scholarly journals Understanding Structure of Poverty Dimensions in East Java: Bicluster Approach

2017 ◽  
Vol 6 (2) ◽  
pp. 289-300 ◽  
Author(s):  
Budi Yuniarto ◽  
Robert Kurniawan
Keyword(s):  
Data Mining ◽  
Poverty Reduction ◽  
Multidimensional Poverty ◽  
Two Dimensional ◽  
View Point ◽  
Dimensional Matrix ◽  
Clustering Patterns

Poverty is still become a main problem for Indonesia, where recently, the view point of poverty is not just from income or consumption, but it’s defined multidimensionally. The understanding of the structure of multidimensional poverty is essential to government to develop policies for poverty reduction. This paper aims to describe the structure of poverty in East Java by using variables forming the dimensions of poverty and to investigate any clustering patterns in the region of East Java with considering the poverty variables using biclustering method. Biclustering is an unsupervised technique in data mining where we are grouping scalars from the two-dimensional matrix. Using bicluster analysis, we found two bicluster where each bicluster has different characteristics.DOI: 10.15408/sjie.v6i2.4769

scholarly journals Evaluating the Impacts of Smallholder Farmer’s Participation in Modern Agricultural Value Chain Tactics for Facilitating Poverty Alleviation—A Case Study of Kiwifruit Industry in Shaanxi, China

Agriculture ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 462
Author(s):  
Hongyu Wang ◽  
Xiaolei Wang ◽  
Apurbo Sarkar ◽  
Lu Qian
Keyword(s):  
Value Chain ◽  
Rural Areas ◽  
Poverty Alleviation ◽  
Poverty Reduction ◽  
Smallholder Farmers ◽  
Multidimensional Poverty ◽  
Well Being ◽  
Reduction Degree ◽  
Poverty Level ◽  
Storage Technology

Market-based initiatives like agriculture value chain (AVC) are becoming progressively pervasive to support smallholder rural farmers and assist them in entering larger market interventions and providing a pathway of enhancing their socioeconomic well-being. Moreover, it may also foster staggering effects towards the post-era poverty alleviation in rural areas and possessed a significant theoretical and practical influence for modern agricultural development. The prime objective of the study is to explore the effects of smallholder farmers’ participation in the agricultural value chain for availing rural development and poverty alleviation. Specifically, we have crafted the assessment employing pre-production (improved fertilizers usage), in-production (modern preservation technology), and post-production (supply chain) participation and interventions of smallholder farmers. The empirical data has been collected from a micro survey dataset of 623 kiwifruit farmers from July to September in Shaanxi, China. We have employed propensity score matching (PSM), probit, and OLS models to explore the multidimensional poverty reduction impact and heterogeneity of farmers’ participation in the agricultural value chain. The results show that the total number of poor farmers who have experienced one-dimensional and two-dimensional poverty is relatively high (66.3%). We also find that farmers’ participation in agricultural value chain activities has a significant poverty reduction effect. The multidimensional poverty level of farmers using improved fertilizer, organizational acquisition, and using storage technology (compared with non-participating farmers) decreased by 30.1%, 46.5%, and 25.0%, respectively. The multidimensional poverty reduction degree of male farmers using improved fertilizer and participating in the organizational acquisition is greater than that of women. The multidimensional poverty reduction degree of female farmers using storage and fresh-keeping technology has a greater impact than the males using storage and improved storage technology. Government should widely promote the value chain in the form of pre-harvest, production, and post-harvest technology. The public–private partnership should also be strengthened for availing innovative technologies and infrastructure development.

Deep convolutional neural networks for human movement detection using wireless signals

2021 ◽  
pp. 1-10
Author(s):  
Chien-Cheng Leea ◽  
Zhongjian Gao ◽  
Xiu-Chi Huanga
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Convolutional Neural Network ◽  
Detection System ◽  
Deep Convolutional Neural Network ◽  
Human Detection ◽  
Two Dimensional ◽  
Dimensional Matrix ◽  
State Classification ◽  
Propagation Paths

This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet’s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective.

scholarly journals Notes on Bhutan’s Gross National Happiness and its Measurement

2016 ◽  
Vol 27 ◽  
pp. 1-15
Author(s):  
Eduardo Monaco
Keyword(s):  
International Development ◽  
Poverty Reduction ◽  
Good Governance ◽  
Early Stage ◽  
Multidimensional Poverty ◽  
Holistic Approach ◽  
Environmental Preservation ◽  
Gross National Happiness ◽  
Stage Of Development ◽  
National Happiness

Bhutan, a Himalayan landlocked country of just about 750,000 inhabitants, has since the 1980s adopted a unique, holistic approach to development governance commonly referred to as 'Gross National Happiness' (GNH), which aims at achieving equitable socio-economic progress in harmony with other fundamental 'pillars' such as environmental preservation, good governance, and protection of the local cultural identity. The strategy - inspired, above all, by solid Tantric Buddhist belief - significantly differentiates itself from the mainstream GDP-driven, output-maximizing paradigms by maintaining that truly sustainable development can only originate from acknowledging the equal dignity and crucial interdependence of various dimensions of both human and natural life. This paper, drafted in the month of December 2015, briefly analyzes GNH policy’s key tenets and achievements – more conspicuous in regards to democratic governance and environment than in terms of inclusive, multidimensional poverty reduction, as well as its recently devised measuring tool, the GNH Index, and the results of its latest surveys. Factors like the peculiar Buddhist culture that informs it, the relatively simple economic infrastructure at this early stage of development, as well as the limited size of the politically active, urbanized population, all make GNH per se a distinctively Bhutanese phenomenon. Nevertheless, the fundamental paradigm shift that GNH advocates has already resonated beyond the countries’ borders, reinforcing a growing trend across international development actors towards a more comprehensive, qualitative definition and measurement of societal development.

Multiple Dimensions of Impoverishment in Iran

2020 ◽  
pp. 26
Author(s):  
Hosnieh Mahoozi ◽  
Jeurgen Meckl
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Poverty Reduction ◽  
Multidimensional Poverty ◽  
Well Being ◽  
Capital City ◽  
Income Poverty ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Multiple Dimensions

Concerning the demands of Sen’s (1984) Capability Approach to the assessment of human well-being, we estimate multidimensional poverty and compare the results with traditional measures of income poverty in Iran. We detect poverty in urban and rural Iran over 1999-2007, a period with relatively high GDP growth. The results reveal that the pace of income poverty reduction is much faster than the pace of multidimensional poverty alleviation. The pace of poverty reduction is much slower in rural areas than in urban areas and the capital city, Tehran. Hence, inequality between rural and urban areas increased over the time. We also show how policymakers may benefit from applying the multidimensional approach in targeting the subgroups by the most deprived aspects.

The Loyal Traveler: Examining a Typology of Service Patronage

1997 ◽  
Vol 35 (4) ◽  
pp. 2-10 ◽  
Author(s):  
Mark P. Pritchard ◽  
Dennis R. Howard
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Service Providers ◽  
Two Dimensional ◽  
Composite Measure ◽  
The Third ◽  
Dimensional Matrix ◽  
Repeat Purchase ◽  
Clear Support

The first goal of this study was to determine whether Day's (1969) measure of loyalty could be extended to better understand travel service patronage. Findings provide clear support that this composite measure, of repeat purchase and loyal attitude, is an effective approach to distinguishing the loyal traveler. A cluster analysis that combined scores on the composite measure from 428 travelers supported a two-dimensional matrix that identified four types of loyalty: true, spurious, latent, and low. This accomplished the study's second purpose by confirming that the four distinct levels of loyalty exist in a variety of service settings. Discriminant analysis was used to achieve the third objective — To identify those characteristics that differentiate the truly loyal patron. The resulting profile found this traveler to be a highly satisfied, symbolically involved consumer drawn to those services that exhibit an empathetic, caring concern for their patrons. These findings generate a much clearer understanding of how service providers can measure and manage their returning patrons.

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