases and the Value of Reliable Belief-Forming Processes

    Science.gov (United States)

    Brock, Richard

    2018-05-01

    The conceptualisation of knowledge as justified true belief has been shown to be, at the very least, an incomplete account. One challenge to the justified true belief model arises from the proposition of situations in which a person possesses a belief that is both justified and true which some philosophers intuit should not be classified as knowledge. Though situations of this type have been imagined by a number of writers, they have come to be labelled Gettier cases. Gettier cases arise when a fallible justification happens to lead to a true belief in one context, a case of `lucky belief'. In this article, it is argued that students studying science may make claims that resemble Gettier cases. In some contexts, a student may make a claim that is both justified and true but which arises from an alternative conception of a scientific concept. A number of instances of lucky belief in topics in science education are considered leading to an examination of the criteria teachers use to assess students' claims in different contexts. The possibility of lucky belief leads to the proposal that, in addition to the acquisition of justified true beliefs, the development of reliable belief-forming processes is a significant goal of science education. The pedagogic value of various kinds of claims is considered and, it is argued, the criteria used to judge claims may be adjusted to suit the context of assessment. It is suggested that teachers should be alert to instances of lucky belief that mask alternative conceptions.

  20. Two Types of Belief Report

    Directory of Open Access Journals (Sweden)

    Michael Hegarty

    2010-12-01

    Full Text Available Ascriptions of belief and other doxastic propositional attitudes are commonly interpreted as quantifying over a set of possible worlds constituting doxastic alternatives for the belief experiencer. Katz (2000, 2003, 2008 has argued that belief predicates and other stative attitude predicates, along with stative predicates generally, lack a Davidsonian event argument and therefore do not report on any eventuality (event or state. Hacquard (2010, in contrast, assumes that all attitude ascriptions describe an event corresponding to the mental state of the attitude experiencer. The present investigation suggests that the strengths of doxastic predicates can be modeled by generalized quantifiers over the doxastic alternative set, permitting us to formulate and test predictions based on standard interactions of these quantifiers with negation when these ascriptions are negated. This provides a middle ground between Katz and Hacquard, whereby some belief ascriptions are interpreted as nothing more than a quantified condition over a doxastic alternative set, while others attribute a Davidsonian belief state to the experiencer. In the latter case, the condition involving quantification over doxastic alternatives is an essential content condition which serves to individuate the eventuality described by the belief report, and to identify it across possible worlds.ReferencesCappelli, G. 2007. “I reckon I know how Leonardo da Vinci must have felt...” Epistemicity, Evidentiality and English Verbs of Cognitive Attitude. Pari: Pari Publishing.Carlson, G. 1998. ‘Thematic roles and the individuation of events’. In S. Rothstein (ed. ‘Events and Grammar’, 35–51. Dordrecht: Kluwer Academic Publishers.Davidson, D. 1980[1967]. ‘The Logical Form of Action Sentences’. In N. Rescher (ed. ‘The Logic of Decision and Action’, 81–95. Pittsburgh: University of Pittsburgh Press. Reprinted in Davidson, D., Essays on Actions and Events, pp. 105

  1. Applying Bayesian belief networks in rapid response situations

    Energy Technology Data Exchange (ETDEWEB)

    Gibson, William L [Los Alamos National Laboratory; Deborah, Leishman, A. [Los Alamos National Laboratory; Van Eeckhout, Edward [Los Alamos National Laboratory

    2008-01-01

    The authors have developed an enhanced Bayesian analysis tool called the Integrated Knowledge Engine (IKE) for monitoring and surveillance. The enhancements are suited for Rapid Response Situations where decisions must be made based on uncertain and incomplete evidence from many diverse and heterogeneous sources. The enhancements extend the probabilistic results of the traditional Bayesian analysis by (1) better quantifying uncertainty arising from model parameter uncertainty and uncertain evidence, (2) optimizing the collection of evidence to reach conclusions more quickly, and (3) allowing the analyst to determine the influence of the remaining evidence that cannot be obtained in the time allowed. These extended features give the analyst and decision maker a better comprehension of the adequacy of the acquired evidence and hence the quality of the hurried decisions. They also describe two example systems where the above features are highlighted.

  2. Vacation portfolio decisions: analysis using a Bayesian belief network

    NARCIS (Netherlands)

    Grigolon, A.B.; Kemperman, A.D.A.M.; Timmermans, H.J.P.

    2011-01-01

    The aim of this study is to analyse the extent to which vacation portfolio decisions are influenced by socio-demographic characteristics. A vacation portfolio involves interdependent decisions related to the facets that make the vacation trip, including transport mode, accommodation, destination,

  3. Modelling life trajectories and mode choice using Bayesian belief networks

    NARCIS (Netherlands)

    Verhoeven, M.

    2010-01-01

    Traditionally, transport mode choice was primarily examined as a stand alone problem. Given a purpose and destination, the choice of transport mode was modelled as a function of the various attributes of the transport mode alternatives. Later, transport mode choice decisions were modelled as part of

  4. Applying Bayesian belief networks in Sun Tzu's Art of war

    OpenAIRE

    Ang, Kwang Chien

    2004-01-01

    Approved for public release; distribution in unlimited. The principles of Sun Tzu's Art of War have been widely used by business executives and military officers with much success in the realm of competition and conflict. However, when conflict situations arise in a highly stressful environment coupled with the pressure of time, decision makers may not be able to consider all the key concepts when forming their decisions or strategies. Therefore, a structured reasoning approach may be used...

  5. Applying Bayesian Belief Networks in Sun Tzu's Art of War

    National Research Council Canada - National Science Library

    Ang, Kwang

    2004-01-01

    .... However, when conflict situations arise in a highly stressful environment coupled with the pressure of time, decision makers may not be able to consider all the key concepts when forming their decisions or strategies...

  6. Learning Document Semantic Representation with Hybrid Deep Belief Network

    Directory of Open Access Journals (Sweden)

    Yan Yan

    2015-01-01

    it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.

  7. Plan-Belief Revision in Jason

    DEFF Research Database (Denmark)

    Jensen, Andreas Schmidt; Villadsen, Jørgen

    2015-01-01

    When information is shared between agents of unknown reliability, it is possible that their belief bases become inconsistent. In such cases, the belief base must be revised to restore consistency, so that the agent is able to reason. In some cases the inconsistent information may be due to use of...... of incorrect plans. We extend work by Alechina et al. to revise belief bases in which plans can be dynamically added and removed. We present an implementation of the algorithm in the AgentSpeak implementation Jason....

  8. The Role of Irrational Beliefs, Self Efficacy and Social Support in Relapse of Abuse Disorder

    Directory of Open Access Journals (Sweden)

    Toraj Hashemi

    2010-05-01

    Full Text Available Aim: This study aimed to determine the role of irrational beliefs system, self efficacy and social support network in predicting of relapse/non-relapse of drug misusing, and comparison of mentioned variables between these two groups. Method: For this purpose 100 persons who had repeated relapse and 100 persons who did not have relapse were selected by available sampling of Rehabilitation Organization of Tabriz city. Albert Alic’s irrational beliefs, Sherer’s self efficacy and Wax’s social support questionnaires administered among selected samples. Results: The results showed that, there were significant differences between two relapse and non-relapse groups on irrational beliefs, self-efficacy and social support. Conclusion: The results have applied implications in addiction treatment clinics.

  9. Assessing students' beliefs, emotions and causal attribution ...

    African Journals Online (AJOL)

    Keywords: academic emotion; belief; causal attribution; statistical validation; students' conceptions of learning ... Sadi & Lee, 2015), through their effect on motivation and learning strategies .... to understand why they may or may not be doing.

  10. Hierarchies of belief and interim rationalizability

    Directory of Open Access Journals (Sweden)

    Jeffrey C. Ely

    2006-03-01

    Full Text Available In games with incomplete information, conventional hierarchies of belief are incomplete as descriptions of the players' information for the purposes of determining a player's behavior. We show by example that this is true for a variety of solution concepts. We then investigate what is essential about a player's information to identify behavior. We specialize to two player games and the solution concept of interim rationalizability. We construct the universal type space for rationalizability and characterize the types in terms of their beliefs. Infinite hierarchies of beliefs over conditional beliefs, which we call Delta-hierarchies, are what turn out to matter. We show that any two types in any two type spaces have the same rationalizable sets in all games if and only if they have the same Delta-hierarchies.

  11. Relationship between patients' beliefs about their antihypertensives ...

    African Journals Online (AJOL)

    ... patients' beliefs about their antihypertensives and adherence in a secondary hospital in ... The study was a cross-sectional study on hypertensive patients in General ... were effective in protecting them from the effects of high blood pressure.

  12. The role of beliefs in teacher agency

    DEFF Research Database (Denmark)

    Biesta, Gert; Priestley, Mark; Robinson, Sarah

    2015-01-01

    ’s Curriculum for Excellence – in order to explore these questions. We focus on teachers’ beliefs in order to get a sense of the individual and collective discourses that inform teachers’ perceptions, judgements and decision-making and that motivate and drive teachers’ action. While the research suggests...... that beliefs play an important role in teachers’ work, an apparent mismatch between teachers’ individual beliefs and values and wider institutional discourses and cultures, and a relative lack of a clear and robust professional vision of the purposes of education indicate that the promotion of teacher agency...... does not just rely on the beliefs that individual teachers bring to their practice, but also requires collective development and consideration....

  13. Descriptor revision belief change through direct choice

    CERN Document Server

    Hansson, Sven Ove

    2017-01-01

    This book provides a critical examination of how the choice of what to believe is represented in the standard model of belief change. In particular the use of possible worlds and infinite remainders as objects of choice is critically examined. Descriptors are introduced as a versatile tool for expressing the success conditions of belief change, addressing both local and global descriptor revision. The book presents dynamic descriptors such as Ramsey descriptors that convey how an agent’s beliefs tend to be changed in response to different inputs. It also explores sentential revision and demonstrates how local and global operations of revision by a sentence can be derived as a special case of descriptor revision. Lastly, the book examines revocation, a generalization of contraction in which a specified sentence is removed in a process that may possibly also involve the addition of some new information to the belief set.

  14. General family of preferential belief removal operators

    CSIR Research Space (South Africa)

    Booth, R

    2009-07-01

    Full Text Available Most belief change operators in the AGM tradition assume an underlying plausibility ordering over the possible worlds which is transitive and complete. A unifying structure for these operators, based on supplementing the plausibility ordering with a...

  15. The Making of Paranormal Belief: History, Discourse Analysis and the Object of Belief

    OpenAIRE

    White, Lewis

    2013-01-01

    The present study comprises a discursive analysis of a cognitive phenomenon, paranormal beliefs. A discursive psychological approach to belief highlights that an important component of the cognitivist work has been how the object of paranormal belief has been defined in formal study. Using discourse analysis, as developed as a method in the history of psychology, this problem is explored through analysis of published scales. The findings highlight three rhetorical themes that are deployed in ...

  16. Language Learner Beliefs from an Attributional Perspective

    OpenAIRE

    Gabillon, Zehra

    2013-01-01

    International audience; This qualitative study, aimed to analyze eight French-speaking learners' beliefs about English and English language learning. The data were obtained via semi-structured interviews. The study drew on Weiner's attribution theory of achievement motivation and Bandura's self-efficacy theory. The novelty about this research is the employment of an attributional analysis framework to study and explain the learners' stated beliefs about English and English language learning.

  17. Plural religious beliefs: A Comparison between the Dutch and white ...

    African Journals Online (AJOL)

    The concept of religious beliefs is distilled from the perspective of one's belief in God. With regard to this belief in God we propose to distinguish between two dimensions: The personal versus the a-personal character of God and his transcendent versus his immanent nature. This leaves us with a plurality of beliefs in God.

  18. Proposing an Operational Definition of Science Teacher Beliefs

    Science.gov (United States)

    Hutner, Todd L.; Markman, Arthur B.

    2016-01-01

    Much research has shown that a science teacher's beliefs are related to their teaching practice. This line of research has often defined "belief" epistemologically. That is, beliefs are often defined relative to other mental constructs, such as knowledge, dispositions, or attitudes. Left unspecified is the role beliefs play in cognition…

  19. Explaining body size beliefs in anorexia.

    Science.gov (United States)

    Gadsby, Stephen

    2017-11-01

    Cognitive neuropsychiatry has had much success in providing theoretical models for the causal origins of many delusional beliefs. Recently, it has been suggested that some anorexia nervosa patients' beliefs about their own body size should be considered delusions. As such, it seems high time the methods of cognitive neuropsychiatry were turned to modelling the false body size beliefs of anorexics. In this paper, I adopt an empiricist approach to modelling the causal origins of false body size beliefs in anorexia. Within the background of cognitive neuropsychiatry, empiricist models claim that abnormal beliefs are grounded by abnormal experiences bearing similar content. I discuss the kinds of abnormal experiences of body size anorexics suffer from which could ground their false beliefs about body size. These oversized experiences come in three varieties: false self-other body comparisons, spontaneous mental imagery of a fat body and distorted perception of affordances. Further theoretical and empirical research into the oversized experiences which anorexics suffer from presents a promising avenue for understanding and treating the disorder.

  20. Mental Rotation in False Belief Understanding.

    Science.gov (United States)

    Xie, Jiushu; Cheung, Him; Shen, Manqiong; Wang, Ruiming

    2018-05-01

    This study examines the spontaneous use of embodied egocentric transformation (EET) in understanding false beliefs in the minds of others. EET involves the participants mentally transforming or rotating themselves into the orientation of an agent when trying to adopt his or her visuospatial perspective. We argue that psychological perspective taking such as false belief reasoning may also involve EET because of what has been widely reported in the embodied cognition literature, showing that our processing of abstract, propositional information is often grounded in concrete bodily sensations which are not apparently linked to higher cognition. In Experiment 1, an agent placed a ball into one of two boxes and left. The ball then rolled out and moved either into the other box (new box) or back into the original one (old box). The participants were to decide from which box they themselves or the agent would try to recover the ball. Results showed that false belief performance was affected by increased orientation disparity between the participants and the agent, suggesting involvement of embodied transformation. In Experiment 2, false belief was similarly induced and the participants were to decide if the agent would try to recover the ball in one specific box. Orientation disparity was again found to affect false belief performance. The present results extend previous findings on EET in visuospatial perspective taking and suggest that false belief reasoning, which is a kind of psychological perspective taking, can also involve embodied rotation, consistent with the embodied cognition view. Copyright © 2018 Cognitive Science Society, Inc.

  1. Folk Beliefs of Cultural Changes in China

    Directory of Open Access Journals (Sweden)

    Yi eXu

    2014-09-01

    Full Text Available For the last several decades, Chinese society has experienced transformative changes. How are these changes understood among Chinese people? To examine this question, Part 1 in this research solicited folk beliefs of cultural change from a group of Chinese participants in an open-ended format, and the generated folk beliefs were rated by another group of participants in Part 2 to gauge each belief’s level of agreement. Part 3 plotted the folk beliefs retained in Part 2 using the Google Ngram Viewer in order to infer the amount of intellectual interests that each belief has received cross-temporarily. These analyses suggested a few themes in Chinese folk beliefs of cultural change (1 rising perceived importance of materialism and individualism in understanding contemporary Chinese culture and Chinese psychology relative to those of the past (2 rising perceived importance of freedom, democracy and human rights and (3 enduring perceived importance of family relations and friendship as well as patriotism. Interestingly, findings from Parts 2 and 3 diverged somewhat, illuminating possible divergence between folk beliefs and intellectual interests especially for issues related to heritage of Confucianism.

  2. False Belief Reasoning in Adults with and without Autistic Spectrum Disorder: Similarities and Differences

    Directory of Open Access Journals (Sweden)

    Monika Sommer

    2018-02-01

    Full Text Available A central diagnostic criteria for autism spectrum disorder (ASD is the qualitative impairment in reciprocal social interaction and a prominent hypotheses that tried to explain this impairment is the Theory of Mind (ToM deficit hypotheses. On a behavioral level the critical test for having a ToM, the understanding of false beliefs (FB, is often used for testing ToM abilities in individuals with ASD. Investigating the neural underpinnings several neuroimaging studies revealed a network of areas involved in FB reasoning in neurotypical individuals. For ASD individuals the neural correlates of false belief processing are largely unknown. Using functional magnetic resonance imaging and an adapted unexpected transfer task, that makes it possible to distinguish between the computation of diverging beliefs and the selection of a belief-associated response, we investigated a group of adult high-functioning individuals with ASD (N = 15 and an age and IQ matched group of neurotypical adults (NT; N = 15. On the behavioral level we found no group differences. On the neural level, results were two-fold: In the story phase, in which participants had to compute whether the character's belief is congruent or incongruent to their own belief, there were no differences between neurotypical participants and those diagnosed with ASD. But, in the subsequent question phase, participants with ASD showed increased activity in the bilateral anterior prefrontal cortex, the left posterior frontal cortex, the left superior temporal gyrus, and the left temporoparietal area. These results suggest that during the story phase in which the participants processed observable actions the neural correlates do not differ between adult individuals with ASD and NT individuals. But in the question phase in which participants had to infer an unobservable mental state results revealed neural differences between the two groups. Possibly, these subtle neural processing differences may

  3. Diabetes screening anxiety and beliefs.

    Science.gov (United States)

    Skinner, T C; Davies, M J; Farooqi, A M; Jarvis, J; Tringham, J R; Khunti, K

    2005-11-01

    This study assesses the impact of screening for diabetes on anxiety levels in an ethnically mixed population in the UK, and explores whether beliefs about Type 2 diabetes account for these anxiety levels. This cross-sectional study recruited individuals who were identified at high risk of developing diabetes through general practitioners' (GPs) lists or through public media recruitment. Participants completed an oral glucose tolerance test (OGTT). Between blood tests, participants completed the Spielberger State Anxiety Scale Short Form, the Emotional Stability Scale of the Big Five Inventory 44 and three scales from the Diabetes Illness Representations Questionnaire, revised for this study. Of the 1339 who completed the OGTT and questionnaire booklet, 54% were female, with 21% from an Asian background. Forty-five per cent of participants reported little to moderate amounts of anxiety at screening (mean 35.2; sd = 11.6). There was no significant effect of family history of diabetes, ethnic group or recruitment method on anxiety. The only variable significantly associated (negatively) with anxiety was the personality trait of emotional stability. Of responders, 64% and 61% agreed that diabetes was caused by diet or hereditary factors, respectively. Only 155 individuals (12%) agreed that diabetes was serious, shortens life and causes complications. The results of this study replicate that of previous studies, indicating that screening for diabetes does not induce significant anxiety. Bivariate analysis indicated that individuals who perceived diabetes to be serious, life shortening and resulting in complications had higher anxiety scores, the personality trait of emotional stability being the strongest predictor of anxiety.

  4. Effects of a Cancer Prevention Advertisement on Beliefs and Knowledge about Cancer Prevention.

    Science.gov (United States)

    Kye, Su Yeon; Yoo, Jisu; Lee, Min Hee; Jun, Jae Kwan

    2015-01-01

    Outcome-expectation beliefs and knowledge may ultimately influence behavior for cancer prevention. The aims of this study were to measure changes in knowledge and beliefs about cancer prevention before and after viewing a television advertisement and identify the factors affecting receptivity to its messages. A one-group pretest-posttest design was used in this study of 1,000 individuals aged 20 to 65 years who were recruited online in November 2014. The outcome variables included cancer prevention beliefs based on the Health Belief Model (five items) and knowledge about risk factors for cancer (seven items). Perceived susceptibility, perceived benefits, and self-efficacy increased significantly and their perceived severity and perceived barriers decreased significantly, after participants viewed the television advertisement. Correct responses to questions about risk factors also increased significantly, except for smoking. The main factors affecting changes in the outcome variables were age, interest in cancer prevention, social network, satisfaction with the ad, and pretest scores. Television advertisements with positive frameworks can be an efficient channel of improving beliefs and knowledge about cancer prevention in a short period. The continuous development of intervention materials that consider the demographics, needs, and satisfaction of the target group will be necessary for future studies.

  5. Revisiting “What They Think”: Adolescent Drinking and the Importance of Peer Beliefs

    Science.gov (United States)

    Ragan, Daniel T.

    2014-01-01

    The association between delinquent peers and delinquent behavior is among the most consistent findings in the criminological literature, and a number of recent studies have raised the standards for determining the nature and extent of peer influence. Despite these advances, however, key questions about how deviant behavior is socially transmitted remain unresolved. In particular, much of the research examining peer influence is limited to peer behavior, despite a rich literature supporting the salience of beliefs, such as expectations and moral approval, in shaping behaviors. The current study takes advantage of advances in the modeling of peer influence and selection processes to re-examine the contributions of peer beliefs and behaviors to adolescent drinking. I employ longitudinal social network analysis to examine how peers contribute to the complex interplay between deviant beliefs and behaviors. I find evidence that beliefs related to peer drinking have both a direct and indirect impact on behavior and also play an important role in the friendship selection process. These results highlight the importance of understanding how peers influence deviant behavior and suggest that peer beliefs are an important part of this relationship. PMID:25382862

  6. Gravity, God and Ghosts? Parents' Beliefs in Science, Religion, and the Paranormal and the Encouragement of Beliefs in Their Children

    Science.gov (United States)

    Braswell, Gregory S.; Rosengren, Karl S.; Berenbaum, Howard

    2012-01-01

    Using a questionnaire, the present study examined parents' beliefs regarding the development of children's beliefs about science, religion, and the paranormal. The study also investigated parental encouragement of children's beliefs, as well as parents' own beliefs within these domains. Results revealed that parents make distinctions between…

  7. Effects of Epistemological Beliefs and Topic-Specific Beliefs on Undergraduates' Cognitive and Strategic Processing of Dual-Positional Text.

    Science.gov (United States)

    Kardash, CarolAnne M.; Howell, Karen L.

    2000-01-01

    Investigates effects of epistemological beliefs and topic-specific beliefs on undergraduates' (N=40) cognitive and strategic processing of a dual-positional text. Findings reveal that epistemological beliefs about the speed of learning affected the overall number of cognitive processes exhibited, whereas topic-specific beliefs interacted with the…

  8. When fast logic meets slow belief: Evidence for a parallel-processing model of belief bias.

    Science.gov (United States)

    Trippas, Dries; Thompson, Valerie A; Handley, Simon J

    2017-05-01

    Two experiments pitted the default-interventionist account of belief bias against a parallel-processing model. According to the former, belief bias occurs because a fast, belief-based evaluation of the conclusion pre-empts a working-memory demanding logical analysis. In contrast, according to the latter both belief-based and logic-based responding occur in parallel. Participants were given deductive reasoning problems of variable complexity and instructed to decide whether the conclusion was valid on half the trials or to decide whether the conclusion was believable on the other half. When belief and logic conflict, the default-interventionist view predicts that it should take less time to respond on the basis of belief than logic, and that the believability of a conclusion should interfere with judgments of validity, but not the reverse. The parallel-processing view predicts that beliefs should interfere with logic judgments only if the processing required to evaluate the logical structure exceeds that required to evaluate the knowledge necessary to make a belief-based judgment, and vice versa otherwise. Consistent with this latter view, for the simplest reasoning problems (modus ponens), judgments of belief resulted in lower accuracy than judgments of validity, and believability interfered more with judgments of validity than the converse. For problems of moderate complexity (modus tollens and single-model syllogisms), the interference was symmetrical, in that validity interfered with belief judgments to the same degree that believability interfered with validity judgments. For the most complex (three-term multiple-model syllogisms), conclusion believability interfered more with judgments of validity than vice versa, in spite of the significant interference from conclusion validity on judgments of belief.

  9. Formal and Informal Normative Beliefs Regarding Purchasing and Using Condoms

    OpenAIRE

    樋口, 匡貴; 中村, 菜々子

    2009-01-01

    Properly using condoms is one of the most effective types of protection against HIV. To clarify the contents of normative beliefs regarding purchasing and using condoms, 390 undergraduate student volunteers were surveyed. The exploratory and confirmatory factor analyses revealed that both males and females held two types of normative beliefs, namely formal normative beliefs and informal normative beliefs, regarding purchasing and using condoms. Formal normative beliefs were concerned with the...

  10. Psychics, aliens, or experience? Using the Anomalistic Belief Scale to examine the relationship between type of belief and probabilistic reasoning.

    Science.gov (United States)

    Prike, Toby; Arnold, Michelle M; Williamson, Paul

    2017-08-01

    A growing body of research has shown people who hold anomalistic (e.g., paranormal) beliefs may differ from nonbelievers in their propensity to make probabilistic reasoning errors. The current study explored the relationship between these beliefs and performance through the development of a new measure of anomalistic belief, called the Anomalistic Belief Scale (ABS). One key feature of the ABS is that it includes a balance of both experiential and theoretical belief items. Another aim of the study was to use the ABS to investigate the relationship between belief and probabilistic reasoning errors on conjunction fallacy tasks. As expected, results showed there was a relationship between anomalistic belief and propensity to commit the conjunction fallacy. Importantly, regression analyses on the factors that make up the ABS showed that the relationship between anomalistic belief and probabilistic reasoning occurred only for beliefs about having experienced anomalistic phenomena, and not for theoretical anomalistic beliefs. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. The extended reciprocity: Strong belief outperforms persistence.

    Science.gov (United States)

    Kurokawa, Shun

    2017-05-21

    The existence of cooperation is a mysterious phenomenon and demands explanation, and direct reciprocity is one key potential explanation for the evolution of cooperation. Direct reciprocity allows cooperation to evolve for cooperators who switch their behavior on the basis of information about the opponent's behavior. Here, relevant to direct reciprocity is information deficiency. When the opponent's last move is unknown, how should players behave? One possibility is to choose cooperation with some default probability without using any further information. In fact, our previous paper (Kurokawa, 2016a) examined this strategy. However, there might be beneficial information other than the opponent's last move. A subsequent study of ours (Kurokawa, 2017) examined the strategy which uses the own last move when the opponent's last move is unknown, and revealed that referring to the own move and trying to imitate it when information is absent is beneficial. Is there any other beneficial information else? How about strong belief (i.e., have infinite memory and believe that the opponent's behavior is unchanged)? Here, we examine the evolution of strategies with strong belief. Analyzing the repeated prisoner's dilemma game and using evolutionarily stable strategy (ESS) analysis against an invasion by unconditional defectors, we find the strategy with strong belief is more likely to evolve than the strategy which does not use information other than the opponent player's last move and more likely to evolve than the strategy which uses not only the opponent player's last move but also the own last move. Strong belief produces the extended reciprocity and facilitates the evolution of cooperation. Additionally, we consider the two strategies game between strategies with strong belief and any strategy, and we consider the four strategies game in which unconditional cooperators, unconditional defectors, pessimistic reciprocators with strong belief, and optimistic reciprocators with

  12. An fMRI study on the comparison of different types of false belief reasoning: False belief-based emotion and behavior attribution.

    Science.gov (United States)

    Döhnel, Katrin; Schuwerk, Tobias; Sodian, Beate; Hajak, Göran; Rupprecht, Rainer; Sommer, Monika

    2017-12-01

    False belief (FB) reasoning is a key Theory of Mind (ToM) competence. By 4 years of age, children understand that a person's behavior can be based on a FB about reality. Children cannot understand that a person's emotion can also be based on a FB before the age of six. In order to generate hypothesis on basic processes distinguishing these two types of belief reasoning, the present functional magnetic resonance imaging study in adults directly compares functional activity associated with these two FB tasks. Both tasks were associated with activity in the ToM network including the medial prefrontal cortex and the left temporo-parietal junction. Differential activity was observed in the anterior dorsolateral prefrontal cortex for FB-based emotion relative to behavior attribution. Contrary to FB behavior attribution, FB-based emotion attribution requires the processing of two different mental states: a belief and an emotion and their relation to each other. The activity pattern may reflect the differential demands on cognitive processes associated with the two different belief-based attribution processes. These results shed new light on the still ongoing debate about the nature of the developmental lag between the two FB tasks.

  13. STATED VS. ENACTED BELIEFS: LOOKING AT PRE-SERVICE TEACHERS' PEDAGOGICAL BELIEFS THROUGH CLASSROOM INTERACTION

    Directory of Open Access Journals (Sweden)

    Alberto Fajardo

    2013-08-01

    Full Text Available This article explores the relationship between pedagogical beliefs and classroom practice. Two Colombian pre-service primary school language teachers in the final stage of their five-year training programme were the research participants. Interview and classroom observation were the methods used, and content analysis was the analytical approach. It is argued in this study that by comparing the stated beliefs (as articulated in interviews and enacted beliefs (as manifested in classroom interaction, it is possible to gain a fine-grained understanding of the relationship between beliefs and teaching practice. The findings suggested that while there were significant cases of coherence between beliefs and classroom action, there was also evidence of some incongruent relationships.

  14. Paranormal beliefs and religiosity: Chinese version of the Revised Paranormal Belief Scale.

    Science.gov (United States)

    Shiah, Yung-Jong; Tam, Wai-Cheong Carl; Wu, Ming-Hsun; Chang, Frances

    2010-10-01

    This paper reports an initial study investigating the relations of paranormal beliefs with religiosity in a Chinese sample, as well as the development of a Chinese version of the Revised Paranormal Belief Scale and a test of its psychometric properties with 310 college students (5.5% Christians, 21.3% Buddhists, 61% believers in traditional Chinese religions, and 12% atheists). The reliability and validity of the Chinese version were satisfactory. In general, traditional Chinese religious believers had higher scores on paranormal belief than did Christians and atheists, and the mean total score of the Chinese participants was higher than previously reported in a Western sample. It was concluded that the greater involvement of practitioners of traditional Chinese religions in activities emphasizing paranormal experiences might contribute to their greater paranormal belief, especially as compared to the minority Christian group. The results are consistent with the idea that Christianity may offer the least support for paranormal belief.

  15. Belief Functions: Theory and Applications - Proceedings of the 2nd International Conference on Belief Functions

    CERN Document Server

    Masson, Marie-Hélène

    2012-01-01

    The theory of belief functions, also known as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the Transferable Belief Model and the Theory of Hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories.   This volume contains the proceedings of the 2nd International Conference on Belief Functions that was held in Compiègne, France on 9-11 May 2012. It gathers 51 contributions describing recent developments both on theoretical issues (including approximation methods, combination rules, continuous belief functions, graphical models and independence concepts) an...

  16. Paranormal beliefs of Latvian college students: a Latvian version of the revised paranormal belief scale.

    Science.gov (United States)

    Utinans, A; Ancane, G; Tobacyk, J J; Boyraz, G; Livingston, M M; Tobacyk, J S

    2015-02-01

    A Latvian version of the Revised Paranormal Belief Scale (RPBS) was completed by 229 Latvian university students. Exploratory and confirmatory factor analyses revealed six relatively independent factors labeled Magical Abilities, Psychokinesis, Traditional Religious Belief, Superstition, Spirit Travel, and Extraordinary Life Forms. Based on the motivational-control model, it was hypothesized that the societal stressors affecting Latvian society during the last 50 yr. have led to a reduced sense of personal control which, in turn, has resulted in increased endorsement of paranormal beliefs to re-establish a sense of control. The motivational-control hypothesis was not supported. Results indicated that (except for Traditional Religious Belief in women), the majority of these students were disbelievers in paranormal phenomena. As hypothesized, Latvian women reported significantly greater paranormal belief than men.

  17. Dynamics of organizational culture: Individual beliefs vs. social conformity.

    Science.gov (United States)

    Ellinas, Christos; Allan, Neil; Johansson, Anders

    2017-01-01

    The complex nature of organizational culture challenges our ability to infer its underlying dynamics from observational studies. Recent computational studies have adopted a distinctly different view, where plausible mechanisms are proposed to describe a wide range of social phenomena, including the onset and evolution of organizational culture. In this spirit, this work introduces an empirically-grounded, agent-based model which relaxes a set of assumptions that describes past work-(a) omittance of an individual's strive for achieving cognitive coherence; (b) limited integration of important contextual factors-by utilizing networks of beliefs and incorporating social rank into the dynamics. As a result, we illustrate that: (i) an organization may appear to be increasingly coherent in terms of its organizational culture, yet be composed of individuals with reduced levels of coherence; (ii) the components of social conformity-peer-pressure and social rank-are influential at different aggregation levels.

  18. Health beliefs, attitudes and service utilization among Haitians.

    Science.gov (United States)

    Allen, Jennifer D; Mars, Dana R; Tom, Laura; Apollon, Guy; Hilaire, Dany; Iralien, Gerald; Cloutier, Lindsay B; Sheets, Margaret M; Zamor, Riché

    2013-02-01

    Understanding the factors that influence health beliefs, attitudes, and service use among Haitians in the United States is increasingly important for this growing population. We undertook a qualitative analysis to explore the factors related to cancer screening and utilization of health services among Haitians in Boston. Key informant interviews (n=42) and nine focus groups (n=78) revealed that Haitians experience unique barriers to health services. These include language barriers, unfamiliarity with preventive care, confidentiality concerns, mistrust and stigma concerning Western medicine, and a preference for natural remedies. Results suggest that many Haitians could benefit from health system navigation assistance, and highlight the need for comprehensive, rather than disease-focused programs, to decrease stigma and increase programmatic reach. Faith-based organizations, social service agencies, and Haitian media were identified as promising channels for disseminating health information. Leveraging positive cultural traditions and existing communication networks could increase the impact of Haitian health initiatives.

  19. Functional neuroimaging of belief, disbelief, and uncertainty.

    Science.gov (United States)

    Harris, Sam; Sheth, Sameer A; Cohen, Mark S

    2008-02-01

    The difference between believing and disbelieving a proposition is one of the most potent regulators of human behavior and emotion. When one accepts a statement as true, it becomes the basis for further thought and action; rejected as false, it remains a string of words. The purpose of this study was to differentiate belief, disbelief, and uncertainty at the level of the brain. We used functional magnetic resonance imaging (fMRI) to study the brains of 14 adults while they judged written statements to be "true" (belief), "false" (disbelief), or "undecidable" (uncertainty). To characterize belief, disbelief, and uncertainty in a content-independent manner, we included statements from a wide range of categories: autobiographical, mathematical, geographical, religious, ethical, semantic, and factual. The states of belief, disbelief, and uncertainty differentially activated distinct regions of the prefrontal and parietal cortices, as well as the basal ganglia. Belief and disbelief differ from uncertainty in that both provide information that can subsequently inform behavior and emotion. The mechanism underlying this difference appears to involve the anterior cingulate cortex and the caudate. Although many areas of higher cognition are likely involved in assessing the truth-value of linguistic propositions, the final acceptance of a statement as "true" or its rejection as "false" appears to rely on more primitive, hedonic processing in the medial prefrontal cortex and the anterior insula. Truth may be beauty, and beauty truth, in more than a metaphorical sense, and false propositions may actually disgust us.

  20. Linking unfounded beliefs to genetic dopamine availability

    Science.gov (United States)

    Schmack, Katharina; Rössler, Hannes; Sekutowicz, Maria; Brandl, Eva J.; Müller, Daniel J.; Petrovic, Predrag; Sterzer, Philipp

    2015-01-01

    Unfounded convictions involving beliefs in the paranormal, grandiosity ideas or suspicious thoughts are endorsed at varying degrees among the general population. Here, we investigated the neurobiopsychological basis of the observed inter-individual variability in the propensity toward unfounded beliefs. One hundred two healthy individuals were genotyped for four polymorphisms in the COMT gene (rs6269, rs4633, rs4818, and rs4680, also known as val158met) that define common functional haplotypes with substantial impact on synaptic dopamine degradation, completed a questionnaire measuring unfounded beliefs, and took part in a behavioral experiment assessing perceptual inference. We found that greater dopamine availability was associated with a stronger propensity toward unfounded beliefs, and that this effect was statistically mediated by an enhanced influence of expectations on perceptual inference. Our results indicate that genetic differences in dopaminergic neurotransmission account for inter-individual differences in perceptual inference linked to the formation and maintenance of unfounded beliefs. Thus, dopamine might be critically involved in the processes underlying one's interpretation of the relationship between the self and the world. PMID:26483654

  1. Linking unfounded beliefs to genetic dopamine availability

    Directory of Open Access Journals (Sweden)

    Katharina eSchmack

    2015-09-01

    Full Text Available Unfounded convictions involving beliefs in the paranormal, grandiosity ideas or suspicious thoughts are endorsed at varying degrees among the general population. Here, we investigated the neurobiopsychological basis of the observed inter-individual variability in the propensity towards unfounded beliefs. 109 healthy individuals were genotyped for four polymorphisms in the COMT gene (rs6269, rs4633, rs4818 and rs4680, also known as val158met that define common functional haplotypes with substantial impact on synaptic dopamine degradation, completed a questionnaire measuring unfounded beliefs, and took part in a behavioural experiment assessing perceptual inference. We found that greater dopamine availability was associated with a stronger propensity towards unfounded beliefs, and that this effect was mediated by an enhanced influence of expectations on perceptual inference. Our results indicate that genetic differences in dopaminergic neurotransmission account for inter-individual differences in perceptual inference linked to the formation and maintenance of unfounded beliefs. Thus, dopamine might be critically involved in the processes underlying one's interpretation of the relationship between the self and the world.

  2. Cultural expressions of social class and their implications for group-related beliefs and behaviors

    OpenAIRE

    Rheinschmidt-Same, Michelle; Becker, Julia; Kraus, Michael

    2017-01-01

    In the wake of the Great Recession, rising inequality has increased social class disparities between people in society. In this research, we examine how differences in social class shape unique patterns of cultural expression, and how these cultural expressions affirm ingroup beliefs. In Study 1 (N=113), we provide evidence that cultural expressions of social class on an online social network can signal the social class of targets: by simply viewing the cultural practices of individuals captu...

  3. False belief reasoning in the brain: An ERP study

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Understanding others mind and interpersonal interaction are the cognitive basis of successful social interactions. People’s mental states and behaviors rely on their holding beliefs for self and others. To investigate the neural substrates of false belief reasoning, the 32 channels event-related potentials (ERP) of 14 normal adults were measured while they understood false-belief and true belief used de-ceptive appearance task. After onset of the false-belief or true-belief questions, N100, P200 and late negative component (LNC) were elicited at centro-frontal sites. Compared with true belief, false belief reasoning elicited significant declined LNC in the time window from 400 to 800 ms. The source analysis of difference wave (False minus True) showed a dipole located in the middle cingulated cortex. These findings show that false belief reasoning probably included inhibitive process.

  4. False belief reasoning in the brain: An ERP study

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Understanding others mind and interpersonal interaction are the cognitive basis of successful social interactions. People's mental states and behaviors rely on their holding beliefs for self and others. To investigate the neural substrates of false belief reasoning, the 32 channels event-related potentials (ERP) of 14 normal adults were measured while they understood false-belief and true belief used deceptive appearance task. After onset of the false-belief or true-belief questions, N100, P200 and late negative component (LNC) were elicited at centro-frontal sites. Compared with true belief, false belief reasoning elicited significant declined LNC in the time window from 400 to 800 ms. The source analysis of difference wave (False minus True) showed a dipole located in the middle cingulated cortex. These findings show that false belief reasoning probably included inhibitive process.

  5. Knowledge and Beliefs About E-Cigarettes in Straight-to-Work Young Adults.

    Science.gov (United States)

    Gowin, Mary; Cheney, Marshall K; Wann, Taylor F

    2017-02-01

    Young adults are a growing segment of electronic cigarette (e-cigarette) users. Young adults who go straight to work (STW) from high school make up a large portion of the young adult population, yet research to date has focused on college-educated young adults. This study explored STW young adult beliefs and knowledge about e-cigarettes. Semistructured individual interviews were used to elicit in-depth information from STW young adults ages 19-31 from a state in the southwest United States. Thirty interviews were conducted focusing on beliefs about e-cigarettes, current knowledge, and information-seeking practices. Interviews were recorded, transcribed, and analyzed using NVivo. Nine themes were identified falling into three categories: (1) beliefs about e-cigarettes, (2) knowledge about e-cigarettes, and (3) personal rules about e-cigarettes. STW young adults held positive beliefs about the health and safety of e-cigarettes for themselves, others, and the environment. They reported their social networks and the Internet as reliable sources of information about e-cigarettes, but they reported parents as the best source for advice. Participants had rules about e-cigarettes that contradicted some of their beliefs such as using e-cigarettes around children indicating that their beliefs were not as strongly held as they initially reported. Industry marketing and contradictory information may contribute to STW young adult knowledge and beliefs about e-cigarettes. Lack of credible public health information may also contribute to this issue. Ensuring that what is known about the benefits and harms of e-cigarettes is conveyed through multichannel communication and continued monitoring of marketing practices of the e-cigarette industry in light of the soon to be implemented regulations should be top priorities for public health. Beliefs and knowledge of STW young adults have not been explored even though they are heavily targeted by the e-cigarette industry. This group

  6. Betting and Belief: Modeling the Impact of Prediction Markets on Public Attribution of Climate Change

    Science.gov (United States)

    Gilligan, J. M.; Nay, J. J.; van der Linden, M.

    2016-12-01

    Despite overwhelming scientific evidence and an almost complete consensus among scientists, a large fraction of the American public is not convinced that global warming is anthropogenic. This doubt correlates strongly with political, ideological, and cultural orientation. [1] It has been proposed that people who do not trust climate scientists tend to trust markets, so prediction markets might be able to influence their beliefs about the causes of climate change. [2] We present results from an agent-based simulation of a prediction market in which traders invest based on their beliefs about what drives global temperature change (here, either CO2 concentration or total solar irradiance (TSI), which is a popular hypothesis among many who doubt the dominant role of CO2). At each time step, traders use historical and observed temperatures and projected future forcings (CO2 or TSI) to update Bayesian posterior probability distributions for future temperatures, conditional on their belief about what drives climate change. Traders then bet on future temperatures by trading in climate futures. Trading proceeds by a continuous double auction. Traders are randomly assigned initial beliefs about climate change, and they have some probability of changing their beliefs to match those of the most successful traders in their social network. We simulate two alternate realities in which the global temperature is controlled either by CO2 or by TSI, with stochastic noise. In both cases traders' beliefs converge, with a large majority reaching agreement on the actual cause of climate change. This convergence is robust, but the speed with which consensus emerges depends on characteristics of the traders' psychology and the structure of the market. Our model can serve as a test-bed for studying how beliefs might evolve under different market structures and different modes of decision-making and belief-change. We will report progress on studying alternate models of belief-change. This

  7. Examining Belief and Confidence in Schizophrenia

    Science.gov (United States)

    Joyce, Dan W.; Averbeck, Bruno B.; Frith, Chris D.; Shergill, Sukhwinder S.

    2018-01-01

    Background People with psychoses often report fixed, delusional beliefs that are sustained even in the presence of unequivocal contrary evidence. Such delusional beliefs are the result of integrating new and old evidence inappropriately in forming a cognitive model. We propose and test a cognitive model of belief formation using experimental data from an interactive “Rock Paper Scissors” game. Methods Participants (33 controls and 27 people with schizophrenia) played a competitive, time-pressured interactive two-player game (Rock, Paper, Scissors). Participant’s behavior was modeled by a generative computational model using leaky-integrator and temporal difference methods. This model describes how new and old evidence is integrated to form both a playing strategy to beat the opponent and provide a mechanism for reporting confidence in one’s playing strategy to win against the opponent Results People with schizophrenia fail to appropriately model their opponent’s play despite consistent (rather than random) patterns that can be exploited in the simulated opponent’s play. This is manifest as a failure to weigh existing evidence appropriately against new evidence. Further, participants with schizophrenia show a ‘jumping to conclusions’ bias, reporting successful discovery of a winning strategy with insufficient evidence. Conclusions The model presented suggests two tentative mechanisms in delusional belief formation – i) one for modeling patterns in other’s behavior, where people with schizophrenia fail to use old evidence appropriately and ii) a meta-cognitive mechanism for ‘confidence’ in such beliefs where people with schizophrenia overweight recent reward history in deciding on the value of beliefs about the opponent. PMID:23521846

  8. Beliefs underlying Women's intentions to consume alcohol.

    Science.gov (United States)

    Haydon, Helen M; Obst, Patricia L; Lewis, Ioni

    2016-07-13

    Changing trends demonstrate that women, in a number of economically-developed countries, are drinking at higher levels than ever before. Exploring key targets for intervention, this study examined the extent to which underlying beliefs in relation to alcohol consumption predicted intentions to drink in three different ways (i.e. low risk drinking, frequent drinking and binge drinking). Utilizing a prospective design survey, women (N = 1069), aged 18-87 years, completed a questionnaire measuring their beliefs and intentions regarding alcohol consumption. Then, two weeks later, 845 of the original sample, completed a follow-up questionnaire reporting their engagement in the drinking behaviors. A mixed design ANOVA was conducted to examine potential differences between women of different age groups (18-24, 25-34, 35-44, 45-54, 55 years and above) and their intentions to engage in the three different drinking behaviors. Based upon The Theory of Planned Behavior, critical beliefs analyses were carried out to identify key determinants underlying intentions to engage in the three different drinking behaviors. Significant effects of age were found in relation to frequent and binge drinking. The critical beliefs analyses revealed that a number of behavioral, control and normative beliefs were significant predictors of intentions. These beliefs varied according to age group and drinking behavior. Previously unidentified key factors that influence women's decisions to drink in certain ways have been established. Overall, future interventions and public policy may be better tailored so as to address specific age groups and drinking behaviors.

  9. Smoking beliefs and behavior among youth in Malaysia and Thailand.

    Science.gov (United States)

    Parkinson, Carla M; Hammond, David; Fong, Geoffrey T; Borland, Ron; Omar, Maizurah; Sirirassamee, Buppha; Awang, Rahmat; Driezen, Pete; Thompson, Mary

    2009-01-01

    To characterize smoking beliefs among Thai and Malaysian youth and to examine associations with gender, antismoking media exposure, and smoking status. Nationally representative samples of youth completed self-administered questionnaires. A substantial proportion of youth reported positive beliefs about smoking. Those reporting positive beliefs were more likely to be susceptible to smoking. Youth who noticed antismoking media were less likely to report positive beliefs about smoking. As in Western countries, beliefs about smoking held by youth in Southeast Asia are associated with smoking status. Antismoking media may be an important means of targeting beliefs about smoking among youth.

  10. Erosion of belief and disbelief: effects of religiosity and negative affect on beliefs in the paranormal and supernatural.

    Science.gov (United States)

    Beck, R; Miller, J P

    2001-04-01

    The authors investigated the effects of religiosity and negative affect on beliefs in the paranormal and supernatural among 94 undergraduate students enrolled in psychology classes at a small, private U.S. university. They hypothesized that religiosity would predict differential beliefs in the supernatural versus the paranormal but that negative affect would attenuate these beliefs. In addition, the authors predicted that belief in the supernatural and negative affect would interact to predict belief in the paranormal. Overall, the results were consistent with predictions. The religious participants were skeptical of paranormal phenomena but were accepting of supernatural phenomena. In addition, increased reports of negative affect over the preceding year appeared to attenuate belief in the supernatural for the religious participants. By contrast, for the nonreligious participants, increased belief in both the supernatural and paranormal was predicted when reports of negative affect were high. Finally, the interaction of supernatural belief and negative affect significantly predicted belief in the paranormal.

  11. Conflicting belief systems: some implications for education

    Directory of Open Access Journals (Sweden)

    E.J. van Niekerk

    1999-03-01

    Full Text Available In this article the conceptions of knowledge and time within Christianity, secular humanism and traditional African religion are juxtaposed. In order to emphasise the vital role o f belief systems in the field of education, some educational implications are inferred from these different conceptions of knowledge and time. The need to create enough space within the South African education system so that parents will be able to send their children to schools where education is conducted according to their particular belief systems is also foregrounded.

  12. Deep Belief Nets for Topic Modeling

    DEFF Research Database (Denmark)

    Maaløe, Lars; Arngren, Morten; Winther, Ole

    2015-01-01

    -formative. In this paper we describe large-scale content based collaborative filtering for digital publishing. To solve the digital publishing recommender problem we compare two approaches: latent Dirichlet allocation (LDA) and deep be-lief nets (DBN) that both find low-dimensional latent representations for documents....... Efficient retrieval can be carried out in the latent representation. We work both on public benchmarks and digital media content provided by Issuu, an on-line publishing platform. This article also comes with a newly developed deep belief nets toolbox for topic modeling tailored towards performance...

  13. Religious Beliefs and Environmental Behaviors in China

    Directory of Open Access Journals (Sweden)

    Yu Yang

    2018-03-01

    Full Text Available The role of religion in the environment has yet to be empirically investigated in the country with the largest atheist population across the globe. Using data from the Chinese General Social Survey 2013, we examined the effects of religious beliefs on environmental behaviors in China. Dependent variables of private and public environmental behaviors were identified by factor analysis. The estimation revealed a contradictory result that most religious beliefs had negative effects on private environmental behaviors while having positive effects on public environmental behaviors. The findings suggest a religion–politics interactive mechanism to enhance pro-environmental behavior in China.

  14. Self Confidence Spillovers and Motivated Beliefs

    DEFF Research Database (Denmark)

    Banerjee, Ritwik; Gupta, Nabanita Datta; Villeval, Marie Claire

    that success when competing in a task increases the performers’ self-confidence and competitiveness in the subsequent task. We also find that such spillovers affect the self-confidence of low-status individuals more than that of high-status individuals. Receiving good news under Affirmative Action, however......Is success in a task used strategically by individuals to motivate their beliefs prior to taking action in a subsequent, unrelated, task? Also, is the distortion of beliefs reinforced for individuals who have lower status in society? Conducting an artefactual field experiment in India, we show...

  15. Valence-Dependent Belief Updating: Computational Validation

    Directory of Open Access Journals (Sweden)

    Bojana Kuzmanovic

    2017-06-01

    Full Text Available People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates with trials with bad news (worse-than-expected base rates. After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on

  16. Expectations and Beliefs in Science Communication

    DEFF Research Database (Denmark)

    Meyer, Gitte

    2016-01-01

    communication practices, it is argued that deep beliefs may constitute drivers of hype that are particularly difficult to deal with. To participants in science communication, the discouragement of hype, viewed as a practical–ethical challenge, can be seen as a learning exercise that includes critical attention......; gene therapy was not universally hyped. Against that background, attention is directed towards another area of variation in the material: different basic assumptions about science and scientists. Exploring such culturally rooted assumptions and beliefs and their possible significance to science...

  17. The birth beliefs scale - a new measure to assess basic beliefs about birth.

    Science.gov (United States)

    Preis, Heidi; Benyamini, Yael

    2017-03-01

    Basic beliefs about birth as a natural and safe or a medical and risky process are central in the decisions on where and how to birth. Despite their importance, they have not been studied separately from other childbirth-related constructs. Our aim was to develop a measure to assess these beliefs. Pregnant Israeli women (N = 850, gestational week ≥14) were recruited in women's health centers, in online natural birth forums, and through home midwives. Participants filled in questionnaires including sociodemographic and obstetric background, the Birth Beliefs Scale (BBS), dispositional desire for control (DC) and planned mode of delivery. Factor analyses revealed that the BBS is composed of two factors: beliefs about birth as a natural process and beliefs about birth as a medical process. Both subscales showed good internal and test-retest reliability. They had good construct validity, predicted birth choices, and were weakly correlated with DC. Women's medical obstetric history was associated with the BBS, further supporting the validity of the scale. Beliefs about birth may be the building blocks that make up perceptions of birth and drive women's preferences. The new scale provides an easy way to distinctly assess them so they can be used to further understand planned birth behaviors. Additional studies are needed to comprehend how these beliefs form in different cultural contexts and how they evolve over time.

  18. Delusions and the Right Hemisphere: A Review of the Case for the Right Hemisphere as a Mediator of Reality-Based Belief.

    Science.gov (United States)

    Gurin, Lindsey; Blum, Sonja

    2017-01-01

    Delusions are beliefs that remain fixed despite evidence that they are incorrect. Although the precise neural mechanism of delusional belief remains to be elucidated, there is a predominance of right-hemisphere lesions among patients with delusional syndromes accompanied by structural pathology, suggesting that right-hemisphere lesions, or networks with key nodes in the right hemisphere, may be playing a role. The authors discuss the potential theoretical basis and empiric support for a specific right-hemisphere role in delusion production, drawing on its roles in pragmatic communication; perceptual integration; attentional surveillance and anomaly/novelty detection; and belief updating.

  19. Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

    Science.gov (United States)

    Gilligan, J. M.; John, N. J.; van der Linden, M.

    2015-12-01

    Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

  20. Organizational Conspiracy Beliefs: Implications for Leadership Styles and Employee Outcomes.

    Science.gov (United States)

    van Prooijen, Jan-Willem; de Vries, Reinout E

    2016-01-01

    Belief in conspiracy theories about societal events is widespread among citizens. The extent to which conspiracy beliefs about managers and supervisors matter in the micro-level setting of organizations has not yet been examined, however. We investigated if leadership styles predict conspiracy beliefs among employees in the context of organizations. Furthermore, we examined if such organizational conspiracy beliefs have implications for organizational commitment and turnover intentions. We conducted a survey among a random sample of the US working population ( N  = 193). Despotic, laissez-faire, and participative leadership styles predicted organizational conspiracy beliefs, and the relations of despotic and laissez-faire leadership with conspiracy beliefs were mediated by feelings of job insecurity. Furthermore, organizational conspiracy beliefs predicted, via decreased organizational commitment, increased turnover intentions. Organizational conspiracy beliefs matter for how employees perceive their leaders, how they feel about their organization, and whether or not they plan to quit their jobs. A practical implication, therefore, is that it would be a mistake for managers to dismiss organizational conspiracy beliefs as innocent rumors that are harmless to the organization. Three novel conclusions emerge from this study. First, organizational conspiracy beliefs occur frequently among employees. Second, participative leadership predicts decreased organizational conspiracy beliefs; despotic and laissez-faire leadership predict increased organizational conspiracy beliefs due to the contribution of these destructive leadership styles to an insecure work environment. Third, organizational conspiracy beliefs harm organizations by influencing employee commitment and, indirectly, turnover intentions.

  1. Prospective Elemantary Science Teachers' Epistemological Beliefs

    Science.gov (United States)

    Macaroglu Akgul, Esra; Oztuna Kaplan, Aysun

    2009-01-01

    This research study examined "prospective elementary science teachers' epistemological beliefs". Forty-nine prospective elementary science teachers participated into research. The research was designed in both quantitative and qualitative manner, within the context of "Special Methods in Science Teaching I" course.…

  2. Islamic Philosophy and the Ethics of Belief

    NARCIS (Netherlands)

    Booth, Anthony Robert

    In this book the author argues that the Falasifa, the Philosophers of the Islamic Golden Age, are usefully interpreted through the prism of the contemporary, western ethics of belief. He contends that their position amounts to what he calls ‘Moderate Evidentialism’ – that only for the epistemic

  3. Agent Communication for Dynamic Belief Update

    Science.gov (United States)

    Kobayashi, Mikito; Tojo, Satoshi

    Thus far, various formalizations of rational / logical agent model have been proposed. In this paper, we include the notion of communication channel and belief modality into update logic, and introduce Belief Update Logic (BUL). First, we discuss that how we can reformalize the inform action of FIPA-ACL into communication channel, which represents a connection between agents. Thus, our agents can send a message only when they believe, and also there actually is, a channel between him / her and a receiver. Then, we present a static belief logic (BL) and show its soundness and completeness. Next, we develop the logic to BUL, which can update Kripke model by the inform action; in which we show that in the updated model the belief operator also satisfies K45. Thereafter, we show that every sentence in BUL can be translated into BL; thus, we can contend that BUL is also sound and complete. Furthermore, we discuss the features of CUL, including the case of inconsistent information, as well as channel transmission. Finally, we summarize our contribution and discuss some future issues.

  4. Belief-Policies Cannot Ground Doxastic Responsibility

    NARCIS (Netherlands)

    Peels, H.D.

    2013-01-01

    William Alston has provided a by now well-known objection to the deontological conception of epistemic justification by arguing that since we lack control over our beliefs, we are not responsible for them. It is widely acknowledged that if Alston's argument is convincing, then it seems that the very

  5. Cultural Context Shapes Essentialist Beliefs about Religion

    Science.gov (United States)

    Chalik, Lisa; Leslie, Sarah-Jane; Rhodes, Marjorie

    2017-01-01

    The present study investigates the processes by which essentialist beliefs about religious categories develop. Children (ages 5 and 10) and adults (n = 350) from 2 religious groups (Jewish and Christian), with a range of levels of religiosity, completed switched-at-birth tasks in which they were told that a baby had been born to parents of 1…

  6. Imprecise Beliefs in a Principal Agent Model

    NARCIS (Netherlands)

    Rigotti, L.

    1998-01-01

    This paper presents a principal-agent model where the agent has multiple, or imprecise, beliefs. We model this situation formally by assuming the agent's preferences are incomplete. One can interpret this multiplicity as an agent's limited knowledge of the surrounding environment. In this setting,

  7. Parent-Child Agreement on Attributional Beliefs.

    Science.gov (United States)

    Cashmore, Judith A.; Goodnow, Jacqueline J.

    1986-01-01

    Explores extent to which parents and their adolescent children agree with respect to their attributional beliefs. First-born Australian children of Anglo and Italian backgrounds and their parents ranked talent, effort, and teaching according to relative importance in the development of six skill areas. Variations in patterns of attributions…

  8. Meteor Beliefs Project: ``Year of Meteors''

    Science.gov (United States)

    McBeath, Alastair; Drobnock, George J.; Gheorghe, Andrei Dorian

    2011-10-01

    We present a discussion linking ideas from a modern music album by Laura Veirs back to a turbulent time in American history 150 years ago, which inspired poet Walt Whitman to compose his poem "Year of Meteors", and the meteor beliefs of the period around 1859-1860, when collection of facts was giving way to analyses and theoretical explanations in meteor science.

  9. Catastrophizing and Causal Beliefs in Whiplash

    NARCIS (Netherlands)

    Buitenhuis, J.; de Jong, P. J.; Jaspers, J. P. C.; Groothoff, J. W.

    2008-01-01

    Study Design. Prospective cohort study. Objective. This study investigates the role of pain catastrophizing and causal beliefs with regard to severity and persistence of neck complaints after motor vehicle accidents. Summary of Background Data. In previous research on low back pain, somatoform

  10. Political extremism predicts belief in conspiracy theories

    NARCIS (Netherlands)

    van Prooijen, J.W.; Krouwel, A.P.M.; Pollet, T. V.

    2015-01-01

    Historical records suggest that the political extremes—at both the “left” and the “right”—substantially endorsed conspiracy beliefs about other-minded groups. The present contribution empirically tests whether extreme political ideologies, at either side of the political spectrum, are positively

  11. Nonmonotonic belief state frames and reasoning frames

    NARCIS (Netherlands)

    Engelfriet, J.; Herre, H.; Treur, J.

    1995-01-01

    In this paper five levels of specification of nonmonotonic reasoning are distinguished. The notions of semantical frame, belief state frame and reasoning frame are introduced and used as a semantical basis for the first three levels. Moreover, the semantical connections between the levels are

  12. Utilitarian Aggregation of Beliefs and Tastes.

    Science.gov (United States)

    Gilboa, Itzhak; Samet, Dov; Schmeidler, David

    2004-01-01

    Harsanyi's utilitarianism is extended here to Savage's framework. We formulate a Pareto condition that implies that both society's utility function and its probability measure are linear combinations of those of the individuals. An indiscriminate Pareto condition has been shown to contradict linear aggregation of beliefs and tastes. We argue that…

  13. Paternal Attachment, Parenting Beliefs and Children's Attachment

    Science.gov (United States)

    Howard, Kimberly S.

    2010-01-01

    Relationships between fathers' romantic attachment style, parenting beliefs and father-child attachment security and dependence were examined in a diverse sample of 72 fathers of young children. Paternal romantic attachment style was coded based on fathers' endorsement of a particular style represented in the Hazan and Shaver Three-Category…

  14. Incarcerated women's HPV awareness, beliefs, and experiences.

    Science.gov (United States)

    Pankey, Tyson; Ramaswamy, Megha

    2015-01-01

    The purpose of this paper is to explore incarcerated women's awareness, beliefs, and experiences with human papillomavirus (HPV) infection and vaccination. Researchers conducted focus groups with 45 incarcerated women in an urban Midwestern US jail to assess how women talked about their Papanicolaou (Pap) test screening and abnormal Pap test follow-up experiences. Some focus group questions specifically assessed individual awareness, beliefs, and experiences with HPV infection and vaccination. Based on these data, the authors described participants' awareness of HPV, as well as used open coding to ultimately extract themes related to beliefs and experiences with HPV infection and vaccine. While all 45 participants reported experiencing an abnormal Pap test event within the last five years, only two-thirds of participants (n=30) reported having heard of the HPV infection. Several themes emerged from the analysis of the data: the women's beliefs about cause and severity of HPV; frustration with age requirements of the vaccine; varied experiences with vaccinations for themselves and their children; the impact of media exposure on knowledge; and desire for more HPV infection and vaccine information. Incarcerated women's awareness and limited experiences with HPV infection and vaccination may be a barrier to adequate screening and cervical cancer prevention. This study has implications for the development of cervical health education for this high-risk group of women, who are four to five times as likely to have cervical cancer as non-incarcerated women.

  15. Belief in astrology inventory: development and validation.

    Science.gov (United States)

    Chico, Eliseo; Lorenzo-Seva, Urbano

    2006-12-01

    After the paper by Mayo, White, and Eysenck in 1978, a considerable number of papers studied the so-called sun-sign-effect predicted by astrology: people born with the sun in a positive sign are supposed to be extraverted, and those with the sun in a negative sign are supposed to be introverted. In these papers, researchers used ad hoc questionnaires with a few questions related to belief, knowledge, experience, or attitude toward astrology. However, an appropriate inventory with known psychometric properties has yet to be developed to assess the belief in astrology. In the present paper, the Belief in Astrology Inventory is presented with some psychometric data. The participants were 743 undergraduates studying Psychology and Social Sciences at a university in Spain. Correlation of scores on Belief in Astrology and Extraversion was small but significant (r = .22; r2 = .04) for positive sun-sign participants. This value accounts for negligible common variance. Women had significandy higher scores on the inventory than men.

  16. Sociology: Drivers of climate change beliefs

    Science.gov (United States)

    Givens, Jennifer E.

    2014-12-01

    Direct experience of global warming is expected to increase the number of people who accept that it is real and human-caused. A study now shows that people's perceptions about abnormal temperatures mostly match actual measurements but do not affect climate change beliefs.

  17. Health beliefs and practices among Arab women.

    Science.gov (United States)

    Kridli, Suha Al-Oballi

    2002-01-01

    The purpose of this article is to describe the healthcare beliefs and practices of Arab American women, specifically those regarding menstruation, pregnancy, childbirth, and family planning. The information in this paper is derived from the author's experience as a researcher, as an Arab healthcare provider, and from the literature. Guidelines for nurses who provide care to Arab American women are also presented.

  18. Changing public stigma with continuum beliefs.

    Science.gov (United States)

    Corrigan, Patrick W; Schmidt, Annie; Bink, Andrea B; Nieweglowski, Katherine; Al-Khouja, Maya A; Qin, Sang; Discont, Steve

    2017-10-01

    Given the egregious effect of public stigma on the lives of people with mental illness, researchers have sought to unpack and identify effective components of anti-stigma programs. We expect to show that continuum messages have more positive effect on stigma and affirming attitudes (beliefs that people with mental illness recover and should be personally empowered) than categorical perspectives. The effect of continuum beliefs will interact with contact strategies. A total of 598 research participants were randomly assigned to online presentations representing one of the six conditions: three messages (continuum, categorical, or neutral control) by two processes (education or contact). Participants completed measures of continuum beliefs (as a manipulation check), stigma and affirming attitudes after viewing the condition. Continuum messages had significantly better effect on views that people with mental illness are "different," a finding that interacted with contact. Continuum messages also had better effects on recovery beliefs, once again an effect that interacted significantly with contact. Implications of these findings for improving anti-stigma programs are discussed.

  19. Customers' values, beliefs on sustainable corporate performance, and buying behavior

    NARCIS (Netherlands)

    Collins, Christy M.; Steg, Linda

    Sustainable corporate performance (SCP) requires balancing a corporation's economic, social, and environmental performance. This research explores values, beliefs about the importance of SCP, and buying behaviors of supermarket customers from within a stakeholder framework. Beliefs about the

  20. Skepticism: Genuine unbelief or implicit beliefs in the supernatural?

    Science.gov (United States)

    Lindeman, Marjaana; Svedholm-Häkkinen, Annika M; Riekki, Tapani

    2016-05-01

    We examined whether skeptics hold implicit supernatural beliefs or implicit cognitive underpinnings of the beliefs. In study 1 (N=57), participants read a biological or a religious story about death. The story content had no effect on skeptics' (or believers') afterlife beliefs. Study 2 examined the relationships between religious and non-religious paranormal beliefs and implicit views about whether supernatural and religious phenomena are imaginary or real (n1=33, n2=31). The less supernatural beliefs were endorsed the easier it was to connect "supernatural" with "imaginary". Study 3 (N=63) investigated whether participants' supernatural beliefs and ontological confusions differ between speeded and non-speeded response conditions. Only non-analytical skeptics' ontological confusions increased in speeded conditions. The results indicate that skeptics overall do not hold implicit supernatural beliefs, but that non-analytically thinking skeptics may, under supporting conditions, be prone to biases that predispose to supernatural beliefs. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. oral health related behaviour, knowledge, attitudes and beliefs

    African Journals Online (AJOL)

    The findings of this study have shown that the participants had conducive oral health behavior, sufficient knowledge, positive attitude and held positive beliefs regarding dental treatments. ORAL HEALTH RELATED BEHAVIOUR, KNOWLEDGE, ATTITUDES. AND BELIEFS AMONG SECONDARY SCHOOL STUDENTS IN.

  2. Teacher participation in facilitating beliefs and values in life ...

    African Journals Online (AJOL)

    Teacher participation in facilitating beliefs and values in life orientation programmes: ... strategies of belief and value orientations in a multicultural education system. ... and religious backgrounds of learners represented in participating schools.

  3. What Happens When a Teacher's Science Belief Structure Is in Disequilibrium? Entangled Nature of Beliefs and Practice

    Science.gov (United States)

    Martin, Anita; Park, Soonhye; Hand, Brian

    2017-08-01

    This qualitative case study examined the process of change in an experienced elementary teacher's belief structure during implementation of an inquiry-based science program. Difficulties generally associated with ascertaining beliefs were minimized by using Leatham's (Journal of Mathematics Teacher Education, 9, 91-102 (2006) Sensible System Framework, enabling researchers to obtain rich descriptions of the teacher's belief structure by focusing on words (professed beliefs), intentions (intended beliefs), and actions (enacted beliefs). Models were constructed of the teacher's belief structure before and after implementation of the Science Writing Heuristic (SWH) approach (Hand et al. International Journal of Science Education, 26(2), 131-149, 2004), an inquiry-based approach to teaching science. Key beliefs for this teacher were related to how students learn, goals for teaching science, focus of instruction, and roles of teacher and student. Ultimately, the teacher shifted her professed, intended, and enacted beliefs resulting in a shift from a teacher-centered to a student-centered classroom. Findings support Thagard's Coherence Theory of Justification (2002), positing that change in one belief creates a state of disequilibrium that must be alleviated by changing/realigning other beliefs in order to re-establish coherence in the overall belief structure. This research focus is distinct from the general trend in teacher beliefs research in important ways. Most significant is that this study was not focused on the traditional two lists—those beliefs that were consistent with practice and those that were inconsistent with practice—but instead focused on the entwined nature of beliefs and practice and have shown that a teacher's practice can be viewed as their enacted beliefs, an integral part of the teacher's overall belief structure.

  4. Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become “Normalized”

    Directory of Open Access Journals (Sweden)

    Tahir Rahman

    2018-01-01

    Full Text Available Extreme overvalued beliefs (EOB are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.

  5. Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become “Normalized”

    Science.gov (United States)

    Rahman, Tahir

    2018-01-01

    Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience. PMID:29329259

  6. Validation of the vaccine conspiracy beliefs scale

    Directory of Open Access Journals (Sweden)

    Gilla K. Shapiro

    2016-12-01

    Full Text Available Background: Parents’ vaccine attitudes influence their decision regarding child vaccination. To date, no study has evaluated the impact of vaccine conspiracy beliefs on human papillomavirus vaccine acceptance. The authors assessed the validity of a Vaccine Conspiracy Beliefs Scale (VCBS and determined whether this scale was associated with parents’ willingness to vaccinate their son with the HPV vaccine. Methods: Canadian parents completed a 24-min online survey in 2014. Measures included socio-demographic variables, HPV knowledge, health care provider recommendation, Conspiracy Mentality Questionnaire (CMQ, the seven-item VCBS, and parents’ willingness to vaccinate their son at two price points. Results: A total of 1427 Canadian parents completed the survey in English (61.2% or French (38.8%. A Factor Analysis revealed the VCBS is one-dimensional and has high internal consistency (α=0.937. The construct validity of the VCBS was supported by a moderate relationship with the CMQ (r=0.44, p<0.001. Hierarchical regression analyses found the VCBS is negatively related to parents’ willingness to vaccinate their son with the HPV vaccine at both price points (‘free’ or ‘$300′ after controlling for gender, age, household income, education level, HPV knowledge, and health care provider recommendation. Conclusions: The VCBS is a brief, valid scale that will be useful in further elucidating the correlates of vaccine hesitancy. Future research could use the VCBS to evaluate the impact of vaccine conspiracies beliefs on vaccine uptake and how concerns about vaccination may be challenged and reversed. Keywords: Cancer prevention, Conspiracy beliefs, Human papillomavirus, Vaccine hesitancy, Vaccines, Vaccine Conspiracy Belief Scale

  7. The Role of Science Teachers' Beliefs in International Classrooms

    DEFF Research Database (Denmark)

    for educators. Within each of these areas there are specific explorations that examine important areas such as, the roles of beliefs in teaching and learning, the impact of beliefs on student achievement, and ways in which beliefs are connected to teacher actions in the classroom. Throughout all...... of these discussions, there is a focus on international perspectives. Those reading this book can use the research presented to consider how to confront, challenge, and cultivate beliefs during the teacher professional development process....

  8. Should informed consent be based on rational beliefs?

    OpenAIRE

    Savulescu, J; Momeyer, R W

    1997-01-01

    Our aim is to expand the regulative ideal governing consent. We argue that consent should not only be informed but also based on rational beliefs. We argue that holding true beliefs promotes autonomy. Information is important insofar as it helps a person to hold the relevant true beliefs. But in order to hold the relevant true beliefs, competent people must also think rationally. Insofar as information is important, rational deliberation is important. Just as physicians should aim to provide ...

  9. A Method for Reasoning about other Agents' Beliefs from Observations

    OpenAIRE

    Nittka, Alexander; Booth, Richard

    2007-01-01

    Traditional work in belief revision deals with the question of what an agent should believe upon receiving new information. We will give an overview about what can be concluded about an agent based on an observation of its belief revision behaviour. The observation contains partial information about the revision inputs received by the agent and its beliefs upon receiving them. We will sketch a method for reasoning about past and future beliefs of the agent and predicting which inputs i...

  10. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  11. The Pesticide Risk Beliefs Inventory: A Quantitative Instrument for the Assessment of Beliefs about Pesticide Risks

    OpenAIRE

    LePrevost, Catherine E.; Blanchard, Margaret R.; Cope, W. Gregory

    2011-01-01

    Recent media attention has focused on the risks that agricultural pesticides pose to the environment and human health; thus, these topics provide focal areas for scientists and science educators to enhance public understanding of basic toxicology concepts. This study details the development of a quantitative inventory to gauge pesticide risk beliefs. The goal of the inventory was to characterize misconceptions and knowledge gaps, as well as expert-like beliefs, concerning pesticide risk. This...

  12. Beliefs and brownies: in search for a new identity for 'belief' research

    DEFF Research Database (Denmark)

    Skott, Jeppe

    2014-01-01

    Belief research (BR) has contributed with better understandings of teachers’ acts and meaning making, but is fraught with conceptual and methodological problems. Also, the premise that teachers’ beliefs impact practice is often not confirmed. I compare BR with a conceptual framework, Patterns...... of the rationale of BR, but involves a fundamental shift of identity for research on affect, which alleviates some of the problems of BR and is useful for understanding the dynamics of teachers’ contribution to classroom practice....

  13. Mentalizing regions represent distributed, continuous, and abstract dimensions of others' beliefs.

    Science.gov (United States)

    Koster-Hale, Jorie; Richardson, Hilary; Velez, Natalia; Asaba, Mika; Young, Liane; Saxe, Rebecca

    2017-11-01

    The human capacity to reason about others' minds includes making causal inferences about intentions, beliefs, values, and goals. Previous fMRI research has suggested that a network of brain regions, including bilateral temporo-parietal junction (TPJ), superior temporal sulcus (STS), and medial prefrontal-cortex (MPFC), are reliably recruited for mental state reasoning. Here, in two fMRI experiments, we investigate the representational content of these regions. Building on existing computational and neural evidence, we hypothesized that social brain regions contain at least two functionally and spatially distinct components: one that represents information related to others' motivations and values, and another that represents information about others' beliefs and knowledge. Using multi-voxel pattern analysis, we find evidence that motivational versus epistemic features are independently represented by theory of mind (ToM) regions: RTPJ contains information about the justification of the belief, bilateral TPJ represents the modality of the source of knowledge, and VMPFC represents the valence of the resulting emotion. These representations are found only in regions implicated in social cognition and predict behavioral responses at the level of single items. We argue that cortical regions implicated in mental state inference contain complementary, but distinct, representations of epistemic and motivational features of others' beliefs, and that, mirroring the processes observed in sensory systems, social stimuli are represented in distinct and distributed formats across the human brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  14. Failure diagnosis using deep belief learning based health state classification

    International Nuclear Information System (INIS)

    Tamilselvan, Prasanna; Wang, Pingfeng

    2013-01-01

    Effective health diagnosis provides multifarious benefits such as improved safety, improved reliability and reduced costs for operation and maintenance of complex engineered systems. This paper presents a novel multi-sensor health diagnosis method using deep belief network (DBN). DBN has recently become a popular approach in machine learning for its promised advantages such as fast inference and the ability to encode richer and higher order network structures. The DBN employs a hierarchical structure with multiple stacked restricted Boltzmann machines and works through a layer by layer successive learning process. The proposed multi-sensor health diagnosis methodology using DBN based state classification can be structured in three consecutive stages: first, defining health states and preprocessing sensory data for DBN training and testing; second, developing DBN based classification models for diagnosis of predefined health states; third, validating DBN classification models with testing sensory dataset. Health diagnosis using DBN based health state classification technique is compared with four existing diagnosis techniques. Benchmark classification problems and two engineering health diagnosis applications: aircraft engine health diagnosis and electric power transformer health diagnosis are employed to demonstrate the efficacy of the proposed approach

  15. Superstitious Beliefs as Constraints in The Learning of Science ...

    African Journals Online (AJOL)

    This paper examines the nature, prevalence and effect of superstitious beliefs as constraints to the appropriate learning of science in our schools. Studies done on identification and analysis of types and degrees of superstitious beliefs have been reported as well as to how these beliefs inhibit the individual learner\\'s ...

  16. In-Service EFL Teachers' Beliefs about Teaching Reading Strategies

    Science.gov (United States)

    Bamanger, Ebrahim M.; Gashan, Amani K.

    2014-01-01

    Recent trends in teacher education have focused on exploring teachers' beliefs. Earlier studies have shown the important influence of teachers' beliefs on teaching practices. The present study was conducted to explore the beliefs of Saudi EFL teachers about the significance of teaching English reading strategies. The study aimed also to find the…

  17. Psychosis or Faith? Clinicians' Assessment of Religious Beliefs

    Science.gov (United States)

    O'Connor, Shawn; Vandenberg, Brian

    2005-01-01

    This study investigated mental health professionals' assessment of the pathognomonic significance of religious beliefs. A total of 110 participants reviewed 3 vignettes depicting individuals possessing the religious beliefs associated with Catholicism, Mormonism, and Nation of Islam. The religious beliefs of the individuals in the vignettes were…

  18. Preservice Teachers' Belief Systems toward Curricular Outcomes for Physical Education

    Science.gov (United States)

    Kulinna, Pamela Hodges; Brusseau, Timothy; Ferry, Matthew; Cothran, Donetta

    2010-01-01

    This study was grounded in the belief systems and physical activity literature and investigated preservice teachers' belief systems toward curricular outcomes for physical education programs. Preservice teachers (N = 486; men = 62%, women = 38%) from 18 U.S. colleges/universities shared their beliefs about curricular outcomes. Preservice teachers…

  19. Beyond "born this way?" reconsidering sexual orientation beliefs and attitudes.

    Science.gov (United States)

    Grzanka, Patrick R; Zeiders, Katharine H; Miles, Joseph R

    2016-01-01

    Previous research on heterosexuals' beliefs about sexual orientation (SO) has been limited in that it has generally examined heterosexuals' beliefs from an essentialist perspective. The recently developed Sexual Orientation Beliefs Scale (SOBS; Arseneau, Grzanka, Miles, & Fassinger, 2013) assesses multifarious "lay beliefs" about SO from essentialist, social constructionist, and constructivist perspectives. This study used the SOBS to explore latent group-based patterns in endorsement of these beliefs in 2 samples of undergraduate students: a mixed-gender sample (n = 379) and an all-women sample (n = 266). While previous research has posited that essentialist beliefs about the innateness of SO predict positive attitudes toward sexual minorities, our research contributes to a growing body of scholarship that suggests that biological essentialism should be considered in the context of other beliefs. Using a person-centered analytic strategy, we found that that college students fell into distinct patterns of SO beliefs that are more different on beliefs about the homogeneity, discreteness, and informativeness of SO categories than on beliefs about the naturalness of SO. Individuals with higher levels of endorsement on all 4 SOBS subscales (a group we named multidimensional essentialism) and those who were highest in discreteness, homogeneity, and informativeness beliefs (i.e., high-DHI) reported higher levels of homonegativity when compared with those who were high only in naturalness beliefs. We discuss the implications of these findings for counseling and psychotherapy about SO, as well educational and social interventions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  20. Pre-Service EFL Teachers' Beliefs about Foreign Language Learning

    Science.gov (United States)

    Altan, Mustafa Zulkuf

    2012-01-01

    Beliefs are central constructs in every discipline which deals with human behaviour and learning. In addition to learner beliefs about language learning, language teachers themselves may hold certain beliefs about language learning that will have an impact on their instructional practices and that are likely to influence their students' beliefs…

  1. Belief Inhibition in Children's Reasoning: Memory-Based Evidence

    Science.gov (United States)

    Steegen, Sara; Neys, Wim De

    2012-01-01

    Adult reasoning has been shown as mediated by the inhibition of intuitive beliefs that are in conflict with logic. The current study introduces a classic procedure from the memory field to investigate belief inhibition in 12- to 17-year-old reasoners. A lexical decision task was used to probe the memory accessibility of beliefs that were cued…

  2. On revision of partially specified convex probabilistic belief bases

    CSIR Research Space (South Africa)

    Rens, G

    2016-08-01

    Full Text Available We propose a method for an agent to revise its incomplete probabilistic beliefs when a new piece of propositional information is observed. In this work, an agent’s beliefs are represented by a set of probabilistic formulae – a belief base...

  3. The Development of Reasoning about Beliefs: Fact, Preference, and Ideology.

    Science.gov (United States)

    Heiphetz, Larisa; Spelke, Elizabeth S; Harris, Paul L; Banaji, Mahzarin R

    2013-05-01

    The beliefs people hold about the social and physical world are central to self-definition and social interaction. The current research analyzes reasoning about three kinds of beliefs: those that concern matters of fact (e.g., dinosaurs are extinct), preference (e.g., green is the prettiest color), and ideology (e.g., there is only one God). The domain of ideology is of unique interest because it is hypothesized to contain elements of both facts and preferences. If adults' distinct reasoning about ideological beliefs is the result of prolonged experience with the physical and social world, children and adults should reveal distinct patterns of differentiating kinds of beliefs, and this difference should be particularly pronounced with respect to ideological beliefs. On the other hand, if adults' reasoning about beliefs is a basic component of social cognition, children and adults should demonstrate similar belief representations and patterns of belief differentiation. Two experiments demonstrate that 5-10 year old children and adults similarly judged religious beliefs to be intermediate between factual beliefs (where two disagreeing people cannot both be right) and preferences (where they can). From the age of 5 years and continuing into adulthood, individuals distinguished ideological beliefs from other types of mental states and demonstrated limited tolerance for belief-based disagreements.

  4. Conceptions about the mind-body problem and their relations to afterlife beliefs, paranormal beliefs, religiosity, and ontological confusions.

    Science.gov (United States)

    Riekki, Tapani; Lindeman, Marjaana; Lipsanen, Jari

    2013-01-01

    We examined lay people's conceptions about the relationship between mind and body and their correlates. In Study 1, a web survey (N = 850) of reflective dualistic, emergentistic, and monistic perceptions of the mind-body relationship, afterlife beliefs (i.e., common sense dualism), religiosity, paranormal beliefs, and ontological confusions about physical, biological, and psychological phenomena was conducted. In Study 2 (N = 73), we examined implicit ontological confusions and their relations to afterlife beliefs, paranormal beliefs, and religiosity. Correlation and regression analyses showed that reflective dualism, afterlife beliefs, paranormal beliefs, and religiosity were strongly and positively related and that reflective dualism and afterlife beliefs mediated the relationship between ontological confusions and religious and paranormal beliefs. The results elucidate the contention that dualism is a manifestation of universal cognitive processes related to intuitions about physical, biological, and psychological phenomena by showing that especially individuals who confuse the distinctive attributes of these phenomena tend to set the mind apart from the body.

  5. Application of Bayesian belief net in modelling the origin and effects of terrigenous dissolved organic matter in a boreal aquatic ecosystem

    Science.gov (United States)

    Rahikainen, Mika; Hoikkala, Laura; Soinne, Helena

    2013-04-01

    Bayesian belief nets (BBN) are capable of developing holistic understanding of the origin, transportation, and effects of dissolved organic matter (DOM) in ecosystems. The role of riverine DOM, transporting carbon and macronutrients N and P into lakes and coastal areas, has been largely neglected in research about processes influencing aquatic ecosystem functions although dissolved organic matter provides a significant nutrient source for primary producers in aquatic environments. This neglect has also contributed to the environmental policies which are focused in the control of inorganic N and P load. It is of great social and economic interest to gain improved knowledge of whether the currently applied policy instruments act in synchrony in mitigating eutrophication caused by N and P versus DOM load. DOM is a complex mixture of compounds that are poorly characterized. DOM export is strongly regulated by land use (urban, forest, agricultural land, peat land), in addition to soil type and soil organic carbon concentration. Furthermore, the composition of DOM varies according to its origin. The fate and effects of DOM loads in the fresh water and coastal environments depend, for example, on their biodegradability. Degradation kinetics again depends on the interactions between composition of the DOM pool and the receiving environment. Impact studies of dissolved organic matter pose a complicated environmental impact assessment challenge for science. There exists strategic uncertainty in the science about the causal dependencies and about the quality of knowledge related to DOM. There is a clear need for systematization in the approach as uncertainty is typically high about many key processes. A cross-sectorial, integrative analysis will aid in focusing on the most relevant issues. A holistic and unambiguous analysis will provide support for policy-decisions and management by indicating which outcome is more probable than another. The task requires coupling complex

  6. Development and Validation of the Family Beliefs Inventory: A Measure of Unrealistic Beliefs among Parents and Adolescents.

    Science.gov (United States)

    Roehling, Patricia Vincent; Robin, Arthur L.

    1986-01-01

    Evaluated the criterion-related validity of the Family Beliefs Inventory, a new self-report measure of unreasonable beliefs regarding parent-adolescent relationships. Distressed fathers displayed more unreasonable beliefs concerning ruination, obedience, perfectionism, and malicious intent than nondistressed fathers. Distressed adolescents…

  7. Designing neural networks that process mean values of random variables

    International Nuclear Information System (INIS)

    Barber, Michael J.; Clark, John W.

    2014-01-01

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

  8. Designing neural networks that process mean values of random variables

    Energy Technology Data Exchange (ETDEWEB)

    Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

    2014-06-13

    We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

  9. Development of a Bayesian model to estimate health care outcomes in the severely wounded

    Directory of Open Access Journals (Sweden)

    Alexander Stojadinovic

    2010-08-01

    Full Text Available Alexander Stojadinovic1, John Eberhardt2, Trevor S Brown3, Jason S Hawksworth4, Frederick Gage3, Douglas K Tadaki3, Jonathan A Forsberg5, Thomas A Davis3, Benjamin K Potter5, James R Dunne6, E A Elster31Combat Wound Initiative Program, 4Department of Surgery, Walter Reed Army Medical Center, Washington, DC, USA; 2DecisionQ Corporation, Washington, DC, USA; 3Regenerative Medicine Department, Combat Casualty Care, Naval Medical Research Center, Silver Spring, MD, USA; 5Integrated Department of Orthopaedics and Rehabilitation, 6Department of Surgery, National Naval Medical Center, Bethesda, MD, USABackground: Graphical probabilistic models have the ability to provide insights as to how clinical factors are conditionally related. These models can be used to help us understand factors influencing health care outcomes and resource utilization, and to estimate morbidity and clinical outcomes in trauma patient populations.Study design: Thirty-two combat casualties with severe extremity injuries enrolled in a prospective observational study were analyzed using step-wise machine-learned Bayesian belief network (BBN and step-wise logistic regression (LR. Models were evaluated using 10-fold cross-validation to calculate area-under-the-curve (AUC from receiver operating characteristics (ROC curves.Results: Our BBN showed important associations between various factors in our data set that could not be developed using standard regression methods. Cross-validated ROC curve analysis showed that our BBN model was a robust representation of our data domain and that LR models trained on these findings were also robust: hospital-acquired infection (AUC: LR, 0.81; BBN, 0.79, intensive care unit length of stay (AUC: LR, 0.97; BBN, 0.81, and wound healing (AUC: LR, 0.91; BBN, 0.72 showed strong AUC.Conclusions: A BBN model can effectively represent clinical outcomes and biomarkers in patients hospitalized after severe wounding, and is confirmed by 10-fold

  10. Behaviour in O of the Neural Networks Training Cost

    DEFF Research Database (Denmark)

    Goutte, Cyril

    1998-01-01

    We study the behaviour in zero of the derivatives of the cost function used when training non-linear neural networks. It is shown that a fair number offirst, second and higher order derivatives vanish in zero, validating the belief that 0 is a peculiar and potentially harmful location. These calc......We study the behaviour in zero of the derivatives of the cost function used when training non-linear neural networks. It is shown that a fair number offirst, second and higher order derivatives vanish in zero, validating the belief that 0 is a peculiar and potentially harmful location....... These calculations arerelated to practical and theoretical aspects of neural networks training....

  11. Heterogeneous Beliefs, Public Information, and Option Markets

    DEFF Research Database (Denmark)

    Qin, Zhenjiang

    In an incomplete market setting with heterogeneous prior beliefs, I show that public information and strike price of option have substantial infl‡uence on asset pricing in option markets, by investigating an absolute option pricing model with negative exponential utility investors and normally...... distributed dividend. I demonstrate that heterogeneous prior variances give rise to the economic value of option markets. Investors speculate in option market and public information improves allocational efficiency of markets only when there is heterogeneity in prior variance. Heterogeneity in mean is neither...... a necessary nor sufficient condition for generating speculations in option markets. With heterogeneous beliefs, options are non-redundant assets which can facilitate side-betting and enable investors to take advantage of the disagreements and the differences in con…dence. This fact leads to a higher growth...

  12. Sensitivity to coincidences and paranormal belief.

    Science.gov (United States)

    Hadlaczky, Gergö; Westerlund, Joakim

    2011-12-01

    Often it is difficult to find a natural explanation as to why a surprising coincidence occurs. In attempting to find one, people may be inclined to accept paranormal explanations. The objective of this study was to investigate whether people with a lower threshold for being surprised by coincidences have a greater propensity to become believers compared to those with a higher threshold. Participants were exposed to artificial coincidences, which were formally defined as less or more probable, and were asked to provide remarkability ratings. Paranormal belief was measured by the Australian Sheep-Goat Scale. An analysis of the remarkability ratings revealed a significant interaction effect between Sheep-Goat score and type of coincidence, suggesting that people with lower thresholds of surprise, when experiencing coincidences, harbor higher paranormal belief than those with a higher threshold. The theoretical aspects of these findings were discussed.

  13. Belief Propagation Algorithm for Portfolio Optimization Problems.

    Science.gov (United States)

    Shinzato, Takashi; Yasuda, Muneki

    2015-01-01

    The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

  14. Belief Propagation Algorithm for Portfolio Optimization Problems.

    Directory of Open Access Journals (Sweden)

    Takashi Shinzato

    Full Text Available The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

  15. Harm beliefs and coping expectancies in youth with specific phobias.

    Science.gov (United States)

    Ollendick, Thomas H; Öst, Lars-Göran; Ryan, Sarah M; Capriola, Nicole N; Reuterskiöld, Lena

    2017-04-01

    Catastrophic beliefs and lowered coping expectancies are often present in individuals with specific phobias (SPs). The current study examined these beliefs and expectancies in 251 youth who received One Session Treatment for one of the three most common types of SP in youth (animals, natural environment, and situational). We compared the children's subjective beliefs to objective ratings of the likelihood of occurrence and the dangerousness of the feared events. Results revealed pre-treatment differences in the youths' beliefs across phobia types and age. Specifically, children with animal phobias rated their beliefs as more likely to occur than did children with environmental and situational phobias. In addition, older children rated their beliefs as more dangerous than younger children. However, regardless of phobia type or child age, the beliefs improved following treatment. Changes in catastrophic beliefs and coping expectancies were related to changes in clinical severity following treatment but not 6-months following treatment. Moreover, at pre-treatment, children viewed their beliefs as significantly more catastrophic and likely to occur than did independent coders of these beliefs; however, these differences were no longer evident following treatment. Clinical implications are discussed, highlighting how changes in beliefs and expectancies might be associated with treatment outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Analytic cognitive style predicts religious and paranormal belief.

    Science.gov (United States)

    Pennycook, Gordon; Cheyne, James Allan; Seli, Paul; Koehler, Derek J; Fugelsang, Jonathan A

    2012-06-01

    An analytic cognitive style denotes a propensity to set aside highly salient intuitions when engaging in problem solving. We assess the hypothesis that an analytic cognitive style is associated with a history of questioning, altering, and rejecting (i.e., unbelieving) supernatural claims, both religious and paranormal. In two studies, we examined associations of God beliefs, religious engagement (attendance at religious services, praying, etc.), conventional religious beliefs (heaven, miracles, etc.) and paranormal beliefs (extrasensory perception, levitation, etc.) with performance measures of cognitive ability and analytic cognitive style. An analytic cognitive style negatively predicted both religious and paranormal beliefs when controlling for cognitive ability as well as religious engagement, sex, age, political ideology, and education. Participants more willing to engage in analytic reasoning were less likely to endorse supernatural beliefs. Further, an association between analytic cognitive style and religious engagement was mediated by religious beliefs, suggesting that an analytic cognitive style negatively affects religious engagement via lower acceptance of conventional religious beliefs. Results for types of God belief indicate that the association between an analytic cognitive style and God beliefs is more nuanced than mere acceptance and rejection, but also includes adopting less conventional God beliefs, such as Pantheism or Deism. Our data are consistent with the idea that two people who share the same cognitive ability, education, political ideology, sex, age and level of religious engagement can acquire very different sets of beliefs about the world if they differ in their propensity to think analytically. Copyright © 2012 Elsevier B.V. All rights reserved.

  17. Italian retail gasoline activities: inadequate distribution network

    International Nuclear Information System (INIS)

    Verde, Stefano

    2005-01-01

    It is common belief that competition in the Italian retail gasoline activities is hindered by oil companies' collusive behaviour. However, when developing a broader analysis of the sector, low efficiency and scarce competition could results as the consequences coming from an inadequate distribution network and from the recognition of international markets and focal point [it

  18. Frameless ALOHA Protocol for Wireless Networks

    DEFF Research Database (Denmark)

    Stefanovic, Cedomir; Popovski, Petar; Vukobratovic, Dejan

    2012-01-01

    We propose a novel distributed random access scheme for wireless networks based on slotted ALOHA, motivated by the analogies between successive interference cancellation and iterative belief-propagation decoding on erasure channels. The proposed scheme assumes that each user independently accesse...

  19. Social Networks: Rational Learning and Information Aggregation

    Science.gov (United States)

    2009-09-01

    predecessor, Gale and Kariv (2003) who generalize the payoff equalization result of Bala and Goyal (1998) in connected social networks (discussed below...requires more notation. Using Bayes’ Rule and the assumption of equal priors on the state θ, we have that the social belief given by observing... Social Networks: Rational Learning and Information Aggregation by Ilan Lobel B.Sc., Pontif́ıcia Universidade Católica do Rio de Janeiro (2004

  20. Childhood physical abuse and differential development of paranormal belief systems.

    Science.gov (United States)

    Perkins, Stefanie L; Allen, Rhiannon

    2006-05-01

    This study compared paranormal belief systems in individuals with and without childhood physical abuse histories. The Revised Paranormal Belief Scale and the Assessing Environments III Questionnaire were completed by 107 University students. Psi, precognition, and spiritualism, which are thought to provide a sense of personal efficacy and control, were among the most strongly held beliefs in abused subjects, and were significantly higher in abused versus nonabused subjects. Superstition and extraordinary life forms, thought to have an inverse or no relation to felt control, were the least strongly held beliefs in abused subjects, and, along with religious beliefs, did not differ between the two abuse groups. Witchcraft was unexpectedly found to be the most strongly held belief among those with abuse histories. Results suggest that by providing a sense of control, certain paranormal beliefs may offer a powerful emotional refuge to individuals who endured the stress of physical abuse in childhood.

  1. Executive functions in morality, religion, and paranormal beliefs.

    Science.gov (United States)

    Wain, Omar; Spinella, Marcello

    2007-01-01

    Moral, religious, and paranormal beliefs share some degree of overlap and play important roles in guiding peoples' behavior. Although partly cultural phenomena, they also have neurobiological components based on functional neuroimaging studies and research in clinical populations. Because all three show relationships to prefrontal system functioning, the current study examined whether they related to executive functions as measured by the Executive Function Inventory in a community sample. As in previous research, religious beliefs related positively to both moral attitudes and paranormal beliefs. Moral attitudes, however, did not relate to paranormal beliefs. Paranormal beliefs related inversely to impulse control and organization, whereas small positive correlations occurred between traditional religious beliefs, impulse control, and empathy. Moral attitudes, on the other hand, showed consistent positive correlations with all executive functions measured, independent of demographic influences. These findings concordantly support that prefrontal systems play a role in morality, religion, and paranormal beliefs.

  2. Mentalizing Deficits Constrain Belief in a Personal God

    Science.gov (United States)

    Norenzayan, Ara; Gervais, Will M.; Trzesniewski, Kali H.

    2012-01-01

    Religious believers intuitively conceptualize deities as intentional agents with mental states who anticipate and respond to human beliefs, desires and concerns. It follows that mentalizing deficits, associated with the autistic spectrum and also commonly found in men more than in women, may undermine this intuitive support and reduce belief in a personal God. Autistic adolescents expressed less belief in God than did matched neuro-typical controls (Study 1). In a Canadian student sample (Study 2), and two American national samples that controlled for demographic characteristics and other correlates of autism and religiosity (Study 3 and 4), the autism spectrum predicted reduced belief in God, and mentalizing mediated this relationship. Systemizing (Studies 2 and 3) and two personality dimensions related to religious belief, Conscientiousness and Agreeableness (Study 3), failed as mediators. Mentalizing also explained the robust and well-known, but theoretically debated, gender gap in religious belief wherein men show reduced religious belief (Studies 2–4). PMID:22666332

  3. Beliefs about God and mental health among American adults.

    Science.gov (United States)

    Silton, Nava R; Flannelly, Kevin J; Galek, Kathleen; Ellison, Christopher G

    2014-10-01

    This study examines the association between beliefs about God and psychiatric symptoms in the context of Evolutionary Threat Assessment System Theory, using data from the 2010 Baylor Religion Survey of US Adults (N = 1,426). Three beliefs about God were tested separately in ordinary least squares regression models to predict five classes of psychiatric symptoms: general anxiety, social anxiety, paranoia, obsession, and compulsion. Belief in a punitive God was positively associated with four psychiatric symptoms, while belief in a benevolent God was negatively associated with four psychiatric symptoms, controlling for demographic characteristics, religiousness, and strength of belief in God. Belief in a deistic God and one's overall belief in God were not significantly related to any psychiatric symptoms.

  4. Assessment of dysfunctional beliefs in borderline personality disorder.

    Science.gov (United States)

    Butler, Andrew C; Brown, Gregory K; Beck, Aaron T; Grisham, Jessica R

    2002-10-01

    This study had two aims: to test the hypothesis that borderline personality disorder (BPD) patients hold numerous dysfunctional beliefs associated with a variety of Axis II disorders, and to construct a BPD belief scale which captures these beliefs. Beliefs were measured using the Personality Belief Questionnaire (PBQ) which is designed to assess beliefs associated with various personality disorders, although not specifically BPD. Eighty-four BPD patients and 204 patients with other personality disorders (OPD) were randomly split into two study samples. Fourteen PBQ items were found to discriminate BPD from OPD patients in both samples. These items came from the PBQ Dependent, Paranoid, Avoidant, and Histrionic scales and reflect themes of dependency, helplessness, distrust, fears of rejection/abandonment/losing emotional control, and extreme attention-seeking behavior. A BPD beliefs scale constructed from these items showed good internal consistency and diagnostic validity among the 288 study patients. The scale may be used to assist in diagnosis and cognitive therapy of BPD.

  5. Incentives for Subjective Evaluations with Private Beliefs

    OpenAIRE

    Radanovic, Goran; Faltings, Boi

    2015-01-01

    The modern web critically depends on aggregation of information from self-interested agents, for example opinion polls, product ratings, or crowdsourcing. We consider a setting where multiple objects (questions, products, tasks) are evaluated by a group of agents. We first construct a minimal peer prediction mechanism that elicits honest evaluations from a homogeneous population of agents with different private beliefs. Second, we show that it is impossible to strictly elicit honest evaluatio...

  6. Beliefs regarding diet during childhood illness

    Directory of Open Access Journals (Sweden)

    Asha D Benakappa

    2012-01-01

    Full Text Available Background: Fifty percent to 70% of the burden of childhood diarrhea and respiratory infections is attributable to undernutrition. It is compounded by food restriction during illness due to false beliefs, leading to a vicious cycle of malnutrition and infection. In the long run, it decreases the child′s productivity, which is an obstacle to sustainable socioeconomic development. Objectives: To assess the dietary practices during different illnesses, to study the role of education, culture and religion in feeding an ill child and to create awareness against detrimental practices. Materials and Methods: A cross-sectional study was undertaken among 126 caregivers of ill children using an open-ended pretested questionnaire. Statistical package for social sciences software was used for data analysis. Simple proportions, percentages and Chi-square were used. Results: Caregivers believed that a child must be fed less during illness. Educational status did not play a role in maintaining beliefs, but elders and religion did. Doctors too were responsible for unwanted dietary restrictions. Media did not have an impact in spreading nutrition messages. Decreased breast feeds, initiating bottle feeds, feeding diluted milk and reducing complementary feeds during illness was widely practiced. Calorie intake during illness was very less and statistically significant. Firmly rooted beliefs about "hot" and "cold" foods lead to restriction of food available at home. Conclusions: Healthy feeding practices were few, and inappropriate ones predominant. Dietary education was overlooked. While planning community-based nutrition programs, firmly rooted beliefs should be kept in mind. Involving the elderly caregivers and mothers actively along with the health workers is the need of the hour.

  7. Reincarnation belief and the Christian churches

    OpenAIRE

    Waterhouse, Helen; Walter, Tony

    2003-01-01

    Reincarnation has never been part of mainstream Christian theology. This is true in spite of periodic speculations by Christian theologians, and in spite of the fact that reincarnation believers sometimes wrongly impute belief in reincarnation to prominent Christian thinkers. Even so, in 1984 Paul Badham was able to point to statistics which indicated that as many Anglicans believed in reincarnation as believed in heaven and hell. This paper is based on the responses of the many Christians wh...

  8. Importance of Beliefs, Attitudes and Values in the Frame of Human Resource Motivation

    Directory of Open Access Journals (Sweden)

    Claudia MOISE

    2014-06-01

    Full Text Available The article deals with a complex and original field of analyse – the role that concepts such as beliefs, attitudes and values can entail in the modern human resources management techniques that are dealing with employee’s motivation. Nowadays employees have a complex approach regarding motivation. Especially when we speak about big organisations such as multinational companies, we will find complex jobs having many tasks and a complicated network of inter-relations within the organisation. In such cases, as we speak about middle and top management positions, employee’s motivation is relying on different types of motivation: intrinsic and extrinsic altogether. The substantiation of an efficient motivational strategy can be based on the link between beliefs, attitudes and values of the employees and their motivation development process.

  9. Yoruba customs and beliefs pertaining to twins.

    Science.gov (United States)

    Leroy, Fernand; Olaleye-Oruene, Taiwo; Koeppen-Schomerus, Gesina; Bryan, Elizabeth

    2002-04-01

    The Yoruba are an important ethnic group mainly occupying Southwestern Nigeria. Mainly for genetic reasons, this very large tribe happens to present the highest dizygotic twinning rate in the world (4.4 % of all maternities). The high perinatal mortality rate associated with such pregnancies has contributed to the integration of a special twin belief system within the African traditional religion of this tribe. The latter is based on the concept of a supreme deity called Olodumare or Olorun, assisted by a series of secondary gods (Orisha) while Yoruba religion also involves immortality and reincarnation of the soul based on the animistic cult of ancestors. Twins are therefore given special names and believed to detain special preternatural powers. In keeping with their refined artistic tradition, the Yoruba have produced numerous wooden statuettes called Ibejis that represent the souls of deceased newborn twins and are involved in elaborate rituals. Among Yoruba traditional beliefs and lore some twin-related themes are represented which are also found in other parts of the world. Basic features of the original Yoruba beliefs have found their way into the religious traditions of descendants of African slaves imported in the West Indies and in South America.

  10. Validation of the vaccine conspiracy beliefs scale.

    Science.gov (United States)

    Shapiro, Gilla K; Holding, Anne; Perez, Samara; Amsel, Rhonda; Rosberger, Zeev

    2016-12-01

    Parents' vaccine attitudes influence their decision regarding child vaccination. To date, no study has evaluated the impact of vaccine conspiracy beliefs on human papillomavirus vaccine acceptance. The authors assessed the validity of a Vaccine Conspiracy Beliefs Scale (VCBS) and determined whether this scale was associated with parents' willingness to vaccinate their son with the HPV vaccine. Canadian parents completed a 24-min online survey in 2014. Measures included socio-demographic variables, HPV knowledge, health care provider recommendation, Conspiracy Mentality Questionnaire (CMQ), the seven-item VCBS, and parents' willingness to vaccinate their son at two price points. A total of 1427 Canadian parents completed the survey in English (61.2%) or French (38.8%). A Factor Analysis revealed the VCBS is one-dimensional and has high internal consistency (α=0.937). The construct validity of the VCBS was supported by a moderate relationship with the CMQ (r=0.44, pparents' willingness to vaccinate their son with the HPV vaccine at both price points ('free' or '$300') after controlling for gender, age, household income, education level, HPV knowledge, and health care provider recommendation. The VCBS is a brief, valid scale that will be useful in further elucidating the correlates of vaccine hesitancy. Future research could use the VCBS to evaluate the impact of vaccine conspiracies beliefs on vaccine uptake and how concerns about vaccination may be challenged and reversed. Copyright © 2016. Published by Elsevier B.V.

  11. Further tests of belief-importance theory.

    Directory of Open Access Journals (Sweden)

    K V Petrides

    Full Text Available Belief-importance (belimp theory hypothesizes that personality traits confer a propensity to perceive convergences or divergences between the belief that we can attain certain goals and the importance that we place on these goals. Belief and importance are conceptualized as two coordinates, together defining the belimp plane. We tested fundamental aspects of the theory using four different planes based on the life domains of appearance, family, financial security, and friendship as well as a global plane combining these four domains. The criteria were from the areas of personality (Big Five and trait emotional intelligence and learning styles. Two hundred and fifty eight participants were allocated into the four quadrants of the belimp plane (Hubris, Motivation, Depression, and Apathy according to their scores on four reliable instruments. Most hypotheses were supported by the data. Results are discussed with reference to the stability of the belimp classifications under different life domains and the relationship of the quadrants with the personality traits that are hypothesized to underpin them.

  12. Determinants and beliefs of health information mavens among a lower-socioeconomic position and minority population

    Science.gov (United States)

    Emmons, Karen M.; Puleo, Elaine; Viswanath, K.

    2011-01-01

    People of lower-socioeconomic position (SEP) and most racial/ethnic minorities face significant communication challenges which may negatively impact their health. Previous research has shown that these groups rely heavily on interpersonal sources to share and receive health information; however, little is known about these lay sources. The purpose of this paper is to apply the concept of a market maven to the public health sector with the aims of identifying determinants of high health information mavenism among low-SEP and racial/ethnic minority groups and to assess the information they may be sharing based on their own health beliefs. Data for this study were drawn from the baseline survey (n=325) of a US randomized control intervention study aimed at eliciting an understanding of Internet-related challenges among lower-SEP and minority individuals. Regression models were estimated to distinguish significant determinants of health information mavenism among the sample. Similarly, bivariate and logistic multivariable models were estimated to determine the association between health information mavenism and accurate health beliefs relating to diet, physical activity and smoking. The data illustrate that having a larger social network, being female and being older were important factors associated with higher mavenism scores. Additionally being a moderate consumer of general media as well as fewer years in the US and lower language acculturation were significant predictors of higher mavenism scores. Mavens were more likely than non-mavens to maintain accurate beliefs regarding diet; however, there was no distinction between physical activity and smoking beliefs between mavens and non-mavens. These results offer a unique understanding of health information mavenism which could better leverage word-of-mouth health communication efforts among lower-SEP and minority groups in order to reduce communication inequalities. Moreover, the data indicate that health information

  13. Beliefs About Sexual Intimate Partner Violence Perpetration Among Adolescents in South Africa.

    Science.gov (United States)

    Pöllänen, Katri; de Vries, Hein; Mathews, Catherine; Schneider, Francine; de Vries, Petrus J

    2018-02-01

    Sexual intimate partner violence (IPV) is a public health problem worldwide. Research regarding beliefs about perpetrating sexual IPV is, however, limited. This study investigated attitudes, social influence, and self-efficacy beliefs and intentions toward perpetrating sexual IPV among Grade 8 adolescents ( M age = 13.73, SD = 1.04) in the Western Cape Province of South Africa. The study sample was taken from the baseline data of the Promoting sexual and reproductive health among adolescents in Southern and Eastern Africa (PREPARE) study, a cluster-randomized controlled trial. Young adolescents ( N = 2,199), from 42 randomly selected high schools, participated in the study and answered a paper-and-pencil questionnaire. Multivariate ANOVA were conducted to assess differences in beliefs and intention toward perpetrating sexual IPV between boys and girls, and between perpetrators and nonperpetrators. Results showed that boys were more frequently perpetrators (11.3% vs. 3.2%) and victims (13.6% vs. 6.4%) of sexual IPV than girls. Boys' attitudes toward perpetrating sexual IPV were more supportive than girls'. Boys perceived their social network to be more likely to think that putting pressure on a boyfriend or girlfriend to have sex is okay, and boys had a lower self-efficacy to refrain from pressuring a boyfriend or girlfriend to have sex compared with girls. Both boys and girls, who have perpetrated sexual IPV, had more tolerant attitude, social influence, and self-efficacy beliefs toward sexual IPV perpetration, compared with nonperpetrators. Intention not to perpetrate sexual IPV did not differ between boys and girls, or between perpetrators and nonperpetrators. Our findings suggest that interventions should address attitude and social influence beliefs regarding sexual IPV perpetration. More attention should be given to sexual IPV perpetration among boys. Given that sexual IPV victimization and perpetration are significantly linked, prevention of sexual IPV

  14. The relationship between clients' depression etiological beliefs and psychotherapy orientation preferences, expectations, and credibility beliefs.

    Science.gov (United States)

    Tompkins, Kelley A; Swift, Joshua K; Rousmaniere, Tony G; Whipple, Jason L

    2017-06-01

    The purpose of this study was to examine the relationship between clients' etiological beliefs for depression and treatment preferences, credibility beliefs, and outcome expectations for five different depression treatments-behavioral activation, cognitive therapy, interpersonal psychotherapy, pharmacotherapy, and psychodynamic psychotherapy. Adult psychotherapy clients (N = 98) were asked to complete an online survey that included the Reasons for Depression Questionnaire, a brief description of each of the five treatment options, and credibility, expectancy, and preference questions for each option. On average, the participating clients rated pharmacotherapy as significantly less credible, having a lower likelihood of success, and being less preferred than the four types of psychotherapy. In general, interpersonal psychotherapy was also rated more negatively than the other types of psychotherapy. However, these findings depended somewhat on whether the participating client was personally experiencing depression. Credibility beliefs, outcome expectations, and preferences for pharmacotherapy were positively associated with biological beliefs for depression; however, the other hypothesized relationships between etiological beliefs and treatment attitudes were not supported. Although the study is limited based on the specific sample and treatment descriptions that were used, the results may still have implications for psychotherapy research, training, and practice. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  15. Agency Beliefs Over Time and Across Cultures: Free Will Beliefs Predict Higher Job Satisfaction

    Science.gov (United States)

    Feldman, Gilad; Farh, Jiing-Lih; Wong, Kin Fai Ellick

    2017-01-01

    In three studies, we examined the relationship between free will beliefs and job satisfaction over time and across cultures. Study 1 examined 252 Taiwanese real-estate agents over a 3-months period. Study 2 examined job satisfaction for 137 American workers on an online labor market over a 6-months period. Study 3 extended to a large sample of 14,062 employees from 16 countries and examined country-level moderators. We found a consistent positive relationship between the belief in free will and job satisfaction. The relationship was above and beyond other agency constructs (Study 2), mediated by perceived autonomy (Studies 2-3), and stronger in countries with a higher national endorsement of the belief in free will (Study 3). We conclude that free-will beliefs predict outcomes over time and across cultures beyond other agency constructs. We call for more cross-cultural and longitudinal studies examining free-will beliefs as predictors of real-life outcomes. PMID:29191084

  16. SCIENCE PRE SERVICE TEACHERS BELIEF ON ASSESMENT

    Directory of Open Access Journals (Sweden)

    Ridwan Effendi

    2017-10-01

    Full Text Available This study aims to reveal personal beliefs of prospective science teachers about assessment. The study involved 46 prospective science teachers who have passed the 7th semester the course evaluation. Personal beliefs of prospective science teachers about assessment revealed using Personal Beliefs about Assessment Scale (SKDA. SKDA developed based on standards of assessment literacy and construct validity is done using Rasch models, with a Cronbach Alpha value of 0.93. Analysis and classification level of personal beliefs of prospective science teacher about assessment is done using the Rasch model is based on the logit ability of prospective science teachers based on the separation. The results showed that personal beliefs of prospective science teachers about assessment varies between two or three levels, depending on the standard of assessment literacy. There are still some aspects of the assessment of each standard that is trusted or considered less important by prospective teachers of science, namely: 1 consider the learning targets, learning experiences, and learning decision in choosing methods of assessment; 2 using the existing assessment and available in developing assessment methods; 3 interpret summary score; 4 use the assessment results to decision-making about the school and curriculum development; 5 consider extracurricular activities when developing procedures for judging; 6 report the result to another level with appropriate means and methods; and 7 to know when the assessment results are used inappropriately/inappropriate by others. Abstrak Studi ini bertujuan mengungkap kepercayaan calon guru sains tentang asesmen. Studi melibatkan 46 mahasiswa calon guru sains semester 7 yang telah lulus perkuliahan evaluasi pembelajaran. Kepercayaan calon guru sains tentang asesmen diungkap dengan menggunakan Skala Kepercayaan Diri Asesmen (SKDA. SKDA dikembangkan mengacu pada standar literasi asesmen dan validitas konstruk dilakukan dengan

  17. Predictors of anonymous cyber aggression: the role of adolescents' beliefs about anonymity, aggression, and the permanency of digital content.

    Science.gov (United States)

    Wright, Michelle F

    2014-07-01

    Little attention has been given to whether adolescents' beliefs about anonymity and their normative beliefs about cyber aggression jointly increase their perpetration of cyber aggression. To this end, the present longitudinal study examined the moderating influence of these variables on the relationships among adolescents' attitudes toward the permanency of digital content, confidence with not getting caught, and anonymous cyber aggression (ACA) assessed 1 year later (Time 2). These associations were examined among 274 7th and 8th graders and through five technologies, including social networking sites (SNS), e-mail, instant messenger (IM), mobile phones, and chatrooms. Findings indicated that increases in Time 2 ACA and attitudes toward the permanency of digital content were more strongly related when adolescents reported greater confidence with not getting caught and higher normative beliefs concerning cyber aggression through SNS and mobile phones. In addition, higher levels of attitudes toward the permanency of digital content, confidence with not getting caught, beliefs about anonymity, and normative beliefs regarding cyber aggression were related to greater Time 2 ACA through e-mail, IM, and chatrooms. All findings are discussed in the context of adolescents' positive attitudes toward ACA, and an appeal for additional research is made to understand more about anonymity in cyberspace.

  18. Strong commitment to traditional Protestant religious beliefs is negatively related to beliefs in paranormal phenomena.

    Science.gov (United States)

    Hillstrom, E L; Strachan, M

    2000-02-01

    Numerous studies have yielded small, negative correlations between measures of paranormal and "traditional religious beliefs". This may partly reflect opinions of Christians in the samples who take biblical sanctions against many "paranormal" activities seriously. To test this, 391 college students (270 women and 121 men) rated their beliefs in various paranormal phenomena and were classified as Believers, Nominal Believers, and Nonbelievers on the strength of their self-rated commitment to key biblical (particularly Protestant) doctrines. As predicted, Believers were significantly less likely than Nominal Believers or Nonbelievers to endorse reincarnation, contact with the dead, UFOs, telepathy, prophecy, psychokinesis, or healing, while the beliefs of Nominal Believers were similar to those of Nonbelievers. Substantial percentages of Nominal and Nonbelievers (30-50%) indicated at least moderate acceptance of the paranormal phenomena surveyed.

  19. Apocalypse soon? Dire messages reduce belief in global warming by contradicting just-world beliefs.

    Science.gov (United States)

    Feinberg, Matthew; Willer, Robb

    2011-01-01

    Though scientific evidence for the existence of global warming continues to mount, in the United States and other countries belief in global warming has stagnated or even decreased in recent years. One possible explanation for this pattern is that information about the potentially dire consequences of global warming threatens deeply held beliefs that the world is just, orderly, and stable. Individuals overcome this threat by denying or discounting the existence of global warming, and this process ultimately results in decreased willingness to counteract climate change. Two experiments provide support for this explanation of the dynamics of belief in global warming, suggesting that less dire messaging could be more effective for promoting public understanding of climate-change research.

  20. Probabilistic reasoning in intelligent systems networks of plausible inference

    CERN Document Server

    Pearl, Judea

    1988-01-01

    Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic. The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provid

  1. The effect of belief in free will on prejudice.

    Science.gov (United States)

    Zhao, Xian; Liu, Li; Zhang, Xiao-xiao; Shi, Jia-xin; Huang, Zhen-wei

    2014-01-01

    The current research examined the role of the belief in free will on prejudice across Han Chinese and white samples. Belief in free will refers to the extent to which people believe human beings truly have free will. In Study 1, the beliefs of Han Chinese people in free will were measured, and their social distances from the Tibetan Chinese were used as an index of ethnic prejudice. The results showed that the more that Han Chinese endorsed the belief in free will, the less that they showed prejudice against the Tibetan Chinese. In Study 2, the belief of the Han Chinese in free will was manipulated, and their explicit feelings towards the Uyghur Chinese were used as an indicator of ethnic prejudice. The results showed that the participants in the condition of belief in free will reported less prejudice towards Uyghur Chinese compared to their counterparts in the condition of disbelief in free will. In Study 3, white peoples' belief in free will was manipulated, and their pro-black attitudes were measured as an indirect indicator of racial prejudice. The results showed that, compared to the condition of disbelief in free will, the participants who were primed by a belief in free will reported stronger pro-black attitudes. These three studies suggest that endorsement of the belief in free will can lead to decreased ethnic/racial prejudice compared to denial of the belief in free will. The theoretical and practical implications are discussed.

  2. Comparisons of Belief-Based Personality Constructs in Polish and American University Students: Paranormal Beliefs, Locus of Control, Irrational Beliefs, and Social Interest.

    Science.gov (United States)

    Tobacyk, Jerome J.; Tobacyk, Zofia Socha

    1992-01-01

    Uses Social Learning Theory to compare 149 university students from Poland with 136 university students from the southern United States for belief-based personality constructs and personality correlates of paranormal beliefs. As hypothesized, Poles reported a more external locus of control and significantly greater endorsement of irrational…

  3. The Relative Ineffectiveness of Criminal Network Disruption

    Science.gov (United States)

    Duijn, Paul A. C.; Kashirin, Victor; Sloot, Peter M. A.

    2014-01-01

    Researchers, policymakers and law enforcement agencies across the globe struggle to find effective strategies to control criminal networks. The effectiveness of disruption strategies is known to depend on both network topology and network resilience. However, as these criminal networks operate in secrecy, data-driven knowledge concerning the effectiveness of different criminal network disruption strategies is very limited. By combining computational modeling and social network analysis with unique criminal network intelligence data from the Dutch Police, we discovered, in contrast to common belief, that criminal networks might even become ‘stronger’, after targeted attacks. On the other hand increased efficiency within criminal networks decreases its internal security, thus offering opportunities for law enforcement agencies to target these networks more deliberately. Our results emphasize the importance of criminal network interventions at an early stage, before the network gets a chance to (re-)organize to maximum resilience. In the end disruption strategies force criminal networks to become more exposed, which causes successful network disruption to become a long-term effort. PMID:24577374

  4. Perceived parental beliefs about the causes of success in sport: relationship to athletes' achievement goals and personal beliefs.

    Science.gov (United States)

    White, Sally A; Kavussanu, Maria; Tank, Kari M; Wingate, Jason M

    2004-02-01

    This study examined the relationship between perceived parental beliefs and young athletes' achievement goal orientations and personal beliefs about the causes of success in sport. Participants were 183 male and female athletes, 11-18 years old, involved in team sports. Athletes completed the Task and Ego Orientation in Sport Questionnaire, the Beliefs about the Causes of Sport Success Questionnaire, and two modified versions of the latter inventory to assess their perceptions of their parents' beliefs. Canonical correlation analysis revealed that perceived parental beliefs were related to goal orientations and personal beliefs in a conceptually coherent fashion. Thus, the perceived parental belief that effort leads to success in sport was related to athletes' task orientation and personal belief that effort causes sport success. In contrast, the perceived parental beliefs that superior ability, external factors, and using deceptive tactics are precursors to success in sport corresponded to athletes' ego orientation and the same personal beliefs. The findings are discussed in terms of their implications for understanding the socialization experiences of young athletes.

  5. DNA motif elucidation using belief propagation

    KAUST Repository

    Wong, Ka-Chun; Chan, Tak-Ming; Peng, Chengbin; Li, Yue; Zhang, Zhaolei

    2013-01-01

    Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ?10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors' websites: e.g. http://www.cs.toronto.edu/?wkc/kmerHMM. 2013 The Author(s).

  6. DNA motif elucidation using belief propagation.

    Science.gov (United States)

    Wong, Ka-Chun; Chan, Tak-Ming; Peng, Chengbin; Li, Yue; Zhang, Zhaolei

    2013-09-01

    Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k=8∼10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors' websites: e.g. http://www.cs.toronto.edu/∼wkc/kmerHMM.

  7. DNA motif elucidation using belief propagation

    KAUST Repository

    Wong, Ka-Chun

    2013-06-29

    Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ?10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors\\' websites: e.g. http://www.cs.toronto.edu/?wkc/kmerHMM. 2013 The Author(s).

  8. Preschool Teachers' Attitudes and Beliefs Toward Science

    Science.gov (United States)

    Lloyd, Sharon Henry

    In the United States, a current initiative, Advancing Active STEM Education for Our Youngest Learners, aims to advance science, technology, engineering, and math (STEM) education in early childhood. The purpose of this study was to understand preschool teachers' proficiency with science and address the problem of whether or not science learning opportunities are provided to young children based on teachers' attitudes and beliefs. A theoretical framework for establishing teachers' attitudes toward science developed by van Aalderen-Smeets, van der Molen, and Asma, along with Bandura's theory of self-efficacy were the foundations for this research. Research questions explored preschool teachers' attitudes and beliefs toward science in general and how they differed based on education level and years of preschool teaching experience. Descriptive comparative data were collected from 48 preschool teacher participants using an online format with a self-reported measure and were analyzed using nonparametric tests to describe differences between groups based on identified factors of teacher comfort, child benefit, and challenges. Results indicated that the participants believed that early childhood science is developmentally appropriate and that young children benefit from science instruction through improved school-readiness skills. Preschool teachers with a state credential or an associate's degree and more teaching experience had more teacher comfort toward science based on attitudes and beliefs surveyed. The data indicated participating preschool teachers experienced few challenges in teaching science. The study may support positive social change through increased awareness of strengths and weaknesses of preschool teachers for the development of effective science professional development. Science is a crucial component of school-readiness skills, laying a foundation for success in later grades.

  9. Predicting dyadic adjustment from general and relationship-specific beliefs.

    Science.gov (United States)

    DeBord, J; Romans, J S; Krieshok, T

    1996-05-01

    The cognitive mediation model of human psychological functioning has received increasing attention by researchers studying the role of cognitive variables in relationship distress. This study is an examination of the role of general irrational beliefs, as measured by the Irrational Beliefs Test (IBT; Jones, 1968), and relationship-specific irrational beliefs, as measured by the Relationship Belief Questionnaire (RBQ; Romans & DeBord, 1994), in predicting the perceived quality of relationships by married or cohabiting couples. Results indicated that respondents who reported higher levels of relationship-specific irrational beliefs also reported higher levels of dyadic adjustment; but contrary to expectation, higher levels of general irrational beliefs correlated with lower levels of dyadic adjustment. Implications of these findings are discussed in relation to the depressive realism hypothesis.

  10. The self-attribution bias and paranormal beliefs.

    Science.gov (United States)

    van Elk, Michiel

    2017-03-01

    The present study investigated the relation between paranormal beliefs, illusory control and the self-attribution bias, i.e., the motivated tendency to attribute positive outcomes to oneself while negative outcomes are externalized. Visitors of a psychic fair played a card guessing game and indicated their perceived control over randomly selected cards as a function of the congruency and valence of the card. A stronger self-attribution bias was observed for paranormal believers compared to skeptics and this bias was specifically related to traditional religious beliefs and belief in superstition. No relation between paranormal beliefs and illusory control was found. Self-report measures indicated that paranormal beliefs were associated to being raised in a spiritual family and to anomalous experiences during childhood. Thereby this study suggests that paranormal beliefs are related to specific cognitive biases that in turn are shaped by socio-cultural factors. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Childhood trauma and the development of paranormal beliefs.

    Science.gov (United States)

    Berkowski, Monisha; MacDonald, Douglas A

    2014-04-01

    Belief in the paranormal is fairly prevalent in the general population. Previous research has shown a link between several personological characteristics and paranormal beliefs. The current study attempted to further investigate this link by replicating previous models that have shown a link between childhood trauma, fantasy proneness, and paranormal beliefs. In addition, the study attempted to expand on this model by including other variables such as stigma, resiliency, and coping style. The study used a sample of 198 undergraduate students. A significant correlation between trauma and paranormal beliefs was found. Partial correlations and path analyses revealed that fantasy proneness and avoidant coping style fully mediate the relationship between trauma and paranormal beliefs. The results imply that researchers need to take into account how a person responds to trauma via the development of coping strategies to accurately understand any observed relationship between trauma and paranormal beliefs.

  12. Validation of the Paranormal Health Beliefs Scale for adults.

    Science.gov (United States)

    Donizzetti, Anna Rosa; Petrillo, Giovanna

    2017-01-01

    We present the validation study of the Paranormal Health Beliefs Scale adult version, aimed to measure illusory beliefs about health. The scale was administered to 643 participants (54.3% females), having an average age of 29.7 years (standard deviation = 18.31). The results of the analyses confirmed the dimensions of the Paranormal Health Beliefs Scale as developed in the previous adolescent study (Beliefs: Religious, Superstitious, in Extraordinary Events, Parapsychological, and Pseudo-scientific of a biomedical nature), as well as the convergent and discriminant validity through the correlation with other constructs (locus of control and self-efficacy). The results also showed significant differences between subgroups by gender and age. The Paranormal Health Beliefs Scale shows satisfactory psychometric properties and thus may be used effectively to identify the varied range of illusory beliefs related to health, even within the context of lifelong educational programs aimed at health promotion.

  13. Probability misjudgment, cognitive ability, and belief in the paranormal.

    Science.gov (United States)

    Musch, Jochen; Ehrenberg, Katja

    2002-05-01

    According to the probability misjudgment account of paranormal belief (Blackmore & Troscianko, 1985), believers in the paranormal tend to wrongly attribute remarkable coincidences to paranormal causes rather than chance. Previous studies have shown that belief in the paranormal is indeed positively related to error rates in probabilistic reasoning. General cognitive ability could account for a relationship between these two variables without assuming a causal role of probabilistic reasoning in the forming of paranormal beliefs, however. To test this alternative explanation, a belief in the paranormal scale (BPS) and a battery of probabilistic reasoning tasks were administered to 123 university students. Confirming previous findings, a significant correlation between BPS scores and error rates in probabilistic reasoning was observed. This relationship disappeared, however, when cognitive ability as measured by final examination grades was controlled for. Lower cognitive ability correlated substantially with belief in the paranormal. This finding suggests that differences in general cognitive performance rather than specific probabilistic reasoning skills provide the basis for paranormal beliefs.

  14. Validation of the Paranormal Health Beliefs Scale for adults

    Directory of Open Access Journals (Sweden)

    Anna Rosa Donizzetti

    2017-12-01

    Full Text Available We present the validation study of the Paranormal Health Beliefs Scale adult version, aimed to measure illusory beliefs about health. The scale was administered to 643 participants (54.3% females, having an average age of 29.7 years (standard deviation = 18.31. The results of the analyses confirmed the dimensions of the Paranormal Health Beliefs Scale as developed in the previous adolescent study (Beliefs: Religious, Superstitious, in Extraordinary Events, Parapsychological, and Pseudo-scientific of a biomedical nature, as well as the convergent and discriminant validity through the correlation with other constructs (locus of control and self-efficacy. The results also showed significant differences between subgroups by gender and age. The Paranormal Health Beliefs Scale shows satisfactory psychometric properties and thus may be used effectively to identify the varied range of illusory beliefs related to health, even within the context of lifelong educational programs aimed at health promotion.

  15. Construction and Validation of Afterlife Belief Scale for Muslims.

    Science.gov (United States)

    Ghayas, Saba; Batool, Syeda Shahida

    2017-06-01

    The purpose of this study was to develop a scale in Urdu language for measuring different dimensions of afterlife belief. The scale was subjected to exploratory and confirmatory factor analysis on a sample of 504 individuals (235 men and 269 women) recruited from different cities in the Punjab, Pakistan. After exploratory and confirmatory factor analysis, 16 items were retained with three well-defined factor structures of afterlife belief: positive, negative, and extinction. The alpha coefficients of the subscales ranged from .65 to .78. Convergent and discriminant validity of the subscales of Afterlife Belief Scale was determined by finding its relationship with the Pleasant Afterlife Belief Scale, the Unpleasant Afterlife Belief Scale, the Anxiety Subscale of DASS, and the Belief in Equitable World Scale. The results support that the newly developed scale has promising validity.

  16. Mental illness complicated by the santeria belief in spirit possession.

    Science.gov (United States)

    Alonso, L; Jeffrey, W D

    1988-11-01

    Santeria, a religious system that blends African and Catholic beliefs, is practiced by many Cuban Americans. One aspect of this system is the belief in spirit possession. Basic santeria beliefs and rituals, including the fiesta santera (a gathering at which some participants may become possessed), are briefly described, and four cases in which the patients' belief in possession played a role in their mental illness are presented. The belief in possession can complicate the diagnosis and treatment of mental illness, but it should not be considered a culture-bound syndrome. Rather, it may be a nonspecific symptom of a variety of mental illnesses and should be evaluated in the context of the patient's overall belief system and ability to carry out usual activities.

  17. Feeling Is Believing: Inspiration Encourages Belief in God.

    Science.gov (United States)

    Critcher, Clayton R; Lee, Chan Jean

    2018-05-01

    Even without direct evidence of God's existence, about half of the world's population believes in God. Although previous research has found that people arrive at such beliefs intuitively instead of analytically, relatively little research has aimed to understand what experiences encourage or legitimate theistic belief systems. Using cross-cultural correlational and experimental methods, we investigated whether the experience of inspiration encourages a belief in God. Participants who dispositionally experience more inspiration, were randomly assigned to relive or have an inspirational experience, or reported such experiences to be more inspirational all showed stronger belief in God. These effects were specific to inspiration (instead of adjacent affective experiences) and a belief in God (instead of other empirically unverifiable claims). Being inspired by someone or something (but not inspired to do something) offers a spiritually transcendent experience that elevates belief in God, in part because it makes people feel connected to something beyond themselves.

  18. Contemporary Inuit Traditional Beliefs Concerning Meteorites

    Science.gov (United States)

    Mardon, A. A.; Mardon, E. G.; Williams, J. S.

    1992-07-01

    Inuit religious mythology and the importance of meteorites as "messages" from the Creator of all things is only now being recognized. Field investigations near Resolute, Cornwallis Island in the high Canadian Arctic in 1988 are the bases for this paper. Through interpreters, several elders of the local Inuit described in detail the Inuit belief, recognition, and wonder at the falling meteors & meteorites during the long Polar Night and Polar Day. Such events are passed on in the oral tradition from generation to generation by the elders and especially those elders who fulfill the shamanistic roles. The Inuit have come across rocks that they immediately recognize as not being "natural" and in the cases of a fall that was observed and the rock recovered the meteorite is kept either on the person or in some hidden niche known only to that person. In one story recounted a meteorite fell and was recovered at the birth of one very old elder and the belief was that if the rock was somehow damaged or taken from his possession he would die. Some indirect indication also was conveyed that the discovery and possession of meteorites allow shaman to have "supernatural" power. This belief in the supernatural power of meteorites can be seen historically in many societies, including Islam and the "black rock" (Kaaba) of Mecca. It should also be noted, however, that metallic meteorites were clearly once the major source of iron for Eskimo society as is indicated from the recovery of meteoritical iron arrow heads and harpoon heads from excavated pre-Viking contact sites. The one evident thing that became clear to the author is that the Inuit distinctly believe that these meteorites are religious objects of the highest order and it brings into question the current academic practice of sending meteorites south to research institutes. Any seeming conflict with the traditional use of meteoric iron is more apparent than real--the animals, the hunt, and the act of survival--all being

  19. Perkembangan Proses Pembuatan Biodiesel sebagai Bahan Bakar Nabati (BBN

    Directory of Open Access Journals (Sweden)

    Joelianingsih

    2006-12-01

    Full Text Available As energy dernands increase and fossil fuel reservas are limited, research is directed towards alternative renewable fluls. A potential diesel fuel substitusi is biodiesel, obtained from fatty acids methyl esters (FAME and produced by the transesterfication reaction of triglyceride or free fatty acid (FFA of vegetable oils with short-chain alcohol, mainly methanol. Most of the currently of alcohol. Although the removal of the excess alcohol can be easily achieved by distillation, however the removal of catlyst and the by-product formed from its reaction with the reactants is complicated while several methode for glycerol purification have been reported. The disadvantages resulting from the use of a catalyst and itsremoval from theproducts can beeliminated if a non-catalytic reaction of the vegetable oils with alcohol can be realized and a simpler and cheaper process can be developed.indonesia has the opportunity to expand oil palm and other plantations such as jatropha curcas (jarak pagarin order to provide sufficient amount of crude oil for development of biodiesel industry.

  20. BBN PLUM: MUC-4 Test Results and Analysis

    National Research Council Canada - National Science Library

    Weischedel, Ralph; Ayuso, Damaris; Boisen, Sean; Fox, Heidi; Gish, Herbert; Ingria, Robert

    1992-01-01

    Our mid-term to long-term goals in data extraction from text for the next one to three years are to achieve much greater portability to new languages and new domains, greater robustness, and greater scalability...

  1. Knowledge formalization for vector data matching using belief theory

    Directory of Open Access Journals (Sweden)

    Ana-Maria Olteanu-Raimond

    2015-06-01

    Full Text Available Nowadays geographic vector data is produced both by public and private institutions using well defined specifications or crowdsourcing via Web 2.0 mapping portals. As a result, multiple representations of the same real world objects exist, without any links between these different representations. This becomes an issue when integration, updates, or multi-level analysis needs to be performed, as well as for data quality assessment. In this paper a multi-criteria data matching approach allowing the automatic definition of links between identical features is proposed. The originality of the approach is that the process is guided by an explicit representation and fusion of knowledge from various sources. Moreover the imperfection (imprecision, uncertainty, and incompleteness is explicitly modeled in the process. Belief theory is used to represent and fuse knowledge from different sources, to model imperfection, and make a decision. Experiments are reported on real data coming from different producers, having different scales and either representing relief (isolated points or road networks (linear data.

  2. Effect of restriction of working memory on reported paranormal belief.

    Science.gov (United States)

    Dudley, R T

    1999-02-01

    56 college students completed Tobacyk's 1988 Revised Paranormal Belief Scale and Watson, Clark, and Tellegen's 1988 Positive and Negative Affect Scale. Experimental group participants, but not control group participants, rehearsed a five-digit number while completing the Paranormal Belief Scale. Analysis showed higher reported paranormal belief for experimental group participants but no differences on the Positive and Negative Affect Scale. Results are discussed in terms of the effect of restriction in working memory on the critical evaluation of paranormal phenomena.

  3. Physical education candidate teachers' beliefs about vocational self-esteem

    OpenAIRE

    OZSAKER, Murat; CANPOLAT, A. Meliha

    2014-01-01

    The purpose of this study was to determine epistemological belief and vocational self-esteem physical education candidate teachers of Physical Education and Sports Department in 3 different universities, and also to examine effect of epistemological beliefs on vocational self-esteem. A total of 346 candidate teacher respondents (137 female and 209 male) participated in the study. Epistemological Beliefs and Vocational Self-Esteem Scale were used to determine candidate teachers’ epistemologica...

  4. Affective Beliefs Influence the Experience of Eating Meat

    OpenAIRE

    Anderson, Eric C.; Barrett, Lisa Feldman

    2016-01-01

    People believe they experience the world objectively, but research continually demonstrates that beliefs influence perception. Emerging research indicates that beliefs influence the experience of eating. In three studies, we test whether beliefs about how animals are raised can influence the experience of eating meat. Samples of meat were paired with descriptions of animals raised on factory farms or raised on humane farms. Importantly, the meat samples in both conditions were identical. Howe...

  5. Belief Revision in the GOAL Agent Programming Language

    DEFF Research Database (Denmark)

    Spurkeland, Johannes Svante; Jensen, Andreas Schmidt; Villadsen, Jørgen

    2013-01-01

    Agents in a multiagent system may in many cases find themselves in situations where inconsistencies arise. In order to properly deal with these, a good belief revision procedure is required. This paper illustrates the usefulness of such a procedure: a certain belief revision algorithm is consider...... in order to deal with inconsistencies and, particularly, the issue of inconsistencies, and belief revision is examined in relation to the GOAL agent programming language....

  6. Topological structures of complex belief systems (II): Textual materialization

    OpenAIRE

    Nescolarde Selva, Josué; Usó i Domènech, Josep Lluís

    2013-01-01

    Mythical and religious belief systems in a social context can be regarded as a conglomeration of sacrosanct rites, which revolve around substantive values that involve an element of faith. Moreover, we can conclude that ideologies, myths and beliefs can all be analyzed in terms of systems within a cultural context. The significance of being able to define ideologies, myths and beliefs as systems is that they can figure in cultural explanations. This, in turn, means that such systems can figur...

  7. Testing a biopsychosocial model of the basic birth beliefs.

    Science.gov (United States)

    Preis, Heidi; Chen, Rony; Eisner, Michal; Pardo, Joseph; Peled, Yoav; Wiznitzer, Arnon; Benyamini, Yael

    2018-03-01

    Women perceive what birth is even before they are pregnant for the first time. Part of this conceptualization is the basic belief about birth as a medical and natural process. These two separate beliefs are pivotal in the decision-making process about labor and birth. Adapting Engel's biopsychosocial framework, we explored the importance of a wide range of factors which may contribute to these beliefs among first-time mothers. This observational study included 413 primiparae ≥24 weeks' gestation, recruited in medical centers and in natural birth communities in Israel. The women completed a questionnaire which included the Birth Beliefs Scale and a variety of biopsychosocial characteristics such as obstetric history, birth environment, optimism, health-related anxiety, and maternal expectations. Psychological dispositions were more related to the birth beliefs than the social or biomedical factors. Sociodemographic characteristics and birth environment were only marginally related to the birth beliefs. The basic belief that birth is a natural process was positively related to optimism and to conceiving spontaneously. Beliefs that birth is a medical process were related to pessimism, health-related anxiety, and to expectations that an infant's behavior reflects mothering. Expectations about motherhood as being naturally fulfilling were positively related to both beliefs. Psychological factors seem to be most influential in the conceptualization of the beliefs. It is important to recognize how women interpret the messages they receive about birth which, together with their obstetric experience, shape their beliefs. Future studies are recommended to understand the evolution of these beliefs, especially within diverse cultures. © 2017 Wiley Periodicals, Inc.

  8. Modeling intelligent agent beliefs in a card game scenario

    Science.gov (United States)

    Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

    In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

  9. Multiculturalism, Medicine, and Health Part III: Health Beliefs

    OpenAIRE

    Masi, Ralph

    1988-01-01

    Supernatural beliefs relate to a Power or powers considered beyond nature. Persons who wish to draw upon the power of supernatural forces often attempt to do so through prayers, ceremonies, or special acknowledgement. While some physicians feel uncomfortable at times with beliefs that differ from their own, the chaplaincy system, in place in most hospitals, is evidence that health-care systems can comfortably accommodate supernatural beliefs. We must make an effort to understand and accommoda...

  10. Explanatory Coherence and Belief Revision in Naive Physics

    Science.gov (United States)

    1988-07-01

    continental drift (Thagard & Nowak, 1988), and debates about why the dinosaurs became extinct . Application of ECHO to the belief revisions in Pat and Hal...rewono of nocuamy Idid 4onoly by bodck number) Students of reasoning have long tried to understand how people revise systems of beliefs. We maintain...Princeton University Students of reasoning have long tried to understand how people revise systems of beliefs (see Wertheimer, 1945, for example). We will

  11. Analyzing Sexual Health-Related Beliefs Among Couples in Marriage Based on the Health Belief Model

    Directory of Open Access Journals (Sweden)

    Majid Barati

    2014-06-01

    Full Text Available Introduction: Sexual health is the integrity between mind, emotions, and body, and any disorder leading to discoordination, can be associated with sexual dysfunction. The aim of this study was to investigate the beliefs of couples attending marriage counseling centers toward sexual health based on the health belief model. Materials and Methods: This cross sectional descriptive study was performed on 400 couples referring to marriage counseling centers of Hamadan recruited with a random sampling method. The participants completed a self-administered questionnaire including demographic characteristics, knowledge and health belief model constructs. Data analysis was performed using SPSS-16 software, by Pearson’s coefficient correlation, independent T-test, and one-way ANOVA. Results: Couples had a moderate knowledge of sexual health. In addition, perceived susceptibility and severity of the consequences of unsafe sexual behavior among couples were not satisfactory however, perceived benefits and barriers were reported in a relatively good level. Internet and friends were the most important sources for sexual health information. Conclusion: Promoting knowledge and beliefs toward sexual health by preparing training packages based on the needs of couples and removing obstacles to have normal sexual behavior are necessary.

  12. Having belief(s) in social virtual worlds: A decomposed approach

    NARCIS (Netherlands)

    Merikivi, J.; Verhagen, T.; Feldberg, J.F.M.

    2013-01-01

    The interest in social virtual worlds with multiple functions has mushroomed during the past few years. The key challenge social virtual worlds face while attempting to anchor and serve the masses is to reflect the core beliefs of their users. As existing research lacks insight into these core

  13. Measuring epistemological beliefs in history education : An exploration of naïve and nuanced beliefs

    NARCIS (Netherlands)

    Stoel, G.; Logtenberg, A.; Wansink, B.; Huijgen, T.; van Boxtel, C.; van Drie, J.

    2017-01-01

    This study investigates a questionnaire that measures epistemological beliefs in history. Participants were 922 exam students. A basic division between naïve and nuanced ideas underpins the questionnaire. However, results show this division oversimplifies the underlying structure. Exploratory factor

  14. Beliefs about Meditating among University Students, Faculty, and Staff: A Theory-Based Salient Belief Elicitation

    Science.gov (United States)

    Lederer, Alyssa M.; Middlestadt, Susan E.

    2014-01-01

    Objective: Stress impacts college students, faculty, and staff alike. Although meditation has been found to decrease stress, it is an underutilized strategy. This study used the Reasoned Action Approach (RAA) to identify beliefs underlying university constituents' decision to meditate. Participants: N = 96 students, faculty, and staff at a large…

  15. Logic, Beliefs, and Instruction: A Test of the Default Interventionist Account of Belief Bias

    Science.gov (United States)

    Handley, Simon J.; Newstead, Stephen E.; Trippas, Dries

    2011-01-01

    According to dual-process accounts of thinking, belief-based responses on reasoning tasks are generated as default but can be intervened upon in favor of logical responding, given sufficient time, effort, or cognitive resource. In this article, we present the results of 5 experiments in which participants were instructed to evaluate the…

  16. Belief in a just what? : Demystifying just world beliefs by distinguishing sources of justice

    NARCIS (Netherlands)

    Stroebe, Katherine; Postmes, Tom; Täuber, Susanne; Stegeman, Alwin; John, Melissa-Sue

    2015-01-01

    People’s Belief in a Just World (BJW) plays an important role in coping with misfortune and unfairness. This paper demonstrates that understanding of the BJW concept, and its consequences for behavior, is enhanced if we specify what (or who) the source of justice might be. We introduce a new scale,

  17. A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

    Science.gov (United States)

    Hossain, Moinul; Muromachi, Yasunori

    2012-03-01

    The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. When Do Types Induce the Same Belief Hierarchy?

    Directory of Open Access Journals (Sweden)

    Andrés Perea

    2016-10-01

    Full Text Available Type structures are a simple device to describe higher-order beliefs. However, how can we check whether two types generate the same belief hierarchy? This paper generalizes the concept of a type morphism and shows that one type structure is contained in another if and only if the former can be mapped into the other using a generalized type morphism. Hence, every generalized type morphism is a hierarchy morphism and vice versa. Importantly, generalized type morphisms do not make reference to belief hierarchies. We use our results to characterize the conditions under which types generate the same belief hierarchy.

  19. THE PRONUNCIATION COMPONENT IN ESL LESSONS: TEACHERS’ BELIEFS AND PRACTICES

    Directory of Open Access Journals (Sweden)

    Shanina Sharatol Ahmad Shah

    2017-01-01

    Full Text Available Research has shown that teachers’ beliefs on teaching and learning exert an influence on their actual classroom practices. In the teaching of English pronunciation, teachers’ beliefs play a crucial role in the choice of pronunciation components taught in the ESL classrooms. This paper explores teachers’ beliefs about teaching English pronunciation in Malaysian classrooms and the extent to which these beliefs influenced the teachers’ classroom instructions. Employing a multiple case study of five ESL teachers in secondary schools, this study investigated the beliefs the teachers have formed about pronunciation focused areas and classroom practices in teaching English pronunciation. Data were collected through actual classroom observations and semi-structured interviews with the teachers and students. The findings of the study found that ESL teachers seem to believe that pronunciation skills are to be taught integratedly with other English language skills. Results also indicate a discrepancy between these teachers’ beliefs on the focused areas of pronunciation and the stated curriculum specifications.  Additionally, the ESL teachers seem to have vague and contradictory beliefs about pronunciation focused areas. These beliefs are based on their previous language learning and professional experience as well as other contextual factors such as examination demands and time constraints. As a result, these beliefs lead to the pronunciation component being neglected despite it being stipulated by the curriculum.

  20. Objective measurement of paranormal belief: a rebuttal to Vitulli.

    Science.gov (United States)

    Lange, R; Irwin, H J; Houran, J

    2001-06-01

    Effects of age and sex in paranormal belief remain controversial because issues of scaling and differential item function are not given due attention. Therefore, in response to the recent debate between Irwin and Vitulli, these issues are reviewed and validated as crucial approaches for obtaining an objective measure of paranormal belief. A Rasch version of Tobacyk's Paranormal Belief Scale has been developed, but research with this scale suggests that--contrary to past literature and recently refined studies--age and sex are neither consistent nor crucial factors mediating paranormal belief.