• Journal of Korean Society of Environmental Engineers
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• v.34 no.3
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• pp.162-167
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• 2012

The removal of orthophosphate ions from aqueous solutions by the anion exchange resin in the form of $Cl^-$ ion was investigated to elucidate the ion exchange mechanism which depends on the forms of orhthophoshate ions. In addition, the effects of alkalinity and other common anions were studied. The results showed that the orhthophosphate ions with the oxidation state of 2 and 3 ($HPO{_4}^{2-}$ and $PO{_4}^{3-}$) were effectively removed by the anion exchange resin, whereas the part of the $H_2PO_4{^-}$ ion passed through the ion exchange column. This suggested that the affinity of $H_2PO_4{^-}$ to the ion exchange resin was comparable with that of $Cl^-$ ion. In all cases, the effluent pHs have shown to be much lower than the calculated values, indicating that more $Cl^-$ ions than the orthophosphate equivalents in the influent were eluded. As the alkalinity increases, the decrease in pH was minimized. When the alkalinity was 100 mg/L ($CaCO_3$) or greater, 100 mg/L orthophosphate ions including $H_2PO_4{^-}$ were completely removed. The common anions such as $SO{_4}^{2-}$ and $NO_3{^-}$ were also removed by the anion exchange resin, and thus decreased the ion exchange capacity for the removal of orthophosphate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4437-4446
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• 2013

The purpose of this study was to development and evaluate the effects of cardiocerebrovascular disease prevention program for taxi drivers on physiological variables(blood pressure, blood sugar, serum lipids) and physical variables(body fat, muscle endurance, cardiopulmonary endurance, balance). This study consisted of two phases: developing the program and evaluating its effectiveness. 1 phase, 321 taxi drivers investigated a health condition and a life habit and an educational need and developed a program with the ground which will reach. 2 phases, The effectiveness of the program was tested in October 2011, with 51 taxi driver. The experimental group was given 12 weeks period exercise 1 weeks 3 time, disease education 4 time, 2 nutrition consultations. Although there was no significant reduction in blood pressure, heart rate, blood sugar, serum lipids, there were statistically significant increases in muscle endurance (t=-7.62 p<.001), cardiopulmonary endurance (t=-3.39, p<.001), balance(t=-4.13, p<.001) and decreased body fat (t= -3.11, p<.015) in before compared to after. These findings suggest that an integrated cardiocerebro-vascular disease prevention program improves physical fitness.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.113-124
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• 2009

With increasing multicore system, much effort has been put on the performance improvement of its application. Because multicore system has multiple processing devices in one system, its processing power increases compared to the single core system. However in many cases the advantages of multicore can not be exploited fully because the existing software and hardware were designed to be suitable for single core. When the existing software runs on multicore, its performance improvement is limited by the bottleneck of sharing resources and the inefficient use of cache memory on multicore. Therefore, according as the number of core increases, it doesn't show performance improvement and shows performance drop in the worst case. In this paper we propose a method of performance improvement of multicore system by applying Flow-Level Parallelism to the existing TCP/IP network application and operating system. The proposed method sets up the execution environment so that each core unit operates independently as much as possible in network application, TCP/IP stack on operating system, device driver, and network interface. Moreover it distributes network traffics to each core unit through L2 switch. The proposed method allows to minimize the sharing of application data, data structure, socket, device driver, and network interface between each core. Also it allows to minimize the competition among cores to take resources and increase the hit ratio of cache. We implemented the proposed methods with 8 core system and performed experiment. Experimental results show that network access speed and bandwidth increase linearly according to the number of core.

• Informatization Policy
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• v.24 no.3
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• pp.3-26
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• 2017

The amount of unstructured data generated online is increasing exponentially and the analysis of text data is being done in various fields. In order to identify the research trends on the platform government, the title, year, academic society, and abstract information of the academic papers on the subject of platform government were collected from the database of the domestic papers, DBPIA(www.dbpia.co.kr). The results of the existing research on the platform government and related fields were analyzed based on each stage of the national informatization promotion. The technology, service, and governance topics were extracted from papers on platform government and the trends of core topics were analyzed by year. Entering the era of the intelligent information society, this study has significance for providing the basis for defining a new role of government - the platform government that sets the stage for the private sector to lead the innovation, and plays the role of an 'enabler' and 'facilitator' instead. The purpose of this study is to understand the platform government research through objective analysis of its trends. Looking for future directions, this study will contribute to future research by providing reference materials.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.219-224
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• 2020

The purpose of this study is mainly to provide theoretical basis of private security industry by analyzing the perception and flow of private security from the press-released materials according to periodic classification and duties through 'Big Kinds', a website of analyzing news big data. The research method has been changed to structured data to allow an analysis of various scattered unstructured data, and the keywords trend and related words by duties of private security were analyzed in growth period of private security. The perception of private security based on the results of the study was exposed a lot by the media through various crimes, accidents and incidents, and the issues related permanent position. Also, it tended to be perceived as a simple security guard, not recognized as the area of private security, and judging from the high correlation between private security and police, it was recognized not only as a role to assist the police force, but also as a common agent in charge of the public peace. Therefore, it should objectively judge the perception of private security, and through this, it is believed that it should be a foundation for recognizing private security as a main agent responsible for the safety of the nation and maintaining social orders.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.76-83
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• 2021

This study examines the bending behavior of lap-spliced ultra-high-strength fiber-reinforced concrete members and evaluates the safety of the design codes for ultra-high-strength fiber-reinforced concrete structures. An experiment on a total of six beams was performed. The main variables were the fiber-inclusion and the lap-spliced length at the center of the beams. The steel fibers in a volume fraction of 2% were used, and the lap-splice lengths were determined to be 8db and 16db. As a result of the test, the specimens not reinforced with fiber lost abrupt load-bearing capacity at the lap region and did not experience yielding of the reinforcing bar. In the case of fiber-reinforced concrete, if a lap-splice length of 16db is secured, the yielding of the main reinforcing bar can be experienced, and appropriate flexural strength can be expressed. Based on the experimental results of this study, as a result of reviewing the lap-splice length calculation formulas of the current design standards and the ultra-high-strength concrete structural design recommendations, it was found that all of them were evaluated conservatively.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.93-103
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• 2021

Despite the efforts of financial authorities in conducting the direct management and supervision of collection agents and bond-collecting guideline, the illegal and unfair collection of debts still exist. To effectively prevent such illegal and unfair debt collection activities, we need a method for strengthening the monitoring of illegal collection activities even with little manpower using technologies such as unstructured data machine learning. In this study, we propose a classification model for illegal debt collection that combine machine learning such as Support Vector Machine (SVM) with a rule-based technique that obtains the collection transcript of loan companies and converts them into text data to identify illegal activities. Moreover, the study also compares how accurate identification was made in accordance with the machine learning algorithm. The study shows that a case of using the combination of the rule-based illegal rules and machine learning for classification has higher accuracy than the classification model of the previous study that applied only machine learning. This study is the first attempt to classify illegalities by combining rule-based illegal detection rules with machine learning. If further research will be conducted to improve the model's completeness, it will greatly contribute in preventing consumer damage from illegal debt collection activities.

• The Journal of Bigdata
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• v.6 no.1
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• pp.63-81
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• 2021

The performance of natural language processing is rapidly improving due to the recent development and application of machine learning and deep learning technologies, and as a result, the field of application is expanding. In particular, as the demand for analysis on unstructured text data increases, interest in NLP(Natural Language Processing) is also increasing. However, due to the complexity and difficulty of the natural language preprocessing process and machine learning and deep learning theories, there are still high barriers to the use of natural language processing. In this paper, for an overall understanding of NLP, by examining the main fields of NLP that are currently being actively researched and the current state of major technologies centered on machine learning and deep learning, We want to provide a foundation to understand and utilize NLP more easily. Therefore, we investigated the change of NLP in AI(artificial intelligence) through the changes of the taxonomy of AI technology. The main areas of NLP which consists of language model, text classification, text generation, document summarization, question answering and machine translation were explained with state of the art deep learning models. In addition, major deep learning models utilized in NLP were explained, and data sets and evaluation measures for performance evaluation were summarized. We hope researchers who want to utilize NLP for various purposes in their field be able to understand the overall technical status and the main technologies of NLP through this paper.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.330-337
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• 2021

3D printing is not only at the fundamental study and small-scale level, but has recently been producing buildings that can be inhabited by people. Buildings require a lot of cost and labor to work on the form work, but if 3D printing is applied to the building, the construction industry is received attention from technologies using 3D printing as it can reduce the construction period and cost. 3D printing technology for buildings can be divided into structural and non-structural materials, of which 3D printing is applied to non-structural materials. Because 3D printing needs to be additive manufacturing, control such as curing speed and workability is needed. Since cement mortar has a large shrinkage due to evaporation of water, cement polymer dispersion is used to improve the hardening speed, workability, and adhesion strength. The addition of polymer dispersion to cement mortar improves the tensile strength and brittleness between the cement hydrate and the polymer film. Cement mortar using polymer materials can be additive manufacturing but it has limited height that can be additive manufacturing due to its high density. When light-weight materials are mixed with polymer cement mortar, the density of polymer cement mortar is lowered and the height of additive manufacturing, so it is essential to use light-weight materials. However, the use of EVA redispersible polymer powder and light-weight materials, additional damage such as cracks in cement mortar can occur at high temperatures such as fires. This study produced a test specimen incorporating light-weight materials and EVA redispersible polymer powder to produce exterior building materials using 3D printing, and examined flame resistance performance through water absorption rate, length change rate, and cone calorimeter test and non-flammable test. From the test result, the test specimen using silica sand and light-weight aggregate showed good flame resistance performance, and if the EVA redispersible polymer powder is applied below 5%, it shows good flame resistance performance.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.281-291
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• 2022

This study attempts to use big data to determine the indicators necessary for a fire risk assessment of buildings. Because most of the causes affecting the fire risk of buildings are fixed as indicators considering only the building itself, previously only limited and subjective assessment has been performed. Therefore, if various internal and external indicators can be considered using big data, effective measures can be taken to reduce the fire risk of buildings. To collect the data necessary to determine indicators, a query language was first selected, and professional literature was collected in the form of unstructured data using a web crawling technique. To collect the words in the literature, pre-processing was performed such as user dictionary registration, duplicate literature, and stopwords. Then, through a review of previous research, words were classified into four components, and representative keywords related to risk were selected from each component. Risk-related indicators were collected through analysis of related words of representative keywords. By examining the indicators according to their selection criteria, 20 indicators could be determined. This research methodology indicates the applicability of big data analysis for establishing measures to reduce fire risk in buildings, and the determined risk indicators can be used as reference materials for assessment.