• Iberoamérica
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• v.13 no.1
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• pp.123-152
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• 2011

The long standing people's culture of Latin America based on social solidarity of the communities makes the political relations between the leader and the people very different from them of the european societies based on the representative democracy. At any rate, the main stream of the Populist Discourses sees the real populist political processes with the pejorative senses attributing the demagogue style of the leaders. In these sense, it is very important to re-consider the populism discourses of Ernesto Laclau who thinks that the populism is a way of interpreting the emergence of the people to establish the social demands in the context of populist real politics. According to Laclau, "the populism seeks for the radical reconfiguration of the revolt of the 'Status Quo' and new order". This work will confirm if this interpretation of Laclau can be applied to Peronist political regime. Meanwhile the first group of the orthodox line of the discourses on populism including Gino Germani shows that the populism is a political movement based on the manipulation and demagogue by the charismatic leader of the irrational mass during the period in transition after the crises of the traditional oligarchy in Latin America. And another line of the main stream of discourses on populism including Cardoso and O'Donnell says that the populism is a political phenomena in a period of transition towards the modernization and the national development by means of the industrialization through the substitution of the imports and the alliance between the classes after the 1930's. But these principal interpretations on populism disregards that in Argentina many urban poor working class people had lived under the racist, unequal painful social relations due to the underestimation and the discrimination by the upper and the middle class with many intellectuals. But Peronism had considered them as the new social subjects with human dignities. And so we have to rethink the clientelism also with another meanings. In this sense, the theories of Ernesto Laclau on populism is very helpful to illuminate the sensitive and ambiguous meanings of Peronism. Especially Peronism makes the urban working class maintain their life styles more tended to them of the traditional communities and go towards the anti-Status Quo. That is a key of success of Peronism not only that time but until these days. And so this study will show that it is the most important thing that Peronist regime had made the emergence of the 'people' in the meaning of advancing the democracy in Argentina.

• Korean Journal of Social Welfare Studies
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• v.42 no.2
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• pp.467-491
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• 2011

The purpose of this study is to examine relationship between social strains such as status strains and relational strains and adolescent suicidality by gender. As method, a self-report survey was completed by students (n = 819) from 3 middle schools in Seodaemun area, Seoul, Korea. Logistic regression analyses were conducted to identify factors associated with adolescent suicidality, t-test analyses were used to verify gender difference. Results show that male adolescents are more likely to experience abuse from their father, and school violence related to relational strains than female. Differences were found in strains for males and females contributing to suicidality; male are responsive to economic status, a dimension of status strain, whereas female are reactive to non-physical abuse from father, a type of relational strains. Non-physical school violence was appeared to be a significant factor influencing suicidality for both genders. Based on these findings, research draws implications for social work interventions. First, different approaches by gender are needed to prevent adolescent suicide in consideration of the tendency that men are status-oriented and women are relationship-oriented. Second, it is suggested to hire full-time school social worker to provide consistent social service for students. Third, intensive effort is necessary to reduce non-physical school violence.

• Korean Journal of Social Welfare Studies
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• v.40 no.2
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• pp.5-32
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• 2009

The purpose of this study is analyze the pattern and factors affecting the shelter exit and the patterns of homeless women in Korea. For this study, survey data were collected from 139 sheltered homeless women in Seoul in May of 2007. And respondent's exit time and exit pattern from the shelter were investigated through administration data of shelter in December of 2008. Life table analysis, Cox-proportional hazard analysis and competing risk survival analysis were employed in order to analyze data. The major findings were as follows. First, life table analysis shows that the exit ratio of homeless women started to fall sharply in 24 months from entry into shelter. Second, subjective health status, ratio of the homeless in social network and shelter entry with children affected the likelihood of shelter exit of homeless women. Third, age, subjective health status, depression and shelter entry with children affected the likelihood of positive exit. And ratio of the homeless in social network affected the likelihood of negative exit. Based on these findings, this study implied the introduction of case management service concerning individual shelter exit plan and policy for residential stability of homeless women.

• Smart Media Journal
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• v.11 no.11
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• pp.17-24
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• 2022

With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.149-158
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• 2023

As data utilization is becoming more important recently, the importance of data centers is also increasing. However, the data center is a problem in terms of environment and economy because it is a massive power-consuming facility that runs 24 hours a day. Recently, studies using deep learning techniques to reduce power used in data centers or servers or predict traffic have been conducted from various perspectives. However, the amount of traffic data processed by the server is anomalous, which makes it difficult to manage the server. In addition, many studies on dynamic server management techniques are still required. Therefore, in this paper, we propose a dynamic server management technique based on Long-Term Short Memory (LSTM), which is robust to time series data prediction. The proposed model allows servers to be managed more reliably and efficiently in the field environment than before, and reduces power used by servers more effectively. For verification of the proposed model, we collect transmission and reception traffic data from six of Wikipedia's data centers, and then analyze and experiment with statistical-based analysis on the relationship of each traffic data. Experimental results show that the proposed model is helpful for reliably and efficiently running servers.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1261-1270
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• 2022

The purpose of this study is to collect and analyze information related to water leaks that cannot be easily accessed, and utilized by using the news search results that people can easily access. We applied a web crawling technique for extracting big data news on water leakage accidents in the water supply system and presented an algorithm in a procedural way to obtain accurate leak accident news. In addition, a data analysis technique suitable for water leakage accident information analysis was developed so that additional information such as the date and time of occurrence, cause of occurrence, location of occurrence, damaged facilities, damage effect. The primary goal of value extraction through big data-based leak analysis proposed in this study is to extract a meaningful value through comparison with the existing waterworks statistical results. In addition, the proposed method can be used to effectively respond to consumers or determine the service level of water supply networks. In other words, the presentation of such analysis results suggests the need to inform the public of information such as accidents a little more, and can be used in conjunction to prepare a radio wave and response system that can quickly respond in case of an accident.

• Knowledge Management Research
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• v.24 no.1
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• pp.73-97
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• 2023

Recently, the MyData market has been growing as the importance of data and issues related to personal information protection have drawn much attention together. MyData refers to the concept of guaranteeing an individual's right to personal information and providing and utilizing one's data according to individual consent. MyData service providers can combine and analyze customer information to provide personalized services. In the early days, the MyData business was activated mainly by private companies and the financial industry, but recently, public institutions are also actively taking advantage of MyData. Meanwhile, the importance of an individual's intention to provide MyData for the success of MyData businesses continues to increase, but research related to this is lacking. Moreover, existing studies have been mainly conducted on individual benefits of MyData; there are not enough studies in which both public benefit and perceived risk factors are considered at the same time. In this regard, this study intends to derive factors affecting the intention to provide MyData based on the privacy calculus model, examine their influencing mechanism, and further verify the moderating effects of individual capabilities and institutional type. This study can find academic significance in that it expanded and demonstrated the privacy calculus model in the context of MyData providing intention. In addition, the results of this study are expected to offer practical guidelines for developing and managing new services in MyData businesses.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.171-190
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• 2022

This study aims to examine the current status of managing elementary school libraries in Busan and suggest the ways to improve it with the viewpoint of 'the five laws of library science'. The scope of study was set as the elementary school libraries in Busan, and the operation status of 304 elementary school libraries was analyzed. And for in-depth investigation, D elementary school library was examined as a case. The operation status of elementary school libraries in Busan was analyzed with the analysis elements; existence of school library, placement of teacher librarian, library collection, annual use, budget, and library seats for 6 years from 2016 to 2021. As a result, especially the placement rate of full-time teacher librarians was only 10.5%, indicating that the problem of manpower shortage was serious. As case study, the current state of managing D elementary school library was deeply investigated with perspectives of the first law and the third law of library science among Ranganathan's five laws of library science. With the first law, the investigation was divided into the aspects of open-shelf system, library location, library hours, furniture, and staff. With the third law, the investigation was done as the aspects of shelf arrangement, catalog, extended service, book selection. Especially, books with more than 50 copies for the program of reading one book each semester accounted for 4.8% of the total collection, showing the problem of unbalanced collection. As the result of this study, 'expanding the placement of teacher librarians', 'making better reading environment through remodeling', and 'balanced collection development' were suggested as the ways of developing school libraries.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.15-22
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• 2022

In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.116-126
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• 2022

Many studies using trademark information have suggested that trademark information is good data to monitor business trends. This study intends to analyze the trend change before and after COVID-19 using trademark information. Changes before and after COVID-19 were analyzed by using goods & service classification, similar group code, and designated goods information as trademark information. Among the trademark information, it was statistically significant that the change in trends before and after COVID-19 using designated goods names. To verify the results, the changes in keywords using designated goods names before and after COVID-19 were compared with the frequency of keywords in Google Trends. Among the top 8 keywords extracted from designated goods names, the frequency of Google trend searches for 'online, antibacterial, prevention of epidemics, meal kit, virtual' is on the rise, and 'mask, droplet' is not on the rise, but it increased rapidly at the time of COVID-19, and even after COVID-19, it showed a higher level than before. The frequency of 'unmanned' does not differ much before and after COVID-19, but it has been maintained at a consistently high level, and related businesses have been active since before COVID-19, and it can be interpreted as a keyword with high public interest. This study has academic achievements in that it specifically identified information that could be used in business trends by using three types of trademark information.