Modeling the economic dependence between town development policy and increasing energy effectiveness with neural networks. Case study: The town of Zielona Góra

2017 ◽  
Vol 188 ◽  
pp. 356-366 ◽  
Author(s):  
Marta Skiba ◽  
Maria Mrówczyńska ◽  
Anna Bazan-Krzywoszańska
Keyword(s):  
Neural Networks ◽  
Development Policy ◽  
Economic Dependence ◽  
Energy Effectiveness ◽  
Town Development ◽  
The Town

A Case Study of Shenyang’s New Town Development Policy

2021 ◽  
Vol 60 ◽  
pp. 57-80
Author(s):  
Tong Liu ◽  
Soo-Won Eum ◽  
Kwang-Seong Lee
Keyword(s):  
Development Policy ◽  
New Town ◽  
Town Development

scholarly journals USING INQUIRY-BASED LEARNING TO EXPLORE RESPECT OF CULTURAL BASE DESIGN: A CASE STUDY IN AMPHAWA TOURISM COMMUNITY, THAILAND

2021 ◽  
Vol 34 (1) ◽  
pp. 164-169
Author(s):  
Natapon ANUSORNTHARANGKUL ◽  
◽  
Yanin RUGWONGWAN ◽  
Keyword(s):  
Cultural Identity ◽  
Cultural Tourism ◽  
Inquiry Based Learning ◽  
Community Stakeholders ◽  
Town Development ◽  
Cultural Base ◽  
Tourism Community ◽  
The Town ◽  
Base Design

Amphawa is a Thai valuable cultural heritage. This cultural tourism has been amplified thanks to the UNESCO award. Despite the recognition, there exists a conflict as seen obviously in the town development by cross-cultural designers. This research focuses on establishment of a proper learning model. Qualitative research was undertaken using a tool namely Ethnographic Delphi Futures Research. The results found that the method of Inquiry-Based Learning significantly made learners gain insights because of the direct interactions with the community stakeholders who truly take part in reaching the consensus which improved consistency of the design works to preserve the cultural identity.

Interactive acculturation of Turkish-Belgian parents and children in Flanders: A case study of Beringen

2019 ◽  
Vol 16 (3) ◽  
pp. 417-428
Author(s):  
Özgün Ünver ◽  
Ides Nicaise
Keyword(s):  
Early Childhood ◽  
Maternal Employment ◽  
Domain Specificity ◽  
Specific Context ◽  
Childhood Education ◽  
Parents And Children ◽  
Education And Care ◽  
The Relationship ◽  
The Town

This article tackles the relationship between Turkish-Belgian families with the Flemish society, within the specific context of their experiences with early childhood education and care (ECEC) system in Flanders. Our findings are based on a focus group with mothers in the town of Beringen. The intercultural dimension of the relationships between these families and ECEC services is discussed using the Interactive Acculturation Model (IAM). The acculturation patterns are discussed under three main headlines: language acquisition, social interaction and maternal employment. Within the context of IAM, our findings point to some degree of separationism of Turkish-Belgian families, while they perceive the Flemish majority to have an assimilationist attitude. This combination suggests a conflictual type of interaction. However, both parties also display some traits of integrationism, which points to the domain-specificity of interactive acculturation.

Multi-Criteria Decision Making for Vulnerability Mapping of Flood Hazard: A Case Study of Pune City

2019 ◽  
Vol 2 (1) ◽  
pp. 41-52
Author(s):  
Nitin Mundhe
Keyword(s):  
Decision Making ◽  
Flood Hazard ◽  
Geographical Information ◽  
Multi Criteria Decision Making ◽  
Flood Hazards ◽  
Very High Frequency ◽  
Flood Vulnerability ◽  
Natural Risk ◽  
The Town

Floods are natural risk with a very high frequency, which causes to environmental, social, economic and human losses. The floods in the town happen mainly due to human made activities about the blockage of natural drainage, haphazard construction of roads, building, and high rainfall intensity. Detailed maps showing flood vulnerability areas are helpful in management of flood hazards. Therefore, present research focused on identifying flood vulnerability zones in the Pune City using multi-criteria decision-making approach in Geographical Information System (GIS) and inputs from remotely sensed imageries. Other input data considered for preparing base maps are census details, City maps, and fieldworks. The Pune City classified in to four flood vulnerability classes essential for flood risk management. About 5 per cent area shows high vulnerability for floods in localities namely Wakdewadi, some part of the Shivajinagar, Sangamwadi, Aundh, and Baner with high risk.

Withdrawn: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC)

2019 ◽  
Vol 13 ◽  
Author(s):  
Abeer A. Amer ◽  
Soha M. Ismail
Keyword(s):  
Diabetes Mellitus ◽  
Neural Networks ◽  
Fuzzy Logic ◽  
Computer Science ◽  
Recent Advances ◽  
Vascular Center ◽  
Copyright Permission ◽  
Legal Right

The following article has been withdrawn on the request of the author of the journal Recent Advances in Computer Science and Communications (Recent Patents on Computer Science): Title: Diabetes Mellitus Prognosis Using Fuzzy Logic and Neural Networks Case Study: Alexandria Vascular Center (AVC) Authors: Abeer A. Amer and Soha M. Ismail* Bentham Science apologizes to the readers of the journal for any inconvenience this may cause BENTHAM SCIENCE DISCLAIMER: It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

scholarly journals Policy Strategies to Revive Rural Land in Peri-Metropolitan Towns: Resource Identification, Capitalization, and Financialization

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 132
Author(s):  
Wei Li ◽  
Zhanwei Zhang ◽  
Yang Zhou
Keyword(s):  
Rural Areas ◽  
Master Planning ◽  
Leading Role ◽  
Multifunctional Land Use ◽  
Key Stakeholders ◽  
Resource Identification ◽  
The Government ◽  
Interpretative Approach ◽  
The Town

Previous planning for rural revival in towns has emphasized construction and government-led policies. However, we argue that the dilemmas of peri-metropolitan rural areas, such as Desakota in China, are far more complex faced with rural super village and hollowed village transformations. Rural revival planning needs to coordinate with the development of urbanized and rural areas towards multifunctional goals and plans as a whole. Therefore, we selected the town master plan of Lijia, a typical peri-metropolitan village in China, as a case study. Through a historical–interpretative approach involving analysis of planning policies, questionnaires, and in-depth interviews with the key stakeholders involved, we structured the process and mechanism of rural revival in Lijia into three phases: resource identification, capitalization, and financialization. In different phases, different stakeholders adopt different roles. The government takes a leading role in resource identification and capitalization, while firms take a leading role in the process of financialization. “Market-dominant and government-guided” planning stimulates villagers to participate in rural revival. We highlight the importance of multifunctional land-use in terms of rural revival in the master planning of peri-metropolitan villages and provide a practical reference for uniting multiple stakeholders, including governments, firms, and villagers.

Employment of artificial neural networks for non-invasive estimation of leaf water status using color features: a case study in Spathiphyllum wallisii

2021 ◽  
Vol 43 (5) ◽  
Author(s):  
Amin Taheri-Garavand ◽  
Abdolhossein Rezaei Nejad ◽  
Dimitrios Fanourakis ◽  
Soodabeh Fatahi ◽  
Masoumeh Ahmadi Majd
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Water Status ◽  
Leaf Water ◽  
Leaf Water Status ◽  
Non Invasive ◽  
Color Features ◽  
Artificial Neural

Medina Gounass: Constructing Extra-National Space in a West African Borderland

2021 ◽  
pp. 1-26
Author(s):  
David Newman Glovsky
Keyword(s):  
Islamic Law ◽  
West African ◽  
Religious Community ◽  
National Space ◽  
Cross Border ◽  
History Of ◽  
Postcolonial Africa ◽  
Postcolonial States ◽  
The Town

Abstract The historical autonomy of the religious community of Medina Gounass in Senegal represents an alternative geographic territory to that of colonial and postcolonial states. The borderland location of Medina Gounass allowed the town to detach itself from colonial and independent Senegal, creating parallel governmental structures and imposing a particular interpretation of Islamic law. While in certain facets this autonomy was limited, the community was able to distance itself through immigration, cross-border religious ties, and smuggling. Glovsky’s analysis of the history of Medina Gounass offers a case study for the multiplicity of geographical and territorial entities in colonial and postcolonial Africa.

scholarly journals Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Markus J. Ankenbrand ◽  
Liliia Shainberg ◽  
Michael Hock ◽  
David Lohr ◽  
Laura M. Schreiber
Keyword(s):  
Neural Networks ◽  
Sensitivity Analysis ◽  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Cardiac Mri ◽  
Magnetic Resonance Images ◽  
Model Interpretation ◽  
First Case ◽  
Segmentation Models

Abstract Background Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance. Results We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model. Conclusions Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.

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