Search results for: hierarchical inequality

Authors: Sumanta Kumar Saha, Jie Qin

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This study analyzes the impact of financial inclusion on gender inequality in 126 countries belonging to different income groups during the 2005–2019 period. Due to its positive influence on poverty alleviation, economic growth, women empowerment, and income inequality reduction, financial inclusion may help reduce gender equality. This study constructs a novel composite financial inclusion index and applies both fixed-effect panel estimation and instrumental variable approach to examine the impact of financial inclusion on gender inequality. The results indicate that financial inclusion can reduce gender inequality in developing and low- and lower-middle-income countries, but not in higher-income countries. The impact is not always immediate. Past financial inclusion initiatives have a significant influence on future gender inequality. Financial inclusion is also significant if the poverty level is high and women's access to financial services is low compared to men. When the poverty level is low, or women have equal access to financial services, financial inclusion does not significantly affect gender inequality. The study finds that compulsory education and improvement in institutional quality promote gender equality in developing countries apart from financial inclusion. The study proposes that lower-income countries use financial inclusion initiatives to improve gender equality. Other countries need to focus on other aspects such as promoting educational support and institutional quality improvements to achieve gender equality.

Keywords: financial inclusion, gender inequality, institutional quality, women empowerment

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Authors: Mary Fargher

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This paper examines the opportunities of using a more hierarchical approach to geospatial enquiry in using GIS in school geography. A case is made that it is not just the lack of teacher technological knowledge that is stopping some teachers from using GIS in the classroom but that there is a gap in their understanding of how to link GIS use more specifically to the pedagogy of teaching geography with GIS. Using a hierarchical approach to geospatial enquiry as a theoretical framework, the analysis shows clearly how concepts of spatial distribution, interaction, relation, comparison, and temporal relationships can be used by teachers more explicitly to capitalise on the analytical power of GIS and to construct what can be interpreted as powerful geographical knowledge. An exemplar illustrating this approach on the topic of geo-hazards is then presented for critical analysis and discussion. Recommendations are then made for a model of progression for geography teacher education with GIS through hierarchical geospatial enquiry that takes into account beginner, intermediate, and more advanced users.

Keywords: digital geography, GIS, education, hierarchical geospatial enquiry, powerful geographical knowledge

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Authors: Pouneh Soleimaninejadian, Chengyu Yang

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In this paper, we use data on Household Income and Expenditure survey of Statistics Centre of Iran, conducted from 2005-2014, to calculate several inequality measures and to estimate the effects of Iran’s targeted subsidy reform act on consumption and income inequality. We first calculate Gini coefficients for income and consumption in order to study the relation between the two and also the effects of subsidy reform. Results show that consumption inequality has not been always mirroring changes in income inequality. However, both Gini coefficients indicate that subsidy reform caused improvement in inequality. Then we calculate Generalized Entropy Index based on consumption and income for years before and after the Subsidy Reform Act of 2010 in order to have a closer look into the changes in internal structure of inequality after subsidy reforms. We find that the improvement in income inequality is mostly caused by the decrease in inequality of lower income individuals. At the same time consumption inequality has been decreased as a result of more equal consumption in both lower and higher income groups. Moreover, the increase in Engle coefficient after the subsidy reform shows that a bigger portion of income is allocated to consumption on food which is a sign of lower living standard in general. This increase in Engle coefficient is due to rise in inflation rate and relative increase in price of food which partially is another consequence of subsidy reform. We have conducted some experiments on effect of subsidy payments and possible effects of change on distribution pattern and amount of cash subsidy payments on income inequality. Result of the effect of cash payments on income inequality shows that it leads to a definite decrease in income inequality and had a bigger share in improvement of rural areas compared to those of urban households. We also examine the possible effect of constant payments on the increasing income inequality for years after 2011. We conclude that reduction in value of payments as a result of inflation plays an important role regardless of the fact that there may be other reasons. We finally experiment with alternative allocations of transfers while keeping the total amount of cash transfers constant or make it smaller through eliminating three higher deciles from the cash payment program, the result shows that income equality would be improved significantly.

Keywords: consumption inequality, generalized entropy index, income inequality, Irans subsidy reform

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Authors: Atefeh Bagherianziarat, Dana Hamplova

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The inverse social gradient in life satisfaction (LS) is a well-established research finding. To estimate the influence of inequality on LS, most of the studies have explored the effect of the objective aspects of inequality or individuals’ socioeconomic status (SES). However, relatively fewer studies have confirmed recently the significant effect of the subjective aspect of inequality or subjective socioeconomic status (SSS) on life satisfaction over and above SES. In other words, it is confirmed by some studies that individuals’ perception of their unequal status in society or SSS can moderate the impact of their absolute unequal status on their life satisfaction. Nevertheless, this newly confirmed moderating link has not been affirmed to work likewise in societies with different levels of social inequality and also for people who believe in the value of equality, at different levels. In this study, we compared the moderative influence of subjective inequality on the link between objective inequality and life satisfaction. In particular, we focus on differences across welfare state regimes based on Esping-Andersen's theory. Also, we explored the moderative role of believing in the value of equality on the link between objective and subjective inequality on LS in the given societies. Since our studied variables were measured at both individual and country levels, we applied a multilevel analysis to the European Social Survey data (round 9). The results showed that people in deferent regimes reported statistically meaningful different levels of life satisfaction that is explained to different extends by their household income and their perception of their income inequality. The findings of the study supported the previous findings of the moderator influence of perceived inequality on the link between objective inequality and LS. However, this link is different in various welfare state regimes. The results of the multilevel modeling showed that country-level subjective equality is a positive predictor for individuals’ life satisfaction, while the GINI coefficient that was considered as the indicator of absolute inequality has a smaller effect on life satisfaction. Also, country-level subjective equality moderates the confirmed link between individuals’ income and their life satisfaction. It can be concluded that both individual and country-level subjective inequality slightly moderate the effect of individuals’ income on their life satisfaction.

Keywords: individual values, life satisfaction, multilevel analysis, objective inequality, subjective inequality, welfare regimes status

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Authors: Koffi Sodokin

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Financing microstructures are increasingly seen as a means of financial inclusion and improving overall well-being in developing countries. In practice, digital transformation in finance can accelerate the optimal functioning of financing microstructures, such as access by households to microfinance and microinsurance. Large households' access to finance can lead to a reduction in income inequality and an overall improvement in well-being. This paper explores the impact of access to digital finance and financing microstructures on household well-being and the reduction of income inequality. To this end, we use the propensity score matching, the double difference, and the smooth instrumental quantile regression as estimation methods with two periods of survey data. The paper uses the FinScope consumer data (2016) and the Harmonized Living Standards Measurement Study (2018) from Togo in a comparative perspective. The results indicate that access to digital finance, as a cultural game changer, and to financing microstructures improves overall household well-being and contributes significantly to reducing income inequality.

Keywords: financing microstructure, microinsurance, microfinance, digital finance, well-being, income inequality

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Authors: Ying Zhao, Xingyan Bin

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Semi-supervised clustering algorithms have been shown effective to improve clustering process with even limited supervision. However, semi-supervised hierarchical clustering remains challenging due to the complexities of expressing constraints for agglomerative clustering algorithms. This paper proposes novel semi-supervised agglomerative clustering algorithms to build a hierarchy based on a known reference tree. We prove that by enforcing distance constraints defined by a reference tree during the process of hierarchical clustering, the resultant tree is guaranteed to be consistent with the reference tree. We also propose a framework that allows the hierarchical tree generation be aware of levels of levels of the agglomerative tree under creation, so that metric weights can be learned and adopted at each level in a recursive fashion. The experimental evaluation shows that the additional cost of our contraint-based semi-supervised hierarchical clustering algorithm (HAC) is negligible, and our combined semi-supervised HAC algorithm outperforms the state-of-the-art algorithms on real-world datasets. The experiments also show that our proposed methods can improve clustering performance even with a small number of unevenly distributed labeled data.

Keywords: semi-supervised clustering, hierarchical agglomerative clustering, reference trees, distance constraints

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Authors: Sanjay Sinha, Mohd Umair Khan

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The level of income inequality in India has been worrisome as the World Inequality Report termed it as a “poor and unequal country, with an affluent elite”. As important as income is to understand inequality and deprivation, it is just one dimension. But the historical roots and current realities of inequality and deprivation in India lies in many of the non-income dimensions such as housing, nutrition, education, agency, sense of inclusion etc. which are often ignored, especially in solution-oriented research. The level of inequality and deprivation among the tribal is one such case. There is a corpus of literature establishing that the tribal communities in India are disadvantageous on various grounds. Given their rural geography, issues of access and quality of basic facilities such as education and healthcare are often unaddressed. COVID-19 has further exacerbated this challenge and climate change will make it even more worrying. With this background, a succinct measurement tool at the village level is necessary to design short to medium-term actions with reference to risk mitigation for tribal communities. This research paper examines the level of inequality and deprivation among the tribal communities in the rural areas of Andhra Pradesh state of India using a Multidimensional Inequality and Deprivation Index based on the Alkire-Foster methodology. The methodology is theoretically grounded in the capability approach propounded by Amartya Sen, emphasizing on achieving the “beings and doings” (functionings) an individual reason to value. In the index, the authors have five domains, including Livelihood, Food Security, Education, Health and Housing and these domains are divided into sixteen indicators. This assessment is followed by domain-wise short-term and long-term solutions.

Keywords: Andhra Pradesh, Alkire-Foster methodology, deprivation, inequality, multidimensionality, poverty, tribal

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Authors: Julia Yi

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Using the Household Pulse Survey conducted by the U.S Census Bureau, this study finds that the pandemic increased the prevalence and inequality of food insecurity among US households. About 28% of households were food secure, which doubled the 2019 level. Hispanic and black, low-income households, households lost income, and households with children were impacted most. Food banks provided most free groceries and meals. This study recommends mobilizing emergency food organizations, improving food assistance programs and supply chains, and creating innovative community support.

Keywords: covid-19 pandemic, food insecurity, US, inequality

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Authors: Rene Valdiviezo-Issa

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In this paper, we use Mexico’s Households Income and Expenditures (ENIGH) survey to explain the behaviour that the urban-rural expenditure gap has had since Mexico’s incorporation to the North American Free Trade Agreement (NAFTA) in 1994 and we compare it with the latest available survey, which took place in 2014. We use real trimestral expenditure per capita (RTEPC) as the measure of welfare. We use quantile regressions and a quantile regression decomposition to describe the gap between urban and rural distributions of log RTEPC. We discover that the decrease in the difference between the urban and rural distributions of log RTEPC, or inequality, is motivated because of a deprivation of the urban areas, in very specific characteristics, rather than an improvement of the urban areas. When using the decomposition we observe that the gap is primarily brought about because differences in returns to covariates between the urban and rural areas.

Keywords: quantile regression, urban-rural inequality, inequality in Mexico, income decompositon

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Authors: Jin Liang, Guanghua Shi

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In this paper, we are concerned with the further refinements of the Heinz operator inequalities in Hilbert spaces. Our purpose is to derive several new Heinz-type operator inequalities. First, with the help of the Taylor series of some hyperbolic functions, we obtain some refinements of the ordering relations among Heinz means defined by Bhatia with different parameters, which would be more suitable in obtaining the corresponding operator inequalities. Second, we present some generalizations of Heinz operator inequalities. Finally, we give a matrix version of the Heinz inequality for the Hilbert-Schmidt norm.

Keywords: Hilbert space, means inequality, norm inequality, positive linear operator

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Authors: Temitope Faloye

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The absence of equity and transparency in Nigeria's economic system has resulted in unemployment. Women’s unemployment rate remains higher because women's range of jobs is often narrower due to discriminatory attitudes of employers and gender segregation in the labor market. Gender inequality is one of the strong factors of unemployment, especially in developing countries like Nigeria, where the female gender is marginalized in the labor force market. However, gender equality in terms of labor market access and employment condition has not yet been attained. Feminist theory is considered as an appropriate theory for this study. The study will use a mixed-method design, collecting qualitative and quantitative data to provide answers to the research questions. Therefore, the research study aims to investigate the present situation of gender inequality in the Nigerian labor market.

Keywords: unemployment, gender inequality, gender equality, labor market, female graduate

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Authors: Tapan Jain, Davender Singh Saini

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Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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Authors: Revaz Gvelesiani

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Nowadays, social inequality increasingly strengthens the trend from business entrepreneurship to social entrepreneurship. It can be said that business entrepreneurs, according to their interests, move towards social entrepreneurship. Effectively operating markets create mechanisms, which lead to 'good' behavior. This is the most important feature of the rationally functioning society. As for the prospects of social entrepreneurship, expansion of entrepreneurship concept at the social arena may lead to such an outcome, when people who are skeptical about business, become more open towards entrepreneurship as a type of activity. This is the way which by means of increased participation in entrepreneurship promotes fair distribution of wealth. Today 'entrepreneurship for all' is still a dream, although the one, which may come true.

Keywords: social entrepreneurship, business entrepreneurship, functions of entrepreneurship, social inequality, social interests, interest groups, interest conflicts

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Authors: Zhaoxin Luo, Michael Zhu

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In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Roya Kelishadi, Mostafa Amini-Rarani, Mostafa Qorbani

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Introduction: As a health-related behavior, physical activity (PA) has an unequal distribution relating to individual's socioeconomic status. This study aimed to assess socioeconomic inequality in PA among Iranian students and their parents at national level and according to socioeconomic status (SES) of the living regions. Method: This study was conducted as part of a national surveillance program conducted among 14400 Iranian students and their parents. Non-linear principal component analysis was used to construct the households' socioeconomic status, and the concentration index approach was applied to measure inequality in father, mother, and student’s PA. Results: The data of 13313 students and their parents were complete for the current study. At national level and SES regions, students had more PA than their parents (except in the lowest SES region), and fathers have more PA than mothers. The lowest means of mother and student's PA were find in the highest SES region. At national level, the concentration indices of father and mother’s PA were -0.050 (95 % CI: -0.067 ~ -0.030) and -0.028 (95% CI: -0.044 ~ -0.012), respectively; indicating pro-poor inequality and, the CI value of student PA was nearly equal to zero (P > 0.05). At SES regions, father and mother's PA were more concentrated in the poor, except for lower middle region. Regional concentration indices for students reveal that inequality not statistically significant at all regions. Conclusion: This study suggests that reliable evidence that comparing different aspects of inequality of PA, based on socioeconomic status and residence areas of students and their parents, could be used for better planning for health promotion programs. Moreover, given the average of mother's and student’s PA in the richer regions were low, it can be suggested that richer focused-PA planning may further increase the level of PA across higher SES and, consequently, reduce inequality in PA. These findings can be applied in the health system services.

Keywords: concentration index, health system services, physical activity, socioeconomic inequality

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Authors: Fayssal Ynineb, Toufik Hadjersi, Fatsah Moulai, Wafa Achour

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Currently, tremendous attention has been paid to the rational design and synthesis of core/shell heterostructures for high-performance supercapacitors. In this study, the hierarchical NiO/ZnCo₂O₄ Core-Shell Nanorods Arrays were successfully deposited onto ITO substrate via a two-step hydrothermal and electrodeposition methods. The effect of the thin carbon layer between NiO and ZnCo₂O₄ in this multi-scale hierarchical structure was investigated. The selection of this structure was based on: (i) a high specific area of pseudo-capacitive NiO to maximize specific capacitance; (ii) an effective NiO-electrolyte interface to facilitate fast charging/discharging; and (iii) conducting carbon layer between ZnCo₂O₄ and NiO enhance the electric conductivity which reduces energy loss, and the corrosion protection of ZnCo₂O₄ in alkaline electrolyte. The obtained results indicate that hierarchical NiO/ZnCo₂O₄ present a high specific capacitance of 63 mF.cm⁻² at a current density of 0.05 mA.cm⁻² higher than that of pristine NiO and ZnCo₂O₄ of 6 and 3 mF.cm⁻², respectively. The carbon layer improves the electrical conductivity among NiO and ZnCo₂O₄ in the hierarchical NiO/C/ZnCo₂O₄ electrode. As well, the specific capacitance drastically increased to reach 125 mF.cm⁻². Moreover, this multi-scale hierarchical structure exhibits superior cycling stability with ~ 95.7 % capacitance retention after 65k cycles. These results indicate that the NiO/C/ZnCo₂O₄ nanocomposite material is an outstanding electrode material for supercapacitors.

Keywords: NiO/C/ZnCo₂O₄, specific capacitance, hydrothermal, supercapacitors

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Colin Smith, Linsey S Passarella

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Due to the proliferation and decentralized nature of academic publication, no widely accepted scheme exists for organizing papers by their scientific field of study (FoS) to the author’s best knowledge. While many academic journals require author provided keywords for papers, these keywords range wildly in scope and are not consistent across papers, journals, or field domains, necessitating alternative approaches to paper classification. Past attempts to perform field-of-study (FoS) classification on scientific texts have largely used a-hierarchical FoS schemas or ignored the schema’s inherently hierarchical structure, e.g. by compressing the structure into a single layer for multi-label classification. In this paper, we introduce an application of a Layered Neural Network (LNN) to the problem of performing supervised hierarchical classification of scientific fields of study (FoS) on research papers. In this approach, paper embeddings from a pretrained language model are fed into a top-down LNN. Beginning with a single neural network (NN) for the highest layer of the class hierarchy, each node uses a separate local NN to classify the subsequent subfield child node(s) for an input embedding of concatenated paper titles and abstracts. We compare our LNN-FOS method to other recent machine learning methods using the Microsoft Academic Graph (MAG) FoS hierarchy and find that the LNN-FOS offers increased classification accuracy at each FoS hierarchical level.

Keywords: hierarchical classification, layer neural network, scientific field of study, scientific taxonomy

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Authors: Hamid Boustanifar, Geraldo Cerqueiro, María Fabiana Penas

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We exploit state-level changes in the amount of personal wealth individuals can protect under Chapter 7 to analyze the causal effect of debtor protection on income inequality. We find that an increase in state exemptions significantly increases inequality by reducing income for low-income individuals and by increasing income for high-income individuals. The increase in inequality is four times larger among the self-employed than among wage earners, and it is due mainly to a growing income gap between skilled (i.e., individuals with a college degree) and unskilled entrepreneurs. We also find that the employment rate of skilled entrepreneurs significantly increases, while the employment rate of unskilled wage earners falls. Our results are consistent with a recent literature that shows that higher exemptions redistribute credit from low-wealth to high-wealth entrepreneurs, affecting the performance of their businesses.

Keywords: debtor protection, credit markets, income inequality, debtor protection laws

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Authors: Baqir Khawari

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This study has been undertaken to investigate the impact of remittances on household poverty and inequality using OLS and Logit Models with a strictly multi-random sampling method. The result of the OLS model reveals that if the per capita international remittances increase by 1%, then it is estimated that the per capita income will increase by 0.071% and 0.059% during 2019/20 and 2020/21, respectively. In addition, a 1% increase in external remittances results in a 0.0272% and 0.025% reduction in per capita depth of poverty and a 0.0149% and 0.0145% decrease in severity of poverty during 2019/20 and 2020/21, respectively. It is also shown that the effect of external remittances on poverty is greater than internal remittances. In terms of inequality, the result represents that remittances reduced the Gini coefficient by 2% and 7% during 2019/20 and 2020/21, respectively. Further, it is bold that COVID-19 negatively impacts the amount of received remittances by households, thus resulting in a reduction in the size of the effect of remittances. Therefore, a concerted effort of effective policies and governance and international assistance is imperative to address this prolonged problem.

Keywords: migration, remittances, poverty, inequality, COVID-19, Afghanistan

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Authors: Vorya Shabrandi

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The study factors of poverty and inequality causes in countries is the subject of many scholars and economists in the last century, theorists in various areas of economic science know different factors as the roots of poverty and inequality in Iran after the 1979 revolution. Economists have emphasized political elements and political scientists on political elements. This research reviews the political economy of poverty and corruption in Iran after the revolution. The findings of this research, based on AcemOgluand Robinson theory, show how the institutional structural dependence of Iran's economy to raw has led to the growth of its non-economic economic institutions and its consequence of the continuity of the release and looting economy and poverty and inequality in Iran's political economy Is. This research was carried out using descriptive-analytical and comparative methods. Many economists try to justify the conditions of the country based on war, sanctions; And the external factors, and ... knows. In this study, we tried to examine the roots of poverty and the looting economy of Iran by implementing Research AcemOgluand Robinson on the institutions and roots of poverty. Looking for a framework for understanding why countries, such as Iran, the reason for the difference in revenue in different countries, as well as the poor or wealth of countries, regardless of the non-effective and non-professional institutions, and why inefficient institutions in some countries, such as Iran, such as Iran It remains and does not have a voluntary political powers to change these institutions. Findings The research shows that institutions are broadly the main reason for the roots of the robust and looting economy (poverty and inequality) in Iran.

Keywords: Iran, plunderable (Loot) economy, raw shopping, poverty and inequality, acem oglu and robinson, non-inclusive institutions

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Authors: Rishmidevi Kirtie Algoe

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Advocating for gender equality in sports is a global struggle but a greater challenge for small nations with weak economies like Suriname, a Dutch-speaking country in the Caribbean. This paper presents the experience of the Suriname Olympic Committee (SOC) in addressing gender inequality in sports in the global context of the policies implemented by the International Olympic Committee (IOC). The case of Suriname is interesting because it shows the results of a small nation in creating protective measures. The SOC has succeeded in developing a code of conduct for sports and is now taking steps to establish a sports justice institute. All of this is happening in a situation where there are few women leaders in sport: only three of the seventeen national member federations are led by women, and there are two women on SOC's 9-member board. Three arguments are made. First, gender inequality in sports in Suriname is a reflection of national power structures and cultural barriers to women in sports. Second, IOC policies and resources to reduce gender inequality in sports, while important, do not guarantee national change. Third, and more importantly, the SOC has addressed gender inequality with an approach based on the principles of "walk the talk" and "trial and error." All three arguments are elaborated on using the framework of intersectionality. The study draws empirically on data collected during and on SOC Gender and Sport Commission seminars and workshops, including two surveys, transcripts, and newspaper articles.

Keywords: Caribbean, gender inequality, safeguarding, Suriname Olympic Committee

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Authors: Davood Mousanezhad, Ashkan Vaziri

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As a traditional cellular structure, hexagonal honeycombs are known for their high strength-to-weight ratio. Here, we introduce a class of fractal-appearing hierarchical metamaterials by replacing the vertices of the original non-hierarchical hexagonal grid with smaller hexagons and iterating this process to achieve higher levels of hierarchy. It has been recently shown that the isotropic in-plane Young's modulus of this hierarchical structure at small deformations becomes 25 times greater than its regular counterpart with the same mass. At large deformations, we find that hierarchy-dependent elastic buckling introduced at relatively early stages of deformation decreases the value of Poisson's ratio as the structure is compressed uniaxially leading to auxeticity (i.e., negative Poisson's ratio) in subsequent stages of deformation. We also show that the topological hierarchical architecture and instability-induced pattern transformations of the structure under compression can be effectively used to tune the propagation of elastic waves within the structure. We find that the hierarchy tends to shift the existing phononic bandgaps (defined as frequency ranges of strong wave attenuation) to lower frequencies while opening up new bandgaps. Deformation is also demonstrated as another mechanism for opening more bandgaps in hierarchical structures. The results provide new insights into the role of structural organization and hierarchy in regulating mechanical properties of materials at both the static and dynamic regimes.

Keywords: cellular structures, honeycombs, hierarchical structures, metamaterials, multifunctional structures, phononic crystals, auxetic structures

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Authors: Mackenzie Leake, Liyu Xia, Kamil Rocki, Wayne Imaino

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In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed.

Keywords: hierarchical temporal memory, HTM, learning algorithms, machine learning, spatial pooler

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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Authors: Seung-Jun Yu, Yeong-Seop Ahn, Young-Min Ko, Hyoung-Kyu Song

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In order to achieve high data rate and increase the spectral efficiency, multiple input multiple output (MIMO) system has been proposed. However, multiple antennas are limited by size and cost. Therefore, recently developed cooperative diversity scheme, which profits the transmit diversity only with the existing hardware by constituting a virtual antenna array, can be a solution. However, most of the introduced cooperative techniques have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In this paper, we propose a cooperative cyclic delay diversity (CDD) scheme that uses hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.

Keywords: MIMO, cooperative communication, CDD, hierarchical modulation

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Authors: Acumsiri Tantikarnpanit

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This paper aims to examine the relationship between urbanization and income inequality in Thailand during the period 2002–2020. Using a panel of data for 76 provinces collected from Thailand’s National Statistical Office (Labor Force Survey: LFS), as well as geospatial data from the U.S. Air Force Defense Meteorological Satellite Program (DMSP) and the Visible Infrared Imaging Radiometer Suite Day/Night band (VIIRS-DNB) satellite for nineteen selected years. This paper employs two different definitions to identify urban areas: 1) Urban areas defined by Thailand's National Statistical Office (Labor Force Survey: LFS), and 2) Urban areas estimated using nighttime light data from the DMSP and VIIRS-DNB satellite. The second method includes two sub-categories: 2.1) Determining urban areas by calculating nighttime light density with a population density of 300 people per square kilometer, and 2.2) Calculating urban areas based on nighttime light density corresponding to a population density of 1,500 people per square kilometer. The empirical analysis based on Ordinary Least Squares (OLS), fixed effects, and random effects models reveals a consistent U-shaped relationship between income inequality and urbanization. The findings from the econometric analysis demonstrate that urbanization or population density has a significant and negative impact on income inequality. Moreover, the square of urbanization shows a statistically significant positive impact on income inequality. Additionally, there is a negative association between logarithmically transformed income and income inequality. This paper also proposes the inclusion of satellite imagery, geospatial data, and spatial econometric techniques in future studies to conduct quantitative analysis of spatial relationships.

Keywords: income inequality, nighttime light, population density, Thailand, urbanization

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Authors: Benny Benyamin Nasution, Rahmat Widia Sembiring, Abdul Rahman Dalimunthe, Nursiah Mustari, Nisfan Bahri, Berta br Ginting, Riadil Akhir Lubis, Rita Tavip Megawati, Indri Dithisari

Abstract:

The earth coordinate system is an important part of an attempt for earthquake forecasting, such as the one using Single Layer Hierarchical Graph Neuron (SLHGN). However, there are a number of problems that need to be worked out before the coordinate system can be utilized for the forecaster. One example of those is that SLHGN requires that the focused area of an earthquake must be constructed in a grid-like form. In fact, within the current earth coordinate system, the same longitude-difference would produce different distances. This can be observed at the distance on the Equator compared to distance at both poles. To deal with such a problem, a coordinate system has been developed, so that it can be used to support the ongoing earthquake forecasting using SLHGN. Two important issues have been developed in this system: 1) each location is not represented through two-value (longitude and latitude), but only a single value, 2) the conversion of the earth coordinate system to the x-y cartesian system requires no angular formulas, which is therefore fast. The accuracy and the performance have not been measured yet, since earthquake data is difficult to obtain. However, the characteristics of the SLHGN results show a very promising answer.

Keywords: hierarchical graph neuron, multidimensional hierarchical graph neuron, single layer hierarchical graph neuron, natural disaster forecasting, earthquake forecasting, earth coordinate system

Procedia PDF Downloads 216

Authors: Kimberly McCabe

Abstract:

The trafficking of women and children for abuse and exploitation is not a new problem under the umbrella of human trafficking; however, over the last decade, the problem has attracted increased attention from international governments and non-profits attempting to reduce victimization and provide services for survivors. Research on human trafficking suggests that the trafficking of human beings is, largely, a symptom of poverty. As the trafficking of human beings may be viewed as a response to the demand for people for various forms of exploitation, a product of poverty, and a consequence of the subordinate positions of women and children in society, it reaches beyond randomized victimization. Hence, human trafficking, and especially the trafficking of women and children, goes beyond the realm of poorness. Therefore, to begin to understand the reasons for the existence of human trafficking, one must identify and consider not only the immediate causes but also those underlying structural determinants that facilitate this form of victimization. Specifically, one must acknowledge the economic, social, and cultural factors that support human trafficking. This research attempts to study human trafficking at the country level by focusing on economic, social, and cultural characteristics. This study focuses on inequality and, in particular, gender inequality as related to legislative attempts to address human trafficking. Within the design of this project is the use of the US State Department’s tier classification system for Trafficking in Persons (TIP) and the USA CIA Fact Sheet of country characteristics for over 150 countries in an attempt to model legal outcomes as related to human trafficking. Results of this research demonstrate the significance of characteristics beyond poverty as related to country-level responses to human trafficking.

Keywords: child trafficking, gender inequality, human trafficking, inequality

Procedia PDF Downloads 240

Authors: Kalpana Dahiya

Abstract:

This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm.

Keywords: global optimization, hierarchical optimization, transportation problem, concave minimization

Procedia PDF Downloads 162