• Journal of the Korean Wood Science and Technology
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• v.51 no.4
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• pp.295-308
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• 2023

This study applied a real-time IoT (Internet of Things) environmental monitoring system to wooden cultural heritages (WCHs) located in suburbs and forests in Korea. It automated the graphs of seasonal Temperature (T) and relative humidity (RH) changes inside the heritage structures and seasonal Performance Index (PI) values. While utilizing line graphs of the existing T and RH change trends and a bar graph expressing the PI values, this study examined the current status of the conservation environment inside the WCHs throughout the year and its diagnosis. Consequently, at higher latitudes, the organic cultural heritage repeatedly experienced large T fluctuations, and the risk of physical and chemical degradation of the materials was greater. However, the RH showed significant seasonal differences, even within the same latitude, indicating that the impact of latitude was not significant. Therefore, the staff in charge must manage RH by considering the surrounding environmental conditions and adjusting the internal environment of the structures. The PI values for the year-round T and RH inside the heritages were confirmed to only be a maximum of approximately 60% of the environmental suitability for conservation throughout the year, depending on the season. The relationship between the germination and growth potential period of xerophilic fungi and the monthly internal temperature and humidity in five heritages located at different latitudes was analyzed. As a result, we could thus determine that four particular months of the year (June-September) represent the periods with the highest risk of damage from xerophilic fungi in the country, regardless of latitude.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.4
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• pp.439-446
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• 2023

Objectives: The aims of this study are to investigate how X-rays are emitted to surrounding parts during the ion implantation process, to analyze these emissions in relation to the properties of the ion implanter equipment, and to estimate the resulting exposure dose. Eight ion implanters equipped with high-voltage electrical systems were selected for this study. Methods: We monitored X-ray emissions at three locations outside of the ion implanters: the accelerator equipped with a high-voltage energy generator, the impurity ion source, and the beam line. We used a Personal Portable Dose Rate and Survey Meter to monitor real-time X-ray levels. The SX-2R probe, an X-ray Features probe designed for use with the Radiagem^TM meter, was also utilized to monitor lower ranges of X-ray emissions. The counts per second (CPS) measured by the meter were estimated and then converted to a radiation dose (𝜇Sv/hr) based on a validated calibration graph between CPS and μGy/hr. Results: X-rays from seven ion implanters were consistently detected in high-voltage accelerator gaps, regardless of their proximity. X-rays specifically emanated from three ion implanters situated in the ion box gap and were also found in the beam lines of two ion implanters. The intensity of these X-rays did not show a clear pattern relative to the devices' age and electric properties, and notably, it decreased as the distance from the device increased. Conclusions: In conclusion, every gap, in which three components of the ion implanter devices were divided, was found to be insufficiently shielded against X-ray emissions, even though the exposure levels were not estimated to be higher than the threshold.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.95-101
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• 2024

The numberlink puzzle(NLP), which non-crossings with other numbers of connection in connecting lines through empty cells between a given pair of numbers, is an NP-complete problem with no known way to solve the puzzle in polynomial time. Until now, arbitrary numbers have been selected and puzzles have been solved using trial-and-error methods. This paper converts empty cells into vertices in lattice graphs connected by edge between adjacent cells for a given problem. Next, a straight line was drawn between the pairs of numbers and divided into groups of numbers where crossing occurred. A bypass route was established to avoid intersection in the cross-number group. Applying the proposed algorithm to 18 benchmarking data showed that the puzzle could be solved with a linear time complexity of O(n) for all data.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.91-121
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• 2008

Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.

• Journal of Korean Society of Forest Science
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• v.90 no.3
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• pp.331-337
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• 2001

This study was performed to develope stem analysis program(Stemwin1.0) which can be used in PC with MS-Windows operating system. Stemwin1.0 uses width of annual tree ring measured with 1/100mm unit, and calculate increments of several growth factors such as DBH, height and volume with various methods. Mean DBH can be calculated by arithmetic and quadratic mean methods. Height can be estimated by parallel line, line extending and height curve methods. Volume can be estimated by Huber, Smalian, and Spline functions. Not only Total growth, Mean Annual Increment(MAI) and Current Annual Increment(CAI) of growth factors, but also merchantable volume and height, form factor, growth rate, and merchantable volume rate are automatically calculated. Stemwin1.0 can also output accurate stem taper curve with various scale, and prepare stem taper data(diameter at different disk heights) for statistical analysis for deriving stem taper model. Stemwin1.0 can export output data and graph to Excel for more compatible use of it.

• The Mathematical Education
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• v.61 no.3
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• pp.419-439
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• 2022

This study is based on Freudenthal's mathmatising process and the didactical phenomenology of linear function concept, I have described and examined the process in which students represent the constant rate of change into tables, graphs and equations and, in this way, how they construct mental objects and essence of the linear function concept. The students used the proportionality as composite units, when they represented the phenomenon with constant rate of change into tables. When representing in graphs, all but one student represented it into a line. There were differences among the students in the level they were using the given conditions, co-variation perspective, and corresponding rules when formulating equations. The students compared the relationship between two variables in a multiplicative way, and under the guidance of teachers they reached to the understanding that its relationship becomes a constant. Moreover, they could construct mental objects of a constant rate of change, understanding the situation where the relationship between time difference and distance difference becomes one value, namely speed. The students had difficulties in connecting the rate of change with the inclination of a line. The students constructed the essence (concept) of linear functions, after building and organizing the image that the rate of change is constant, the graph is linear, and the equation is formulated as y=ax+b (a: inclination, b: intercept).

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• Radiation Oncology Journal
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• v.23 no.1
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• pp.51-60
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• 2005

Purpose : Selective inhibition of multiple molecular targets may improve the antitumor activity of radiation. Two specific inhibitors of selective cyclooxygenase-2 (COX-2) and epidermal growth factor receptor (EGFR) were combined with radiation on the HeLa cell line. To investigate cooperative mechanism with selective COX-2 inhibitor and EGFR blocker, in vitro experiments were done. Materials and Methods : Antitumor effect was obtained by growth inhibition and apoptosis analysis by annexin V-Flous method. Radiation modulation effects were determined by the clonogenic cell survival assay. Surviving fractions at 2 Gy ($SF_2$) and dose enhancement ratio at a surviving fraction of 0.25 were evaluated. To investigate the mechanism of the modulation of radiosensitivity, the cell cycle analyses were done by flow cytometry. The bcl-2 and bax expressions were analyzed by western blot. Results : A cooperative effect were observed on the apoptosis of the HeLa ceil line when combination of the two drugs, AG 1478 and NS 398 with radiation at the lowest doses, apoptosis of $22.70\%$ compare with combination of the one drug with radiation, apoptosis of $8.49\%$. In cell cycle analysis, accumulation of cell on $G_0/G_l$ phase and decrement of S phase fraction was observed from 24 hours to 72 hours after treatment with radiation, AG 1478 and NS 398. The combination of NS 398 and AG 1478 enhanced radiosensitivity on a concentration-dependent manner in HeLa cells with dose enhancement ratios of 3.00 and $SF_2$ of 0.12 but the combination of one drug with radiation was not enhanced radlosensitivity with dose enhancement ratios of 1.12 and SF2 of 0.68 (p=0.005). The expression levels of bcl-2 and bax were reduced when combined with AG 1478 and NS 398. Conclusion : Our results indicate that the selective COX-2 inhibitor and EGFR blocker combined with radiation have potential additive or cooperative effects on radiation treatment and may act through various mechanisms including direct inhibition of tumor cell proliferation, suppression of tumor cell cycle progression and inhibition of anti-apoptotic proteins.

• Journal of agricultural medicine and community health
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• v.30 no.2
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• pp.127-135
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• 2005

Objectives: This study was conducted to investigate the trend of tuberculosis mortality rate by years and by areas. Methods: We calculated raw and age-adjusted mortality rate of tuberculosis from 1995 to 2002. The calculation was based on the data from resident registration data and death certification registration data gathered by 232 basic local authority. We used direct age standardization method for calculating age-adjusted mortality rate. We compared patterns of change in tuberculosis mortality rate of metropolitan areas, cities, and countryside by determinating the comparability of medels to explore linear relationship. We also analyzed the data of mortality rate between urban and rural area by comparing ANOVA and post-hoc by two periods: one from 1995 to 1998, and the other from 1999 to 2002. Results: In national mortality rate, both raw and age-adjusted mortality rate showed negative linear relationship. However, the graph become more horizontal: the slope line is close to zero. From 1995 to 1998, countryside showed significantly higher age-adjusted mortality rate than in metropolitan areas and cities. Ever after considering more horizontal graph in national mortality rate, the data shows that the countryside still have significantly higher mortality rate from 1999 to 2002. In model diagnostic checking, metropolitan areas and cities showed apparently linear pattern on the decrease of age-adjusted mortality rate. Pattern of mortality rate in countryside was decreased initially, but became flat. Conclusions: Further research is necessary to explore the characteristics of quality of tuberculosis control program in rural area. Different approach and strategies should be considered to decrease tuberculosis mortality rate in rural areas.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.281-290
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• 2020

With the spread of smartphones, services that want to use personalized data are increasing. In particular, healthcare-related services deal with a variety of data, and data visualization techniques are used to effectively show this. As data visualization techniques are used, interactions in visualization are also naturally emphasized. In the PC environment, since the interaction for data visualization is performed with a mouse, various filtering for data is provided. On the other hand, in the case of interaction in a mobile environment, the screen size is small and it is difficult to recognize whether or not the interaction is possible, so that only limited visualization provided by the app can be provided through a button touch method. In order to overcome the limitation of interaction in such a mobile environment, we intend to enable data visualization interactions through conversations with chatbots so that users can check individual data through various visualizations. To do this, it is necessary to convert the user's query into a query and retrieve the result data through the converted query in the database that is storing data periodically. There are many studies currently being done to convert natural language into queries, but research on converting user queries into queries based on visualization has not been done yet. Therefore, in this paper, we will focus on query generation in a situation where a data visualization technique has been determined in advance. Supported interactions are filtering on task x-axis values and comparison between two groups. The test scenario utilized data on the number of steps, and filtering for the x-axis period was shown as a bar graph, and a comparison between the two groups was shown as a line graph. In order to develop a natural language processing model that can receive requested information through visualization, about 15,800 training data were collected through a survey of 1,000 people. As a result of algorithm development and performance evaluation, about 89% accuracy in classification model and 99% accuracy in query generation model was obtained.