• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.1
• /
• pp.135-144
• /
• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Atmosphere
• /
• v.24 no.3
• /
• pp.433-444
• /
• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• Journal of the East Asian Society of Dietary Life
• /
• v.17 no.3
• /
• pp.393-401
• /
• 2007

This study was performed to investigate the antioxidant activity of Korean ginseng using an ORAC(Oxygen Radical Absorbance Capacity) assay. Four fractions each (80% ethanol, ethyl acetate, water saturated 1-butanol, and water) were obtained from different ginseng samples (White Ginseng: ; 6 yrs-., 5 yrs-., ; Cork Ginseng: ; 5 yrs-., 4 yrs-.). The saponin content of each fraction was quantified by LC/MS, and the antioxidant capacity of the ginseng was measured by the ORAC assay. The ORAC method, which was recently validated using automatic liquid handling systems, has been adapted for manual handling with the use of a conventional fluorescence microplate reader. Furthermore, the ORAC assay provides a direct measure of hydrophilic chain-breaking antioxidant capacity against peroxy radical, which is the exiting and emission of 2,2'-Azobis (2-methylpropionamidine)-dihychloride (AAPH). As a result of our experiments, ginsenosides Rg1 and Rb1 were the two major saponins found in the ginseng samples, and Rc, Rb2, Re, Rd, Rg3, and Rh1 were detected in a small quantities. For the antioxidant capacities of the fractions (80% ethanol, ethyl acetate, butanol, and water), we found that the organic solvent fraction had similar antioxidant capacities, and were higher than the capacity of the water fraction. When determining the similarities in each fraction, only the ethyl acetate fraction showed similarity compared to other fractions (p>0.05). The antioxidant capacity of ginseng may come from phenolic compounds and some nonpolar saponins. However, based on the results of this study, we hypothesize that some acidic polysaccharides and other biological components may contribute to its antioxidant capacity. Additional research is required to determine other possible biological response modifiers that contribute to the antioxidant capacity of ginseng.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.5
• /
• pp.416-422
• /
• 2016

Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.

• Agricultural and Biosystems Engineering
• /
• v.4 no.1
• /
• pp.8-15
• /
• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

• Korean Chemical Engineering Research
• /
• v.53 no.5
• /
• pp.553-556
• /
• 2015

The usage of the correct combustion characteristic of the treated substance for the safety of the process is critical. For the safe handling of dimethylacetamide (DMAc) being used in various ways in the chemical industry, the flash point and the autoignition temperature (AIT) of DMAc was experimented. And, the lower explosion limit of DMAc was calculated by using the lower flash point obtained in the experiment. The flash points of DMAc by using the Setaflash and Pensky-Martens closed-cup testers measured $61^{\circ}C$ and $65^{\circ}C$, respectively. The flash points of DMAc by using the Tag and Cleveland automatic open cup testers are measured $68^{\circ}C$ and $71^{\circ}C$. The AIT of DMAc by ASTM 659E tester was measured as $347^{\circ}C$. The lower explosion limit by the measured flash point $61^{\circ}C$ was calculated as 1.52 vol%. It was possible to predict lower explosion limit by using the experimental flash point or flash point in the literature.

• Fire Science and Engineering
• /
• v.29 no.4
• /
• pp.21-25
• /
• 2015

The usage of the correct combustion characteristics of the treated substance for the safety of the process is critical. For the safe handling of bromobenzene being used in various ways in the chemical industry, the flash point and the autoignition temperature (AIT) of bromobenzene was experimented. And, the lower explosion limit of bromobenzene was calculated by using the lower flash point obtained in the experiment. The flash points of bromobenzene by using the Setaflash and Pensky-Martens closed-cup testers measured $44^{\circ}C$ and $50^{\circ}C$, respectively. The flash points of bromobenzene by using the Tag and Cleveland automatic open cup testers are measured $56^{\circ}C$ and $64^{\circ}C$. The AIT of bromobenzene by ASTM 659E tester was measured as $573^{\circ}C$. The lower explosion limit by the measured flash point $44^{\circ}C$ was calculated as 1.63 Vol%. It was possible to predict lower explosion limit by using the experimental flash point or flash point in the literature.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.29 no.1
• /
• pp.423-428
• /
• 2005

Due to the fast growing rate of the global container trade, every major port is under the pressure of meeting the projected capacity demand. As a result, alternative solutions have been sought for improving capacity and meeting the growing demand for container storage area and terminal capacity. Moreover, material handling process re-engineering is now a critical issue for logistics and supply chain managers of airline, shipping lines, terminal and warehousing enterprises around the world. Therefore, the purpose of this paper is to develop the 3D simulator for executing performance valuation of port transportation systems. The developed 3D simulator system is to measure the effectiveness of the proposed total system and compare it with existing practices. The performance analysis variables are also defined for these comparisons.

• Journal of Navigation and Port Research
• /
• v.29 no.1 s.97
• /
• pp.29-34
• /
• 2005

A mis-handling of the ship operators, treated as one qf the main causes of a ship accidents, normally has caused a ship to collide with obstacles like a reef, a rock and other ships etc. since their ability has been declining little by little even though the port conditions have been getting worse. The ship needs a highly sophisticated technology as her size and speed increase as the ship have been demanded. For example, Auto Avoidance Control System gradually has been receiving a growing interest to control the entire ship safely. From that purpose, this research has been done. The research was based on the MMG mathematical model, used Surge-Sway-Yaw-Roll motion equation and Fuzzy theory for calculating the collision-risk Also the research successively was done when the ship encountered continual multitude ships.

• Journal of KIISE:Software and Applications
• /
• v.35 no.2
• /
• pp.59-69
• /
• 2008

Automatic obfuscation is known to be the most viable method for preventing reverse engineering intentional1y making code more difficult to understand for security purposes. In this paper, we study and implement an obfuscation method for protecting MS Visual C++ programs against attack on the intellectual property in software like reverse engineering attack. That is, the paper describes the implementation of a code obfuscator, a tool which converts a Visual C++ source program into an equivalent one that is much harder to understand. We have used ANTLR parser generator for handling Visual C++ sources, and implemented some obfuscating transformations such as 'Remove comments', 'Scramble identifiers', 'Split variables', 'Fold array', 'Insert class', 'Extend loop condition', 'Add redundant operands', and 'Insert dead code'. We have also evaluated the performance and effectiveness of the obfuscator in terms of potency, resilience, and cost. When the obfuscated source code has been compared with the original source code, it has enough effectiveness for software protection though it incurs some run-time overheads.