• Korean Parent-Child Health Journal
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• v.3 no.2
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• pp.18-24
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• 2000

The purpose of this research is to investigate Sleep/Activity pattern of normal neonate in Kangwon area. The subjects of this research were 23 normal neonate who visited pediatric clinic of kangneung general hospital from Jun 15, 1999 to August 10, 2000. The instrument of this research was the NCASA. The results of this research were as follows: 1. The mean time of daytime sleep was 8.21 hours. The mean time of nighttime sleep was 5.70 hours. The mean time of total daily sleep was 13.92 hours. The mean time of longest sleep period was 5.02 hours. The mean time of regularity of sleep were daytime 46.59%, nighttime 74.43%, total daily sleep 55.88%. The mean frequency of nighttime wakening was 2.03 times. 2. The each mean time of activity were daytime 7.72 hours, nighttime 2.28 hours, daily total activity 9.99 hours. The mean time of the longest activity period was 6.16 hours. The mean times of feeding frequency were daytime feeding 4.53, nighttime feeding 1.92, total daily feeding 6.45. The mean of regularity of feeding frequency was 65.71%.

• Korean Parent-Child Health Journal
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• v.3 no.1
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• pp.46-59
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• 2000

The purpose of this study is to determine whether the NCASA (Nursing Child Assessment Sleep/Activity Record) would be suitable to evaluate and to provide the basic resources for a Korean model of sleep/activity patterns during the first 6 months Korean infants' lives and to provide a basis for nursing intervention for mothers of early infants. The subjects of this study were 94 normal infants from birth to 6 months of age who visited the postpartum care center and two general hospitals located in Pusan from February 1 to April 28, 2000. The method of data collection was through convenient sampling. The instrument of this study was the NCASA translated by the Korean parent Child Health Academic Association. The collected data were analysed by mean, standard deviation, frequency percentage and ANOVA, Post Hoc test by use of SPSS/PC. The conclusions obtained from this study are summarized as follows: 1. The mean amount of daytime sleep was 8.06 hours. The mean amount of nighttime sleep was 6.31 hours. The mean amount of total daily sleep was 14.37 hours. The mean of the longest sleep period was 5.20 hours. The mean regularity of daytime sleep was 25.84%. The mean regularity of nighttime sleep was 77.69%. The mean regularity of total daily sleep was 42.60%. The mean frequency of nighttime wakenings was 2.33 times. 2. The mean amount of daytime activity was 8.25 hours. The mean amount of nighttime activity was 1.39 hours. The mean amount of daily total activity was 9.64 hours. The mean of the longest activity period was 3.80 hours The mean frequency of daytime feeding was 5.69 times. The mean frequency of nighttime feeding was 2.08 times. The mean frequency of total daily feeding was 7.74 times. The mean frequency regularity of feeding was 54.62%. The mean frequency of wakenings was 5.14 times. The mean frequency of crying was 1.90 times. 3. According to an analysis of sleep patterns based on an infant's age, there were some significant differences in the following factors: amount of daytime sleep(p<.001), amount of night time sleep(p<.05), amount of total daily sleep (p<.001), longest sleep period(p<.001), regularity of daytime sleep(p<.001), regularity of nighttime sleep(p<.01), regularity of total daily sleep(p<.001), frequency of nighttime wakenings(p<.001). 4. According to an analysis of activity patterns based on an infant's age, there were some significant differences in the following factors: amount of daytime activity(p<.001), amount of nighttime activity(p<.01), amount of total daily activity(p<.001), longest activity period(p<.05), frequency of nighttime feeding(p<.01), frequency of wakenings(p<.001). 5. The mean amount of a mother's day time was 16.30 hours. The mean amount of a mother's night time was 7.70 hours. In conclusion, the initial irregular sleeping and activity patterns of the early infant became regurized as the infant grew older and estabilished firmer patterns of sleeping and of activity.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.203-214
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• 2000

Health risk assessment is applied to streamlining LCA(Life Cycle Assessment) using Monte carlo simulation for probabilistic/stochastic exposure and risk distribution analysis caused by data variability and uncertainty. A case study was carried out to find benefits of this application. BTC(Benzene, Trichloroethylene, Carbon tetrachloride mixture alias) personal exposure cases were assumed as production worker(in workplace), manager(in office) and business man(outdoor). These cases were different from occupational retention time and exposure concentration for BTC consumption pattern. The result of cancer risk in these 3 scenario cases were estimated as $1.72E-4{\pm}1.2E+0$(production worker; case A), $9.62E-5{\pm}1.44E-5$(manger; case B), $6.90E-5{\pm}1.16E+0$(business man; case C), respectively. Portions of over acceptable risk 1.00E-4(assumed standard) were 99.85%, 38.89% and 0.61%, respectively. Estimated BTC risk was log-normal pattern, but some of distributions did not have any formal patterns. Except first impact factor(BTC emission quantity), sensitivity analysis showed that main effective factor was retention time in their occupational exposure sites. This case study is a good example to cover that LCA with probabilistic risk analysis tool can supply various significant information such as statistical distribution including personal/environmental exposure level, daily time activity pattern and individual susceptibility. Further research is needed for investigating real data of these input variables and personal exposure concentration and application of this study methodology.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.157-165
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• 2009

In this paper, we propose a distributed model that recognize ADLs of human can be occurred in daily living places. We collect and analyze user's environmental, location or activity information by simple sensor attached home devices or utensils. Based on these information, we provide a lifecare services by inferring the user's life pattern and health condition. But in order to provide a lifecare services well-refined activity recognition data are required and without enough inferred information it is very hard to build an ADL activity recognition model for high-level situation awareness. The sequence that generated by sensors are very helpful to infer the activities so we utilize the sequence to analyze an activity pattern and propose a distributed linear time inference algorithm. This algorithm is appropriate to recognize activities in small area like home, office or hospital. For performance evaluation, we test with an open data from MIT Media Lab and the recognition result shows over 75% accuracy.

• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.171-183
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• 2007

Urban transport demand is derived from activity participation. A variety of individual daily activities based on the decisions on activity participation result in collective spatial behavior. The travel derived from the effort to overcome the spatially distributed locations of adjacent activities represents the detailed structural relationships among activities. An activity-based approach provides an important framework of analyzing contemporary urban daily life in the sense that it studies the interaction between individuals' daily decision making and social practice in time and space, on the one hand, and socio-spatial environment on the other. The current study identifies representative patterns of urban daily activity implementations and analyzes the correlation between representative patterns and individuals' characteristics and contextual characteristics. The study shows that urban daily activity patterns can be grouped in a limited number of representative patterns, which are systematically correlated with socio-spatial characteristics. The results provide related transportation policy implications.

• Korean Parent-Child Health Journal
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• v.3 no.1
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• pp.60-72
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• 2000

Studies are needed to determine the standard norms for sleep/activity patterns in new born baby and there have been no established reports of discrepancy of sleep/activity patterns in new born baby among various races. The purpose of this study is to determine whether the NCASA(Nursing Child Assessment Sleep Activity Record) would be suitable to evaluate and to provide the basic resources for a Korean model of sleep/activity patterns during the new born baby, and to provide a basis for nursing intervention for mothers of new born baby. The subjects of this study were 38 normal new born baby who visited the postpartum care center and two general hospitals located in pusan from January 1 to April 28, 2000. They all agreed to participate in this study. The method of data collection was through convenient sampling. Data were collected through questionnaires including demographic data, birth hi story, and general informations concerning the infant, mother and family. The instrument of this study was the NCASA translated by the Korean parent Child Health Academic Association. The collected data were analysed by mean. standard deviation, frequency, and percentage by use of SPSS/PC. The conclusions obtained from this study are summarized as follows: 1. The mean amount of daytime sleep was 10.23 hours. The mean amount of nighttime sleep was 5.53 hours. The mean amount of total daily sleep was 15.77 hours. The mean of the longest sleep period was 4.49 hours. The mean regularity of daytime sleep was 49.69%. The mean regularity of nighttime sleep was 66.98%. The mean regularity of total daily sleep was 55.81%. The mean frequency of nighttime wakenings was 3.09 times. 2. The mean amount of daytime awake periods was 6.12 hours. The mean amount of nighttime awake periods was 2.11 hours. The mean amount of daily total awake periods was 8.23 hours. The mean of the longest awake periods was 3.76 hours. 3. The mean frequency of daytime feeding was 5.71 times. The mean frequency of nighttime feeding was 2.65 times. The mean frequency of total daily feeding was 8.36 times. The mean frequency regularity of feeding was 62.50%. 4. The mean amount of a mother's day time was 16.36 hours. The mean amount of a mother's night time was 7.64 hours. In conclusion, The new born baby slept more during the daytime compare than nighttime and more active during the daytime. On the other hand. although nighttime sleeping the length of the mother was normal, but sleep was interrupted by the infant over 3 times on average. Therefore this research study will contribute to nursing practice and nursing research by its implication through postnatal educational nursing programs at hospital and nursing intervention programs that would help individual caring of early infant mothers at home.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.115-121
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• 2020

This study aims to investigate the effects of restrictions in economic activity on the spread of COVID-19 in the Philippines. This research employs daily time-series data of confirmed new COVID-19 cases, Apple mobility trends (i.e., use of public transport to destinations, volume of people driving, and amount of walking to destinations) and Google community mobility (i.e., visits to transit stations, visits to workplaces, and staying-at-home) indicators covering the period February 17 to September 11, 2020. The analysis starts by establishing the correlation pattern of new confirmed COVID-19 daily infections to each independent variable. The results show negative linear correlation of the number of new COVID-19 daily infections with less visit to transit station, increase stay-at-home, less use of public transport, and less amount of walking to destinations. Interestingly, the number of new COVID-19 daily infections indicates some form of positive linear correlation with visits to workplaces and volume of people driving. Moreover, employing robust least square regression via the method of MM-estimation, major findings reveal that across mobility measures, staying-at-home has the highest impact on reducing the spread of COVID-19, followed by visiting transit stations less, less use of public transport, less amount of walking, and less workplace visits.

• Journal of Korean Academy of Nursing
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• v.20 no.1
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• pp.79-87
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• 1990

Clinical and epedemiologic studies of coronary heart disease(CHD)have from time to time over the last three decades found associations between prevalence of CHD and behavioral attributes and cigarette smoking. The main purpose of this study is reduced to major risk factor of coronary heart disease through prohibition of smoking and control of behavior pattern. The subjects consisted of 120 smokers and 90 non-smokers who were married men older than 30 years working in officers. The officers were surveyed by means of questionnaire September 26 through October 6, 1989. The Instruments used for this study was a self-administered measurement tool composed of 59 items was made through modifications of Jenkuns Activity Survery(JAS). The Data were analysed by SAS(Statistical Analsis System) program personal computer. The statistical technique used for this study were Frequency, x$^2$-test, t-test, ANOVA, Pearson Correlation Coefficient. The 15 items were chosen with items above 0.3 of the factor loading in the factor analysis. In the first factor analysis 19 factors were extracted and accounted for 86% of the total variance. However when the number of factors were limited to 3 in order to derive Jenkins classification, three factors were derived. There names are Job-Involvement, Speed & Impatience, Hard-Driving. Each of them includes 21 items, 21 and 9, respectively. The results of this study were as follow : 1. The score of the smoker group and non-smoker group in Job-Involvement(t＝5.7147, p＜0.0001), Speed & Impatience(t＝4.6756, p＜.0001), Hard-Driving(t＝8.0822, p＜.0001) and total type A behavior pattern showed statistically significant differences(t＝8.1224, p＜.0001). 2. The score of type A behavior pattern by number of cigarettes smoked daily were not statistically significant differences. 3. The score of type A behavior pattern by duration of smoking were not significant differences. It was concluded that the relationship between smokers and non - smokers of type A behavior pattern was statistically significant difference but number of cigarettes smoked daily and duration of smoking were not significant differences. Therefore this study is needed to adequate nursing intervention of type A behavior pattern in order to elevated to educational effect for prohibition of cigarette smoking.

• Journal of Environmental Health Sciences
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• v.37 no.2
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• pp.94-101
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• 2011

Objectives: The purpose of this study is to evaluate the noise exposures of firefighters according to their time-dependent activity patterns. Methods: Personal exposure levels were measured for six days and nights using noise dosimeters; three days and nights for on-duty tasks, the other days and nights for off-duty activities. Results: The total amount of time spent in the workplace was 13,677 min (67%), outside areas 4,833 min (23%), in transit 1,002 min (5%), and other indoor area 807 min (4%) during a working period. However, during off-days they spent 10,858 min (76%) at home, 1,382 min (10%) outdoors, 1,225 min (9%) other indoors, and 493 min (3%) in transit. As a result of individual exposure levels, TWA did not exceed 90 dBA of the occupational exposure limit for the majority of the firefighters, whereas the levels of Lmax were 119 dBA, which were higher than the noise levels of firefighters in USA. Sometimes during dispatching the levels of Lpeak exceeded the ACGIH exposure standard (140 dBC). The Leq levels in transit were higher than the levels in home and other indoors even though the activity time is short. Conclusions: This paper characterized the noise exposure patterns of firefighters in Korea. We suggest that special noise sources, including sirens and speaker phones, should be readjusted to reduce noise exposure.