• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.77-82
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• 2022

This study aims to understand how mobile and stationary air pollution sources affect the air quality and soil properties in urban parks. We selected three sites of urban parks in Seoul as follows: Ha-neul Park in Mapo-gu (Site_M), Ill-won Eco-Park in Gangnam-gu (Site_G), and Yangjae Citizen's Forest in Seocho-gu (Site_Y), and compared the results of each site's traffic volume, air quality concentration, and soil analysis. Traffic volume was high in Site_M, followed by Site_G and Y; Site_M and G were closer to the resource recovery facility than Site_Y. Hence, we hypothesized that PM and NO₂ concentrations in the atmosphere were higher in Site_M than Site_G and Y, causing different soil nitrogen content among sites due to different atmospheric deposition. Consistent with our hypothesis, the concentrations of PM2.5 and NO₂ were higher in Site_M and G than Site_Y, while Site_Y had higher PM10 than other sites. The soil NO₃^- contents showed no significant difference among three sites, whereas the soil NH₄+ content was extremely high in Site_Y. This high content of soil NH₄⁺ is thought to be due to acidification from excessive fertilization. Lower soil pH of Site_Y further supported the evidence of heavy fertilization in this site. Overall nitrogen dynamics implies that soil nitrogen status is more influenced by park management such as fertilization rather than atmospheric deposition. Despite of lower soil NH₄⁺ content of Site_M and G than Y, vegetation vitality looked similar among three sites. This indirectly indicates that excessive fertilizer input in urban park management needs to be reconsidered. This study showed that even if the air quality was different due to mobile and stationary sources, it did not directly affect the soil nitrogen nutrient status of the adjacent urban park.

• Journal of Korean Academy of Nursing
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• v.23 no.3
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• pp.467-486
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• 1993

Today, more chronically ill and handicapped people are being cared for at home by a family member caregiver. The task of caring for a family momber may mean that the caregiver has less time and money and more work which may result in increased fatigue and symptoms of illness. This study was done to examine the well-being of family caregivers. Fifty three family caregivers were interviewed. Concepts were measured using existing tools and included : Burden(25 item 5 point scale), Social sup-port (21 item 7 point scale), Health status defined by a symptom checklist(48 item S point scale), and Well -being defined by a quality of life scale (14 item 7 point scale) and caregiving activities. Data collection was done by interview and Q-sort. Social support and well - being were positively correlated as were symptoms and burden. Symptoms and burden were negatively correlated with social support and well-being. Items on the quality of life scale had a mean score range from 3.09 to 4.96. Quality of life related to income was lowest (3.09) but the desire to use more money for the patient was rated 2.90 on the burden scale where the item means ranged from 0.73 to 3.55. The high mean of 3.55 was for obligation to give care and the low 0.73 was (or not feeling that this was helping the patient. Mean scores for symptoms ranged from 0.26 to 2.15 with the 2.15 being for “worry about all the things that have to be done.” Over half of the patients were dependent for help with some activities of daily living. The caregivers reported doing an average of 3.40 out of five patient care activities including bathing (77.4%), shampooing (67.9%), and washing face and hands (49.1％), and 3.74 out of seven home maintenance activities including laundry (98.1％), cooking (83.0%), and arranging bed-ding(75.5%). The caregivers reported their spouse as one of the main sources of social support, including in times of loneliness and anger The mean score for loneliness as burden was 2.15 and ranked fourth and 31 (58.5％) of the sample reported being lonely recently and not being satisfied with the support received. Similarly anger caused by the patient was given a mean score of 2.13, and anger was reported to have been present recently by 38 (71.7%) of the sample and satis-faction with the support given was low. Having someone to help deal with anger ranked twelfth out of 21 items on the social support scale and had a mean score of 3.98 (range 3.49 to 5.98). Spouses were reported as a major source of social support but the fact that 50% of the caregivers were caring for a spouse, may account for the quality of this source of social support having been affected. These caregivers faced the same problems as others at the same stage of life. but because of the situation, there was a strain on their resources, particularly financial and social. In conclusion it was found that burden is correlated negatively to quality of life and positively to symptoms, but in this sample, symptoms and bur-den were scored relatively low. Does this indicate that the caregivers accept caregiving as part of their destiny and accept the quality of their lives with burden and symptoms just being a part of caregiving\ulcorner Does the correlation between the bur-den and symptoms indicate they are a measure of the same phenomenon or that the sample was of a more mobile, less burdened group of caregivers\ulcorner Quality of life was the one variable that was significant in explaining the varience on burden. Further study is needed to validate the conclusions found in this study but they indicate a need for nurses to ap-proach these caregivers with a plan tailored to each individual situation and to give consideration to interventions directed at improving quality of life and expanding social support networks for those caring for spouses.

• Journal of the Korean Society of Urban Environment
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• v.18 no.4
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• pp.485-494
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• 2018

This study aims to identify the characteristics of oxidation and chemical composition of PM in winter season, 2017 at Incheon area. The mean concentration of air pollutants were $46{\pm}22{\mu}g/m^3-PM_{10}$, $29{\pm}18{\mu}g/m^3/-PM_{2.5}$, $5{\pm}3ppb-SO_2$, $0.56{\pm}0.24ppm-CO$, $21{\pm}13ppb-O_3$ and $28{\pm}17ppb-NO_2$, respectively. The dominant ion of the $PM_{1.0}$ chemical component were organic with $3.2{\mu}g/m^3$ and nitrate with $1.9{\mu}g/m^3$. The day and night variation of the $PM_{1.0}$ chemical components was higher in nighttime than those of daytime. The averaged nitrate oxidation rate (SOR) was 0.06 and sulfate oxidation rate was 0.11 during the field campaign. In the high mass loading period, nitrate oxidation rate (NOR) was up to 0.6 and also the nitrate in $PM_{1.0}$ was increased. The averaged ratio of $NO_x/SO_2$ was 8.7 and nitrate/sulfate was 3.1, respectively. In this results, the nitrate component in $PM_{1.0}$ was influenced by NOx from the stationary source as power plant and the mobile source around the measurement site.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.1
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• pp.25-35
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• 2005

This study analyzed total concentrations and existing forms of heavy metals in soils of Ulsan using a sequential extraction method. Soil samples were collected from 6 categorized areas including green, residential, heavy traffic, petrochemical industrial complex(IC), mechanical and shipbuilding IC, and non-ferrous metal IC areas. which represent different emission characteristics. The highest total concentrations of heavy metals by a sequential extraction analysis were observed in the soils collected from the non-ferrous metal IC area, followed by the mechanical and shipbuilding IC and heavy traffic areas. Dominant(> 50%) existing forms of Cd, Cr and Ni were residual forms followed by Fe and Mn oxides in almost areas. Residual fractions in the non-ferrous metal IC areas were relatively lower than those in other areas. However, the fractions of organic and sulphides in the IC areas were higher. The dominant farms of Cu were much different with the investigated areas. In most areas, the dominant forms of Pb and Zn were Fe and Mn oxides, followed by residual fraction for Pb. The exchangeable and carbonate fractions represent mobility of metallic elements in soils. They are also significantly affected by the environmental renditions, such as pHs of soil and rainfall. In this study the exchangeable and carbonate fractions were lower than other fractions. Because the total concentrations of heavy metals in the soils of the non-ferrous metal IC area were extremely high, however, the mobile fractions of heavy metals in the IC area would be significant. Thus a large amount of heavy metals can be released into plants, water bodies, and soils. Therefore, urgent measures, such as source control for soil remediation of heavy metals, in the non-ferrous metal IC areas are essentially required. Analysis results obtained from the sequential extraction and the aqua regia extraction showed a high correlation, whose determination coefficients(R2) of heavy metals except Cd approximately ranged from 0.7 to 0.9.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.237-246
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• 2016

This study is therefore aimed at measuring the surface dose rate and the spatial dose rate in and outside the radionuclide facility in order to ensure safety of the patients, radiation workers and family care-givers in their use of such equipment and to provide a basic framework for further research on radiation protection. The study was conducted at 4 restrooms in and outside the radionuclide facility of a general hospital in Incheon between May 1 and July 31, 2014. During the study period, the spatial contamination dose rate and the surface contamination dose rate before and after radiation use were measured at the 4 places-thyroid therapy room, PET center, gamma camera room, and outpatient department. According to the restroom use survey by hospitals, restrooms in the radionuclide facility were used not only by patients but also by family care-givers and some of radiation workers. The highest cumulative spatial radiation dose rate was 8.86 mSv/hr at camera room restroom, followed by 7.31 mSv/hr at radioactive iodine therapy room restroom, 2.29 mSv/hr at PET center restroom, and 0.26 mSv/hr at outpatient department restroom, respectively. The surface radiation dose rate measured before and after radiation use was the highest at toilets, which are in direct contact with patient's excretion, followed by the center and the entrance of restrooms. Unsealed radioactive sources used in nuclear medicine are relatively safe due to short half lives and low energy. A patient who received those radioactive sources, however, may become a mobile radioactive source and contaminate areas the patient contacts-camera room, sedation room, and restroom-through secretion and excretion. Therefore, patients administered radionuclides should be advised to drink sufficient amounts of water to efficiently minimize radiation exposure to others by reducing the biological half-life, and members of the public-family care-givers, pregnant women, and children-be as far away from the patients until the dose remains below the permitted dose limit.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.9
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• pp.14-23
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• 2010

This paper reports the fabrication of a DVB-T/H System in Package (SiP) that is able to receive and process the DVB-T/H signal. The DVB-T/H is the European telecommunication standard for Digital Video Broadcasting (DVB). An IC-embedded Printed Circuit Board (PCB) process, interpose a chip between PCB layers, has applied to the DVB-T/H SiP. The chip inserted in DVB-T/H SiP is the System on Chip (SoC) for mobile TV. It is comprised of a RF block for DVB-T/H RF signal and a digital block to convert received signal to digital signal for an application processor. To operate the DVB-T/H IC, a 3MHz DC-DC converter and LDO are on the DVB-T/H SiP. And a 38.4MHz crystal is used as a clock source. The fabricated DVB-T/H SiP form 4 layers which size is $8mm{\times}8mm$. The DVB-T/H IC is located between 2nd and 3rd layer. According to the result of simulation, the RF signal sensitivity is improved since the layout modification of the ground plane and via. And we confirmed the adjustment of LC value on power transmission is necessary to turn down the noise level in a SiP. Although the size of a DVB-T/H SiP is decreased over 70% than reference module, the power consumption and efficiency is on a par with reference module. The average power consumption is 297mW and the efficiency is 87%. But, the RF signal sensitivity is declined by average 3.8dB. This is caused by the decrease of the RF signal sensitivity which is 2.8dB, because of the noise from the DC-DC converter.

• Journal of Environmental Impact Assessment
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• v.24 no.6
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• pp.578-592
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• 2015

To investigate characteristics and seasonal variations of carbonaceous species for $PM_{2.5}$ in Seoul metropolitan area, Korea, we measured organic carbon (OC) and elemental carbon (EC) from January 2014 to December 2014 using a semi-continuous OC/EC Analyzer (Model-4, Sunset Lab.). Mean concentrations of OC and EC were estimated $4.1{\pm}2.7{\mu}g/m^3$ and $1.6{\pm}1.0{\mu}g/m^3$, respectively. The annual averaged OC/EC ratio was $2.9{\pm}2.7$. Concentrations of OC and EC comprised 13% and 5% of $PM_{2.5}$ and the mass fraction of both was the highest in fall. OC and EC showed similar trend in seasonal variations. Concentrations of those showed a clear seasonal variation with the highest in winter and the lowest in summer. The correlations between the two were the best during the winter ($r^2=0.88$). As results of carbonaceous species analysis, the dominant factor in view of fine particle ($PM_{2.5}$) is primary emission source such as mobile, fossil fuel combustion during commute time(08:00~10:00 or 17:00~21:00) and winter season. Continuous monitoring of atmospheric carbonaceous species is essential to provide the science-based data to policy-maker establishing the air quality improvement policy.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.1
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• pp.9-18
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• 2017

Arsenic (As) has been considered as the most toxic one among various hazardous materials and As contamination can be caused naturally and anthropogenically. Major forms of arsenic in groundwater are arsenite [(As(III)] and/or arsenate [(As(V)], depending on redox condition: arsenite and arsenate are predominant in reduced and oxidized environments, respectively. Because arsenite is much more toxic and mobile than arsenate, there have been a number of studies on the reduction of its toxicity through oxidation of As(III) to As(V). This study was initiated to develop photocatalytic oxidation process for treatment of groundwater contaminated with arsenite. The performance of two types of light sources (UV lamp and UV LED) was compared and the feasibility of goethite as a photocatalyst was evaluated. The highest removal efficiency of the process was achieved at a goethite dose of 0.05 g/L. Based on the comparison of oxidation efficiencies of arsenite between two light sources, the apparent performance of UV LED was inferior to that of UV lamp. However, when the results were appraised on the basis of their emitting UV irradiation, the higher performance was achieved by UV LED than by UV lamp. This study demonstrates that environmentally friendly process of goethite-catalytic photo-oxidation without any addition of foreign catalyst is feasible for the reduction of arsenite in groundwater containing naturally-occurring goethite. In addition, this study confirms that UV LED can be used in the photo-oxidation of arsenite as an alternative light source of UV lamp to remedy the drawbacks of UV lamp, such as long stabilization time, high electrical power consumption, short lifespan, and high heat output requiring large cooling facilities.