Scholarly article on topic 'Life-log Data-based Window Opening and Closing for Individual Customized Services in Symbiosis Houses'

Life-log Data-based Window Opening and Closing for Individual Customized Services in Symbiosis Houses Academic research paper on "Art (arts, history of arts, performing arts, music)"

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{Symbiosis / "Symbiosis House" / "Customized Service" / "Life-Log data" / "Window Automation" / "Companion dog"}

Abstract of research paper on Art (arts, history of arts, performing arts, music), author of scientific article — Yoora Kim, Jungeun Lee, Hyunsoo Lee

Abstract Smart residential spaces designed for residents departs from simply providing conventional standardized services, to go beyond and provide personalized experiences that take individual circumstances into account. Such services play a key role in enhancing the residents’ quality of life. This study looks into such personalized services that reflect different characteristics of a diverse range of residents who have different behavior patterns. Such services can increase the satisfaction of the residents by providing flexible services that take into account the lifestyle and circumstances of each resident. A problem with offering customized services, however, is that there is a dearth of data on individuals. Sufficient amount of data must be collected in order to determine what a proper service for an individual is. As such, this study explains the life-log data and discusses its collection method. The life-log data collected serves as crucial grounds for decision-making. How decisions are made using the life log data is an intriguing research topic. This study proposes and discusses logics and processes of various decision-making methods that can be executed using the life log-data. In their homes, residents tend to regularly display certain behaviors in patterns, which allows for identifying the residents’ behavior patterns, as well as the predicting the residents’ future behavior. In this aspect, the residents’ location, needs, and current behavior must be recognized in order to provide personalized services. As such, this study proposes decision-making method by verifying in-house behavior of Korean elderly with companion dogs in symbiosis homes. Such dog's hair and foul smells cause indoor pollutions that damage elderly heath. This study proposes an automatic personalized window opening and closing service by using life-log data of the resident.

Academic research paper on topic "Life-log Data-based Window Opening and Closing for Individual Customized Services in Symbiosis Houses"

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Procedia Environmental Sciences 22 (2014) 247 - 256

12th International Conference on Design and Decision Support Systems in Architecture and Urban

Planning, DDSS 2014

Life-log data-based window opening and closing for individual customized services in symbiosis houses

Yoora Kim, Jungeun Lee, Hyunsoo Lee*

Yonsei University

#707 College of Human Ecology, 50 Yonsei RD, Seodaemun-Gu , Seoul, Republic of Korea

postal code City: 120-749

Abstract

Smart residential spaces designed for residents departs from simply providing conventional standardized services, to go beyond and provide personalized experiences that take individual circumstances into account. Such services play a key role in enhancing the residents' quality of life. This study looks into such personalized services that reflect different characteristics of a diverse range of residents who have different behavior patterns. Such services can increase the satisfaction of the residents by providing flexible services that take into account the lifestyle and circumstances of each resident. A problem with offering customized services, however, is that there is a dearth of data on individuals. Sufficient amount of data must be collected in order to determine what a proper service for an individual is. As such, this study explains the life-log data and discusses its collection method. The life-log data collected serves as crucial grounds for decision-making. How decisions are made using the life log data is an intriguing research topic. This study proposes and discusses logics and processes of various decision-making methods that can be executed using the life log-data. In their homes, residents tend to regularly display certain behaviors in patterns, which allows for identifying the residents' behavior patterns, as well as the predicting the residents' future behavior. In this aspect, the residents' location, needs, and current behavior must be recognized in order to provide personalized services. As such, this study proposes decision-making method by verifying in-house behavior of Korean elderly with companion dogs in symbiosis homes. Such dog's hair and foul smells cause indoor pollutions that damage elderly heath. This study proposes an automatic personalized window opening and closing service by using life-log data of the resident.

© 2014TheAuthors. Publishedby ElsevierB.VThis is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/3.0/).

Peer-review under responsibility of the Eindhoven University of Technology, Faculty of the Built Environment, Urban Planning Group Keywords: Symbiosis, Symbiosis House, Customized Service, Life-Log data, Window Automation, Companion dog

* Corresponding author. Tel. +2-2123-3136. E-mail address: hyunsl@yonsei.ac.kr

1878-0296 © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Peer-review under responsibility of the Eindhoven University of Technology, Faculty of the Built Environment, Urban Planning Group doi: 10.1016/j.proenv.2014.11.024

1. Introduction

In a rapidly changing society, it is very hard for senior citizens to adapt themselves. As a result, there is a high possibility that they would suffer from social disadvantage, feeling of isolation or depression. This kind of loneliness has a negative effect on people's life satisfaction. Therefore, as the level of loneliness increases, life satisfaction decreases.1 As they become more isolated from their family and society, they have been exposed to physical and mental stresses, which have in turn caused some serious social problems such as elderly suicide. In particular, the aged living alone live a lonely life in poor surroundings compared to other elderly couples, they tend to become more sensitive to negative changes caused by aging. In addition, they usually believe that they are less healthy than they actually are. Since they don't go along with others and local community because of their unfavorable residential conditions and living environment, they are more vulnerable to solitude.2 Because of the sharp rise of aged population, geriatric depression has emerged a major social problem. In fact, this kind of the elderly depression aggravates pain and handicap which have a significant effect on those with chronic disease and cognitive impairment and increases death rates.3 As one of the ways to solve elderly loneliness, a house in which they live with a companion dog is suggested. To the elderly who live alone after losing their spouse, friends and relatives, a companion dog is like family. Some reports reported that the aged living with a companion dog is less severe than those living alone without a companion animal around in terms of the symptoms of depression.4 A companion animal is one good strategy to eliminate elderly depression and loneliness in a modern society. In addition, it makes the aged exercise regularly, improving their health. However, a companion animal has negative effects as well. For example, it could bring diseases to the aged living together. The contaminated substances from the companion animal's hair and secretion can be fatal to the aged with weak immune systems. Despite these negative aspects, a companion animal can greatly reduce the owner's loneliness as a life companion. Therefore, a house designed for symbiosis with a companion animal is very important. As the pace of aging picks up, it is likely that a demand for the house designed to live with a companion animal would further increase. To meet these residents' needs, this study attempted to explain a concept of the house designed for symbiosis with a companion dog. Under this kind of concept, it also tried to come up with a solution to the problems of the house designed to live with a companion dog. To solve a problem of air pollution, in particular, air should be ventilated by opening and closing windows regularly. The purpose of this study is to develop a customized window opening & closing control method for the dwellers of the house specially designed for symbiosis with a companion dog.

2. House specially designed for symbiosis with companion dog

2.1. Concept of symbiosis

When we live with other people, we often face a variety of conflicts. Therefore, it appears that living with an animal would cause a lot of problems. That's why it is critical to decide how to live with a companion animal in this specially designed house. Before deciding the method, a process of defining 'symbiosis' is very important in setting a concept of the house specially designed for symbiosis with a companion animal. From the biological standpoint, symbiosis refers to interactions between two different species. It covers both benefits and damages on both species. The scope of symbiosis is far broader than generally expected.5

From the narrow perspective, it includes mutualism which confers benefits on both sides and parasitism in which only one species benefit while the opponent damages from the relationship. From a broad point of view, there are commensalism in which only one species benefit from relationship and amensalism in which only one species benefit while the opponent have any damages. Under any symbiosis, it isn't hard to find symbiotic relationship in most biological species. Many creatures have parasites in their body, and most herbivores have microbes in their intestines. Among them, symbiotic relationships are found. This kind of symbiosis from nature exists in all creates including human-nature and inter-human relationships. Among these diverse symbiotic relationships, mutualism is deemed as the genuine symbiosis. Just like developing a social space for people, it is very exciting to plan a space for both human and companion dog.

Both of species benefit from the relationship

Only one species benefit from the relationship

Only one species benefit and opponent have any damages

Only one species benefit and opponent damages from the relationship

Fig.1. Type of Symbiosis.

2.2. Elements to be considered in the house specially designed for symbiosis with companion dog

To develop relationships into mutualism in which both sides benefit from the relationship in the house specially designed for symbiosis, various factors should be considered. For example, it is needed to set territoriality for the owner and his/her companion dog. It is also necessary to come up with a way to build refreshing environment by taking care of hair and bad smell arising from the companion dog. The problems from the house designed for symbiosis with a companion dog include bad smell, infection caused by pet hair, sleep interruption, conflict with neighbours, damage on interior design and frequent cleaning. Among them, bad smell, dirt caused by the pet hair and air pollution were investigated in this study. According to a previous study,6 in terms of stresses caused by symbiosis with a companion animal, the owner's health, bad smell, hair and secretions accounted for great portions. The indoor air pollutants include pet hair, secretions, dirt, mites and bad smell. These causes pollute indoor air, make the resident uncomfortable and would isolate the pet dog. A dog often shakes its body and hair fly out accordingly. During the Molt-period (twice a year), in particular, a lot of hair fly out and pollute indoor air. To maintain clean and refreshing indoor environment, it is important to check the optimum level. The optimum dust concentration level for indoor air environment is 0.1 mg/ m' or below. In domestic and foreign industrial safety regulations, '25-35ppm' was reported for ammonia exposure limit. However, the ammonia exposure limit for indoor air quality in residential space isn't reported yet. However, Finnish Ministry of Environment has recommended setting the indoor ammonia concentration to 20^g/ m'. The Korean Indoor Air Alliance divided indoor air quality to three stages according to the indoor air quality classification system and suggested 30-40 №/ m* of ammonia concentration. Once the indoor air exposure limit is exceeded, there is a high possibility of being infected with diverse diseases. In fact, the pet's blood, secretions, dandruff and hair can cause nasal congestion, difficulty in breathing and rhinitis. If symptoms are severe, they can even cause asthma. In particular, the elderly with weak immune systems are more vulnerable to diverse infections. To solve indoor air pollution, air should be ventilated by opening and closing the windows. However, an automated window opening and closing system is not that simple. This study concentrated on developing a flexible window opening and closing method considering both the owner and companion dog in the specially designed for symbiosis with a companion dog. The conventional window opening & closing methods mostly considered natural environment only, without paying much attention to the occupant's desire or circumstances. The method chosen in this study is a window opening and closing method which considered both the owner and his/her companion dog. To implement window opening and closing services for clean and refreshing indoor environment, it is required to outdoor pollutants as well as indoor pollutants, weather and whether or not the occupant is in the house. To execute the window opening and closing services aimed to build clean and refreshing environment, a specific context should be examined and analysed. However, it is very hard to find a study on this kind of user-cantered window opening & closing method. To realize the user-cantered window opening & closing, base data which support this mechanism should be prepared. Considering these aspects, this study attempted to develop a decision-making method for the life-log data-based window opening & closing system, using evidence-based design.

3. Window opening and closing service

In terms of a way to keep indoor air clean and refreshing, ventilation is the most effective. For this kind of ventilation, it is needed to develop an automated window opening & closing system. The window opening & closing method can be divided into two categories: manual system and automatic system. This study focused on the latter. If window is regarded as 'creature,' it should be able to respond to different contexts on its own. Construction has been dreamed of from the organic perspective just like Frank Lloyd Wright which saw buildings as an organic subject and Toyo Ito's Media Tech building which responds to environment. The architectural ideologies which are connected with this kind of concept include Kenzo Tange's metabolism and concept of the Internet of Things (IoT). In other words, it refers to an object which could be the applicant (or partner) of human or mechanism. The necessity of partners is similar to the dweller's consideration of having a companion dog. A house which responds accordingly for the resident's convenience is a desirable direction for future houses. This kind of response can be divided into natural environment response and human response.

3.1. Automated window opening and closing system responding to natural environment

An automated window opening and closing system responding to natural environment refers to a system which controls the opening and closing of windows by responding to natural factors such as light and wind. One of the most typical automated window opening and closing systems is Arab Institute designed by the French architect Jean Nouvel. As shown in the figure below, the window area is automatically adjusted depending on the amount of light just like an iris diaphragm.

Fig.2. Facade design using window automation, Arab Institute.

The automatic ventilation system developed by Kintrol Company in Austria is a system which automatically opens and closes windows by sensing smoke, rain, hail, temperature and wind using diverse sensors. For example, if there is a fire or smoke outside the building, windows are automatically closed to prevent it from entering. If indoor temperature is too high, they are automatically opened for natural ventilation.

Fig.3. Window Automation System for Indoor Ventilation, Kintrol.

In a house which responds to natural environment explained above, windows are opened or closed depending on outdoor environment instead of focusing on residents' needs and demand. Therefore, there is a possibility that the windows are operated against the residents' intention. Since the house which responds to outdoor environment does not consider residents' circumstances, it is not an ideal window opening and closing method. The opening and closing windows considering both environment and residents' needs would enhance residents' dwelling satisfaction. The ultimate goal of the opening and closing windows responding to residents' needs is to provide one-on-one customized services. Even though many people agree that one-on-one customized services are desirable, there haven't many attempts on them because of technical, economic and social constraints. Thanks to remarkable development of information and telecommunication technology, however, these constraints have eased a lot. In terms of social changes, one-on-one customized services aimed to improve the quality of residence are pursued. To provide one-on-one customized services, it is essential to come up with the data needed to determine a direction for the services. From this kind of perspective, it is life-log data-based one-one-one customized services which are developed to cope with conflicts which can occur in some complicated environments in which a resident live with his/her companion dog in a flexible manner. The problem-solving method for life-log data-based one-on-one customized services is included in the category of Case-Based Reasoning (CBR)-based problem-solving method. In CBR which is developed to solve problems under the paradigm of artificial intelligence, it a main concept to solve current problems based on past cases. This study targeted to develop processes which determine the opening and closing of windows based on life-log data.

4. Life-log

Life-log literally means 'record,' and life-log data sort out and store overall personal life records produced from hobby, health and leisure. A user stores photos, videos and memos in person, and user location, bio information and exercise-related data are stored as well. These data can be collected using the sensors attached to digital devices and Global Positioning System (GPS). Because life-log data are the data which directly reflected records on personal experiences, they are highly useful as basic data to clarify personal characteristics. In addition, life-log data differ from conventional data in that they can use diverse information such as time, place and event as search keywords. With the development of information & telecommunication technology, there are now many ways to collect life-log data. 8 9 10 Using these methods, data can be collected through all wearable equipment such as ID card, credit card, navigator and black box as well as SNS and mobile devices. If a context occurs, the data collected by the sensors in the house are transmitted as life-log data and stored in a server computer. Then, current and past contexts are compared and analyzed in the server. Life-log data are sorted out by the following questions (ex: Who, When, What, How, Where, etc.), and past information on the same context can be obtained by entering some search keywords. As more data are accumulated, comparison data needed to find a solution which responds to various contexts can be collected. In other words, as data are accumulated more, data accuracy increases as well.

Table 1. Example of Life-log Data.

Present Life-log Data

who year month day weak time where what how value

place space Sub-who Sub-what

Single person A 2013 June 10 Mon 8:00 Indoor Bedroom Get up/Changing pet's pad

Ammonia sensor 2013 June 10 Mon 8:00 Indoor Living Measure Ammonia sensor Sensing 43ug/m3

Dust sensor 2013 June 10 Mon 8:00 Indoor Living Measure Dust sensor Sensing 0.08mg/m3

Cell phone 2013 June 10 Mon 8:00 Indoor Bedroom Send a message

Window 2013 June 10 Mon 8:00 Indoor Living Open the window Window Open

Single person A 2013 June 10 Mon 10:00 Indoor Living Watching TV

Ammonia Sensor 2013 June 10 Mon 10:00 Indoor Living Measure Ammonia Sensor Sensing 35ug/m3

Window 2013 June 10 Mon 10:00 Indoor Living Close the window Window Closed

Single Person A 2013 June 10 Mon 12:00 Indoor Bathroom Bathe a dog

Dust Sensor 2013 June 10 Mon 12:00 Indoor Living Measure Dust sensor Sensing 0.13mg/m3

Window 2013 June 10 Mon 12:00 Indoor Living Open the window

Past Life-log Data

Single person A 2012 June 10 Tue 8:00 Indoor Bedroom Get up

Ammonia sensor 2012 June 10 Tue 8:00 Indoor Living Measure Ammonia sensor Sensing 44ug/m3

Dust sensor 2012 June 10 Tue 8:00 Indoor Living Measure Dust sensor Sensing 0.07mg/m3

Cell phone 2012 June 10 Tue 8:00 Indoor Bedroom Send a message

window 2012 June 10 Tue 8:00 Indoor Bedroom Open the window Window Open

Single person A 2012 June 10 Tue 10:00 Indoor Bedroom Read newspaper

Ammonia Sensor 2012 June 10 Tue 10:00 Indoor Living Measure Ammonia Sensor Sensing 41ug/m3

Window 2012 June 10 Tue 10:00 Indoor Bedroom Open the window Window Open

Single Person A 2012 June 10 Tue 13:00 Indoor Living Play with a dog

Dust Sensor 2012 June 10 Tue 13:00 Indoor Living Measure Dust sensor Sensing 0.14mg/m3

Window 2012 June 10 Tue 13:00 Indoor Living Open the window Window

5. Decision-making process for the opening and closing of windows

In this study, a CBR approach was chosen for a decision-making method for the automated opening and closing of windows. The CBR approach is operated based on the idea that the problem-solving methods accumulated in the past are taken advantage of. 11 In other words, a process which can implement life-log data-based customized services is needed. Under this kind of process, the most important operation is to search past life-log data which would be helpful in making a decision on the current window opening & closing method. The decision-making process on the automated window opening and closing services aimed to ventilate polluted indoor air in the house specially designed for symbiosis with a companion dog is as follows: First, variables needed in the house living with a companion dog are selected among all variables. Second, current variables are compared to past variables. Third, when there are several data with a similar context at analysis of life-log data, a filtering process should be selected to choose the best one.

Fig.4. Decision-Making Process.

6. Related variable selection

There are a great number of variables that should be considered in a house. Among them, those to be handled in this study and related services were chosen. Variables were selected with a goal of providing window opening and closing services for clean indoor environment in the house specially designed for symbiosis with a companion dog. To implement window opening and closing services at selection of variables, both indoor and outdoor environments should be considered to prevent outdoor air pollutants from entering when windows are opened. In addition, the services were provided after selecting the behavior, time and occupancy of the aged living alone. For example, window opening and closing-related variables include variable time, ammonia, dust, CAI, rain, resident status and window. They are the variables with certain CAI, ammonia and dust variable values. If these values are used as they are, it is hard to check similarity of Life-log data. To check the similarity, therefore, variable values should be grouped. This study attempted to group these variable values as stated in Table 1 below:

Table 2. Simplified Index of Environmental Pollution.

Category Good Average Slightly Bad Bad Very Bad

CAI Value Score Range 0-50 51-100 101-150 151-250 251-500

Simplified Index 1 2 3 4 5

Category Good Average Bad

Ammonia Value Score Range 0-19 20-40 41+

Simplified Index 1 2 3

Category Good Average Bad

Dust Value Score Range 0-0.09 0.1 0.1+

Simplified Index 1 2 3

Fig.5. Related Variables.

7. Similarity Analysis

The conventional widow opening and closing system is automatically operated depending on the general house characteristics without considering customized services for residents. If windows are automatically opened and closed while there is no one in the house, a security problem would occur. Therefore, this study has come up with the following scenario to realize customized window opening and closing services. Life-log data were comprised of the behavior of the senior citizen 'A' living alone, ammonia and dust levels measured during the behavior and occupancy sensor. The data on outdoor air pollutants can be obtained through CAI and weather app. Then, a decision-making method on the opening and closing of windows can be configured through the scenario as follows:

Table 3. Similarity Analysis.

Code Variable/ Object Present situation Lifelog 1 3/17/ 2011 Lifelog 2 5/6/ 2011 Lifelog 3 5/25/ 2012 Lifelog 4 9/22/ 2012 Lifelog 5 11/25/ 2012 Lifelog 6 12/30/ 2012 Lifelog 7 2/13/ 2013 Lifelog 8 6/13/ 2013 Lifelog 9 9/27/ 2013 Lifelog 10 9/30/ 2013 Lifelog 11 12/22/ 2013

V1 Time 8:00 8:00 8:00 8:00 8:00 8:00 15:00 8:00 8:00 14:00 8:00 9:00

V2 Single senior A walk church reading walk sleeping walk walk market walk bath hospital church

V3 Rain No Yes No No No No No No Yes No Yes No

V4 Window ? Closed Open Open Closed Open Open Closed Closed Closed Open Open

O1 Ammonia Sensor (0g/m') 3 3 3 3 2 3 3 2 3 3 2 2

O2 Dust Sensor (mg/m') 3 3 3 2 3 1 1 2 3 3 3 3

O3 CAI 3 3 3 3 3 3 2 3 3 3 2 2

O4 Occupancy Sensor Off Off On Off On Off off off Off On Off off

Table 4. Matching Point Calculation.

Code Variable/ Object, Service L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L11

V1 Time O O O O O X 0 O X O X

V2 Single senior A X X O X O O X O X X X

V3 Rain X O O O O O O X O X O

V4 Window Closed Open Open Open Open Closed Open Closed Open Closed Closed

O1 Ammonia Sensor (w/m') O O O X O O X O O X X

O2 Dust Sensor (mg/m') O O X O X X X O O O O

O3 CAI O O O O O X O O O X X

O4 Occupancy Sensor O X O X O O O O X O O

MP Matching point 5 5 6 4 6 4 4 6 4 3 3

The information above refers to life-log data on the contexts of the senior citizen 'A' at 08:00 (Friday) on January 24, 2014. At 8 o'clock in the morning, he went out to walk his dog leaving its poop in the house. The occupancy sensor was off. While he was out, the ammonia level reached to '3.' The dust level was also high with '3.' Even if it didn't rain, the outdoor air pollutant level of CAI was '3 (slightly bad).' Because the quality of indoor air was aggravated, life-log data were analyzed to make a decision on the opening and closing of windows. Under this context, the life-log data which are similar to the past data of the senior citizen 'A' are selected. In a great number of past data, however, the records which aren't perfectly matched with current context are observed. Under this kind of context, life-log data with the highest frequency of similarity go through a filtering process. In the variables with the highest similarity with current context (L3, L5 and L8), six out of seven variables were matched with current context. Based on the decision on the opening and closing of windows, the windows were opened in L3 and L5 while they were closed in L8. Under this kind of situation, each variable in three similar life-log data is compared in

a way to make a decision under the present context. In L3 and L5, dust levels were matched with current context. In L8, in contract, rain was observed, which wasn't matched with current context. The three life-log data are the variables which are matched with current context in six categories, revealing the highest frequency. However, it was proposed to open windows based on the results of decision making in L3 and L5 in which the frequency of the matched results is higher because of proposal of accurate decision making.

8. Conclusion

This study differs from previous studies in that it proposed methodology to solve indoor air pollution in a house specially designed for symbiosis with a companion dog, which was introduced to solve the loneliness of the elderly living alone. To solve this kind of indoor air pollution, a decision-making method for automated window opening and closing systems was examined. The problem-solving method adopted for decision making is CBR approach which uses the evidence-based decision-making method. This study attempted to propose life-log data-based decision-making approach using the evidence-based problem-solving method. In a computer sector, life-log data refer to data measured by the sensors attached to a human body. In this study, however, they mean living information which includes all data on a human life. However, the sensor values measured in a human body weren't included. Instead, residents' behavior which occur in a daily live and the values measured by sensors installed across the house were only examined in this study. In the CBR approach, similarity check with past life-log data is important. In addition to similarity check, filtering is another important issue. The importance of the life-log-based problem-solving method is that it pursues resident-centered design and one-on-one customized services. In this study, simple examples were introduced for a better understanding of explanation. Even though practicality is considered making the examples more complicated, there would not be a problem in logic. Considering these aspects, a life-log data-based decision-making approach has great potential. It appears that there is a necessity to review decision-making process based on the actually collected life-log data. This study failed to explain how to collect life-log data. A life-log data collection method should also be studied for life-log data-based decision-making process. Because there are a variety of channels to collect life-log data, it is important to figure out how to collect them through what channel in an efficient manner. In addition, life-log data patterns and visualization are important issues as well. With the rapid development of the Internet technology, personal information has become more important. Even though data collection is possible in theory, it is not that easy in reality from the aspect of privacy protection. Furthermore, it is likely that privacy protection act would become stricter. Therefore, there should be continued studies on data collection methods as well.

Acknowledgements

This work has supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MOE) (NRF-2010-0022347) and BK21 Plus funded by the Ministry of Education of Korea. (No. 22A20130000095)

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