• The Korean Journal of Ecology
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• v.24 no.2
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• pp.93-100
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• 2001

One-year-old cottonwood (Populus deltoides Bartr.) clones, which were classified as sensitive or tolerant, were exposed to 150 n1/1 ozone (O$_3$) over 8 days for 8 hours each day under glass chamber conditions with natural sunlight. The leaves of the sensitive clone had black stipple and bifacial necrosis after $O_3$ treatment. Photosynthesis and stomatal conductance were measured before, during, and after the $O_3$ treatment. The photosynthetic rates due to $O_3$ treatment were decreased 51 percent and 34 percent on the sensitive and tolerant clone, respectively. The stomatal conductance of the sensitive clone was more than 40 percent higher than that of the tolerant clone regardless of the $O_3$ treatment. As light intensity increased, the $O_3$ effect on photosynthesis was clear. Compared to the previous growth chamber studies, our natural light exposure system was able to maintain a stable photosynthetic responses of the control treatment throughout the fumigation period. In addition, changes in assimilation versus intercellular $CO_2$ concentration (A/C curves) showed that $O_3$ decreased the slope and asymptote of the curves for the sensitive clone. This indicates that $O_3$ decreases the biochemical capacity of photosynthesis on the sensitive clone. Chlorophyll contents and fluorescence of the two clones were analyzed to examine the $O_3$ effects on photosystem 11, but $O_3$ did not impact these variables on either clone. Although the tolerant clone did not show any foliar injury, we could not find any ecophysiological defensive responses to $O_3$ treated. Stomatal conductance of the tolerant clone was originally much lower than that of the sensitive one. Thus, the mechanisms of the tolerant clone in this system are to narrowly open stomata and efficiently maintain photosynthesis with a more durable biochemical apparatus of photosynthesis under $O_3$ stress. The sensitive clone has higher photosynthetic capacity and more efficient light reaction activity than the tolerant one under charcoal filtered condition, but is not as resilient under stress.

• The korean journal of orthodontics
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• v.26 no.4
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• pp.359-371
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• 1996

The purpose of this study was to investigate the changes about the cellular activity on DNA synthesis in the periodontal ligament of dog, in which experimental tooth movement was performed. A control and 5 experimental dogs, one and half year in age, were studied. Light force (50-75g) was applied by placing open-coil spring between left mandibular premolars ; heavy force (250-300g), between right mandibular premolars. Experimental dogs were sacrificed after infusion of bromodeoxyuridine(BrdU), at 12 hours, 1, 3, 7 and 14 days after force application, respectively. And the histologic and the immunohistochemical evaluation were performed on the obtained periodontal tissue around mandibular premolars, using anti-romodeoxyuridine antibody, which can indicate proliferating cells. The results were as follows: 1. The tearing of periodontal ligament and the vascular dilatation at tension side were observed in 12 hours, increasing until 3 days. After then it decreased; Such a finding was more evident in heavy force group than in light force group. 2. The hyalinization of the periodontal ligament and the activity of osteoclast at pressure side were observed in 12 hours, increasing until 3 days. But from 7 days on, it decreased; Such a finding was more evident in heavy force group than in light force group. 3. The BrdU expression in the control group was positive, mainly in the oral epithelium and the fibroblasts in the periodontal ligament, but negative in bone cells in periodontal ligament. 4. The BrdU expression in the experimental group was more positive in tension side than in pressure side; The expression was a little more positive in the periapical area than in the cervical area of tooth. 5. The BrdU expression in light force group was the highest in 1 day, after which it decreased; In heavy force group, it was the highest in 12 hours, after which it decreased. But in 14 days, there was no difference between the experimental group and control group.

• Journal of the Korean Home Economics Association
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• v.35 no.3
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• pp.193-204
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• 1997

The purpose of this study is to measure some physical environmental factors and to doucument students' perceptions of them. 11 middle schools in Cheju City were divided into four areas according to their locations and two schools were selected for the study. 144 thirteen-year-old students in two middle school in a overcrowded area in Cheju City-one middle school building is insulated and the other is not insulated-were taken for the questionnaire survey. The finding of the study are as follows: 1) The classrooms were not equipped with any heating equipment. The buildings are not insulated well. As a result, the room temperature was much lower(12.9-16.2℃) than comfortable indoor temperature in winter(21.5-24.5℃). The classroom were found to be colder(12.9-16.2℃) than usual pleasant indoor temperature(21.5-24.5℃) in winter. 2) The classroom were so far from the street(20m) that there was little noise from traffic. Nevertheless, the noise level was higher(62.5-66.2 dB(A), when the windows were open; 51.7-62.8dB(A), when closed than the noise tolerance level specified in the Environment Protection Laws(50.0dB(A)). 3) As for the visual environment, the location of classroom, the adequate sun exposure, and the total states of windows in classrooms influenced on the illuminance. While standard indoor illuminance is 300 Lux, the classrooms facing south had illuminance of 231 Lux, from day light: and the ones facing west, 380 Lux. 4) Students generally found other aspects of the physical environment of their classrooms unsatisfactory. Chalk dust was generated to a serious extent near the main chalkboard(0.25mg/㎥) of classrooms.

• Journal of the Korean Solar Energy Society
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• v.22 no.3
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• pp.47-56
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• 2002

The office is an excellent candidate for implementing daylighting techniques because of the relatively high electric lighting power densities and long daytime use pattern. The quantity of light available for a space can be translated in term of the amount of energy savings through a process of a building energy simulation. To get significant energy savings in general illumination, the electric lighting system must be incorporated with a daylight - activated dimmer control. A prototype configuration of an office interior has been established and the integration between the building envelope and lighting and HVAC systems is evaluated based on computer modeling of a lighting control facility. First of all, an energy-efficient luminaire system is designed for both a totally open-plan office interior and a partitioned office. A lighting design and analysis program, Lumen-Micro 2000 predicts the optimal layout of a conventional fluorescent lighting fixture to meet the designed lighting level and calculates unit power density, which translates the demanded amount of electric lighting energy. A dimming control system integrated with the contribution of daylighting has been applied to the operating of the artificial lighting. Annual cooling load due to lighting and the projecting saving amount of cooling load due to daylighting under overcast diffuse sky are evaluated by a computer software, ENER-Win. In brief, the results from building energy simulation with measured daylight illumination levels and the performance of lighting control system indicate that daylighting can save over 70 percent of the required energy for general illumination in the perimeter zones through the year. A 25 % of electric energy for cooling may be saved by dimming and turning off the luminaires in the perimeter zones.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of Korean Academy of Nursing
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• v.12 no.2
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• pp.1-26
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• 1982

The main purpose of this study was to test the effect of the structured information on the sleep amount of the patients undergoing open heart surgery. This study has specifically addressed to the Following two basic research questions: (1) Would the structed in formation influence in the reduction of sleep disturbance related to anxiety and Physical stress before and after the operation? and (2) that would be the effects of the structured information on the level of preoperative state anxiety, the hormonal change, and the degree of behavioral change in the patients undergoing an open heart surgery? A Quasi-experimental research was designed to answer these questions with one experimental group and one control group. Subjects in both groups were matched as closely as possible to avoid the effect of the differences inherent to the group characteristics, Baseline data were also. collected on both groups for 7 days prior to the experiment and found that subjects in both groups had comparable sleep patterns, trait anxiety, hormonal levels and behavioral level. A structured information as an experimental input was given to the subjects in the experimental group only. Data were collected and compared between the experimental group and the control group on the sleep amount of the consecutive pre and post operative days, on preoperative state anxiety level, and on hormonal and behavioral changes. To test the effectiveness of the structured information, two main hypotheses and three sub-hypotheses were formulated as follows; Main hypothesis 1: Experimental group which received structured information will have more sleep amount than control group without structured information in the night before the open heart surgery. Main hypothesis 2: Experimental group with structured information will have more sleep, amount than control group without structured information during the week following the open heart surgery Sub-hypothesis 1: Experimental group with structured information will be lower in the level of State anxiety than control group without structured information in the night before the open heart surgery. Sub-hypothesis 2 : Experimental group with structured information will have lower hormonal level than control group without stuctured information on the 5th day after the open heart surgery Sub-hypothesis 3: Experimental group with structured information will be lower in the behavioral change level than control group without structured information during the week after the open heart surgery. The research was conducted in a national university hospital in Seoul, Korea. The 53 Subjects who participated in the study were systematically divided into experimental group and control group which was decided by random sampling method. Among 53 subjects, 26 were placed in the experimental group and 27 in the control group. Instruments; (1) Structed information: Structured information as an independent variable was constructed by the researcher on the basis of Roy's adaptation model consisting of physiologic needs, self-concept, role function and interdependence needs as related to the sleep and of operational procedures. (2) Sleep amount measure: Sleep amount as main dependent variable was measured by trained nurses through observation on the basis of the established criteria, such as closed or open eyes, regular or irregular respiration, body movement, posture, responses to the light and question, facial expressions and self report after sleep. (3) State anxiety measure: State Anxiety as a sub-dependent variable was measured by Spi-elberger's STAI Anxiety scale, (4) Hormornal change measure: Hormone as a sub-dependent variable was measured by the cortisol level in plasma. (5) Behavior change measure: Behavior as a sub-dependent variable was measured by the Behavior and Mood Rating Scale by Wyatt. The data were collected over a period of four months, from June to October 1981, after the pretest period of two months. For the analysis of the data and test for the hypotheses, the t-test with mean differences and analysis of covariance was used. The result of the test for instruments show as follows: (1) STAI measurement for trait and state anxiety as analyzed by Cronbachs alpha coefficient analysis for item analysis and reliability showed the reliability level at r= .90 r= .91 respectively. (2) Behavior and Mood Rating Scale measurement was analyzed by means of Principal Component Analysis technique. Seven factors retained were anger, anxiety, hyperactivity, depression, bizarre behavior, suspicious behavior and emotional withdrawal. Cumulative percentage of each factor was 71.3%. The result of the test for hypotheses show as follows; (1) Main hypothesis, was not supported. The experimental group has 282 minutes of sleep as compared to the 255 minutes of sleep by the control group. Thus the sleep amount was higher in experimental group than in control group, however, the difference was not statistically significant at .05 level. (2) Main hypothesis 2 was not supported. The mean sleep amount of the experimental group and control group were 297 minutes and 278 minutes respectively Therefore, the experimental group had more sleep amount as compared to the control group, however, the difference was not statistically significant at .05 level. Thus, the main hypothesis 2 was not supported. (3) Sub-hypothesis 1 was not supported. The mean state anxiety of the experimental group and control group were 42.3, 43.9 in scores. Thus, the experimental group had slightly lower state anxiety level than control group, howe-ver, the difference was not statistically significant at .05 level. (4) Sub-hypothesis 2 was not supported. . The mean hormonal level of the experimental group and control group were 338 ㎍ and 440 ㎍ respectively. Thus, the experimental group showed decreased hormonal level than the control group, however, the difference was not statistically significant at .05 level. (5) Sub-hypothesis 3 was supported. The mean behavioral level of the experimental group and control group were 29.60 and 32.00 respectively in score. Thus, the experimental group showed lower behavioral change level than the control group. The difference was statistically significant at .05 level. In summary, the structured information did not influence the sleep amount, state anxiety or hormonal level of the subjects undergoing an open heart surgery at a statistically significant level, however, it showed a definite trends in their relationships, not least to mention its significant effect shown on behavioral change level. It can further be speculated that a great degree of individual differences in the variables such as sleep amount, state anxiety and fluctuation in hormonal level may partly be responsible for the statistical insensitivity to the experimentation.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.163-169
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• 2024

India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.17 no.1
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• pp.13-20
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• 2007

This study was performed to investigate the concentrations of PM($PM_{10}$, $PM_{2.5}$, $PM_{1}$) and it's affecting factors in the subway from line 1 to line 8 in Seoul metropolitan area, from Sep. 1 to 30, 2005. PM concentrations were measured at the entrances and centers in subway passenger cabins by a light scattering equipment. And the affecting factors to PM were estimated based on the number of passenger, door open and close and running area etc. The geometric means of $PM_{10}$, $PM_{2.5}$ and $PM_{1}$ concentration in Seoul subway passenger cabins were $214{\mu}g/m^3$, $86.6{\mu}g/m^3$ and $27.0{\mu}g/m^3$, respectively. These mean concentrations in subway carriage were higher when it ran on an underground track than on a ground track. And running time(7AM-9AM, 11AM-13PM, 6PM-8PM) significantly influenced to the concentrations of $PM_{10}$, $PM_{2.5}$ and $PM_{1}$. Daily profile of $PM_{10}$ and $PM_{2.5}$, $PM_{1}$ expressed as an 10 minutes average, showed similar variation pattern over day period. In correlation analysis, significant relations among $PM_{10}$, $PM_{2.5}$ and $PM_{1}$ were detected(p〈0.01). In particular, correlation coefficient between $PM_{10}$and $PM_{1}$ was highly significant(r=0.94). Further study is needed to identity the sources of PM in subway cabins and to compare pollutants concentration among subway lines.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.103-138
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• 2009

In this article we examine a unique data set of intraday fair disclosure(FD) releases to shed light on market efficiency within the trading day. Specifically, this paper analyze the response of stock prices on fair disclosure disseminated in real-time through KIND(Korea Investor's Network for Disclosure) on Korea stock exchange during the period from January 2003 to September 2004. We find that the prices of stock experiences a statistically and economically significant increase beginning seconds after the fair disclosure is initially announced and lasting approximately two minutes. The stock price responds more strongly to fair disclosure on smaller firm but the response to fair disclosure on the largest firm stock is more gradual, lasting five minutes. We also examine the profitability of a short-term trading strategy based on dissemination of fair disclosure. After controlling for trading costs we find that trader who execute a trade following initial disclosure generate negative profits, but trader buying stock before initial disclosure realize statistically significant positive profit after two minute of disclosure. Summarizing overall results, our evidence supports that security prices on Korea stock exchange reflects all available information within two minutes and the Korea stock market is semi-strongly efficient enough that a trader cannot generate profits based on widely disseminated news unless he acts almost immediately.