• Korean Journal of Child Studies
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• v.37 no.2
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• pp.169-187
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• 2016

Objective: This study aimed to identify profiles based on early childhood and elementary school teachers' goal orientations and to examine differences in teacher efficacy, psychological wellbeing, and job satisfaction among these profile groups. Methods: Data were collected through a teacher questionnaire. The teacher goal-orientation scale consisted of six sub-dimensions: growth, leisure, wealth, relationship, promotion, and social contribution. Data were analyzed using latent profile analyses. Results: Latent profile analyses revealed three distinct profile groups: one group characterized by higher scores across all six dimensions (balanced-goal-orientation group); another characterized by lower scores on all six dimensions, with a relatively higher score on the relationship dimension (relationship-goal-oriented group); another one characterized by lower scores on all dimensions except the leisure goal (leisure-goal-oriented group). MANOVA showed that the balanced-goalorientation group was significantly higher in total years of teaching, educational attainment, and age, compared to the leisure-goal-oriented group. In regression analyses, when controlling for educational attainment, teacher types (kindergarten vs. elementary school) did not significantly predict each of the dummy-coded profile groups (0 = no, 1 = yes). When taking into account teachers' age and educational attainment, belonging to the balanced-goal-orientation group was consistently associated with higher levels of teacher efficacy, job satisfaction, and psychological well-being, whereas the opposite pattern was observed in leisure-goal-oriented group. Conclusion: These findings imply that it is crucial to help pre- and in-service kindergarten and elementary school teachers foster a balance between different types of goals, which would ultimately strengthen and stabilize the supply of a teaching force and the provision of a better education.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.1
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• pp.56-70
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• 2020

This study identifies the impact of social network service (SNS) on the spatial characteristics of retail stores locations in the hyper-connected society, which have been closely related to the everyday lives of urban residents. In particular, we focus on the changes in the spatial distribution of restaurants since the information retrieval process was added to the decision-making process of a consumer's restaurant selection. Empirically, we analyze restaurants in Seoul, Korea since the smart-phone was introduced. By applying the kernel density estimation and Moran's I index, we examine the changes in the spatial distribution pattern of restaurants during the last ten years for running, newly-open and closed restaurants as well as SNS popular ones. Finally, we develop a spatial regression model to identify geographic features affecting their locations. As the results, we identified geographical variables and online factors that influence the location of restaurants. The results of this study could provide important groundwork for food and beverage location planning and policy formulation.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.657-674
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• 2012

This paper presents the effect of spatially-distributed rainfall on both rainfall-sediment-runoff and erosion or deposition in the experimental Cheoncheon catchment: upstream of Yongdam dam basin. The rainfall fields were generated by three rainfall interpolation techniques (Thiessen polygon: TP, Inverse Distance Weighting: IDW, Kriging) based only on ground gauges and two radar rainfall synthetic techniques (Gauge-Radar ratio: GR, Conditional Merging: CM). Each rainfall field was then assessed in terms of spatial feature and quantity and also used for rainfall-sediment-runoff and erosion-deposition simulation due to the spatial difference of rainfall fields. The results showed that all the interpolation methods based on ground gauges provided very similar hydrologic responses in spite of different spatial pattern of erosion and deposition while raw radar and GR rainfall fields led to underestimated and overestimated simulation results, respectively. The CM technique was acceptable to improve the accuracy of raw radar rainfall for hydrologic simulation even though it is more time consuming to generate spatially-distributed rainfall.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.305-321
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• 2004

With the advent of the digital broadcasting, the audiences can access a large number of TV programs and their information through the multiple channels on various media devices. The access to a large number of TV programs can support a user for many chances with which he/she can sort and select the best one of them. However, the information overload on the user inevitably requires much effort with a lot of patience for finding his/her favorite programs. Therefore, it is useful to provide the persona1ized broadcasting service which assists the user to automatically find his/her favorite programs. As the growing requirements of the TV personalization, we introduce our automatic user preference learning algorithm which 1) analyzes a user's usage history on TV program contents: 2) extracts the user's watching pattern depending on a specific time and day and shows our automatic TV program recommendation system using MPEG-7 MDS (Multimedia Description Scheme: ISO/IEC 15938-5) and 3) automatically calculates the user's preference. For our experimental results, we have used TV audiences' watching history with the ages, genders and viewing times obtained from AC Nielson Korea. From our experimental results, we observed that our proposed algorithm of the automatic user preference learning algorithm based on the Bayesian network can effectively learn the user's preferences accordingly during the course of TV watching periods.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.244-254
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• 2009

This paper describes a remote system to monitor the circadian behavioral patterns of elders who live alone. The proposed system was designed and implemented to provide more conveniently and reliably the required functionalities of a remote monitoring system for elders based on the development of first phase prototype[2]. The developed system is composed of an in-house sensing system and a server system. The in-house sensing system is a set of wireless sensor nodes which have pyroelectric infrared (PIR) sensor to detect a motion of elder. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to caregivers (friends, family and social workers) for more cost effective intelligent care service. The improved second phase system can provide 'automatic diagnosis', 'going out detection', and enhanced user interface functionalities. We have evaluated the first and second phase monitoring systems from real field experiments of 3/4 months continuous operation with installation of 9/15 elders' houses, respectively. The experimental results show the promising possibilities to estimate the behavioral patterns and the current status of elder even though the simplicity of sensing capability.

• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.59-66
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• 2021

In this paper, an improved integrated security control procedure is newly proposed by applying artificial intelligence technology to integrated security control and unifying the existing security control and AI security control response procedures. Current cyber security control is highly dependent on the level of human ability. In other words, it is practically unreasonable to analyze various logs generated by people from different types of equipment and analyze and process all of the security events that are rapidly increasing. And, the signature-based security equipment that detects by matching a string and a pattern has insufficient functions to accurately detect advanced and advanced cyberattacks such as APT (Advanced Persistent Threat). As one way to solve these pending problems, the artificial intelligence technology of supervised and unsupervised learning is applied to the detection and analysis of cyber attacks, and through this, the analysis of logs and events that occur innumerable times is automated and intelligent through this. The level of response has been raised in the overall aspect by making it possible to predict and block the continuous occurrence of cyberattacks. And after applying AI security control technology, an improved integrated security control service model was newly proposed by integrating and solving the problem of overlapping detection of AI and SIEM into a unified breach response process(procedure).

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.314-323
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• 2021

The purpose of this study is to analyze the status of medical service use of foreigners living in Korea by their nationality and types of national health insurance. As of 2018, 1,058,886 people were extracted from the qualification DB, excluding people whose insurance premium is missing. The data analysis showed that nearly 78% of foreigners with national health insurance used medical services and the countries with the largest number of users were China, Vietnam, and the United States. The total cost of treatment per capita was highest in the United States regardless of hospitalization and outpatient. The number of medical treatments per person, and the medical expenses of outpatients & inpatients services were highest among the regionally-insured and the length of stay per person was highest among the workers' dependents. Lastly, it was found that Chinese and regionally-insured received much more benefits than other groups compared to the premium they pay. After July 2019, foreign nationals residing in Korea for six months or longer are obligated to enroll in the national health insurance program. Since the latest data was in 2018, the result did not properly reflect the current situation, but it is meaningful that it made basic data for future comparative analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.1
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• pp.213-221
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• 2014

Since 2005, when "The Mobility Enhancement for the Mobility Impaired Act" was enacted, special transport systems(SPS) has been introduced by each responsible local entity. For its efficient operations and service enhancements, a clear understanding of travel patterns of SPS users is required. Yet we currently have a very limited understanding about them due to a lack of necessary data. This study represents an attempt to provide a better understanding of SPS user's travel patterns with the data generated by Gyeongsangnam-do SPS Call Center. The data include the number, time and day of calls, origins and destinations of callers, types of callers' impairement etc. The data thus allow one to analyze users' travel patterns, including area-wide O-D patterns. There were a number of interesting findings. For example, wheelchair users are only about 42% and the trips are made mostly on non-peak daytime periods. The results are expected to provide a helpful information not just for Center's SPS operations, but for other local entities that are interested in developing similar call centers as well. By refining the SPS system, periodic patterns of callers could be identified in the future.

• Journal of Animal Science and Technology
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• v.62 no.1
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• pp.64-73
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• 2020

Producing animal products from farm to table emits massive amounts of greenhouse gases (GHGs). Modified meal plans, mainly including vegetables and grains, have been recommended to reduce GHG emissions. However, these meal plans have not been developed with regard to the micronutrient content, but rather with regard to the energy requirements of grains and vegetables, which could result in a nutritional imbalance. For this reason, we investigated a common Korean suggested meal plan (SMP) from the National Institute of Agricultural Sciences, in which nutritional conditions were considered, and evaluated its GHG emissions using the Life Cycle Assessment Inventory Database and nutritional values. The SMP, which included meat, was based on the Korean Nutrition Society for adult men age 19 to 29, and was changed to a vegan meal plan (VMP). Animal-based protein sources were substituted for meat alternatives, such as beans and tofu, for which carbon footprint data was available. To compare the nutritional differences, the 9^th Korean Food Composition Tables I and II were consulted. To calculate GHG emissions, the carbon footprint data of the food was converted to a CO₂ equivalent (CO₂e) using a procedure from the Foundation of Agriculture Technology Commercialization and Transfer. It was found that GHG emissions per calorie were 18% lower for the VMP when compared to the SMP. However, if GHG emissions per total amino acids were evaluated, the VMP GHG emissions per total amino acids were 0.12 g CO₂e/mg, while the corresponding value for the SMP was 0.06 g CO₂e/mg. The Korean daily meat intake reported by the Korea Agricultural Statistics Service was 37.1% lower than in the SMP, but when converted to a protein intake the figure was 17.0% lower. It was found that each SMP resulted in more GHG emissions than the VMP, but when considered as GHG emissions per total amino acids, the opposite pattern was apparent. There is a need to conduct more detailed studies of the variation in GHG emissions with different meal plans, using the daily meat intake per person.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.427-432
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• 2012

The article herein suggested a compound repository and a descriptive method to develop a compound knowledge process. A data target saved in a compound knowledge repository suggested in this article includes all compound knowledge meta data and digital resources, which can be divided into the three following factors according to the purpose: user roles, functional elements, and service ranges. The three factors are basic components to describe abstract models of repository. In this article, meta data of compound knowledge are defined by being classified into the two factors. A component stands for the property about a main agent, activity unit or resource that use and create knowledge, and a context presents the context in which knowledge object are included. An agent of the compound knowledge process performs classification, registration, and pattern information management of composite knowledge, and serves as data flow and processing between compound knowledge repository and user. The agent of the compound knowledge process consists of the following functions: warning to inform data search and extraction, data collection and output for data exchange in an distributed environment, storage and registration for data, request and transmission to call for physical material wanted after search of meta data. In this article, the construction of a compound knowledge repository for recommendation system to be developed can serve a role to enhance learning productivity through real-time visualization of timely knowledge by presenting well-put various contents to users in the field of industry to occur work and learning at the same time.