• Journal of Korean Society on Water Environment
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• v.28 no.5
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• pp.704-716
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• 2012

This paper provides a detailed account of pilot testing conducted at South Lake Tahoe (California), the Ddukdo (Seoul) water treatment plant (WTP) and the Bokjung (Seongnam) WTP between February, 2010, and February, 2012. The objectives were first, to characterize the reactions of ozone with hydrogen peroxide (Peroxone) for Han River water following sand filtration, second to determine empirical ozone and hydrogen peroxide doses to remove a taste-and-odor surrogate 2-methylisoborneol (MIB) using an advanced oxidation process (AOP) configuration and third, to determine the optimum dosing configuration to reduce residual ozone to a safe level at the exit of the process. The testing was performed in a real-time plant environment at both low- and high seasonal water temperatures. Experimental results including ozone decomposition rates were dependent on temperature and pH, consistent with data reported by other researchers. MIB in post-sand-filtration water was spiked to 40-50 ng/L, and in all cases, it was reduced to below the specified target level (7 ng/liter) and typically non-detect (ND). It was demonstrated that Peroxone could achieve both MIB removal and low effluent ozone residual at ozone+hydrogen peroxide doses less than those for ozone alone. An empirical predictive model, suitable for use by design engineers and operating personnel and for incorporation in plant control systems was developed. Due to a significant reduction in the ozone reaction/decomposition at low winter temperatures, results demonstrate the hydrogen peroxide can be "pre-conditioned" in order to increase initial reaction rates and achieve lower ozone residuals. Results also indicate the method, location and composition of hydrogen peroxide injection is critical to successful implementation of Peroxone without using excessive chemicals or degrading performance.

• Korean Educational Research Journal
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• v.42 no.1
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• pp.1-34
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• 2021

The thesis tries to compare The Structure of World History with Anti-Oedipus in the textual context, and to re-compare in the educational context. I mean by the education an event which contrasts starkly with an essence. It adopts 5W1H, a general reporting form of an accident or event, as the distinctive features at twice comparisons. The purpose of the thesis is not evaluative but interpretive comparison. In the textual context, the thesis discusses, 1) as WHAT, the use of Marx from Kant vs. Nietzsche's point of view, 2) as WHO, the actual subjects of the exchanging human vs. the productive machine, 3) as WHEN/WHERE, the society of the modes of exchange vs. the modes of inscription, 4) as HOW, the revolutionay means of the simultaneous revolution of the world vs. the schizophrenic process, 5) as WHY, the ideal subjects of the associative human vs. the non-human of liberation of desire. In the educational context, the thesis discusses, 1) in the WHAT as educational way, autonomous morality vs. active power, 2) in the WHO as the affirmity of actual subjects, that of the ideal idea vs. that of real power, 3) in the WHEN/WHERE, as the in-between time-space of education, the incommensurable communicative situation of humans vs. the conflictive of machines, 4) in the HOW, as the educational method of achieving the ideal, the involuntary restoration of the already-had ideal vs. the now-have completion and break-through of the schizophrenic process, 5) in the WHY, as the aim of education, cosmopolitan vs. overman.

• Geomechanics and Engineering
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• v.23 no.2
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• pp.151-163
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• 2020

Grouting method is an effective way of reinforcing cracked rock masses and plugging water gushing. Current grouting diffusion models are generally developed for horizontal cracks, which is contradictory to the fact that the crack generally occurs in rock masses with irregular spatial distribution characteristics in real underground environments. To solve this problem, this study selected a cement-sodium silicate slurry (C-S slurry) generally used in engineering as a fast-curing grouting material and regarded the C-S slurry as a Bingham fluid with time-varying viscosity for analysis. Based on the theory of fluid mechanics, and by simultaneously considering the deadweight of slurry and characteristics of non-uniform spatial distribution of viscosity of fast-curing grouts, a theoretical model of slurry diffusion in an oblique crack in rock masses at constant grouting rate was established. Moreover, the viscosity and pressure distribution equations in the slurry diffusion zone were deduced, thus quantifying the relationship between grouting pressure, grouting time, and slurry diffusion distance. On this basis, by using a 3-d finite element program in multi-field coupled software Comsol, the numerical simulation results were compared with theoretical calculation values, further verifying the effectiveness of the theoretical model. In addition, through the analysis of two engineering case studies, the theoretical calculations and measured slurry diffusion radius were compared, to evaluate the application effects of the model in engineering practice. Finally, by using the established theoretical model, the influence of cracking in rock masses on the diffusion characteristics of slurry was analysed. The results demonstrate that the inclination angle of the crack in rock masses and azimuth angle of slurry diffusion affect slurry diffusion characteristics. More attention should be paid to the actual grouting process. The results can provide references for determining grouting parameters of fast-curing grouts in engineering practice.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Bio-Environment Control
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• v.28 no.3
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• pp.273-278
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• 2019

The multi-layer insulating curtains used in the experiment was produced in six combinations using non-woven fabric containing aerogel and compared and analyzed by measuring heat flux and heat perfusion rates due to weight, thickness and temperature changes. Using silica aerogel, which have recently been noted as new material insulation, this study tries to produce a new combination of multi-layer insulating curtains that can complement the shortcomings of the multi-layer insulating curtains currently in use and maintain and improve its warmth, and analyze the thermal properties. The heat flux means the amount of heat passing per unit time per unit area, and the higher the value, the more heat passing through the multi-layer insulating curtain, and it can be judged that the heat retention is low. The weight and thickness of multi-layer insulation curtains were found to be highly correlated with thermal insulation. In particular, insulation curtains combined with aerogel meltblown non-woven fabric had relatively higher thermal insulation than insulation curtains with the same number of insulation materials. However, the aerogel meltblown non-woven fabric is weak in light resistance and durability, and there is a problem that the production process and aerogel are scattering. In order to solve this problems, the combination of expanded aerogel non-woven fabric and hollow fiber non-woven fabric, which are relatively simple manufacturing processes and excellent warmth, are suitable for use in real farms.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.703-711
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• 2018

Water distribution system (WDS) pipe bursts are caused from excessive pressure, pipe aging, and ground shift from temperature change and earthquake. Prompt detection of and response to the failure event help prevent large-scale service interruption and catastrophic sinkhole generation. To that end, this study proposes a improved Western Electric Company (WECO) method to improve the detection effectiveness and efficiency of the original WECO method. The original WECO method is an univariate Statistical Process Control (SPC) technique used for identifying any non-random patterns in system output data. The improved WECO method multiples a threshold modifier (w) to each threshold of WECO sub-rules in order to control the sensitivity of anomaly detection in a water distribution network of interest. The Austin network was used to demonstrated the proposed method in which normal random and abnormal pipe flow data were generated. The best w value was identified from a sensitivity analysis, and the impact of measurement frequency (dt = 5, 10, 15 min etc.) was also investigated. The proposed method was compared to the original WECO method with respect to detection probability, false alarm rate, and averaged detection time. Finally, this study provides a set of guidelines on the use of the WECO method for real-life WDS pipe burst detection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.1-11
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• 2020

As an important basic building block of the smart grid environment, smart meter provides real-time electricity consumption information to the utility. However, ensuring information security and privacy in the smart meter data aggregation process is a non-trivial task. Even though the secure data aggregation for the smart meter has been a lot of attention from both academic and industry researchers in recent years, most of these studies are not secure against internal attackers or cannot provide data integrity. Besides, their computation costs are not satisfactory because the bilinear pairing operation or the hash-to-point operation is performed at the smart meter system. Recently, blockchains or distributed ledgers are an emerging technology that has drawn considerable interest from energy supply firms, startups, technology developers, financial institutions, national governments and the academic community. In particular, blockchains are identified as having the potential to bring significant benefits and innovation for the electricity consumption network. This study suggests a distributed, privacy-preserving, and simple secure smart meter data aggregation system, backed up by Blockchain technology. Smart meter data are aggregated and verified by a hierarchical Merkle tree, in which the consensus protocol is supported by the practical Byzantine fault tolerance algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.2604-2611
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• 2013

The Personal Rapid Transit(PRT) system has been highly interested in future transportation developments due to its on-demand and optimized door-to-door transport capability. However, the major impediments to the commercialization of PRT are the high cost for construction of infrastructures as opposed to the small transport capacity and difficulty in defining the role of PRT in building a balanced transportation system. In this study, the vertical transfer device for the PRT vehicle is developed to provide more flexible and better compatible urban mobility services between means of transportation, which is expected to meet particular demands in a particular environment. This apparatus was initially designed based on the basis of vertical circulating conveyors with steel chains, which is frequently used in logistics. Its advantages are capable of the non-stop loading and reduced head-way time. Most importantly, it was intensified by the additional idea to ensure the stable and reliable transfer of the PRT vehicle fully loaded with passengers. The 1/10-scale prototype was successfully tested to demonstrate a fundamental mechanism of vertical transfer and identify unexpected user requirements prior to a real manufacturing process.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.15 no.3
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• pp.191-197
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• 2017

The Korea Atomic Energy Research Institute (KAERI) has developed a safeguards technology for pyroprocessing based on the Safeguards-By-Design (SBD) concept. KAERI took part in a Member-State Support Program (MSSP) to establish a pyroprocessing safeguards approach. A Reference Engineering-scale Pyroprocessing Facility (REPF) concept was designed on which KAERI developed its safeguards system. Recently the REPF is being upgraded to the REPF+, a scaled-up facility. For assessment of the nuclear-material accountancy (NMA) system, KAERI has developed a simulation program named Pyroprocessing Material Flow and MUF Uncertainty Simulation (PYMUS). The PYMUS is currently being upgraded to include a Near-Real-Time Accountancy (NRTA) statistical analysis function. The Advanced Spent Fuel Conditioning Process Safeguards Neutron Counter (ASNC) has been updated as Non-Destructive Assay (NDA) equipment for input-material accountancy, and a Hybrid Induced-fission-based Pu-Accounting Instrument (HIPAI) has been developed for the NMA of uranium/transuranic (U/TRU) ingots. Currently, performance testing of Compton-suppressed Gamma-ray measurement, Laser-Induced Breakdown Spectroscopy (LIBS), and homogenization sampling are underway. These efforts will provide an essential basis for the realization of an advanced nuclear-fuel cycle in the ROK.