• Journal of Korean Society of Environmental Engineers
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• v.35 no.3
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• pp.179-191
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• 2013

This study was conducted to comparatively assess quantitative indicating factor for biomineralization characterizing $CO_2$ mineralization on three type of minerals (i.e., $CaCl_2$, $MgCl_2$, $CaCl_2-MgCl_2$) in an aqueous solution amended with Bacillus pasteurii or indigenous microorganisms for a S landfill cover soil. For given three types of minerals, $NH_4{^+}$ (urease activity) was released at the highest of 88 mg/L for $MgCl_2$, then 85 mg/L for $CaCl_2$, and the lowest of 42 mg/L for $CaCl_2-MgCl_2$. $CO_2$ gas in the head space was completely removed after 12, 12, and 24 hr for $CaCl_2$, $MgCl_2$ and $CaCl_2-MgCl_2$, respectively. $Ca^{2+}$ concentration in $CaCl_2$ solution was the quickest and the greatest decreased 92% for 12 hr whereas that in $CaCl_2-MgCl_2$ solution was lower at 85% for 36 hr. $Mg^{2+}$ concentration in $MgCl_2$ was more efficiently decreased at 46% for 48 hr than that of $CaCl_2-MgCl_2$ solution of 38.5% for 72 hr. Regardless of types of minerals or their concentration, pH was changed from 5.5 to 9 by biomineralization being progressed. Microbial activity ($OD_{600}$) was also changed from 0 to 0.6. SEM images indicated that spheroidal and trapezoid shape crystal were formed, which were identified as of $CaCO_3$ (Calcite) and $MgCO_3$ (Magnesite) by X-ray diffraction. In the long run, $NH_4{^+}$ (urease activity), $CO_2$ gas, $OD_{600}$, pH, $Ca^{2+}$ and $Mg^{2+}$ would be suitable for reasonable indicating factor in order to assess the degree of biomineralization efficiency.

• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.81-95
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• 2006

The purpose of this study was to evaluate appropriateness of clothing & textiles as educational contents in practical arts or technology home economics in the 7th curriculum. The factors of appropriateness were the amounts of learning, the degrees of understanding, interest and requirement on the educational content recognized by elementary, middle and high school students. The data collected from evaluation sheets were analyzed by frequency analysis, t-test, crossing analysis using SPSSWIN 12.0 program. Results were as follows; First. more than 50% of elementary, middle and high school students were recognized the amounts of tearing of clothing & textiles proper. But boy students of middle school recognized 'making clothes' in practice course too heavy. Second. It were from easy to difficult that the degrees of understanding on the educational contents of clothing & textiles recognized by elementary school students. Elementary school students understood both 'making cushion' and 'sewing machine theory and practice' difficult. Middle school students understood 'basic sewing for repairing clothes' and 'making clothes' difficult whereas high school students thought 'making pillow' and 'making bag' difficult. All students understood practice courses hard. Third, the degrees of interest showed from 'interest' level to 'not interest' level in case of elementary school students whereas 'interest' level in middle school students and 'common' in high school students. Fourth, the requirements of elementary, middle and high school students were in 'necessary' level to 'common' level. Editional contents such as 'learning sewing machine', 'making cushions'. 'making clothes', and 'making pillow-cover and bag' were low in the degrees of requirement. The correlationship between the amount of learning and the each level of understand, interest and requirement of students was indirect. On the other hand, Among the level of understand, interest and requirement were direct in case of high school students.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.855-858
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• 2006

First of all, Developing information technology makes it possible to change a paradigm of all kinds of areas, including an education. Students can choose learning goals and objects themselves and acquire not the accumulation of knowledge but the method of their learning. Moreover, Teachers get to be adviser, and students play a key role in teaming. That is, the subject of leaning is students. Constructivism emphasizes the student-oriented environment of education, which corresponds to the characteristics of hypeimedia. In addition, Internet allows us to make a practical plan for constructivism. Web Based Internet provides us with a proper environment to make constructivism practice md causes an education system to change. Sure Web Based Instruction makes them motivated to learn more, they can gain plenty of information regardless of places or time. Besides, they are able to consult more up-to-date information regarding their learning use hypermedia such as an image, audio, video, and test, and effectively communicate with their instructor through a board, an e-mail, a chatting etc. A school and instructors have been making effort to develop a new model of a teaching method to cope with a new environment change. In this thesis, with 'Design and Implementation of Web Based Instruction Based on Constructivism', providing online learner-oriented and indexed video lesson, learners can get chance of self-oriented learning. In addition, learners doesn't have to cover all contents of a lesson but can choose contents they want to have from a indexed list of a lesson, and they ran search contents they want to have with a 'Keyword Search' on a main page, which can make learners improve learner's achievement.

• Journal of Bio-Environment Control
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• v.30 no.4
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• pp.419-428
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• 2021

In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

• Magazine of the Korean Society of Agricultural Engineers
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• v.13 no.1
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• pp.2206-2217
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• 1971

Spillway and discharge channel of reservoirs require the Control of Large volume of water under high pressure. The energies at the downstream end of spillway or discharge channel are tremendous. Therefore, Some means of expending the energy of the high-velocity flow is required to prevent scour of the riverbed, minimize erosion, and prevent undermining structures or dam it self. This may be accomplished by Constructing an energy dissipator at the downstream end of spillway or discharge channel disigned to dissipated the excessive energy and establish safe flow Condition in the outlet channel. There are many types of energy dissipators, stilling basins are the most familar energy dissipator. In the stilling basin, most energies are dissipated by hydraulic jump. stilling basins have some length to cover hydraulic jump length. So stilling basins require much concrete works and high construction cost. Flip bucket type energy dissipators require less construction cost. If the streambed is composed of firm rock and it is certain that the scour will not progress upstream to the extent that the safety of the structure might be endangered, flip backet type energy dissipators are the most recommendable one. Following items are tested and studied with bucket radius, $R=7h_2$,(medium of $4h_2{\geqq}R{\geqq}10h_2$). 1. Allowable upstream channel slop of bucket. 2. Adequate bucket lip angle for good performance of flip bucket. Also followings are reviwed. 1. Scour by jet flow. 2. Negative pressure distribution and air movement below nappe flow. From the test and study, following results were obtained. 1. Upstream channel slope of bucket (S=H/L) should be 0.25<H/L<0.75 for good performance of flip bucket. 2. Adequated lip angle $30^{\circ}{\sim}40^{\circ}$ are more reliable than $20^{\circ}{\sim}30^{\circ}$ for the safety of structures.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.