• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.4
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• pp.425-434
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• 2022

Objectives: This study analyzes TVOC concentrations in root industry workplaces in order to prevent probable occupational disease among workers. Root industry includes all the infrastructure of manufacturing, such as casting and molding. Methods: Real-time TVOC sensors were deployed in three root industry workplaces. We measured TVOC concentrations with these sensors and analyzed the results using a data-analysis tool developed with Python 3.9. Results: During the study period, the mean of the TVOC concentrations remained in an acceptable range, 0.30, 2.15, and 1.63 ppm across three workplaces. However, TVOC concentrations increased significantly at specific times, with respective maximum values of 4.98, 28.35, and 26.65 ppm for the three workplaces. Moreover, the analysis of hourly TVOC concentrations showed that during working hours or night shifts TVOC concentrations increased significantly to higher than twice the daily mean values. These results were scrutinized through classical decomposition results and autocorrelation indices, where seasonal graphs of the corresponding classical decomposition results showed that TVOC concentrations increased at a specific time. Trend graphs showed that TVOC concentrations vary by day. Conclusions: Deploying a real-time TVOC sensor should be considered to reflect irregularly high TVOC concentrations in workplaces in the root industry. It is expected that the real-time TVOC sensor with the presented data analysis methodology can eradicate probable occupational diseases caused by detrimental gases.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.357-376
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• 2022

This study examines circulation status and trends of a public library during three year periods from January 2019 to December 2021. There was a statistically significant difference in the mean number of circulation between the pre-Covid-19 period and the Covid-19 period, and the Covid-19 period and the Covid-19 recovery period. However, no significant difference was found between the pre-Covid-19 period and the Covid-19 recovery period. Across three years, there was a significant difference in the distribution of circulation per month. Circulation distribution was also significantly different among different days of the week and different hours of the day. Monthly circulation distribution and hourly circulation distribution during the pre-Covid-19 period was similar to those of the Covid-19 recovery period, whereas those of the Covid-19 period differed from the pre-Covid-19 period and the Covid-19 recovery period. It is expected that the results of this study could contribute to the collection development, and the management and improvement of services of public libraries. It is also expected that the results of this study could contribute to the prediction of circulation patterns and information needs of public library users.

• Atmosphere
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• v.32 no.2
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• pp.119-133
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• 2022

From 2015 to 2021, high-concentration fine dust episodes with a daily average PM_2.5 concentration of 50 ㎍ m^-3 or higher were selected and classified into 3 types [long range transport (LRT), mixed (MIX) and Local emission and stagnant (LES)] using synoptic chart and backward trajectory analysis. And relationships between the fine particle data (PM_2.5 and PM₁₀ concentration and PM_2.5/PM₁₀ ratio) and meteorological data (PBLH, Ta, WS, U-wind, and Rainfall) were analyzed using hourly observation for the classification episodes on the Korean Peninsula and the Seoul metropolitan area (SMA). In LRT, relatively large particles such as dust are usually included, and in LES, fine particle is abundant. In the Korean peninsula, the rainfall was relatively increased centered on the middle and western coasts in MIX and LES. In the SMA, wind speed was rather strong in LRT and weak in LES. In LRT, rainfall was centered in Seoul, and in MIX and LES, rainfall appeared around Seoul. However, when the dust cases were excluded, the difference between the LRT and other types of air quality was decreased, but the meteorological variables (Ta, RH, Pa, PBLH, etc.) were further strengthened. In the case of the Korean Peninsula, it is difficult to find a clear relationship because regional influences (topographical elevation, cities and coasts, etc.) are complexly included in a rather wide area. In the SMA, it is analyzed that the effects of urbanization such as the urban heat island centered on Seoul coincide with the sea and land winds, resulting in a combination of high concentrations and meteorological phenomena.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.83-92
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• 2021

There are continuous and tremendous attempts to apply various sensor systems and ICTs into the dairy science for data accumulation and improvement of dairy productivity. However, these only concerns the fields which directly affect to the dairy productivity such as the number of individuals and the milk production amount, while researches on the physiology aspects of dairy cows are not enough which are fundamentally involved in the dairy productivity. This paper proposes the basic approach for extraction of daily behavior pattern from hourly behavioral data of dairy cows to identify the health status and stress. Total four clusters were grouped by k-means clustering and the reasonability was proved by visualization of the data in each groups and the representatives of each groups. We hope that provided results should lead to the further researches on catching abnormalities and disease signs of dairy cows.

• KNOM Review
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• v.24 no.1
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• pp.20-28
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• 2021

Extensive use of social media applications and mobile devices continues to increase data traffic. Social media applications generate an endless and massive amount of multimedia traffic, specifically video traffic. Many social media platforms such as YouTube, Daily Motion, and Netflix generate endless video traffic. On these platforms, only a few popular videos are requested many times as compared to other videos. These popular videos should be cached in the user vicinity to meet continuous user demands. MEC has emerged as an essential paradigm for handling consistent user demand and caching videos in user proximity. The problem is to understand how user demand pattern varies with time. This paper analyzes three publicly available datasets, MovieLens 20M, MovieLens 100K, and The Movies Dataset, to find the user request pattern over time. We find hourly, daily, monthly, and yearly trends of all the datasets. Our resulted pattern could be used in other research while generating and analyzing the user request pattern in MEC-based video caching scenarios.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.393-417
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• 2022

Using hourly SMP data from 2016 to 2020, this paper measures the weekly realized volatility and investigates the main force of its determinants. To this end, we extend the Bayesian variable selection by incorporating the regime-switching model which identifies important variables among a large number of predictors by regimes. We find that the increase in coal and nuclear generation, as well as solar power, reinforce the SMP volatility in both high volatility and low volatility regime. In contrast the increase in gas generation and gas price decrease SMP volatility when SMP volatility is high. These results suggest that the expansion of renewable energy according to 2050 Carbon Neutrality or energy transition policies increases SMP volatility but the increase in the gas generation or reduction of coal generation might offset its impact.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.409-417
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• 2022

The International Association of Lighthouse Authorities (IALA) utilizes a questionnaire to investigate the status of Aids to Navigation (AtoN) around the world. However, results of the IALA questionnaire have limited use because respondent understanding is inconsistent. In addition, there is uncertainty regarding the appropriateness of the questionnaire content. Furthermore, the overall response rate is low. Therefore, the status of AtoN is not clearly understood. AtoN data from around the world are generated hourly. Thus, big data solutions are required to effectively exploit the information. Digitization of analog data is an important component of building big data. Hence, the IALA has developed a Maritime Resource Name (MRN) scheme and an information exchange standard. Here, we used the AtoN information exchange standard and designed an S-201-based big data construction process that could collect and manage global AtoN information. In this study, construction of an IALA AtoN portal was proposed as the core of the construction of the AtoN big data. The process was divided into three stages. IALA AtoN portal is developed by IALA with the goal to provide various meaningful statistical analysis results based on AtoN data while managing AtoN information around the world based on S-201. If an AtoN portal capable of constructing S-201-based big data is developed, then a data collection and storage system that can gather basic S-201 AtoN data from the IALA and global AtoN management agencies could be achieved. Furthermore, insightful statistical analysis of AtoN status worldwide and changes in manufacturing technology will be possible.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.141-163
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• 2022

This paper empirically analyzes the effect of renewable electricity generation on the System Marginal Price (SMP) in Korea. Using an ARX-GARCHX model with hourly data from 2016 to 2020, we evaluate SMP determinants and merit order effects. As a result, we find that solar and wind power, as well as gas price and total load, play a critical role in the SMP. In particular, solar power reduces the SMP level but raises volatility during peak and off-peak periods. This result implies that SMP may fall as renewable electricity generation increases, leading to a decrease in the profitability of existing power plants and investment in renewables. On the other hand, even if the subsidy of renewable energy increases the burden on the SMP, it can be offset by the merit order effect, which lowers the SMP.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.3
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• pp.149-165
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• 2022

The water consumption data of individual consumers must be analyzed and forecast to establish an effective water demand management plan. A k-mean cluster model that can monitor water use characteristics based on hourly water consumption data measured using automated meter reading devices and demographic factors is developed in this study. In addition, the quantification model that can estimate the daily water consumption is developed. K-mean cluster analysis based on the four clusters shows that the average silhouette coefficient is 0.63, also the silhouette coefficients of each cluster exceed 0.60, thereby verifying the high reliability of the cluster analysis. Furthermore, the clusters are clearly classified based on water usage and water usage patterns. The correlation coefficients of four quantification models for estimating water consumption exceed 0.74, confirming that the models can accurately simulate the investigated demographic data. The statistical significance of the models is considered reasonable, hence, they are applicable to the actual field. Because the use of automated smart water meters has become increasingly popular in recent year, water consumption has been metered remotely in many areas. The proposed methodology and the results obtained in this study are expected to facilitate improvements in the usability of smart water meters in the future.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1264-1264
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• 2001

The affect of surface temperatures of fruits on spectrum which measures actual sugar contents was observed. PLSR was applied to develop the sugar content evaluation system that was not affected by temperature. The reflected spectrum was used at the wavelengths of 654 and 1052nm with the separation distance of 2.5nm. To increase the conformance of a model using unknown samples, let the minimum value of PRESS be an optimum factor. 71 Shingo pears stored in a refrigerator were left in a room temperature for a while and these temperatures and reflected spectrums were measured. Reflected spectrums were measured at the wavelengths of 654 and 1052nm, 3 samples in one second. To measure these at different temperatures, the experiment was repeated hourly and four times. Starting temperatures of 2-3 were increased up to 17. The total number of measured spectrum was 284. To develop a sugar content evaluation system model using measured reflected spectrum, three groups of samples were considered. First group had 51 samples at 14 and second group had 141 samples with lower or higher temperatures than 14. Third group had 155 samples with well distributed temperatures. Other samples were used as validations to ensure the conformance. Measuring the sugar contents of samples with surface temperatures other than 14 were difficult with PLS model I, developed by using a sample temperature of 14. If the sugar contents were compensated using samples' temperatures, results of prediction would be close to the expected results and it would be one of the most important factors to develop this system. PLS models I and II could compensate the temperature but the precision would not come up to the standard. High precision was expected by using samples with wide ranges of temperatures and sugar contents. Both models showed the possibility of an improvement of a sugar content evaluation system disregarding the temperature. For practical use of a system, selecting samples should be done carefully to reduce the effect of the temperature.