scholarly journals Questionnaire Investigation on the Needs at Fuji City and its Sensibility Analysis Utilizing Bayesian Network

2019 ◽  
Vol 11 (2) ◽  
pp. 125
Author(s):  
Tsuyoshi Aburai ◽  
Akane Okubo ◽  
Daisuke Suzuki ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Surrounding Area ◽  
Network Sensitivity ◽  
The Future ◽  
Sensibility Analysis

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. These are analyzed by using Bayesian Network. Sensitivity analysis is also conducted. As there are so many items, we focus on “The image of the surrounding area at this shopping street” and pick up former half and make sensitivity analysis in this paper. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Questionnaire Investigation on Tourists’ Behavior and its Sensibility Analysis Utilizing Bayesian Network

2018 ◽  
Vol 7 (1) ◽  
pp. 11
Author(s):  
Akane Okubo ◽  
Tsuyosi Aburai ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Local Government ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Back Propagation ◽  
Izu Peninsula ◽  
Regional Collaboration ◽  
Cherry Blossom ◽  
Sensibility Analysis ◽  
Tourism Service

Tourists from abroad are increasing rapidly in Japan. Kawazu town in Izu Peninsula is famous for its cherry trees. In the cherry blossom season, many tourists visit this town. In order to get much more visitors, tourists’ behavior should be investigated much further. The Kawazu Cherry Blossom Festival was carried out in February 2015. Our research investigation was performed during that period. In this paper, a questionnaire investigation is executed in order to clarify tourists’ behavior, and to seek the possibility of developing regional collaboration among local government, tourism related industry and visitors. In this research, we construct the model utilizing Bayesian Network and causal relationship is sequentially chained by the characteristics of travelers, an objective to visit Izu Peninsula in Japan and the main occasion to visit them. We analyzed them by sensitivity analysis and some useful results were obtained. Sensitivity analysis is performed by back propagation method. We have presented the paper concerning this. But the volume becomes too large, therefore we have split them and this paper shows the latter half of the investigation result by setting evidence to Bayesian Network items. These are utilized for constructing a much more effective and useful tourism service. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Fuji Shopping Street Town

2018 ◽  
Vol 9 (2) ◽  
pp. 46
Author(s):  
Tsuyoshi Aburai ◽  
Akane Okubo ◽  
Daisuke Suzuki ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Network Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Back Propagation ◽  
The Future

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city (two for Fuji Shopping Street Town and two for Yoshiwara Shopping Street Town). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street Town and Yoshiwara Shopping Street Town. Therefore we focus Fuji Shopping Street Town in this paper. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Bayesian Network Analysis for the Questionnaire Investigation on the Impression at Fuji City

2018 ◽  
Vol 9 (6) ◽  
pp. 1
Author(s):  
Daisuke Suzuki ◽  
Akane Okubo ◽  
Tsuyosi Aburai ◽  
Kazuhiro Takeyasu
Keyword(s):  
Sensitivity Analysis ◽  
Network Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
The Future

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. In this paper, we mainly focus the impression the visitors feel and analyze them. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Yoshiwara Shopping Street in Fuji City

2018 ◽  
Vol 9 (1) ◽  
pp. 211
Author(s):  
Kazuhiro Takeyasu ◽  
Tsuyosi Aburai ◽  
Akane Okubo ◽  
Daisuke Suzuki
Keyword(s):  
Sensitivity Analysis ◽  
Network Analysis ◽  
Bayesian Network ◽  
Causal Relationship ◽  
Back Propagation ◽  
The Future

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city (two for Fuji Shopping Street and two for Yoshiwara Shopping Street). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street and Yoshiwara Shopping Street. Therefore we focus Yoshiwara Shopping Street in this paper. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated.

scholarly journals How Does the Location of Urban Facilities Affect the Forecasted Population Change in the Osaka Metropolitan Fringe Area?

2020 ◽  
Vol 13 (1) ◽  
pp. 110
Author(s):  
Haruka Kato
Keyword(s):  
Network Analysis ◽  
Bayesian Network ◽  
Public Housing ◽  
Causal Relationship ◽  
Population Change ◽  
Residential Areas ◽  
New Town ◽  
Location Optimization ◽  
The Future ◽  
Future Population

This study aims to clarify the statistical causal relationship between the locations of urban facilities and forecasted population changes according to types of residential clusters in the Osaka Metropolitan Fringe areas. This paper’s background is the location optimization plan policy formulated by the Japanese MLIT (Ministry of Land, Infrastructure, Transport, and Tourism) in 2015. The methods combined urban ecological analysis, cohort analysis, and Bayesian network analysis. Using the Bayesian network analysis, the causal relationship between the forecasted population change ratio and the urban facility location was analyzed. The results suggest the location of urban facilities for each residential cluster that will prevent a rapid population decline in the future. Specifically, in the sprawl cluster, this study found that residential areas closer to medical facilities will sustain the future population, while in the old new-town cluster, this study found that residential areas closer to train stations will best sustain the future population. However, in the public housing cluster, residential areas more distant from regional resources will best sustain the future population. Therefore, it is worth considering different urban designs in the old new-town and public housing clusters, rather than the location optimization plan policy.

Perception and Reality—Economic Inequality as a Driver of Populism?

2019 ◽  
Vol 41 (2) ◽  
pp. 337-358 ◽  
Author(s):  
Michael Hüther ◽  
Matthias Diermeier
Keyword(s):  
Economic Development ◽  
Income Distribution ◽  
Welfare State ◽  
Causal Relationship ◽  
Economic Inequality ◽  
Public Officials ◽  
Middle Classes ◽  
The Future ◽  
General Criticism ◽  
The Welfare State

Abstract Can the rise of populism be explained by the growing chasm between rich and poor? With regard to Germany, such a causal relationship must be rejected. Income distribution in Germany has been very stable since 2005, and people’s knowledge on actual inequality and economic development is limited: inequality and unemployment are massively overestimated. At the same time, a persistently isolationist and xenophobic group with diverse concerns and preferences has emerged within the middle classes of society that riggers support for populist parties. This mood is based on welfare chauvinism against immigration rather than on a general criticism of distribution. Since the immigration of recent years will inevitably affect the relevant indicators concerning distribution, an open, cautious but less heated approach is needed in the debate on the future of the welfare state. In order to address and take the local concerns of citizens seriously, an increased exchange with public officials on the ground is needed.

Sensitivitätsanalyse des Fördergutverhaltens*/Sensitivity analysis of transported material – Physics simulation based analysis of bulk material related to the topology of vibratory bowl feeders

2015 ◽  
Vol 105 (09) ◽  
pp. 622-626
Author(s):  
C. Stocker ◽  
G. Reinhart
Keyword(s):  
Sensitivity Analysis ◽  
Future Development ◽  
Development Process ◽  
Bulk Material ◽  
Automated Generation ◽  
Simulation Based ◽  
The Future ◽  
Physics Simulation ◽  
Material Physics ◽  
Transported Material

Vibrationswendelförderer (VWF) sind die meistverwendeten Systeme zur automatisierten Vereinzelung und Zuführung von Schüttgut. Zur Verbesserung der derzeit manuellen Entwicklung, werden Methoden zur Simulation von VWF erforscht. Der Fachartikel stellt eine physiksimulationsbasierte Sensitivitätsanalyse des Förderguts bezüglich der Topologie im VWF vor. Die Ergebnisse dieser Analyse dienen als Basis für die Entwicklung eines Verfahrens zur automatischen Generierung von Ordnungsschikanen.   Vibratory bowl feeders (VBF) are the most frequently used systems for automated sorting and feeding of bulk material. To improve the current manual development process, methods for simulation of VBF are researched. The presented paper introduces a physics simulation based sensitivity analysis of the behavior of transported parts related to the topology of the VBF. These results provide a basis for the future development of an algorithm for the automated generation of orienting devices.

scholarly journals Agricultural Commodity Trading: Is it Destabilizing Spot Markets?

2018 ◽  
Vol 43 (1) ◽  
pp. 47-57 ◽  
Author(s):  
C. P. Gupta ◽  
Sanjay Sehgal ◽  
Sahaj Wadhwa
Keyword(s):  
Causal Relationship ◽  
Trading Volume ◽  
Spot Market ◽  
Market Volatility ◽  
Future Market ◽  
Soy Oil ◽  
Open Interest ◽  
Future Trading ◽  
The Future ◽  
Spot Volatility

Executive Summary The future trading has been held responsible by certain political and interest groups of enhancing speculative trading activities and causing volatility in the spot market, thereby further spiralling up inflation. This study examines the effect of future of trading activity on spot market volatility. The study first determined the Granger causal relationship between unexpected future trading volume and spot market volatility. It then examined the Granger causal relationship between unexpected open interest and spot market volatility. The spot volatility and liquidity was modelled using EGARCH and unexpected trading volume. The expected trading volume and open interest was calculated by using the 21-day moving average, and the difference between actual and expected component was treated as the unexpected trading volume and unexpected open interest. Empirical results confirm that for chickpeas ( channa), cluster bean ( guar seed), pepper, refined soy oil, and wheat, the future (unexpected) liquidity leads spot market volatility. The causal relationship implies that trading volume, which is a proxy for speculators and day traders, is dominant in the future market and leads volatility in the spot market. The results are in conformity with earlier empirical findings — Yang, Balyeat and Leathan (2005) and Nath and Lingareddy (2008) —that future trading destabilizes the spot market for agricultural commodities. Results show that there is no causal relationship between future open interest and spot volatility for all commodities except refined soy oil and wheat. The findings imply that open interest, which is a proxy of hedging activity, is leading to volatility in spot market for refined soy oil and wheat. The results are in conformity to earlier empirical studies that there is a weak causal feedback between future unexpected open interest and volatility in spot market ( Yang et al., 2005 ). For chickpeas (channa), the increase in volatility in the spot market increases trading activity in the future market. The findings are contrary to earlier empirical evidence ( Chatrath, Ramchander, & Song, 1996 ; Yang et al., 2005 ) that increase in spot volatility reduces future trading activity. However, they are in conformity to Chen, Cuny and Haugen (1995) that increase in spot volatility increases future open interest. The results reveal that the future market has been unable to engage sufficient hedging activity. Thereby, a causal relationship exists only for future trading volume and spot volatility, and not for future open interest and spot volatility. The results have major implications for policymakers, investment managers, and for researchers as well. The study contributes to literature on price discovery, spillovers, and price destabilization for Indian commodity markets.

scholarly journals Causal Association Between Heart Failure and Alzheimer’s Disease: A Two-Sample Bidirectional Mendelian Randomization Study

2022 ◽  
Vol 12 ◽  
Author(s):  
Chenglin Duan ◽  
Jingjing Shi ◽  
Guozhen Yuan ◽  
Xintian Shou ◽  
Ting Chen ◽  
...  
Keyword(s):  
Heart Failure ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Sensitivity Analysis ◽  
Causal Relationship ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Relationships ◽  
Simple Mode

Background: Traditional observational studies have demonstrated an association between heart failure and Alzheimer’s disease. The strengths of observational studies lie in their speed of implementation, cost, and applicability to rare diseases. However, observational studies have several limitations, such as uncontrollable confounders. Therefore, we employed Mendelian randomization of genetic variants to evaluate the causal relationships existing between AD and HF, which can avoid these limitations.Materials and Methods: A two-sample bidirectional MR analysis was employed. All datasets were results from the UK’s Medical Research Council Integrative Epidemiology Unit genome-wide association study database, and we conducted a series of control steps to select the most suitable single-nucleotide polymorphisms for MR analysis, for which five primary methods are offered. We reversed the functions of exposure and outcomes to explore the causal direction of HF and AD. Sensitivity analysis was used to conduct several tests to avoid heterogeneity and pleiotropic bias in the MR results.Results: Our MR studies did not support a meaningful causal relationship between AD on HF (MR-Egger, p = 0.634 > 0.05; weighted median (WM), p = 0.337 > 0.05; inverse variance weighted (IVW), p = 0.471 > 0.05; simple mode, p = 0.454 > 0.05; weighted mode, p = 0.401 > 0.05). At the same time, we did not find a significant causal relationship between HF and AD with four of the methods (MR-Egger, p = 0.195 > 0.05; IVW, p = 0.0879 > 0.05; simple mode, p = 0.170 > 0.05; weighted mode, p = 0.110 > 0.05), but the WM method indicated a significant effect of HF on AD (p = 0.025 < 0.05). Because the statistical powers of IVW and MR-Egger are more than that of WM, we think that there is no causal effect of HF on AD. Sensitivity analysis and horizontal pleiotropy were not detected in the MR analysis.Conclusion: Our results did not provide significant evidence indicating any causal relationships between HF and AD in the European population. Therefore, more large-scale datasets or datasets related to similar factors are expected for further MR analysis.

Sign in / Sign up

Export Citation Format

Share Document