• Journal of Digital Convergence
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• v.16 no.3
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• pp.157-167
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• 2018

The shortage of research in Vietnam port evolvement is uncontroversial although a huge amount of investment is observed to upgrade both quantity and quality. This study examines the port system performance, in the context of spatially concentration ratio, in Southern Vietnam for the period 2007-2016, by using prevailing indicators for spatially concentration assessment including concentration ratios (CR), the Herfindahl-Hirschman index (HHI), the Gini coefficient, the Lorenz curve and shift-share analysis (SSA), a trend of deconcentration is described in Southern Vietnam port system, since the traditional ports to new deep-water ports. Also, driving forces of this shifting would be discussed in detail. Implications from this study would enable not only port administrators, port operators but also shipping lines, cargo owners, logistics service providers to comprehensively understand the growth of the port system in Southern Vietnam.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.37-46
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• 2020

The aim of this research is to analyze the concentration and deconcentration development of cruise ports in the Mediterranean area by utilizing the concentration ratio (CR), the Herfindahl-Hirschman Index (HHI), the Gini coefficient, and shift share analysis (SSA). The results of analysis indicated a concentration trend in the West Mediterranean. The cruise ports located in Venice, Piraeus, Naples and Livrno in Adriatic and East Med region lost cruise passengers, while the those in West Mediterranean gained the passengers and showed the trend of concentration. This paper providing the shifting passengers among cruise ports that indicates the competitiveness of cruise ports for industrial stake holders to better understand the cruise ports such as tourist boards, ship agents, and port agents.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.295-303
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• 2021

The relevance of the research is due to the fact that the issue of poverty is one of the most acute social problems of the beginning of the third millennium. The phenomenon of poverty is widespread in third world countries as well as it is observed in relatively developed countries. Poverty rates in Latin America are threatening. Consequently, the issue of social and economic inequality in these countries has become extremely acute. The purpose of the research: to identify the causes of poverty and social inequality and substantiate the main directions of poverty reduction in third world countries. The research methods: comparative analysis; index method; systematization; grouping; generalization. Results. The classification of the causes of poverty has been carried out and the directions of its overcoming in the countries of Latin America on groups of indicators have been defined, namely: 1) political; 2) economic; 3) demographic; 4) regional-geographical; 5) social; 6) qualification; 7) personal. Based on the Net Domestic Product indicator, a comparison of economic indicators of the studied countries has been carried out. It has been revealed that from 1990 to 2018 income inequality increased in 52 of 119 countries studied, and decreased in 57 states. Inequality has increased in the world's most populous countries, particularly China and India. In general, countries with growing inequality are home to more than two-thirds (71%) of the world's population. Trends in the distribution of income in the world have been investigated by applying the Gini index, the high level of which is observed in Latin America (Colombia 48,9%, Panama 46,1%, Chile and Mexico 45,9%). The forecast of the impact of the Covid-19 pandemic on this issue has been outlined; the ways of its impact on the economies of the countries have been studied. As a result of the study, the main directions and mechanisms of the strategy for poverty reduction and social inequality in the third world countries have been identified. The implementation of the poverty reduction strategy presented in this academic paper may have a positive impact on the economic situation of the population of Latin American countries.

• Physical Therapy Korea
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• v.30 no.2
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• pp.102-109
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• 2023

Background: While efforts have been made to differentiate fall risk in older adults using wearable devices and clinical methodologies, technologies are still infancy. We applied a decision tree (DT) algorithm using inertial measurement unit (IMU) sensor data and clinical measurements to generate high performance classification models of fall risk of older adults. Objects: This study aims to develop a classification model of fall risk using IMU data and clinical measurements in older adults. Methods: Twenty-six older adults were assessed and categorized into high and low fall risk groups. IMU sensor data were obtained while walking from each group, and features were extracted to be used for a DT algorithm with the Gini index (DT1) and the Entropy index (DT2), which generated classification models to differentiate high and low fall risk groups. Model's performance was compared and presented with accuracy, sensitivity, and specificity. Results: Accuracy, sensitivity and specificity were 77.8%, 80.0%, and 66.7%, respectively, for DT1; and 72.2%, 91.7%, and 33.3%, respectively, for DT2. Conclusion: Our results suggest that the fall risk classification using IMU sensor data obtained during gait has potentials to be developed for practical use. Different machine learning techniques involving larger data set should be warranted for future research and development.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.355-362
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• 2019

In the past, when research and development(R&D) resources were absolutely scarce, the so-called 'choice and concentration' strategy of national R&D projects has been persuasive. Under the current situation where various actors such as GRIs(Government-funded Research Institutes) and universities supported by more abundant R&D resources conduct national R&D projects, this strategy cannot be applied without distinction. In order to see how the strategy has worked, this paper analyzes the concentration of research funds allocated to actors performing national R&D projects. Concentration is measured based on the amount of research funds supported by government from 2002 to 2016 using the Theil index to break down the concentration of individual actors in the overall national R&D project. The results from the Theil index were compared with concentrations using the Gini coefficient, a widely known indicator. As a result, the Theil index could be used to analyze the concentration and sub-components' contribution such as universities and GRIs that make up the entire national R&D system. The results also showed GRIs had the highest concentration, followed by universities, but their concentration has been somewhat reduced compared to 10 years ago. On the other hand, small-sized companies have maintained a certain level, although they are not highly concentrated. In other words, universities and GRIs tend to reduce the gap in the allocation of research funds among institutions, while small-sized companies tend to distribute them evenly.

• The Journal of Engineering Geology
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• v.18 no.1
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• pp.45-54
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• 2008

Based on the data obtained from field investigation and soil testing to slope hazards occurrence section and non-occurrence section in gneiss area, a prediction technique was developed by the use of a decision tree model, which is one of the statistical analysis methods. The slope hazards data of Seoul and Kyonggi Province, which were induced by heavy rainfall in 1998, were 104 sections in gneiss area. The number of data applied in developing prediction model was 61 sections except a vacant value. Among these data, the number of data occurred slope hazards was 34 sections and the number of data non-occurred slope hazards was 27 sections. The statistical analyses using the decision tree model were applied to chi-square statistics, gini index and entrophy index. As the results of analyses, a slope angle, a degree of saturation and an elevation were selected as the classification standard. The prediction model of decision tree using entrophy index is most likely accurate. The classification standard of the selected prediction model is composed of the slope angle, the degree of saturation and the elevation from the first choice stage. The classification standard values of the slope angle, the degree of saturation and elevation are $17.9^{\circ}$, 52.1% and 320 m, respectively.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.143-156
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• 2020

In Southern Vietnam, the competition among Inland Clearance Depot (ICD) has resulted in deconcentration tendencies and shifting share situations. However, related research on Southern Vietnam ICDs in particular and ICDs in Vietnam in general has been extremely limited. Hence, In this study, empirical research is conducted on ICDs located in southern Vietnam from 2010 to 2017. The throughput volume data of ICDs is analyzed by concentration indicators, namely the concentration ratio (CR), the Herfindahl-Hirschman Index (HHI), the Gini coefficient, the Lorenz curve, and the shift share analysis (SSA). The results of adopting all the methodologies indicate that deconcentration was the mainstream trend for ICDs in Southern Vietnam during the period of 2010-2017. The findings provide insights into the process of container terminal development and have academic and managerial implications. The strengthening of the competitiveness of Vietnamese container ports and ICDs could affect the competing Southeast Asian neighbors by facilitating the port of more shipping companies.

• Korean Journal of Social Welfare
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• v.64 no.2
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• pp.185-212
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• 2012

This study examines changes in income inequality and income mobility associated with a transition to old age. In understanding the dynamics of income distribution over the later life course, it is important to explore the changes in income dispersion and the changes in relative income positions jointly. Data come from Korean Labor and Income Panel Study(KLIPS) 2nd, 7th, 12th wave. The results are as follows. First, a transition to old age is associated with an increase in income inequality. The Gini index of inequality increased steadily over the life course. Second, a transition to old age is associated with substantial income mobility. The Spearman's rank correlation coefficient between two periods was the lowest at the time of the transition. Increasing income dispersion and significant income mobility can be conceptualized as "income insecurity", since the older population are less likely to cope with income fluctuations. Third, in explaining such changes over time, changes in work life during old age and a subsequent decrease in earnings seem to be the most influential factor.

• Environmental and Resource Economics Review
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• v.23 no.1
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• pp.67-89
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• 2014

This paper uses patent data of OECD countries in order to investigate if there is converging tendency in renewable energy area. We used the concepts of sigma convergence and beta convergence to measure the convergence. GINI coefficient, HH index are also borrowed from other area of economics. The results show that technology level does not seem to have been converging in this area. Even though the number of patent in relatively less advanced countries has been increased a lot, we could find no evidence that there is the tendency that the gap among the countries have been narrowed. This is quite different from the results of IT industry or other industry since we could find the converging tendency in the data of those industries. Instead, it seems that there is the convergence club among most advance countries in renewable energy area.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.249-261
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• 2014

Ever increasing "Big data" can only be effectively processed by parallel computing. Parallel computing refers to a high performance computational method that achieves effectiveness by dividing a big query into smaller subtasks and aggregating results from subtasks to provide an output. However, it is well-known that parallel computing does not achieve scalability which means that performance is improved linearly by adding more computers because it requires a very careful assignment of tasks to each node and collecting results in a timely manner. Hadoop is one of the most successful platforms to attain scalability. In this paper, we propose a measurement for Hadoop optimization by utilizing a Lorenz curve which is a proxy for the inequality of hardware resources. Our proposed index takes into account the intrinsic overhead of Hadoop systems such as CPU, disk I/O and network. Therefore, it also indicates that a given Hadoop can be improved explicitly and in what capacity. Our proposed method is illustrated with experimental data and substantiated by Monte Carlo simulations.