• Journal of Environmental Impact Assessment
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• v.31 no.3
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• pp.173-183
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• 2022

The purpose of this study is to explore the purpose of introducing the system and the possibility of development by comparing the period before and after the implementation of the Korean Important Agricultural Heritage System (KIAHS) using big data. In terms of perception related to Ulleungdo Island, keywords related to accessibility were derived as higher keywords before and after designation, and in particular, keywords such as various approaches and new ports could be found after designation. It can be seen that positive perception increased after the designation of KIAHS, and the perception of good increased particularly. In addition, the exact name of wild greens and keywords for volcanic island appeared in common, but it was confirmed that the influence increased in the results of the centrality analysis after the designation. In other words, it was found that the designation of KIAHS was helpful in preserving traditional knowledge and developing traditional agricultural culture using it.

• Journal of Radiation Protection and Research
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• v.47 no.2
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• pp.67-76
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• 2022

Background: We conducted a cross-sectional study of residents within and outside Fukushima Prefecture to clarify their perceptions of the need for smartphone applications (apps) for explaining exposure doses. The results will lead to more effective methods for identifying target groups for future app development by researchers and municipalities, which will promote residents' understanding of radiological situations. Materials and Methods: In November 2019, 400 people in Fukushima Prefecture and 400 people outside were surveyed via a web-based questionnaire. In addition to basic characteristics, survey items included concerns about radiation levels and intention to use a smartphone app to keep track of exposure. The analysis was conducted by stratifying responses in each region and then cross-tabulating responses to concerns about radiation levels and intention to use an app by demographic variables. The intention to use an app was analyzed by binomial logistic regression analysis. Text-mining analyses were conducted in KH Coder software. Results and Discussion: Outside Fukushima Prefecture, concerns about the medical exposure of women to radiation exceeded 30%. Within the prefecture, the medical exposure of women, purchasing food products, and consumption of own-grown food were the main concerns. Within the prefecture, having children under the age of 18, the experience of measurement, and having experience of evacuation were significantly related to the intention to use an app. Conclusion: Regional and individual differences were evident. Since respondents differ, it is necessary to develop and promote app use in accordance with their needs and with phases of reconstruction. We expect that a suitable app will not only collect data but also connect local service providers and residents, while protecting personal information.

• Smart Media Journal
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• v.11 no.8
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• pp.9-20
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• 2022

With the rise of the metaverse industry worldwide, relevant national strategies and nurturing systems have been prepared in Korea. As the complexity of policies increases, the importance of establishing data-based policymkaing is growing, and studies diagnosing national R&D trends in the metaverse field are still lacking. Therefore, this paper collected NTIS national R&D information for 9,651 R&D projects promoted from 2002 to 2020. And this study looked at the current status and identified major topics based on the topic modeling, and considered time-series changes in the topics. Eleven major topics of R&D tasks in the metaverse field were derived, hot topics were service/content/platform development and medical/surgical fields of application fields, and cold topics were urban/environment/spatial information fields. Strategic R&D Management, metaverse-related laws, and institutional studies were proposed as policy directions.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.29-41
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• 2022

Alien species cause problems in various ecosystems, reduce biodiversity, and destroy ecosystems. Due to these problems, the problem of a management plan is increasing, and it is difficult to accurately identify each individual and calculate the number of individuals, especially when researching alien turtle species such as GPS and PIT based on capture. this study intends to conduct an individual recognition study using a UAV. Recently, UAVs can take various sensor-based photos and easily obtain high-definition image data at low altitudes. Therefore, based on previous studies, this study investigated five variables to be considered in UAV flights and produced a test paper using them. OCR was used to monitor the displayed turtles using the manufactured test paper, and this confirmed the recognition rate. As a result, the use of yellow numbers showed the highest recognition rate. In addition, the minimum threat distance was confirmed to be 3 to 6m, and turtles with a shell size of 6 to 8cm were also identified during the flight. Therefore, we tried to propose an object recognition methodology for turtle display text using OCR, and it is expected to be used as a new turtle monitoring technique.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.1-10
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• 2022

This study examined the relationship between depression, anxiety, stress, and adaptation to college life of international students living in South Korea during the COVID-19 pandemic and the factors affecting the adaptation to college life. This study was carried out between December 3, 2021, to January 25, 2022, on international students living in South Korea. The questionnaires were composed of self-reported questionnaires, and the survey URL was sent as text messages to international students who understood the purpose and rationale of this study and consented to participate in the survey. The data were analyzed using SPSS WIN 22.0, and t-test, ANOVA, Pearson's Correlation Coefficient, and hierarchical regression were performed. As a result of the study, the average score of the study subjects was 8.44 points for depression, 8.28 points for anxiety, and 9. 28 points for stress. factors with significant differences in adaptation to college life according to general characteristics were living means and smoking. The relationship between the main variables, it was significant with depression (r=-.785, p<.001), anxiety (r=-.593, p<.001), and stress (r=-.726, p<.001). There was one negative correlation. It was found that the higher the depression, anxiety, and stress, the lower the college life adaptation. Lastly, depression (β=-.666, p<.001) was the factor affecting foreign students' adaptation to college life, and the explanatory power was 62%. Therefore, for international students to adapt to college life, it is necessary to establish an institutional strategy to detect depression, a negative psychological emotion, at an early stage and to systematically manage it. Also, it is necessary to find an intervention plan to relieve depression that can be applied in social isolation situations due to the spread of infectious diseases. Research confirming the intervention effect should be upgraded.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.149-159
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• 2021

This study wanted to analyze the types of recognition of messages expressed in clothing for women in their 20s who wear a lot of clothing and fashion products with text. It was intended to provide basic data necessary for the production of typography clothing and fashion products by considering the subjective evaluation of how women in their 20s type the characters expressed in fashion and the characteristics of each type. This study was conducted with the Q method, and the QUANL pc program was used for analysis. Type I thought that letters were a design element and fashion, and the characters expressed in clothes were recognized as images. Type 2 thought it was important that the characters expressed in the clothing were recognized as messages, and that the characters had social messages and period reflections. Type 3 preferred that letters be combined with casual clothes and valued the formability of the characters. Type 4 preferred characters to represent brands and liked to be placed in large positions. In the future, it is thought that additional research by various age groups and genders and detailed research should be conducted to identify differences in font, color, and sentence length.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.131-142
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• 2023

In this paper, we propose a new station selection algorithm to solve the illegal parking problem of shared electric scooters and improve the service quality. Recently, as a solution to the urban transportation problem, shared electric scooters are attracting attention as the first and last mile means between public transportation and final destinations. As a result, the shared electric scooter market grew rapidly, problems caused by electric scooters are becoming serious. Therefore, in this study, text data are collected to understand the nature of the problem, and the problems related to shared scooters are viewed from the perspective of pedestrians and users in 'LDA Topic Modeling', and a station extension algorithm is based on this. Some parking lots have already been installed, but the existing parking lot location is different from the actual area of tow. Therefore, in this study, we propose an algorithm that can install stations at high actual tow density using mixed clustering technology using K-means after primary clustering by DBSCAN, reflecting the 'current state of electric scooter tow in Seoul'.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.89-97
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• 2023

In this paper, we propose factors that make log analysis difficult and design technique for detecting various objects embedded in the logs which helps in the subsequent analysis. In today's IT systems, logs have become a critical source data for many advanced AI analysis techniques. Although logs contain wealth of useful information, it is difficult to directly apply techniques since logs are semi-structured by nature. The factors that interfere with log analysis are various objects such as file path, identifiers, JSON documents, etc. We have designed a BERT-based object pattern recognition algorithm for these objects and performed object identification. Object pattern recognition algorithms are based on object definition, GROK pattern, and regular expression. We find that simple pattern matchings based on known patterns and regular expressions are ineffective. The results show significantly better accuracy than using only the patterns and regular expressions. In addition, in the case of the BERT model, the accuracy of classifying objects reached as high as 99%.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.175-182
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• 2022

In our daily life, we come across different types of information, for example in the format of multimedia and text. We all need different types of information for our common routines as watching/reading the news, listening to the radio, and watching different types of videos. However, sometimes we could run into problems when a certain type of information is required. For example, someone is listening to the radio and wants to listen to jazz, and unfortunately, all the radio channels play pop music mixed with advertisements. The listener gets stuck with pop music and gives up searching for jazz. So, the above example can be solved with an automatic audio classification system. Deep Learning (DL) models could make human life easy by using audio classifications, but it is expensive and difficult to deploy such models at edge devices like nano BLE sense raspberry pi, because these models require huge computational power like graphics processing unit (G.P.U), to solve the problem, we proposed DL model. In our proposed work, we had gone for a low complexity model for Audio Event Detection (AED), we extracted Mel-spectrograms of dimension 128×431×1 from audio signals and applied normalization. A total of 3 data augmentation methods were applied as follows: frequency masking, time masking, and mixup. In addition, we designed Convolutional Neural Network (CNN) with spatial dropout, batch normalization, and separable 2D inspired by VGGnet [1]. In addition, we reduced the model size by using model quantization of float16 to the trained model. Experiments were conducted on the updated dataset provided by the Detection and Classification of Acoustic Events and Scenes (DCASE) 2020 challenge. We confirm that our model achieved a val_loss of 0.33 and an accuracy of 90.34% within the 132.50KB model size.

• Journal of Fashion Business
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• v.26 no.4
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• pp.52-63
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• 2022

As live commerce, mobile sales platforms based on real-time content and text are drawing attention as a new marketing channel. In particular, the fashion industry also using live commerce as a new fashion distribution channel, requiring marketing strategies to utilize it efficiently. This study attempted to verify the effect of information source, sales promotion, and impulse buying tendency characteristics on fashion live commerce purchase intention. The experimental design of this study was 2(characteristics of information source: expertise vs attractiveness) × 2(sales promotion type: value-added vs price discount) × 2(impulse buying tendency: high vs low) three-way mixed analysis of variance(ANOVA). A convenience sampling of 264 women in their 20s and 50s living in Seoul and the Gyeonggi area who had purchased products through Live Commerce was conducted. For the final analysis, 240 questionnaires were used. Data were analyzed by the SPSS 26 program and three-way ANOVA. Simple main effects analysis was conducted. The results of this study follow. First, there were statistically significant differences in purchase intention according to consumers' impulse buying tendencies and sales promotions. Second, information source and sales promotion showed statistically significant interaction effects on purchase intention. Lastly, information source, sales promotion, and impulse buying tendency showed significant three-way interaction effects on fashion live commerce purchase intention. Therefore, conducting appropriate marketing analysis can result in positive attitudes regarding live commerce products and substantive increases in sales.