scholarly journals Bayesian approximations to the theory of visual attention (TVA) in a foraging task

2021 ◽  
Author(s):  
Sophie Le ◽  
Arni Kristjansson ◽  
W. Joseph MacInnes
Keyword(s):  
Decision Making ◽  
Visual Attention ◽  
Selection Process ◽  
High Accuracy ◽  
Foraging Strategies ◽  
Bayesian Classifiers ◽  
Attentional Function ◽  
Sensory Evidence ◽  
Using Data ◽  
Foraging Task

Foraging as a natural visual search for multiple targets has increasingly been studied in humans in recent years. Here, we aimed to model the differences in foraging strategies between feature and conjunction foraging tasks found by Kristjánsson et al. (2014). Bundesen (1990) proposed the Theory of Visual Attention (TVA) as a computational model of attentional function that divides the selection process into filtering and pigeonholing. The theory describes a mechanism by which the strength of sensory evidence serves to categorize elements. We combined these ideas to train augmented Naïve Bayesian classifiers using data from Kristjánsson et al. (2014) as input. Specifically, we attempted to answer whether it is possible to predict how frequently observers switch between different target types during consecutive selections (switch rates) during feature and conjunction foraging using Bayesian classifiers. We formulated eleven new parameters that represent key sensory and bias information that could be used for each selection during the foraging task and tested them with multiple Bayesian models. Separate Bayesian networks were trained on feature and conjunction foraging data, and parameters that had no impact on the model's predictability were pruned away. We report high accuracy for switch prediction in both tasks from the classifiers, although the model for conjunction foraging was more accurate. We also report our Bayesian parameters in terms of their theoretical associations to TVA parameters, π_j (denoting the pertinence value) and β_i (denoting the decision-making bias).

STRATEGI MAKSIMALISASI ANGGARAN BELANJA PADA BALAI PENELITIAN DAN PENGEMBANGAN LINGKUNGAN HIDUP DAN KEHUTANAN MANOKWARI

2016 ◽  
Vol 8 (2) ◽  
Author(s):  
Arif Hasan ◽  
Dedi Budiman Hakim ◽  
Irdika Mansur
Keyword(s):  
Decision Making ◽  
Descriptive Analysis ◽  
Secondary Data ◽  
Primary Data ◽  
Fiscal Year ◽  
The Third ◽  
Swot Matrix ◽  
Three Stages ◽  
Using Data

This study aims to analyze causes of the low uptake of the budget and formulate a strategy of maximizing the absorption of expenditure on Balai Penelitian dan Pengembangan Lingkungan Hidup dan Kehutanan Manokwari. Respondents involved are 20 people that consist of: treasury officials and holder output of activity. The data used were secondary data in the form of reports on budget realization (LRA) quarter I, II, III and IV of the fiscal year 2011 to 2015, and the primary data were in the form of interviews with the help of a questionnaire. While the analysis of the data used was descriptive analysis using data tabulation, and the analysis of the three stages strategy of the decision making used IFE and EFE matrix, SWOT matrix and QSPM matrix.The results showed that there are 19 factors causing low of budget absorption until the end of the third quarter, and there were 10 drafts of policy as a strategy for maximizing the absorption of the budget on Balai Penelitian dan Pengembangan Lingkungan Hidup dan Kehutanan Manokwari.ABSTRAKPenelitian ini bertujuan untuk menganalisis penyebab rendahnya penyerapan anggaran belanja dan merumuskan strategi maksimalisasi penyerapan anggaran belanja pada Balai Penelitian dan Pengembangan Lingkungan Hidup dan Kehutanan Manokwari. Responden yang terlibat adalah 20 orang yaitu pejabat perbendaharaan dan pemegang output kegiatan. Data yang digunakan adalah data sekunder berupa laporan realisasi anggaran (LRA) triwulan I, II, III dan IV tahun anggaran 2011 sampai 2015, dan data primer berupa wawancara dengan bantuan kuesioner. Sedangkan analisis data yang digunakan adalah analisis deskriptif menggunakan analisis tabulasi, dan analisis analisis strategi tiga tahap pengambilan keputusan menggunakan matriks IFE dan EFE, matriks SWOT dan matriks QSPM. Hasil penelitian menunjukkan bahwa terdapat 19 faktor penyebab rendahnya penyerapan anggaran belanja sampai akhir triwulan III, dan terdapat 10 rancangan kebijakan sebagai strategi maksimalisasi penyerapan anggaran belanja di Balai Penelitian dan Pengembangan Lingkungan Hidup dan Kehutanan Manokwari.

Influence of Confucian culture on entrepreneurial decision making using data from China's floating population

2020 ◽  
Vol 48 (7) ◽  
pp. 1-12
Author(s):  
Ran Xiong ◽  
Ping Wei
Keyword(s):  
Decision Making ◽  
Floating Population ◽  
Positive Role ◽  
Confucian Culture ◽  
Chinese Nation ◽  
Using Data ◽  
Entrepreneurial Decision ◽  
And Behavior ◽  
The Relationship

Confucian culture has had a deep-rooted influence on Chinese thinking and behavior for more than 2,000 years. With a manually created Confucian culture database and the 2017 China floating population survey, we used empirical analysis to test the relationship between Confucian culture and individual entrepreneurial choice using data obtained from China's floating population. After using the presence and number of Confucian schools and temples, and of chaste women as instrumental variables to counteract problems of endogeneity, we found that Confucian culture had a significant role in promoting individuals' entrepreneurial decision making among China's floating population. The results showed that, compared with those from areas of China not strongly influenced by Confucian culture, individuals from areas that are strongly influenced by Confucian culture were more likely to choose entrepreneurship as their occupation choice. Our findings reveal cultural factors that affect individual entrepreneurial behavior, and also illustrate the positive role of Confucianism as a representative of the typical cultures of the Chinese nation in the 21st century.

scholarly journals The Impact of Social Media Use on Consumers’ Restaurant Consumption Experiences: A Qualitative Study

2021 ◽  
Vol 13 (12) ◽  
pp. 6581
Author(s):  
Jooyoung Hwang ◽  
Anita Eves ◽  
Jason L. Stienmetz
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Selection Process ◽  
Decision Making Process ◽  
Structured Interviews ◽  
High Standards ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality ◽  
Search For Information ◽  
The Impact

Travellers have high standards and regard restaurants as important travel attributes. In the tourism and hospitality industry, the use of developed tools (e.g., smartphones and location-based tablets) has been popularised as a way for travellers to easily search for information and to book venues. Qualitative research using semi-structured interviews based on the face-to-face approach was adopted for this study to examine how consumers’ restaurant selection processes are performed with the utilisation of social media on smartphones. Then, thematic analysis was adopted. The findings of this research show that the adoption of social media on smartphones is positively related with consumers’ gratification. More specifically, when consumers regard that process, content and social gratification are satisfied, their intention to adopt social media is fulfilled. It is suggested by this study that consumers’ restaurant decision-making process needs to be understood, as each stage of the decision-making process is not independent; all the stages of the restaurant selection process are organically connected and influence one another.

scholarly journals Forecasting and Analysis Tools for Regional Industries’ Dynamics

2021 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Valeriy Semenychev ◽  
Anastasiya Korobetskaya
Keyword(s):  
Decision Making ◽  
Evolutionary Dynamics ◽  
Forecast Accuracy ◽  
High Accuracy ◽  
General Idea ◽  
Russian Regions ◽  
Seasonal Component ◽  
Modeling Analysis ◽  
Splitting Time ◽  
Regions Of Russia

The article is devoted to the author’s approach and tools for regional industries’ modeling, analysis and forecasting, following the general idea of splitting time series into four components: trend, cycles, seasonal component, and residuals. However, the authors introduce new approaches, models, metrics, and identification algorithms, and the components’ interaction structures, having included the analysis of 12 industries in 82 regions of Russia. The models and forecast accuracy were tested on 3–12 month forecasts, thus proving their high accuracy. Therefore, the article proposes not only new systematic econometric tools but a methodology for decision making, developed to provide stable and adequate characteristics of complex non-linear evolutionary dynamics of Russian regions.

scholarly journals New dilemmas, old problems: advances in data analysis and its geoethical implications in groundwater management

2021 ◽  
Vol 3 (6) ◽  
Author(s):  
César de Oliveira Ferreira Silva ◽  
Mariana Matulovic ◽  
Rodrigo Lilla Manzione
Keyword(s):  
Decision Making ◽  
Data Analytics ◽  
Data Science ◽  
Final Decision ◽  
Aquifer Recharge ◽  
Groundwater Governance ◽  
Ethical Attitude ◽  
New Information ◽  
Modeling Experiment ◽  
Using Data

Abstract Groundwater governance uses modeling to support decision making. Therefore, data science techniques are essential. Specific difficulties arise because variables must be used that cannot be directly measured, such as aquifer recharge and groundwater flow. However, such techniques involve dealing with (often not very explicitly stated) ethical questions. To support groundwater governance, these ethical questions cannot be solved straightforward. In this study, we propose an approach called “open-minded roadmap” to guide data analytics and modeling for groundwater governance decision making. To frame the ethical questions, we use the concept of geoethical thinking, a method to combine geoscience-expertise and societal responsibility of the geoscientist. We present a case study in groundwater monitoring modeling experiment using data analytics methods in southeast Brazil. A model based on fuzzy logic (with high expert intervention) and three data-driven models (with low expert intervention) are tested and evaluated for aquifer recharge in watersheds. The roadmap approach consists of three issues: (a) data acquisition, (b) modeling and (c) the open-minded (geo)ethical attitude. The level of expert intervention in the modeling stage and model validation are discussed. A search for gaps in the model use is made, anticipating issues through the development of application scenarios, to reach a final decision. When the model is validated in one watershed and then extrapolated to neighboring watersheds, we found large asymmetries in the recharge estimatives. Hence, we can show that more information (data, expertise etc.) is needed to improve the models’ predictability-skill. In the resulting iterative approach, new questions will arise (as new information comes available), and therefore, steady recourse to the open-minded roadmap is recommended. Graphic abstract

Embracing School Counselors’ Situatedness: Data-Based Decision Making as Fulfillment of a Complex Identity

2021 ◽  
Vol 24 (1_part_3) ◽  
pp. 2156759X2110119
Author(s):  
Brett Zyromski ◽  
Catherine Griffith ◽  
Jihyeon Choi
Keyword(s):  
Decision Making ◽  
School Counselors ◽  
School Counselor ◽  
Use Of Data ◽  
Counselor Identity ◽  
Using Data ◽  
Definition Of ◽  
Support Students ◽  
Students Success ◽  
Data Based Decision Making

Since at least the 1930s, school counselors have used data to inform school counseling programming. However, the evolving complexity of school counselors’ identity calls for an updated understanding of the use of data. We offer an expanded definition of data-based decision making that reflects the purpose of using data in educational settings and an appreciation of the complexity of the school counselor identity. We discuss implications for applying the data-based decision-making process using a multifaceted school counselor identity lens to support students’ success.

scholarly journals Deep learning for cephalometric landmark detection: systematic review and meta-analysis

2021 ◽  
Author(s):  
Falk Schwendicke ◽  
Akhilanand Chaurasia ◽  
Lubaina Arsiwala ◽  
Jae-Hong Lee ◽  
Karim Elhennawy ◽  
...  
Keyword(s):  
Systematic Review ◽  
Deep Learning ◽  
Meta Analysis ◽  
High Accuracy ◽  
Risk Of Bias ◽  
Automated Detection ◽  
Reference Test ◽  
Landmark Detection ◽  
Future Studies ◽  
Using Data

Abstract Objectives Deep learning (DL) has been increasingly employed for automated landmark detection, e.g., for cephalometric purposes. We performed a systematic review and meta-analysis to assess the accuracy and underlying evidence for DL for cephalometric landmark detection on 2-D and 3-D radiographs. Methods Diagnostic accuracy studies published in 2015-2020 in Medline/Embase/IEEE/arXiv and employing DL for cephalometric landmark detection were identified and extracted by two independent reviewers. Random-effects meta-analysis, subgroup, and meta-regression were performed, and study quality was assessed using QUADAS-2. The review was registered (PROSPERO no. 227498). Data From 321 identified records, 19 studies (published 2017–2020), all employing convolutional neural networks, mainly on 2-D lateral radiographs (n=15), using data from publicly available datasets (n=12) and testing the detection of a mean of 30 (SD: 25; range.: 7–93) landmarks, were included. The reference test was established by two experts (n=11), 1 expert (n=4), 3 experts (n=3), and a set of annotators (n=1). Risk of bias was high, and applicability concerns were detected for most studies, mainly regarding the data selection and reference test conduct. Landmark prediction error centered around a 2-mm error threshold (mean; 95% confidence interval: (–0.581; 95 CI: –1.264 to 0.102 mm)). The proportion of landmarks detected within this 2-mm threshold was 0.799 (0.770 to 0.824). Conclusions DL shows relatively high accuracy for detecting landmarks on cephalometric imagery. The overall body of evidence is consistent but suffers from high risk of bias. Demonstrating robustness and generalizability of DL for landmark detection is needed. Clinical significance Existing DL models show consistent and largely high accuracy for automated detection of cephalometric landmarks. The majority of studies so far focused on 2-D imagery; data on 3-D imagery are sparse, but promising. Future studies should focus on demonstrating generalizability, robustness, and clinical usefulness of DL for this objective.

scholarly journals Flexible categorization in perceptual decision making

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Genís Prat-Ortega ◽  
Klaus Wimmer ◽  
Alex Roxin ◽  
Jaime de la Rocha
Keyword(s):  
Decision Making ◽  
Network Models ◽  
Drift Diffusion Model ◽  
Perceptual Decision Making ◽  
Drift Diffusion ◽  
Perceptual Decision ◽  
Attractor Dynamics ◽  
Attractor Model ◽  
Sensory Evidence ◽  
Winner Take All

AbstractPerceptual decisions rely on accumulating sensory evidence. This computation has been studied using either drift diffusion models or neurobiological network models exhibiting winner-take-all attractor dynamics. Although both models can account for a large amount of data, it remains unclear whether their dynamics are qualitatively equivalent. Here we show that in the attractor model, but not in the drift diffusion model, an increase in the stimulus fluctuations or the stimulus duration promotes transitions between decision states. The increase in the number of transitions leads to a crossover between weighting mostly early evidence (primacy) to weighting late evidence (recency), a prediction we validate with psychophysical data. Between these two limiting cases, we found a novel flexible categorization regime, in which fluctuations can reverse initially-incorrect categorizations. This reversal asymmetry results in a non-monotonic psychometric curve, a distinctive feature of the attractor model. Our findings point to correcting decision reversals as an important feature of perceptual decision making.

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