• Journal of Korean Society of Water and Wastewater
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• v.21 no.6
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• pp.727-735
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• 2007

The use of water by cities is increasing owing to industrialization, the concentration of population, and the enhancement of the standard of living. Accordingly, the amount of waste water is also increasing, and the degree of pollution of the water system is rising. In order to solve this problem, it is necessary to remove organisms and suspended particles as well as the products of eutrophication such as nitrates and phosphates. This study developed a high-end treatment engineering solution with maximum efficiency and lower costs by researching and developing a advanced treatment engineering solution with the use of Biosorption. As a result, the study conducted a test with a $50m^3/day$ Pilot Scale Plant by developing treatment engineering so that only the secondary treatment satisfies the standard of water quality and which provided optimal treatment efficiency along with convenient maintenance and management. The removal of organisms, which has to be pursued first for realizing nitrification during the test period, was made in such a way that there would be no oxidation by microorganisms in the reactor while preparing oxygen as an inhibitor for the growth of microorganism in the course of moving toward the primary settling pond. The study introduced microorganisms in the endogeneous respiration stage to perform adhesion, absorption, and filtering by bringing them into contact with the inflowing water with the use of a sludge returning from the secondary settling pond. Also a test was conducted to determine how effective the microorganisms are as an inner source of carbon. The HRT(Hydraulic Retention Time) in the nitrification tank (aerobic tank) could be reduced to two hours or below, and the stable treatment efficiency of the process using the organisms absorbed in the NAR reactor as a source of carbon could be proven. Also, given that the anaerobic condition of the pre-treatment tank becomes basic in the area of phosphate discharge, it was found that there was excellent efficiency for the removal of phosphate when the pre-treatment tank induced the discharge of phosphate and the polishing reactor induced the uptake of phosphate. The removal efficiency was shown to be about 94.4% for $BOD_5$. 90.7% for $COD_{Cr}$ 84.3% for $COD_{Mn}$, 96.0% for SS, 77.3% for TN, and 96.0% for TP.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.2
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• pp.201-208
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• 2010

The $SO_2$ and $NO_x$ removal with an activated coke catalyst was conducted by a two-stage reaction which first $SO_2$ was oxidized to $H_2SO_4$ and then $NO_x$ was reduced to $N_2$. But if unreacted sulfur dioxide entered in the second stage, the $NO_x$ reduction was hindered by the reaction with ammonia. In this study, experimental investigations by using lab-scale column apparatus on the product and the reactivity of $SO_2$ with ammonia over coke catalyst which was activated with sulfuric acid was carried out through ultimate analysis DTA, TGA and SEM of catalyst before and after the reaction. Also, the effect of reaction emperature on the reactivity of $SO_2$ with ammonia was determined by means of breakthrough curves with time. The obtained results from this study were summarized as following; Activated cokes were decreased carbon component and increased oxygen and sulfur components in comparison with original cokes. The products over coke catalyst were faced fine crystal of $(NH_4)_2SO_4$, which results in the pressure loss of reacting system. The order of general reactivity in terms of the reaction temperature after breakthrough for $SO_2$ was found to be $150^{\circ}C$ > $200^{\circ}C$ > $100^{\circ}C$. This was related to adsorption amounts of ammonia on the activated cokes.

• Journal of Korean Society of Forest Science
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• v.106 no.1
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• pp.1-9
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• 2017

Forest harvest as large scale artificial disturbance makes edge environment in both clear-cutted and forested habitat. To clarify the development and recovery process of forest edge after disturbances is essential to understand vegetation responses and landscape level consequences such as edge-distance. In Korea, after clear-cutting, edge-related changes of environment and vegetation was not clarified yet. In Korean red pine (Pinus densiflora) forest, by applying space-for-time approach (sites with undisturbed and 1, 3, 10, 16 yr after cutting), the edge-related change of plant abundance and abiotic factors were determined for 20 line-transect (60 m) and 340 ($1m{\times}5m$) quadrats, and clarified depth and duration of the disturbance. Immediately after edge formation, within 15m form the edge, biotic and abiotic factors such as cover, richness, canopy openness, temperature and moisture content exhibited larger changes compared to forest interior. Plant abundance and abiotic variables were stabilized at the level of forest inside within 16 yr and 10 yr after edge creation, respectively. Woody (tree and shrub) species generally was showed larger increment with proximity to edge than did herb or graminoid species. In addition, negative interactions between woody and herbaceous species were detected during the period of forest edge closure. Our results suggested that depth of forest edge formed by clear-cutting of Korean red pine forest was at least from 15 m to 20 m and edge effect were likely sustained more than 16 years. As the first empirical study on edge-distance between two contrast habitats of clear-cutted and adjacent forest in South Korea, the analytical reality on landscape structure and habitat patches can be improved.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.375-393
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• 2023

The demand for Less than Container Load (LCL) has been on the rise due to the growing need for various small-scale production items and the expansion of the e-commerce market. Consequently, more companies in the International Freight Forwarder are now handling LCL. Given the variety in cargo sizes and the diverse interests of stakeholders, there's a growing need for a container loading algorithm that optimizes space efficiency. However, due to the nature of the current situation in which a cargo loading plan is established in advance and delivered to the Container Freight Station (CFS), there is a limitation that variables that can be identified at industrial sites cannot be reflected in the loading plan. Therefore, this study proposes a container loading methodology that makes it easy to modify the loading plan at industrial sites. By allowing the characteristics of cargo and the status of the container to be considered, the requirements of the industrial site were reflected, and the three-dimensional space was manipulated into a two-dimensional planar layer to establish a loading plan to reduce time complexity. Through the methodology presented in this study, it is possible to increase the consistency of the quality of the container loading methodology and contribute to the automation of the loading plan.

• Information Systems Review
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• v.21 no.4
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• pp.143-156
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• 2019

Types of innovation can be categorized into simplification, information, automation, and intelligence. Intelligence is the highest level of innovation, and RPA can be seen as one of intelligence. Robotic Process Automation(RPA), a software robot with artificial intelligence, is an example of intelligence that is suited for simple, repetitive, large-scale transaction processing tasks. The RPA, which is already in operation in many companies in Korea, shows what needs to be done to naturally focus on the core tasks in a situation where the need for a strong organizational culture is increasing and the emphasis is on voluntary leadership, strong teamwork and execution, and a professional working culture. The introduction was considered naturally according to the need to find. Robotic Process Automation, or RPA, is a technology that replaces human tasks with the goal of quickly and efficiently handling structural tasks. RPA is implemented through software robots that mimic humans using software such as ERP systems or productivity tools. RPA robots are software installed on a computer and are called robots by the principle of operation. RPA is integrated throughout the IT system through the front end, unlike traditional software that communicates with other IT systems through the back end. In practice, this means that software robots use IT systems in the same way as humans, repeat the correct steps, and respond to events on the computer screen instead of communicating with the system's application programming interface(API). Designing software that mimics humans to communicate with other software can be less intuitive, but there are many advantages to this approach. First, you can integrate RPA with virtually any software you use, regardless of your openness to third-party applications. Many enterprise IT systems are proprietary because they do not have many common APIs, and their ability to communicate with other systems is severely limited, but RPA solves this problem. Second, RPA can be implemented in a very short time. Traditional software development methods, such as enterprise software integration, are relatively time consuming, but RPAs can be implemented in a relatively short period of two to four weeks. Third, automated processes through software robots can be easily modified by system users. While traditional approaches require advanced coding techniques to drastically modify how they work, RPA can be instructed by modifying relatively simple logical statements, or by modifying screen captures or graphical process charts of human-run processes. This makes RPA very versatile and flexible. This RPA is a good example of the application of digital to intelligence(D2I).

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.262-269
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• 2005

Since the buried cultural relics are three-dimensional (3-D) objects in nature, 3-D survey is more preferable in archeological exploration. 3-D Ground Penetrating Radar (GPR) survey based on very dense data in principle, however, might need much higher cost and longer time of exploration than other geophysical methods commonly used for the archeological exploration, such as magnetic and electromagnetic methods. We developed a small-scale continuous data acquisition system which consists of two sets of GPR antennas and the precise positioning device tracking the moving-path of GPR antenna automatically and continuously. Since the high cost of field work may be partly attributed to establishing many profile lines, we adopted a concept of data acquisition at arbitrary locations not along the pre-established profile lines. Besides this hardware system, we also developed several software packages in order to effectively process and visualize the 3-D data obtained by the developed system and the data acquisition concept. Using the developed system, we performed 3-D GPR survey to investigate the possible historical remains of Baekje Kingdom at Buyeo city, South Korea, prior to the excavation. Owing to the newly devised system, we could obtain 3-D GPR data of this survey area having areal extent over about $17,000m^2$ within only six-hours field work. Although the GPR data were obtained at random locations not along the pre-established profile lines, we could obtain high-resolution 3-D images showing many distinctive anomalies, which could be interpreted as old agricultural lands, waterways, and artificial structures or remains. This cast: history led us to the conclusion that 3-D GPR method is very useful not only to examine a small anomalous area but also to investigate the wider region of the archeological interests.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.167-181
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• 2018

Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.

• Journal of Life Science
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• v.16 no.3 s.76
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• pp.534-539
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• 2006

In the ozone disinfection unit process of a piston type batch reactor with continuous ozone analysis using a flow injection analysis (FIA) system, the CT values for 1 log inactivation of Cryptosporidium parvum by viability assays of DAPI/PI and excystation were $1.8{\sim}2.2\;mg/L{\cdot}min$ at $25^{\circ}C$ and $9.1mg/L{\cdot}min$ at $5^{\circ}C$, respectively. At the low temperature, ozone requirement rises $4{\sim}5$ times higher in order to achieve the same level of disinfection at room temperature. In a 40 L scale pilot plant with continuous flow and constant 5 minutes retention time, disinfection effects were evaluated using excystation, DAPI/PI, and cell infection method at the same time. About 0.2 log inactivation of Cryptosporidium by DAPI/PI and excystation assay, and 1.2 log inactivation by cell infectivity assay were estimated, respectively, at the CT value of about $8mg/L{\cdot}min$. The difference between DAPI/PI and excystation assay was not significant in evaluating CT values of Cryptosporidium by ozone in both experiment of the piston and the pilot reactors. However, there was significant difference between viability assay based on the intact cell wall structure and function and infectivity assay based on the developing oocysts to sporozoites and merozoites in the pilot study. The stage of development should be more sensitive to ozone oxidation than cell wall intactness of oocysts. The difference of CT values estimated by viability assay between two studies may partly come from underestimation of the residual ozone concentration due to the manual monitoring in the pilot study, or the difference of the reactor scale (50 mL vs 40 L) and types (batch vs continuous). Adequate If value to disinfect 1 and 2 log scale of Cryptosporidium in UV irradiation process was 25 $mWs/cm^2$ and 50 $mWs/cm^2$, respectively, at $25^{\circ}C$ by DAPI/PI. At $5^{\circ}C$, 40 $mWs/cm^2$ was required for disinfecting 1 log Cryptosporidium, and 80 $mWs/cm^2$ for disinfecting 2 log Cryptosporidium. It was thought that about 60% increase of If value requirement to compensate for the $20^{\circ}C$ decrease in temperature was due to the low voltage low output lamp letting weaker UV rays occur at lower temperatures.

• Korean Journal of Occupational Health Nursing
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• v.4
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• pp.5-29
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• 1995

Occupational health services in Korea have been operated as dual types : one is operated by occupational health care manager and the other is health care agency without their own personnel. The performance of occupational health service should be different due to the variety of characteristics of health care manager and workplace, qualification of health care manager. This study is to analyze performance of occupational health care services with a particular consideration of job performance shape and efficiency, based on comparing those two types of health care management to show on the basic data for the settlement of more qualitative health care management system at workplace. For this study, total 391 places in Seoul and Inchon city area ; 154 places (39.4%) managed by designated health care manager and 237 places (60.6%) by the agency with their commission are selected as research samples. Tools for data collection are questionnares that have been investigated during the period of 20 September 1993-20 December 1993. Those data are compared with percentiles, mean, standard deviation and B/C ratio using SPSS PC program. Conclusions observed from the tests and each comparison could be summerized as follows : 1. Occupational health care have been accomplished at workplaces with designated people than with agencies people, and coverage rate of the occupational health care services has differences, due to management types. The reason of these results is due to visit only one or two times monthly by the agencies, while their own health care manager obsess, at the workplaces all the times. 2. Most of the expense for environmental control of all health care services expenditures shows that there is almost no fundamental improvement because more expenses are needed for procuring personal protective equipment and measuring work environment instead of environmental improvement. 3. It is investigated how much the cost of occupational health care services needs per worker, and calculated how much the cost needs per service hour per worker. The results from this show that the cost of occupational health services at workplaces with their own managers used less than the cost of health care agencies, eventually the former gives better services with less cost than the latter. 4. Benefit/Cost ratio is also produced by total benefit/total cost. The result from the above way reads 4.57 as a whole, while their own manager having workplaces reads 4.82 and the agencies do l.56. Even if their own manager performing workplaces spent more cost, this system produces more benefit than the agencies management. 5. The B/C ratio for medical organization such as local clinic, health care center and pharmacy shows more than or equal to at the workplaces controlled by the agencies. It is inferred that benefit would be much less than the cost used, with so being inefficient. 6. It is assumed that the efficiency ratio of health education is equal to reduction rate of workers medical organization visit. Estimated reduction rate 5%, 10%, 15%, show that the efficiency ratio of health education have an effect on producing benefits. It is estimated that more benefit can be produced if more qualitative education will be provided for enhancing health care efficiency. 7. Results of this study cannot be generalized because there are large scale of deviation in case of workplaces with less than 300 full time workers, but B/C ratio reads 2.69 as a whole and 3.25 at workplaces with their own health care manager are higher than 1.63 at the workplaces manged by the agencies. Finally, all the benefit concerning health care services could not be quantified, measured and shown on the value of money. This is a reason that a considerable part of benefits are so underestimated. This is also thought that measurement tools should be developed for measuring benefits of health care services with a comprehensive quantification. in the future. It is also expected that efficiency of occupational health care services should be investigated using cost-effectiveness analysis.

• Asia pacific journal of information systems
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• v.21 no.3
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• pp.71-96
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• 2011

Within the traditional medical delivery system, patients residing in medically vulnerable areas, those with body movement difficulties, and nursing facility residents have had limited access to good healthcare services. However, Information and Communication Technology (ICT) provides us with a convenient and useful means of overcoming distance and time constraints. ICT is integrated with biomedical science and technology in a way that offers a new high-quality medical service. As a result, rapid technological advancement is expected to play a pivotal role bringing about innovation in a wide range of medical service areas, such as medical management, testing, diagnosis, and treatment; offering new and improved healthcare services; and effecting dramatic changes in current medical services. The increase in aging population and chronic diseases has caused an increase in medical expenses. In response to the increasing demand for efficient healthcare services, a telehealth service based on ICT is being emphasized on a global level. Telehealth services have been implemented especially in pilot projects and system development and technological research. With the service about to be implemented in earnest, it is necessary to study its overall acceptance by consumers, which is expected to contribute to the development and activation of a variety of services. In this sense, the study aims at positively examining the structural relationship among the acceptance factors for telehealth services based on the Technology Acceptance Model (TAM). Data were collected by showing audiovisual material on telehealth services to online panels and requesting them to respond to a structured questionnaire sheet, which is known as the information acceleration method. Among the 1,165 adult respondents, 608 valid samples were finally chosen, while the remaining were excluded because of incomplete answers or allotted time overrun. In order to test the reliability and validity of the assessment scale items, we carried out reliability and factor analyses, and in order to explore the causal relation among potential variables, we conducted a structural equation modeling analysis using AMOS 7.0 and SPSS 17.0. The research outcomes are as follows. First, service quality, innovativeness of medical technology, and social influence were shown to affect perceived ease of use and perceived usefulness of the telehealth service, which was statistically significant, and the two factors had a positive impact on willingness to accept the telehealth service. In addition, social influence had a direct, significant effect on intention to use, which is paralleled by the TAM used in previous research on technology acceptance. This shows that the research model proposed in the study effectively explains the acceptance of the telehealth service. Second, the research model reveals that information privacy concerns had a insignificant impact on perceived ease of use of the telehealth service. From this, it can be gathered that the concerns over information protection and security are reduced further due to advancements in information technology compared to the initial period in the information technology industry, and thus the improvement in quality of medical services appeared to ensure that information privacy concerns did not act as a prohibiting factor in the acceptance of the telehealth service. Thus, if other factors have an enormous impact on ease of use and usefulness, concerns over these results in the initial period of technology acceptance may become irrelevant. However, it is clear that users' information privacy concerns, as other studies have revealed, is a major factor affecting technology acceptance. Thus, caution must be exercised while interpreting the result, and further study is required on the issue. Numerous information technologies with outstanding performance and innovativeness often attract few consumers. A revised bill for those urgently in need of telehealth services is about to be approved in the national assembly. As telemedicine is implemented between doctors and patients, a wide range of systems that will improve the quality of healthcare services will be designed. In this sense, the study on the consumer acceptance of telehealth services is meaningful and offers strong academic evidence. Based on the implications, it can be expected to contribute to the activation of telehealth services. Further study is needed to assess the acceptance factors for telehealth services, such as motivation to remain healthy, health care involvement, knowledge on health, and control of health-related behavior, in order to develop unique services according to the categorization of customers based on health factors. In addition, further study may focus on various theoretical cognitive behavior models other than the TAM, such as the health belief model.