scholarly journals System and Neural Network Analysis of Economic and Financial Development – A case study of Dubai and rest of UAE

2018 ◽  
Vol 1 (1) ◽  
pp. 51-67
Author(s):  
Genanew B Worku ◽  
Ananth Rao
Keyword(s):  
Neural Network ◽  
Financial Development ◽  
Small Sample Size ◽  
Core Competencies ◽  
Business Environment ◽  
Small Sample ◽  
Factors Affecting ◽  
Jel C32 ◽  
Using Data ◽  
Start Ups

The study examines the factors affecting the economic and financial development by applying Zellner’s seemingly unrelated regressions (SURE) and Neural Network techniques. It applies multivariate and neural network frameworks for analysing the GDP of Dubai and rest of UAE using data for 2001–2015. The study shows that there exists positive interdependencies between Dubai and rest of UAE economies. This signifies that the core competencies across various sectors in Dubai and rest of UAE economies need to be promoted further to have overall diversified impact on UAE economy. The positive sizable impact of the finance sector in Dubai and negative sizable impact in the rest of the UAE provide many opportunities for designing diversification programs for sustained economic development of the entire UAE economy. The small sample size, non-availability of detailed sectoral data in four of the seven emirates constrained the scope of the study for generalization to other economies in the Middle East. The study findings are crucial for identifying structural reforms, to strengthen competitiveness and accelerate private sector-led job creation for nationals, potential on further opening up foreign direct investment (FDI), improving selected areas of the business environment, and easing access to finance for start-ups and SMEs in both the economies. JEL: C32, C52, D85, N15, N25

scholarly journals Sectoral Evaluation for Economic and Financial Development in Dubai and rest of UAE

2017 ◽  
Vol 1 (1) ◽  
pp. 1-29
Author(s):  
Sumaiyya Wahid Shaikh ◽  
Genanew B Worku ◽  
Ananth Rao
Keyword(s):  
Financial Development ◽  
United Arab Emirates ◽  
Small Sample Size ◽  
Core Competencies ◽  
Business Environment ◽  
Small Sample ◽  
Factors Affecting ◽  
Relative Contribution ◽  
Level Data ◽  
Start Ups

The paper examines sector specific characteristics to analyse the factors affecting the sustainability of the economies of Dubai and rest of the United Arab Emirates (UAE). The study applies system design to analyse the research questions. Consequently, Zellner’s seemingly unrelated regressions (SURE) technique is used to examine the relative contribution of sectors to the economies Dubai, as an individual Emirate, and the rest of UAE as a group of Emirates using time series sectoral level data for 2001–2015. The study shows that there exists positive interdependencies between Dubai and rest of UAE economies. This signifies that the core competencies across various sectors in Dubai and rest of UAE economies need to be promoted further to have overall diversified impact on UAE economy. The positive sizable impact of the finance sector in Dubai and negative sizable impact in the rest of the UAE provide many opportunities for designing diversification programs for sustained economic development of the entire UAE economy. The small sample size, non-availability of detailed sectoral data in four of the seven emirates constrained the scope of the study for generalization to other economies in the middle east.   The study findings are very crucial for identifying structural reforms, to strengthen competitiveness and accelerate private sector-led job creation for nationals, potential on further opening up foreign direct investment (FDI), improving selected areas of the business environment, and easing access to finance for start-ups and SMEs in both the economies. There are very few studies, which have researched the sector specific characteristics to explain the factors affecting the sustainability of the economies of Dubai and the rest of UAE. The study provides insights to the UAE policy makers, for enhancement of policies through development of the key sectors that influence the performance of the two economies. Despite being independent entities though, the seven emirates of the UAE are economically interdependent. Studies on such interactions add unique value to the literature. Keywords: SURE, GDP, Dubai, UAE, Sectoral Evaluation, Financial development.

scholarly journals New findings on protected and strictly protected species confirm the value of the prime hoverfly area network

2018 ◽  
pp. 63-71
Author(s):  
Marina Jankovic ◽  
Marija Milicic ◽  
Dimitrije Radisic ◽  
Dubravka Milic ◽  
Ante Vujic
Keyword(s):  
Protected Areas ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Small Sample Size ◽  
Small Sample ◽  
Area Network ◽  
Distribution Models ◽  
Environmental Pressures ◽  
New Findings ◽  
Using Data

With environmental pressures on the rise, the establishment of pro?tected areas is a key strategy for preserving biodiversity. The fact that many species are losing their battle against extinction despite being within protected areas raises the question of their effectiveness. The aim of this study was to evaluate established Priority Hoverfly Areas (PHAs) and areas that are not yet but could potentially be included in the PHA network, using data from new field surveys. Additionally, species distribution models have been created for two new species recognized as important and added to the list of key hoverfly species. Maps of potential distribution of these species were superimposed on maps of protected areas and PHAs to quantify percentages of overlap. The results of this study are not statisti?cally significant, which could be influenced by a small sample size. However, the results of species distribution models and the extent of overlap with PHAs confirm the utility of these expert-generated designations.

Characteristics and Determinants of New Start-ups in Gujarat, India

2020 ◽  
Vol 1 (2) ◽  
pp. 1-25
Author(s):  
Ajay Kumar ◽  
Bhim Jyoti
Keyword(s):  
Sample Size ◽  
Regression Models ◽  
New Products ◽  
Small Sample ◽  
The Body ◽  
High Tech ◽  
Annual Sale ◽  
Factors Affecting ◽  
Start Up ◽  
Start Ups

Purpose: This study examines the relationship of socio-economic characteristics of start-ups with their size in Gujarat, India. It also assesses the determinants affecting the annual sale of start-ups. Methods: It includes primary information based on a survey of 120 founders of start-ups. Linear and semi-log linear regression models have been applied to assess the determinants of start-ups. Probit regression models have been considered to assess the factors affecting the annual sale of the start-ups. Results: Stage of start-up, the participation of founders in conferences, educational qualification, and new products launched by start-ups, professional connections of founders, source of funding, and support from incubator/accelerator/supporting organizations are found crucial determinants of start-up size in Gujarat. The annual sales of the start-ups are positively associated with stage of start-up, support from a mentor, team members, founder's academic qualification, and collaboration with national or international organizations, unskilled workers. Implications: Technology transfer and commercialization, development of new products, government regulations, the requirement of costumers, free rights for entrepreneurs, appropriate financial support for new entrepreneurs, transparency and clarity in government policies, the establishment of high-tech start-ups, and development of digital infrastructure, increase in R&D spending in research academia, and association of research institutions with entrepreneurs would be conducive to create an appropriate start-ups ecosystem and to reduce regional development disparities across Indian states. Subsequently, it would be helpful to increase sustainable development in India.  Originality: This study has used primary information of 120 founders of start-ups to assess the determinants, and the factors affecting annual sales of start-ups using the regression model in, Gujrat, India. Thus, it has an empirical contribution to the body of knowledge. Limitations: This study could not provide rational justifications on most factors that show an insignificant impact on start-ups due to the small sample size. Further research, therefore, may be considered to identify the association of start-up size with the variables using a large sample size in India.  

Lower rates of mortality, readmission and reoperation in patients receiving acupuncture after hip fracture: a population-based analysis

2020 ◽  
Vol 38 (5) ◽  
pp. 352-360
Author(s):  
Jeff Chien-Fu Lin ◽  
Tzu-Chieh Lin ◽  
Chi-Fung Cheng ◽  
Ying-Ju Lin ◽  
Sophia Liang ◽  
...  
Keyword(s):  
Hip Fracture ◽  
Lower Risk ◽  
Small Sample Size ◽  
Population Based ◽  
Small Sample ◽  
Acupuncture Group ◽  
Research Database ◽  
Complication Rates ◽  
Using Data ◽  
Reoperation Rates

Background: Studies on the effects of acupuncture on mortality and complication rates in hip fracture patients are limited by small sample size and short follow-up time. We aimed to assess the associations of acupuncture use with mortality, readmission and reoperation rates in hip fracture patients using a longitudinal population-based database. Methods: A retrospective matched cohort study was conducted using data for the years 1996–2012 from Taiwan’s National Health Insurance Research Database. Hip fracture patients were divided into an acupuncture group consisting of 292 subjects who received at least 6 acupuncture treatments within 183 days of hip fracture, and a propensity score matched “no acupuncture” group of 876 subjects who did not receive any acupuncture treatment and who functioned as controls. The two groups were compared using survival analysis and competing risk analysis. Results: Compared to non-treated subjects, subjects treated with acupuncture had a lower risk of overall death (hazard ratio (HR): 0.41, 95% confidence interval (CI): 0.24–0.73, p = 0.002), a lower risk of readmission due to medical complications (subdistribution HR (sHR): 0.64, 95% CI: 0.44–0.93, p = 0.019) and a lower risk of reoperation due to surgical complications (sHR: 0.62, 95% CI: 0.40–0.96, p = 0.034). Conclusion: This is the first study to suggest that postoperative acupuncture in hip fracture patients is associated with significantly lower mortality, readmission and reoperation rates compared with those of matched controls.

scholarly journals Factors affecting Happiness of Expatriate Academicians and Expatriate Non-Academicians in Dubai

2018 ◽  
Vol 1 (1) ◽  
pp. 1-12
Author(s):  
Kamarul Zaman Bin Ahmad ◽  
Majid Wahid Shaikh
Keyword(s):  
Small Sample Size ◽  
Academic Staff ◽  
Methodological Approach ◽  
Small Sample ◽  
Teaching Staff ◽  
Cross Sectional ◽  
Factors Affecting ◽  
The University ◽  
Depth Interviews ◽  
Academic Group

Purpose: To determine the antecedents of happiness and compare academicians and non-academicians in selected Dubai Universities. Design/methodological/approach: Qualitative research using in-depth interviews followed by cross-sectional surveys of teaching staff and non-teaching staff from different universities in Dubai.?Findings: There is no significant relationship between knowledge sharing and happiness of academics and well as non-academics. Happiness is significantly related to the other factors.Research implications and limitations: The small sample size of the academic group and the study was targeted at the university staff in Dubai only. Practical implications: The findings of this research gives useful recommendations to Universities to improve happiness among their academic as well as non-academic staff. It will also provide recommendations for developmental purposes for the University of Dubai and the UAE’s “Happiness and Positivity program.”Originality/value: No known research studies the determinants of happiness for academics and non-academics in Dubai Universities.Paper type: Research paper

Sampling-Based Reliability Analysis Using Deep Feedforward Neural Network (DFNN)

2020 ◽  
Author(s):  
Ungki Lee ◽  
Ikjin Lee
Keyword(s):  
Neural Network ◽  
Reliability Analysis ◽  
Surrogate Model ◽  
Small Sample Size ◽  
Small Sample ◽  
Feedforward Neural Network ◽  
Training Data ◽  
Performance Function ◽  
Design Point ◽  
Previous Design

Abstract Reliability analysis that evaluates a probabilistic constraint is an important part of reliability-based design optimization (RBDO). Inverse reliability analysis evaluates the percentile value of the performance function that satisfies the reliability. To compute the percentile value, analytical methods, surrogate model based methods, and sampling-based methods are commonly used. In case the dimension or nonlinearity of the performance function is high, sampling-based methods such as Monte Carlo simulation, Latin hypercube sampling, and importance sampling can be directly used for reliability analysis since no analytical formulation or surrogate model is required in these methods. The sampling-based methods have high accuracy but require a large number of samples, which can be very time-consuming. Therefore, this paper proposes methods that can improve the accuracy of reliability analysis when the number of samples is not enough and the sampling-based methods are considered to be better candidates. This study starts with the idea of training the relationship between the realization of the performance function at a small sample size and the corresponding true percentile value of the performance function. Deep feedforward neural network (DFNN), which is one of the promising artificial neural network models that approximates high dimensional models using deep layered structures, is trained using the realization of various performance functions at a small sample size and the corresponding true percentile values as input and target training data, respectively. In this study, various polynomial functions and random variables are used to create training data sets consisting of various realizations and corresponding true percentile values. A method that approximates the realization of the performance function through kernel density estimation and trains the DFNN with the discrete points representing the shape of the kernel distribution to reduce the dimension of the training input data is also presented. Along with the proposed reliability analysis methods, a strategy that reuses samples of the previous design point to enhance the efficiency of the percentile value estimation is explained. The results show that the reliability analysis using the DFNN is more accurate than the method using only samples. In addition, compared to the method that trains the DFNN using the realization of the performance function, the method that trains the DFNN with the discrete points representing the shape of the kernel distribution improves the accuracy of reliability analysis and reduces the training time. The proposed sample reuse strategy is verified that the burden of function evaluation at the new design point can be reduced by reusing the samples of the previous design point when the design point changes while performing RBDO.

scholarly journals Critical Success Factors for Implementation of Green Building in India

2021 ◽  
Vol 1203 (3) ◽  
pp. 032061
Author(s):  
Boddapati Ganesh Kumar ◽  
Abhay Tawalare
Keyword(s):  
Success Factors ◽  
Small Sample Size ◽  
Green Building ◽  
Green Buildings ◽  
Small Sample ◽  
Primary Data ◽  
Extensive Literature ◽  
Critical Factors ◽  
Factors Affecting ◽  
Building Technology

Abstract For the sustainable built environment, Green Building technology is the most widely adopted trend worldwide, however, it is in a nascent stage in India. Even though the use of green building technology is advantageous over the lifecycle of the project, people are hesitant to adopt. Therefore, this study aims at identifying the critical factors affecting the implementation of green buildings in India. For this purpose, an extensive literature review was done to identify factors affecting the implementation of green buildings. In total 27 factors were identified which may be critical for the adoption of green building technology widely in an Indian context. The questionnaire was prepared using the five-point Likert scale. The questionnaire was sent through emails to 150 consultants in India and 52 valid responses received in return. The primary data is analyzed using factor analysis. The critical factors found are time and knowledge constraints; technical constraints; authenticity of research and awareness about Green Building. Though the findings of this study are based on the small sample size, it will be beneficial to the policymakers

scholarly journals Start-ups, bearers of innovation in globalizing environment and their valuation

2020 ◽  
Vol 74 ◽  
pp. 01001
Author(s):  
Veronika Achimská
Keyword(s):  
Significant Degree ◽  
Business Environment ◽  
Point Of View ◽  
Theoretical Point ◽  
Business Valuation ◽  
Factors Affecting ◽  
Start Up ◽  
External Sources ◽  
Uniform Valuation ◽  
Start Ups

The paper presents chosen methods of star-up valuation. In the context of globalization, innovations are clearly bearers of a potential enterprises’ competitiveness, start-ups are consider as their most important sources. Start-ups are mainly based on the human capital designed to create novel products, services, processes, and bring them to the markets. The basic precondition for meaningful growth of start-ups is favourable business environment (legal and administrative point of view) and framework supporting innovative entrepreneurship including access to external sources of financing. Start-ups are investments with a significant degree of uncertainty, lacking any characteristics pointing to their financial and economic performance from a historical perspective, which restricts the use of “traditional” business valuation methods. It should also be pointed out that, as there is no uniform valuation for maturity enterprises, there is no uniform procedure for valuing of a business even in the case of start-ups. The presented approaches take into account decisive criteria of start-ups, including a life cycle of a start-up in which an investment is made, and other factors affecting valuation. Their use from a theoretical point of view is generalized, the practical use is already determined by specific conditions under which the valuation takes place.

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