• International journal of advanced smart convergence
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• v.10 no.3
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• pp.257-278
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• 2021

As the definition of the vendor-oriented implementation method, which was utilized in adopting an ERP system, has been centered around the project construction business, it was difficult for the EPR adopting organization to systematically prepare ERP projects and have enough deliberative opportunities to change-related policies. Furthermore, this method does not have a fully standardized construction process. Accordingly, by defining an organization that wants to adopt an ERP system as a customer, this paper develops the customer-based ERP construction process framework that assists both customers and developers who construct the system. For this purpose, this paper reviews the previous research and collects the construction processes of the commercial ERP SW vendor and ERP construction cases while proposing the three-layer process framework to construct ERP through the KJ method. The ERP process framework consists of 7 processes, 32 activities, 141 tasks while providing definitions for concepts of each component. Furthermore, the proposed processes and phases were set in order of the recommended execution, while the activities were suggested as an open-ended type so that the application and usability can be increased and polished by reflecting experts' opinions. The contribution of this study is to standardize the ERP project process by transforming the previous supplier-based ERP construction method into the customer-based one while providing important procedure and activity frameworks that apply to diverse ERP solutions per vendor. At the same time, this study provides an theoretical foundation to develop the construction process for the customer -based Cloud ERP. In practice, At the beginning of the ERP system construction project, it provides communication or process tailoring tools for the stakeholder.

• Journal of Industrial Convergence
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• v.19 no.6
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• pp.59-66
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• 2021

Globally, the prolonged pandemic of COVID-19 (COVID-19) has had a great impact on all industries. In particular, in the field of education, online classes (non-face-to-face) had some negative perceptions of online classes, such as lack of preparation for learning and student dissatisfaction with the class. According to the current situation survey in 2020, non-face-to-face classes accounted for about 56% of the class, and streaming real-time classes and video content-based classes accounted for most of the class. This study empirically analyzes the problems to be solved by online classes through the 2020-2021 survey (software application practical class university students), and explains the detailed program and development plan (implementation result). This study intends to contribute to the development of online learning development of each educational institution after the end of the corona crisis.

• Bulletin of the Korean Chemical Society
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• v.29 no.9
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• pp.1742-1746
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• 2008

Catechol and caffeine were simultaneously analyzed with a bismuth-immobilized carbon nanotube paste electrode (BPE) using square wave (SW) stripping voltammetry. Optimum analytical conditions were determined. Simultaneous working ranges of 100-1,500 $mgL^{-1}$ for caffeine and 5-75 $mgL^{-1}$ for catechol were obtained. In the separated cell systems, a working range of 0.1-2.1 $mgL^{-1}$ catechol with a correlation coefficient of 0.9935, and a working range of 10-210 $mgL^{-1}$ caffeine with a correlation coefficient of 0.9921 were obtained. A detection limit (S/N) of 0.15 $mgL^{-1}$ (7.7 ${\times}$ $10^{-7}$ M) and a detection limit of 0.02 $mgL^{-1}$ (1.82 ${\times}$ $10^{-7}$ M), respectively, manifested for catechol and caffeine. It was found that three macro-type electrode systems could be implanted in fish and rat neuro cells. For both ions, the ion currents were observed. The physiological impulse conditions and the neuronal thinking current were also obtained.

• Economic and Environmental Geology
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• v.18 no.4
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• pp.309-320
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• 1985

The crustal structure of the southern part of the Korean peninsula has been investigated based on the results of processing and anlaysis of gravity data. The processing techniques involve i) seperation of regional and residual anomalies by polynomial fittings, ii) power spectral analyses to determine the mean depth to the crustal base, iii) a filtering operation called "high-cut filtering and resampling," and iv) downward continuation to determine the undulation of the crustal base. The Bouguer anomalies show a lineation in the NE-SW direction which is the same as that of most mountains and tectonic lines of this area. The mean crustal depth is found to be 34km. The depth of the crustal base is varying in the estimated range of 26km to 36km with a thinner crust below the east coast than that of the west coast. The relief of the crustal base is appeared to be correlated with the regional surface topography. The linear regression relations computed between elevations and gravity anomalies indicate that the crust of this area seems to be not in perfect isostatic equilibrium but a little undercompensated state.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.931-934
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• 2019

Research using artificial intelligence to generate captions for an image has been studied extensively. However, these systems are unable to create creative stories that include more than one sentence based on image content. A story is a better way that humans use to foster social cooperation and develop social norms. This paper proposes a framework that can generate a relatively short story to describe based on the context of an image. The main contributions of this paper are (1) An unsupervised framework which uses recurrent neural network structure and encoder-decoder model to construct a short story for an image. (2) A huge English novel dataset, including horror and romantic themes that are manually collected and validated. By investigating the short stories, the proposed model proves that it can generate more creative contents compared to existing intelligent systems which can produce only one concise sentence. Therefore, the framework demonstrated in this work will trigger the research of a more robust AI story writer and encourages the application of the proposed model in helping story writer find a new idea.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.459-469
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• 2021

In this paper, a case study of basic data science practice education for field teachers and pre-service teachers was studied. In this paper, for basic data science education, spreadsheet software was used as a data collection and analysis tool. After that, we trained on statistics for data processing, predictive hypothesis, and predictive model verification. In addition, an educational case for collecting and processing thousands of public big data and verifying the population prediction hypothesis and prediction model was proposed. A 34-hour, 17-week curriculum using a spreadsheet tool was presented with the contents of such basic education in data science. As a tool for data collection, processing, and analysis, unlike Python, spreadsheets do not have the burden of learning program- ming languages and data structures, and have the advantage of visually learning theories of processing and anal- ysis of qualitative and quantitative data. As a result of this educational case study, three predictive hypothesis test cases were presented and analyzed. First, quantitative public data were collected to verify the hypothesis of predicting the difference in the mean value for each group of the population. Second, by collecting qualitative public data, the hypothesis of predicting the association within the qualitative data of the population was verified. Third, by collecting quantitative public data, the regression prediction model was verified according to the hypothesis of correlation prediction within the quantitative data of the population. And through the satisfaction analysis of pre-service and field teachers, the effectiveness of this education case in data science education was analyzed.

• Journal of Integrative Natural Science
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• v.11 no.3
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• pp.131-138
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• 2018

In this paper, we have implemented speeches that utilized the emotion information of the user's speech and image matching and recommendation system. To classify the user's emotional information of speech, the emotional information of speech about the user's speech is extracted and classified using the PLP algorithm. After classification, an emotional DB of speech is constructed. Moreover, emotional color and emotional vocabulary through factor analysis are matched to one space in order to classify emotional information of image. And a standardized image recommendation system based on the matching of each keyword with the BM-GA algorithm for the data of the emotional information of speech and emotional information of image according to the more appropriate emotional information of speech of the user. As a result of the performance evaluation, recognition rate of standardized vocabulary in four stages according to speech was 80.48% on average and system user satisfaction was 82.4%. Therefore, it is expected that the classification of images according to the user's speech information will be helpful for the study of emotional exchange between the user and the computer.

• Journal of Integrative Natural Science
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• v.12 no.2
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• pp.35-43
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• 2019

In the content-based image search properties, form information is simple because only the contours of objects are available, and although it can effectively extract the characteristics of the objects, it is sensitive to external noise. The radial distortion, one of these noises, is most prominent in the eyewear and, due to the structural characteristics of the imaging equipment, radiative distortion occurs in almost all imaging equipment. It is very important to determine the similarity of the objects in the images in which these distortions occurred to the actual objects. In order to improve this problem, we propose a strong image search technique for formative noise and radiative distortion using regularization phase angles and moments. Through simulation using Wang DB, the proposed algorithm proved excellent performance for radiation distortion that occurs in general. In addition, a system optimized for database can be implemented by making appropriate changes to the threshold values, enabling image retrieval with the desired level of confidence in various systems. The algorithm proposed in this paper is expected to be utilized as an optimal imaging system by extracting morphological form information of multimedia data.

• Journal of Industrial Convergence
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• v.13 no.2
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• pp.1-9
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• 2015

This Study aims to present the guidelines for the activation of the domestic GS certification market through the assessment of the characteristics of the demands of the domestic SW companies pursuing to acquire GS certification. As the results of the factor analysis of the guidelines for the activation of the domestic GS certification market, (1) strictness of the certification standards, (2) level of satisfaction on the certification services and (3) certification effects were deduced as the specific variables. This study is highly significant in that the fact that the certification market is more effectively activated when the 3 factors, namely, strictness of the certification standards, level of satisfaction on the certification services and certification effects, have been intensively reinforced although there exist countless number of specific variables including certification system, certification cost, certification expertise and certification marketing, etc. in order to activate GS certification market has been statistically verified.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.274-276
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• 2021

As artificial intelligence develops rapidly, we can experience it in our everyday life such as with medical, education, and game applications. Traditional SW services were programmed explicitly by the intention of the programmer, and we have conducted evaluation on it. However, due to the uncertianty of AI services, risk follows to the products. Therefore, UX evaluations need to be different from traditional UX evaluations. Therefore, in this paper we suggest a AI-UX framework that consideres the task delegability, UX evaluations metrics, and individual differences.