• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.300-309
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• 2020

This study identified the types and dimensions of faculty-student interaction (FSI). A narrative methodology was applied within the qualitative research paradigm. Data was collected using individual in-depth interviews involving 10 students who had experiences of faculty-student interaction more than 6 times over the prior 6 semesters. Data was analyzed according to actors' perspectives, the motivation of actions, and actions toward goal achievement. Three major types of faculty-student interactions emerged from our analysis. First, the initiative interaction type reflects active characteristics of the narrator within FSI and is goal achievement-oriented. Second, the stereotyped interaction was characterized as a unified reaction to the FSI and not significantly related to self-development. Lastly, the reciprocal interaction reflected characteristics of narrators who had potential and flexibility for self-development in the circumstances involving support from professors. The results of this study indicate that faculty-student interaction does not represent the best way to support students for their successful school lives. Faculty needs professionality and sensitivity for student teaching, and students must exhibit curiosity and activeness in developing their knowledge. Positive outcomes from the FSI will be expected in supportive school environments.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.19-26
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• 2021

Cultural assets excavated in historical areas have their own characteristics based on the background of the times, and it can be seen that their patterns and characteristics change little by little according to the history and the flow of the spreading area. Cultural properties excavated in some areas represent the culture of the time and some maintain their intact appearance, but most of them are damaged/lost or divided into parts, and many experts are mobilized to research the composition and repair the damaged parts. The purpose of this research is to learn patterns and characteristics of the past through artificial intelligence neural networks for such restoration research, and to restore the lost parts of the excavated cultural assets based on Generative Adversarial Network(GAN)[1]. The research is a process in which the rest of the damaged/lost parts are restored based on some of the cultural assets excavated based on the GAN. To recover some parts of dammed of cultural asset, through training with the 2D image of a complete cultural asset. This research is focused on how much recovered not only damaged parts but also reproduce colors and materials. Finally, through adopted this trained neural network to real damaged cultural, confirmed area of recovered area and limitation.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.12-25
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• 2021

Land cover maps are used in various fields in urban expansion and development. This study analyzed the amount of land cover change over time using multi-sensor information, focusing on the waterfront area of the Taehwa River. In order to apply high-accuracy aerial hyperspectral images, patterns with Field-spectral were reviewed and compared with time series Digital map. The hyperspectral image was set as 13 land cover grades, and the time series digital map was classified into 7 and the waterfront area was classified into 5-6 grades and analyzed. As a result of analysis of the change in land cover of the digital map from the 1990s to 2010, it was found that forest areas were rapidly decreasing and Farmland and grassland were becoming urban. As for the land cover change(2010~2019) in the waterfront area(set 500m) analyzed through hyperspectral images, it was found that Farmland(1.4㎢), Forest(1.0㎢), and grassland (0.8㎢) were converted into urbanized and dried areas, and urbanization was accelerating around the Taehwa River waterfront. Recently, a lot of research has been conducted on the production of land cover maps using high-precision satellite images and aerial hyperspectral images, so it is expected that more detailed and precise land cover maps can be produced and utilized.

• Korean Journal of Environment and Ecology
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• v.36 no.2
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• pp.202-216
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• 2022

Animals exhibit certain behaviors and movement patterns as they react to their internal needs, external stimuli, and surrounding environments. They have a bounded range in which they mostly spend their time, and it is referred to as a home range. Based on the fact that the home range is a critical area for the survival and preservation of species, there has been a growing body of research on developing more precise home range estimation methods to use the estimated ranges as a ground for establishing an effective conservation policy since the early 1940s. Recent rapid advancements in telemetry technology that resulted in the presence of autocorrelation between locations with short time intervals revealed the limitations of the existing estimators. Many novel estimators have been developed to compensate for it by incorporating autocorrelation in calculating home ranges. However, studies on the animal home range are still in their early stage in Korea, and newly developed methodologies have not yet been adopted. Therefore, this study aims to introduce the foreign home range estimation methods and foster domestic research activities on home ranges. Firstly, we compared and contemplated seven estimators by categorizing them into geometrical and statistical methodologies and then divided them into estimators that assume independent observations and those that consider autocorrelation in each category. After that, the home ranges of black-tailed gulls (Larus crassirostris) were calculated using GPS tracking data for the month of June and derived home range estimators by applying the methodology introduced in this study. We analyzed and compared the results to discuss the strengths and weaknesses of each method. Lastly, we proposed a guideline that can help researchers choose an appropriate estimator for home range calculation based on the animal location data characteristics and analysis purpose.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.45-54
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• 2021

Jeong Sun-Ah built up her performance career for twenty years with bold and energetic acting and solidified her status as a leading actress of Korean musical since her debut. To benefit from the value of her experience this study performed an in-depth interview with her, applying the Theory of "Projection" and "Back-projection", which are the psychological principles of acting, and derived "acting(entering the roles)" and "de-acting(leaving the roles)" techniques. As result, Her acting mechanism involved emptying her ego, embodying a persona by projecting the role created by intensive exploration of materials like previous performance, film of the same title, original novel, and script, and then getting the ego back by back-projecting through dynamic activities such as overseas travel and dance. She pre-studied the roles by physically visiting sites that are important to the characters. She was unique in that she pursued a difference by changing vocal trainers for each musical production and undertook more intense physical training than vocal practice to achieve powerful singing performance. In most of her works (75%), she suffered from aftereffects such as depression, narcissism, hysteria, and insomnia due to disorder caused by breaking away from the roles. However, she relied on self-help and alternatives are needed in the future such as reinforcement of expert counselling. Jeong Sun-Ah appeared on an average of 1.6 productions per year, practiced for an average of 1.7 months, and performed for an average of 3.9 months with an average of 100 days of break between productions. Her performance record from this research demonstrates her constant preparation and passion, as well as the know-how of reserving and distributing energy. So, it has a valuable implications for acting education and self-management of actors and actress.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.1
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• pp.37-43
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• 2022

Patients tend to return to normal pronunciation patterns after fitting new dentures. However, for some patients, it takes a long time to adapt the new complete denture. In this case, the patient came to the hospital at the address of wanting to remake dentures due to wear and tear. After diagnosis through clinical and radiological examination, the maxillary complete denture and mandibular removable partial denture were remade. The patient complained whistling /s/ sound at the first check-up after placement of the new denture. The anterior palatal area of polished surface of the new maxillary complete denture was concave comparing to old denture, and this was the cause of the whistling /s/ sound. A tissue conditioning material was applied to the maxillary complete denture and patient made /s/ sound. The tissue conditioning material was replaced with self-curing type denture base resin, and the patient was immediately satisfied with clear /s/ sound. As an objective assessment, palatogram and speech analytics software was applied. In this case, a patient who received denture treatment complaining of difficulty in pronunciation underwent immediate denture repair, which resulted in patient satisfaction and improved pronunciation through objective evaluation.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.523-533
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• 2022

This paper presents a two-stage spatio-spectral fusion method (2SSFM) based on area-to-point regression kriging (ATPRK) to enhance spatial and spectral resolutions using multi-sensor satellite images with complementary spatial and spectral resolutions. 2SSFM combines ATPRK and random forest regression to predict spectral bands at high spatial resolution from multi-sensor satellite images. In the first stage, ATPRK-based spatial down scaling is performed to reduce the differences in spatial resolution between multi-sensor satellite images. In the second stage, regression modeling using random forest is then applied to quantify the relationship of spectral bands between multi-sensor satellite images. The prediction performance of 2SSFM was evaluated through a case study of the generation of red-edge and short-wave infrared bands. The red-edge and short-wave infrared bands of PlanetScope images were predicted from Sentinel-2 images using 2SSFM. From the case study, 2SSFM could generate red-edge and short-wave infrared bands with improved spatial resolution and similar spectral patterns to the actual spectral bands, which confirms the feasibility of 2SSFM for the generation of spectral bands not provided in high spatial resolution satellite images. Thus, 2SSFM can be applied to generate various spectral indices using the predicted spectral bands that are actually unavailable but effective for environmental monitoring.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.87-94
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• 2022

Recently, with the development of information and communication infrastructure, the number of Internet access devices is rapidly increasing. Smartphones, laptops, computers, and even IoT devices are receiving information and communication services through Internet access. Since most of the device operating environment consists of web (WEB), it is vulnerable to web cyber attacks using web shells. When the web shell is uploaded to the web server, it is confirmed that the attack frequency is high because the control of the web server can be easily performed. As the damage caused by the web shell occurs a lot, each company is responding to attacks with various security devices such as intrusion prevention systems, firewalls, and web firewalls. In this case, it is difficult to detect, and in order to prevent and cope with web shell attacks due to these characteristics, it is difficult to respond only with the existing system and security software. Therefore, it is an automated defense system through the collection and analysis of web shells based on artificial intelligence machine learning that can cope with new cyber attacks such as detecting unknown web shells in advance by using artificial intelligence machine learning and deep learning techniques in existing security software. We would like to propose about. The machine learning-based web shell defense system model proposed in this paper quickly collects, analyzes, and detects malicious web shells, one of the cyberattacks on the web environment. I think it will be very helpful in designing and building a security system.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.2
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• pp.96-109
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• 2021

Since terrestrial input plays a major role in coastal primary production, an understanding of land-ocean coupling (LOC) is key to understand coastal ecological changes. In this study, the LOC has been classified into three stages (i.e., the baseflow, plume event and residual flow). In order to characterize its pattern in Nakdong River estuary, multi-platform data were obtained from remote sensing (geostationary ocean color image (GOCI)), in-situ measurement (marine environment information system (MEIS)), on-site measurement (discharge data and meteorological data). The MEIS data were grouped into three stages of LOC using principal component analysis (PCA), and the LOC (2013 ~ 2018) was examined at each stage using multi-platform data. In the Nakdong River estuary, the maximum value of chlorophyll-a (chl-a) was unexpectedly appeared during the plume event. It is assumed that there was no significant increase in turbidity, expected during the typical plume event, together with the weak flushing effect, caused the enhanced phytoplankton growth. Compared with other estuaries, LOC is common in estuaries affected by freshwater inflow, but LOC has different pattern depending on the size of the plume. While estuaries that form small plumes of about 10 km (low freshwater discharge and weak flushing effect) observed high chl-a in the plume event because the phytoplankton can response to the increased nutrient more rapidly. estuaries that form large plumes of more than 100 km est (high freshwater discharge and strong flushing effect) follow the typical LOC pattern conceptualized in this study (high chl-a in the residual flow).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.273-280
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• 2021

The purpose of this study was to identify groups depending on the four years of changing trajectories in self-efficacy and its relationship with life satisfaction and interpersonal competence of adults with disabilities who were aged above 25. The 1st to 4th year of the second wave from Panel Survey of Employment for the Disabled (PSED) was used to identify the groups and explore their relationship with life satisfaction and interpersonal competence through growth mixture modeling. The results identified three latent classes according to changing trajectories in self-efficacy: a 'high level-increasing group', an 'average level-increasing group', and a 'low level-stable group'. These three groups showed different characteristics in life satisfaction and interpersonal competence. For example, life satisfaction for groups decreased from the 'high level-increasing group' to the 'low level-stable group' and interpersonal competence increased in both 'high level-increasing group' and 'average level-increasing group', whereas it was stabilized in the 'low level-stable group'. These findings suggest that the life satisfaction and interpersonal competence of adults with disabilities are associated with their self-efficacy.