Application of GA-based Projection Pursuit Model in the Comprehensive Evaluation of Governance Level of "Peasant-to-citizen" Community

Headnote

Abstract: As a livelihood project for China's urban-rural overall development and urban-rural integrated construction, the "peasant-to-citizen" project has a very important realistic significance. The governance level of "peasant-to-citizen" community is the key determining whether this livelihood project can be promoted continuously. In order to make a scientific and correct evaluation on the governance level of "peasant-to-citizen" community in Jiangxi province, the "peasant-tocitizen" communities in Nanchang and Jiujiang were selected as the objects of research; after field investigation and collection of original data, the GA-based (genetic algorithm-based) projection pursuit model was used to evaluate the index system built. It is found through the research that there are some differences in the governance level of "peasant-to-citizen" communities in the two cities; besides, with the assistance of optimized projection direction, it indicates the difference of all level-II evaluation indexes in the overall judgment of samples; this also shows that the governance level of "peasant-to-citizen" community is influenced by multiple factors, which have different degrees of effect.

Keywords: peasant-to-citizen; community governance; projection pursuit model

(ProQuest: ... denotes formulae omitted.)

1.Introduction

With the continuous promotion of urbanization process and rapid implementation of overall rural-urban development, rural-urban integrated development and other policies concerned, on the one hand, the extensive requisition of land in the suburban areas and urban villages leads to a large number of land-lost peasants; on the other hand, the urban migrant workers live in cities. To settle down in cities for a long time, the two groups of people need to live in cities finally, so the former village system is changed into the community system and unique "peasant-to-citizen" communities are formed. Because of the different subjects of community, there are significant differences between the "peasant-to-citizen" community and the general urban community (Sá et al., 2016). Meanwhile, in consideration of the short existence of such communities and relatively complicated community conditions, the governance requirements for "peasant-tocitizen" communities are stricter. In order to build a harmonious "peasant-to-citizen" community relationship and effectively carry out the "peasant-to-citizen" policy, good "peasant-to-citizen" community governance is not only the basic connotation promoting land-lost peasants to become urban residents but also the necessary requirement of the new urbanization road.

According to the current research content, scholars have obtained abundant achievements after making a series of studies on China's "peasant-to-citizen" problem. Their studies mainly focus on the group satisfaction analysis of "peasant-to-citizen" community, "peasant-to-citizen" cost estimation, "peasant-to-citizen" community management and "peasant-to-citizen" level analysis etc. From the perspective of range of study, the provincial studies mainly analyze the people citizenization from the view angle of inclusive growth and give policy suggestions on people citizenization from many aspects (Wang, 2016); the municipal studies mainly discuss the employment issue of "peasant-to-citizen" residents and emphasize the government's major responsibility for the employment issue (Ding, 2013). From the perspective of research methods, mainly the data analysis method, comprehensive index evaluation method and factor analysis method are included. The data analysis methods is to collect, analyze and systemize the original data of some urban "peasant-to-citizen" costs so as to explore and discuss the major influencing factors of "peasant-to-citizen" project (Wei and Sui, 2015). The comprehensive index evaluation method is used to build the satisfaction evaluation index system and analyze the community residents' satisfaction for "peasant-to-citizen" community (Xia and Xu, 2010). The factor analysis method is to analyze the issues in "peasant-to-citizen" communities and explore the measures and approaches to optimize the community management system (Xu and Lu, 2007). In addition to such frequently-used methods, there are also methods such as analytic hierarchy process (AHP) (Geng, 2007), fuzzy evaluation method (Chen, 2015), game theory (Lu, 2015) and AHM algorithm (Wang, 2013) based on specific problems. The existing research achievements have solved some issues in the "peasant-to-citizen" process and provided a new thought for the subsequent researches.

Based on the analysis and systemization of the existing research content, we know that "peasant-to-citizen" policy is a new population policy benefiting people is different in various areas, so the "peasant-to-citizen" community governance measures also need to be adjusted based on the local conditions and proper ways and measures are required for governance; therefore, the region-restricted researches concerned are also needed. From the perspective of research methods, there are some defects in the frequentlyused methods currently. For instance, there is artificial subjective assumption in determining the weight evaluation index in AHP; the fuzzy evaluation method lacks recognition for some positive factors; the factor analysis method involves the loss of reliability of indexes when processing the index data. Such defects also limit the research achievements' interpretability and further expansion of research content. For this reason, this research plans to evaluate the governance level of "peasant-to-citizen" community in Jiangxi province with the GA-based projection pursuit model, contrastively analyze the governance levels of three typical "peasant-to-citizen" communities in Nanchang County with the multiple index data demission deduction method, and infer the relevant factors influencing the community governance level through the result of comparison.

2.Building the comprehensive evaluation projection pursuit model

The GA-based projection pursuit model, which organically combines the genetic algorithm with the projection pursuit model, is a sample data-driven exploratory data analysis method, which can project high-dimensional data to a low-dimensional space through a combination. As for the projected configuration, the projection index function is used to describe the possibility that the projection reveals a certain classification and sorting organization of the original system and to find out the projection value which can optimize the projection index function (namely, reflect the high-dimensional data structure or characteristics); then, the characteristics of classification structure of highdimensional data can be analyzed based on the project value (Ma, 2014). When reducing dimensions, the projection pursuit model can keep the data stability and realize that low dimension can also faithfully reflect the architectural characteristics of data. The projection pursuit model based on the genetic algorithm can not only obtain the comprehensive evaluation quality, but also optimize the projection direction and analyze the degree of influence of all evaluation indexes on the overall judgment of samples.

2.1.Normalization of index sample data

Based on the specific characteristics of this research and to show the governance level of "peasant-to-citizen" community, the initial evaluation sample set built by using communities as objects of research is {X*(i, j) | i=i, 2, 3,..., n; j=i, 2, 3,...,p}. X*(i, j) is the evaluation index j of "peasant-to-citizen" community i. "n" and "p" respectively denote the number of "peasant-to-citizen" communities and the quantity of evaluation indexes. In order to eliminate the dimension of each index value and to unify the range of variation of each index, extremums can be normalized according to formula (1) and formula (2).

As for a benefit-oriented index, the bigger index value will be the better. Numerical values should be normalized according to formula (1):

... (1)

As for a cost-oriented index, the smaller index value will be the better. Numerical values should be normalized according to formula (2):

... (2)

In the formula above, min(xj ) and max( ) are respectively the minimum and maximum of original index data j among n "peasant-to-citizen" communities.

2.2.Building the projection index function

The GA-based projection pursuit model is to synthesize the P-dimensional data {X*(i, j) | i=i, 2, 3,...,n; j=i, 2, 3,...,p} into the one-dimensional projection value Z(i) in the projection direction a={a(i), a(2),..., a(p)}. its expression is shown in formula (3).

... (3)

In the formula above, a is the unit length vector. At the synthetical projection value, the distribution characteristics of projection value are required to be as follows: the local projection points should be possibly intensive and would better gather into some point clusters; however, on the whole, the projection points and clusters should possibly disperse. On the basis of this, the projection index function can be built below:

... (4)

In the formula above, Sz is the standard deviation of projection value Z (i) ; is the local density of projection value Z(i). The calculation formulas for the two are shown below:

... (5)

... (6)

In formula (4), z is the mean value of sequence {z(i ) |i = 1,-,m}. Formula (5) is the local width parameter determined based on the data feature. When the space among points vÿ is less than or equal to R, it can be calculated as one type; otherwise, it should calculated according to different types; vÿ = |z(i) - z(j) ; the sign function u(R -v{j) is the unit step function; when R > vij, the function value is 1; otherwise, the function value is 0.

2.3.Optimization of projection index function

Based on the characteristics of projection pursuit, the optimal projection direction should be the projection direction that maximally reveals a certain feature structure of high-dimensional data. In this research, the high-dimensional global optimization problem can be carried out by simulating the rules of the survival of the fittest of creatures and the accelerated genetic algorithm (AGA) of chromosome information exchange mechanism inside a group. When the sample set of all index values is set, the projection index function Q(a) only changes with the change in the projection direction a. The optimal projection direction which maximally reveals a certain feature structure of high-dimensional data can be estimated by solving the maximization problem of projection index function. Thus, the optimized projection index function expression (7) can be obtained.

... (7)

2.4.Evaluation on governance level

When the optimal projection direction a* in Step III is put into formula (1), the projection value z (i) of each sample point can be obtained. The whole process of dimension reduction is shown in Fig. 1. Verify and analyze the modeling process based on the model verification process put forward by Tomás San Feliu, a Spanish scholar (Tomás, 2016). Then, judge the samples according to the projection value; besides, after normalizing the samples to be evaluated through the comprehensive evaluation method for the governance levels of "peasant-to-citizen" communities built, calculate the actual projection value. z* (i) can also be compared pair wise; if the two are more approximate, samples are more likely to be classified into one category.

3.Evaluation index system

3.1.Selection of sample index

In combination with the existing research achievements and based on China's development strategy of new urbanization, we know that raising the governance level of "peasant-to-citizen" community plays an important role in facilitating population urbanization and realizing the overall rural-urban development. Compared with the ordinary urban community, the "peasant-to-citizen" community is specially characterized by resettlement. Strengthening the "peasant-to-citizen" community governance is a key part to improve residents' cultural quality and living quality as well as maintaining the urban social stability and harmonious development. Based on the basic requirements of community governance, the comprehensive evaluation index system for the governance level of "peasant-to-citizen" community is established according to the scientific, reasonable, correct and effective basic principle with a proper scope (Zhou, 2015). The primary indexes with four dimensions, including community life, environment, management and customs, are set; under the primary indexes, N secondary indexes are set correspondingly. In addition, as a livelihood policy to resettle land-lost peasants in cities, the "peasant-to-citizen" policy varies based on different local conditions. Jiangxi province was selected as the region of this research. Therefore, when building the comprehensive evaluation index system, it is required to combine the specific features of "peasant-to-citizen" community governance in Jiangxi province and reasonably construct the comprehensive evaluation system for the governance level of "peasant-to-citizen" community (Table 1).

3.2.Collection of original data

The "peasant-to-citizen" policy is an effective method proposed to help land-lost peasants to become urban residents under the macro policies of overall rural-urban development and rural-urban integrated construction. Moreover, the "peasant-to-citizen" realization rate is closely linked with the local urbanization level. In consideration of the differences in the urbanization development level of each local city, the "peasant-to-citizen" realization rate and the implementation of "peasant-to-citizen" policy at each region are also different. For this reason, it is required to fully consider the differences of all regions when selecting samples and choose the most representative samples. The agricultural population accounts for a large part of the population in Jiangxi province, an important big agricultural province in the middle part of China. As shown in the data issued by the Jiangxi Survey Corps of National Bureau of Statistics, the migrant workers exceed 10,000,000 persons in Jiangxi, including 3,500,000 migrant workers in all prefecture-level cities in the province; especially, the number of migrant workers in Nanchang and Jiujiang accounts the largest proportion (National Bureau of Statistics, 2014). Nanchang and Jiujiang has relatively high urbanization levels in Jiangxi province and their economic strength and social development level are among the best in the whole province, so the two cities can easily attract migrant workers to settle down here and they are very representative. For this reason, 10 "peasant-to-citizen" community samples in Nanchang and Jiujiang were selected as objects of research in this research.

Interviews and investigations were carried out for the 5 sample communities in Nanchang and Jiujiang respectively. Residents are randomly interviewed from these "peasant-tocitizen" communities. Based on the questionnaires and data collected during interviews, the statistical data of the two prefecture-level cities were combined; through the analysis and systemization, we can know that the basic conditions of investigation samples are shown in Fig. 2. The male/female ratio of respondents in "peasant-to-citizen" communities was appropriate. As the community residents were land-lost peasants prior to the realization of "peasant-to-citizen" policy, the majority of respondents has a low educational level and mainly serves as clerk and salesman etc.

3.3.Data processing

Totally 10 "peasant-to-citizen" communities in Nanchang and Jiujiang were used as analytical units. According to the selection typicality of "peasant-to-citizen" communities, the conclusion of field investigation and the principles of reasonable distribution of community location, approximate community completion time and consistent community scales, the "peasant-to-citizen" communities were selected. Finally, Xingfu Yayuan Community, Tangzhuang Community, Lianhua Jiayuan Community, Yijing Jiayuan Community and Xiangyang Community were selected in Nanchang; Chaishang Community, Liansheng Community, Zhaojia Huayuan Community, Binjiang Huayuan Community and Wanfu Huayuan Community were selected in Jiujiang. The basic information on the governance levels of "peasant-to-citizen" communities in Nanchang and Jiujiang was obtained by choosing the original data gathered through interviews and investigations and combining the statistical data related to the two prefecture-level cities, using the calculating method of fraction and frequency and comprehensively using SPSS23.0. See Table 2 for such information.

Based on the basic information on the governance levels of "peasant-to-citizen" communities in Table 2, there is significant difference in the governance levels of communities in the two prefecture-level cities, Nanchang and Jiujiang and obvious difference in the two dimensions, community life and management. The health security of community life as well as the employment service management and assistance management of community management also need to be improved. However, there is a relatively small difference in legal compliance under the dimension of community customs.

4.Analysis on the empirical result

Projection measurements were made respectively for the comprehensive evaluation indexes of governance levels of 10 "peasant-to-citizen" communities in Nanchang and Jiujiang based on the basic information in Table 2 and the basic steps of GA-based comprehensive evaluation projection pursuit model described above; the maximum index values obtained through measurements for the two cities were respectively 1.2154 and 0.8703. Meanwhile, some data were normalized; besides, the optimal projection direction ( a* ) was obtained via optimized calculation; then, the weights of all secondary indexes under the four dimensions were calculated based on formula (7).

... (8)

In the formula above, n is the number of secondary indexes. There are 12 secondary indexes in total.

It can be seen from the conditions defined in this research that the optimal projection direction reflects the effect degree of all secondary indexes on the comprehensive evaluation on the governance level of "peasant-to-citizen" community. In order to make a contrastive analysis on the governance levels of "peasant-to-citizen" communities in Nanchang and Jiujiang, an arrangement can be made based on the size order of optimal projection direction a* (see Table 3). The difference in ranking shows the difference in the influence of primary indexes to some degree; namely, the difference in the weights of primary indexes shows the difference in the governance level of "peasant-to-citizen" community.

The difference in ranking of projection directions in Nanchang and Jiujiang can reflect the difference in the governance levels of "peasant-to-citizen" communities in the two cities; the difference can be specifically shown in the difference in some aspects of governance level and focus. To figure out the difference in the governance levels of "peasant-to-citizen" communities in the two cities more clearly, the optimal projection a* of Nanchang and Jiujiang was used as independent variable and put into the projection index function; besides, the Matlab 2010b was used for programming; finally, the protection values z '(i ) of the governance levels of "peasant-to-citizen" communities in the two cities can be obtained, as shown in Table 4.

Both Nanchang and Jiujiang have a good development momentum on the background of the integrated macro policy. In Jiangxi province, the two cities, which have relatively high new urbanization levels, are the major cities for the construction of "peasantto-citizen" community. Besides, they are the major cities where migrant workers are attracted to settle down. The governance level of "peasant-to-citizen" community directly concerns the success or failure of migrant workers' settling down in cities. Moreover, the community governance level involves numerous factors, including way of community governance, community governance system and government's supporting policy etc. Even though both Nanchang and Jiangxi are the major cities for the construction of "peasant-to-citizen" community in Jiangxi province, their different local policies and humanistic environments etc. inevitably lead to the different governance levels of "peasant-to-citizen" communities. To clearly express the difference in the governance level, the projection values of community governance levels are specially divided into four different grades: the projection value between 0~1.5 means the elementary level; the projection value between 1.5~2.5 means the intermediate level; the projection value between 2.5~3 means the senior level; the projection value over 3.5 means the excellent level. The original data in Table 4 were draw into a histogram (as shown in Fig. 3) in a proper order. As shown in the histogram for governance levels of "peasant-to-citizen" communities in Nanchang and Jiujiang in Fig. 3, the governance levels of the 5 "peasantto-citizen" communities in Nanchang are distributed in the intermediate and senior levels on the whole; even, the governance level of Xingfu Yayuan Community has reached the excellent level and is the highest among the 10 "peasant-to-citizen" communities. However, the governance levels of the 5 "peasant-to-citizen" communities in Jiujiang are distributed in the elementary and intermediate levels; only the governance level of Liansheng Community has reached the senior level. As a whole, there is a large space to improve the governance levels of "peasant-to-citizen" communities in Jiujiang.

According to the conditions reflected in Table 4 and Fig. 3, there are some differences in governance level of "peasant-to-citizen" communities in Nanchang and Jiujiang. The governance levels of the 5 "peasant-to-citizen" communities in Nanchang are higher than those in Jiujiang. Meanwhile, the great difference in the community governance levels within a region shows the difference in management among different "peasant-tocitizen" communities in a region. The reasons for the above-mentioned differences are from the social development, economic structure, humanistic environment, population policy and other aspects of cities. As the only national innovation-oriented city in Jiangxi province, Nanchang has many national-level industrial zones, which are the important cornerstones attracting the employment of migrant workers and can relatively guarantee both the employment rate and posts of migrant workers; this also can help to lay the material foundation for migrant workers to settle down here and indirectly facilitate the construction of "peasant-to-citizen" communities. Meanwhile, to support migrant workers to settle down in the city, Nanchang government also issued a series of supportive policies, which have largely raised the governance level of "peasant-tocitizen" community. As a fertile "land of fish and rice", Jiujiang has great advantages in its agricultural production; as a result, some peasants don't want to abandon agricultural production and work in cities is also their interim departure from their hometowns. The secondary industries in Jiujiang are dominated by the textile, printing and other light industries, whose post wages cannot meet migrant workers' life demands in the city, so the "peasant-to-citizen" process is affected in the area. The main reasons for the low governance level of "peasant-to-citizen" community in Jiujiang are the imperfect social security and unsound community management system; therefore, it is required to further improve the "peasant-to-citizen" community management structure and continuously enhance the governance level of "peasant-to-citizen" community.

5.Conclusion

Based on the interviews and investigations on 10 "peasant-to-citizen" communities in Nanchang and Jiujiang and the practical "peasant-to-citizen" conditions in Jiangsu, this paper comprehensively evaluated the governance level of "peasant-to-citizen" communities from the four dimensions, which are respectively community life, environment, management and customs, successively established 12 evaluation indexes, made a quantitative evaluation on the governance levels of investigation sample communities by using the GA-based projection pursuit model, and made the conclusion below.

Firstly, the application of the GA-based projection pursuit model in the comprehensive evaluation on the governance level of "peasant-to-citizen" community can effectively reflect the advantages and disadvantages in the governance levels of "peasant-to-citizen" communities in Nanchang and Jiujiang. It can be seen from the maximum projection values of the two cities, the governance level of "peasant-to-citizen" community in Nanchang is higher than that in Jiujiang and the difference in the community governance level is highly related to the practical conditions of development levels of new urbanization in the two cities. As the leading city of economic development in Jiangxi, Nanchang attracts migrant workers to live here because of its abundant employment opportunities. Meanwhile, with the government's policy guidance, the "peasant-to-citizen" governance has become more scientific and standardized. By contrast, due to the incomplete laws and policies and poor community supervision, the governance level of "peasant-tocitizen" community in Jiujiang is low and needs to be continuously improved in the next management so as to build the "peasant-to-citizen" community into a safe, comfortable and convenient livelihood project.

Secondly, the optimized projection direction of the GA-based projection pursuit model can not only reflect the degrees of influences of all secondary indexes on the comprehensive evaluation on the governance level of "peasant-to-citizen" community but also be dynamically regulated based on changes in practical conditions so that the evaluation result will be more scientific and effective. Even though Nanchang and Jiujiang are major cities for the construction of "peasant-to-citizen" community in Jiangsu province, the different economic development levels, industrial compositions and structures and humanistic environments of society lead to different focuses on the comprehensive evaluation indexes of governance level of "peasant-to-citizen" community. As for this, we can modify it by adjusting the weight coefficient of evaluation index so that the evaluation system will be more applicable to the practical conditions.

Finally, based on the actual result of research in this paper, the application of the GAbased projection pursuit model in the comprehensive evaluation on the governance level of "peasant-to-citizen" community is extremely effective. The method avoids the lack of systematic theory, calculating process disorder and other issues when some evaluation models are determining the index weight, effectively lowers the degree of influence of subjective factors in the evaluation process, meanwhile, can adjust evaluation indexes based on different regional conditions, and raises the scientificity and validity of the evaluation system.

Acknowledgements

Fund projects:China Postdoctoral Science Foundation Project (2016M592113); Jiangxi Postdoctoral Scientific Research Preference Funding Project (2016KY59); Special Project for Economic and Social Development in Jiangxi Province (15ZT42)

References

References

Chen Y., Liu T. (2015). Study on the Satisfaction of Residents in Concentrated Peasant Residential Areas Based on the Fuzzy Evaluation Method. Areal Research and Development, 36(6), 58-62. doi: 10.3969Zj.issn.1003-2363.2015.06.011

Ding Z.Q. (2015). Employment Problem of "Peasant-to-citizen" Residents in Urban Construction - Taking the New Area of Luoyang in Henan for Example. Journal of Henan University of Science and Technology (Social Science), 31(5), 14-19. doi: 10.15926Zj.cnki.hkdsk.2013.05.019

Geng J.H., Gao Q.S. (2007). Community Satisfaction Evaluation System Based on AHP and Factor Analysis. Journal of Systems and Management, 16(6), 673-677. doi: 10.3969Zj.issn.1005-2542.2007.06.016

Lu X.K. (2007). How to Manage the Suburban "Peasant-to-Citizen" Communities. Community Work, (5), 20-21.

Lu X.M., Lin W.M. (2015). Study on Land-lost Peasant Problem on the Background of New Urbanization Based on Game Theory. Taiwan Agricultural Research, 39(5), 39-42. doi: 10.16006Zj.cnki.twnt.2015.05.009

Ma G.Y., Chen H. (2014). Study on the Evaluation of Circular Agriculture Based on Projection Pursuit Model. Jiangsu Agricultural Sciences, 42(8), 437-440. doi: 10.3969Zj.issn.1002-1302.2014.08.156

National Bureau of Statistics of the People's Republic of China. (2014). Report on Supervision and Investigation of Nationwide Migrant Workers in 2014. from http:// www.stats.gov.cn/tjsj/zxfb/201504/t20150429_797821.html

Puello, J.J., Feliu T.S., Calvo-Manzano J.A. (2016). Una aproximación basada en metamodelado del área de proceso de Validación del CMMI: Un caso de estudio. RISTI - Revista Ibérica de Sistemas e Tecnologias de Informaçdo, 17, 26-40. doi: 10.17013/risti.17.26-40

Sá, F., Rocha, Á., & Cota, M. P. (2016). From the quality of traditional services to the quality of local e-Government online services: A literature review. Government Information Quarterly, 33(1), 149-160.

Sui H.X., Chen J.J. (2015). Study on the Cost Sharing Mechanism of Urbanization of Population Transferred from Agriculture in Chengdu on the Background of New Urbanization. Rural Economy, (2), 119-123. doi:

Wang Y.C. (2016). Study on Citizenization of Population Transferred from Agricultural from the View Angle of Inclusive Growth - Shandong-based Field Investigation. Reform and Opening, (1), 82-84. doi: 10.16653/j.cnki.32-1034/f.2016.01.031

Wei H.K., Chen X.Y. (2014). Calculation of Peasant-to-citizen Cost in Megalopolises of China - Taking Beijing for Example. Regional Economic Review, (4), 114-121. doi: 10.3969Zj.issn.1003-4919.2014.04.022

Wang G.Z., Xiao J. (2013). Study on Satisfaction of Floating Population Migration Based On Ahm Algorithm. Journal of Guangxi Normal University: Natural Science, 31(2), 7-12. doi: 0.16088 /j. issn.1001 -6600.2013.02.019

Xia Y.J., Zhu X.G. (2013). Study on Satisfaction Evaluation of Urban Passive Relocation Resident Community -Taking Nanjing for Example. Chinese Geographical Science, 33(8), 918-925. doi: 10.13249/j.cnki.sgs.2013.08.004

Xu T.T. (2008). Study on Satisfaction Evaluation Index System of Peasant-To-Citizen Apartments in Hangzhou. Economic Forum, 33(22), 33-43. doi: 10.3969/j. issn.1003-3580.2008.22.010

Xu R. (2010). Improvement of Organizational System of "Village-To-Community" Community and Problem Analysis - Taking Community A In Chengdu on The Background of Reform of Rural Land Property Rights System for Example. Journal of Yunnan Administration College, 12(6), 109-111. doi: 10.16273/j.cnki.531134/d.2010.06.044

Zhou Y.W., Liu J. (2015). Study on Regional Difference in Intensive Use Level of Cultivated Land in China - Panel Data Analysis Based on Projection Pursuit Model. Chinese Journal of Agricultural Resources and Regional Planning, 36(1), 22-30. doi: 10.7621/ajarrp.1005-9121.20150104