• Fourth Industrial Review
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• v.2 no.1
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• pp.9-17
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• 2022

Purpose -In general, elementary school is the time to take the first social step away from family relationships with parents or siblings. Recently, AI technology has been widely used in everyday life and society. The purpose of this study is to propose a program that can cultivate AI literacy and self-expression for elementary school students according to the trend of the times. Research design, data, and methodology - In this study, prior to developing a self-expression class program for cultivating AI literacy, we looked at the related literature on what AI literacy is. In addition, the digital learning program was analyzed considering that the current AI literacy is based on the cutting edge of digital technology and is located in the same area as digital literacy. Result -This study developed a curriculum for self-expression and AI literacy cultivation. The main feature of this study is that the education program of this study allows 3rd, 4th, and 5th graders of elementary school to express themselves and to express their career problems by combining culture and art with AI programs. Conclusion -Self-expression activity education for cultivating AI literacy should be oriented toward holistic education and should be education as a way to express oneself in order to improve the quality of life of learners

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.79-86
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• 1999

This study was carried out to estimate the area of damaged forest and the volume of stand tree in burned area, Mt. Weol-A in eastern Chinju, Korea using digital maps derived from supervised classification of Landsat thematic mapper(TM) imagery as reference data. Criterion laser estimator and WinDENDRO$^{tm}$(v. 6.3b) system as a computer-aided tree ring measuring system were used to measure a volume and age of sampled tree. The sample site had been chosen in unburned areas having the same terrain condition and forest type of burned areas. The tree age, diameter at breast height, tree height and volume of the sample tree selected from sample site in unburned area were 27years, 20.9cm, 9.7m and $0.1396m^3$ respectively. Total stand volume of sample site was estimated $2.9316m^3$/0.04ha, Damaged stand volume evaluated to about $16,007m^3$ in the burned area of 218.4ha.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.1-10
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• 2006

The objective of this study was to develop a GIS application model for analyzing site-specific suitability and investment efficiency of major plantation tree species. The model was designed to choose the best plantation species in terms of both potential stand growth and investment efficiency. Site index and IRR were used as the criteria for the potential of stand growth and investment efficiency, respectively. In the model, the conditions of forest stand management and site index are estimated as the function of site-environmental factors extracted by a series of spatial analyses of digital maps of FGIS. Based on site index values of tree species, the model screens out all the high potential tree species, in terms of stand growth, as the candidates for species selection and, then, calculates IRR for managing plantation forest stands for all the candidate tree species. The tree species of the highest IRR would be chosen as the one possessing the highest potential in terms of stand growth and profit. The model was applied to a case study for analyzing the site-specific suitability of 6 tree species in Taehwa University Forest of Seoul National University and the results are given in this paper.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.75-82
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• 2015

Major corporations and portals have implemented a link server that connects Content Management Systems (CMS) to the physical address of content in a database (DB) to support efficient content use in web-based environments. In particular, a link server automatically connects the physical address of content in a DB to the content URL shown through a web browser screen, and re-connects the URL and the physical address when either is modified. In recent years, the number of users of digital content over the web has increased significantly because of the advent of the Big Data environment, which has also increased the number of link validity checks that should be performed in a CMS and a link server. If the link validity check is performed through an existing URL-based sequential method instead of petabyte or even etabyte environments, the identification rate of dead links decreases because of the degradation of validity check performance; moreover, frequent link checks add a large amount of workload to the DB. Hence, this study is aimed at providing a link server that can recognize URL link deletion or addition through analysis on the B-tree-based Information Identifier count per interval based on a large amount of URLs in order to resolve the existing problems. Through this study, the dead link check that is faster and adds lower loads than the existing method can be performed.

• Journal of Digital Convergence
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• v.11 no.5
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• pp.429-436
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• 2013

Context aware environment u-health service is to provide health service with recognition of a computer. The computer recognizes that a patient can contact real life in many context. Context aware environment service for recommend have to definition of context data and service recommendations related to factors shall be identified. In this paper, Context aware environment of u-health service will be provide context data related to identifies recommendations factors using multivariate analysis method and recommendations factors creation to decision tree, association rule based decision model. health service recommend for significantly context data can be distinguish through recommendation factors of identify. Also, context data of patient can know preference factors through preference decision model.

• Journal of Digital Convergence
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• v.18 no.6
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• pp.401-409
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• 2020

The purpose of this study is to develop a convergence inpatient medical service patient experience management model(IMSPEMM) that can help in the management strategy of a medical institution to create a patient-centered medical culture. Using the original data from the 2018 Medical Service Experience Survey, 593 people with medical services inpatient(MSI) over the age of 15 were analyzed. By using the decision tree model, we developed a prediction model for overall satisfaction(OS) with the inpatient medical service experience(IMSE) and the intention to recommend patient experience(RI), and were classified into 4 and 7 types. The accuracy of the model was 68.9% and 78.3%. The OS level of IMSE was the nurse area and the hospital room noise management area, and the RI decision factor was the nurse area. It is significant that the IMSPEMM for MSI was presented and confirmed that the nurse area and the noise management area of the hospital room are important factors for the inpatient experience. It is considered that further research is needed to generalize the IMSPEMM.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2009-2019
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• 2013

In this paper, we propose an automatic modulation recognition algorithm based on cyclic moment and new modified cumulant for analog and digital modulation signals. It is noteworthy that each modulated signal has different cycle frequency characteristics according to its order of cyclic moment. By means of this characteristics as classification features, various modulated signals can be efficiently classified. Also, to identify modulated signals having the same cycle frequency characteristics, we take advantage of the additional classification factors such as variations of envelope and phase as well as modified cumulant. The proposed algorithm was evaluated by considering the number of symbols, SNR, and frequency offset. In the simulation condition where the number of gathered symbols was about 819, and SNR and frequency offset were above 10dB and below 25%, respectively, the average accuracy of the proposed algorithm was more than 95%.

• Journal of Digital Convergence
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• v.11 no.6
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• pp.221-233
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• 2013

This study aims to develop the severity-adjusted length of stay(LOS) model for acute stroke patients using data from the hospital discharge survey and propose management of length of stay(LOS) for acute stroke patients and using for Hospital management. The dataset was taken from 23,134 database of the hospital discharge survey from 2004 to 2009. The severity-adjusted LOS model for the acute stroke patients was developed by data mining analysis. From decision making tree model, the main reasons for LOS of acute stroke patients were acute stroke type. The difference between severity-adjusted LOS from the decision making tree model and real LOS was compared and it was confirmed that insurance type and bed number of hospital, location of hospital were statistically associated with LOS. And to conclude, hospitals should manage the LOS of acute stroke patients applying it into the medical information system.

• Journal of Digital Convergence
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• v.16 no.6
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• pp.151-161
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• 2018

Income is a vital aspect of economic life. Knowing what their income will help people create budgets that allow them to pay for their living expenses. Income data is used by banks, stores, and service companies for marketing purposes and for retaining loyal customers; it is a crucial demographic element used at a wide variety of customer touch points. Therefore, it is essential to be able to make income predictions for existing and potential customers. This paper aims to predict employment earnings or income based on history, and uses machine learning techniques such as SVMs (Support Vector Machines), Gaussian, decision tree and DCNNs (Deep Convolutional Neural Networks) for predicting employment earnings. The results show that the DCNN method provides optimum results with 88% compared to other machine learning techniques used in this paper. Improvement of the data length such PCA has the potential to provide more optimum result.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.7
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• pp.53-61
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• 2004

In this paper, we proposed a new architecture of MAC(Multiplier-Accumulator) to operate high-speed multiplication-accumulation. We used the MBA(Modified radix-4 Booth Algorithm) which is based on the 1's complement number system, and CSA(Carry Save Adder) for addition of the partial products. During the addition of the partial product, the signed numbers with the 1's complement type after Booth encoding are converted in the 2's complement signed number in the CSA tree. Since 2-bit CLA(Carry Look-ahead Adder) was used in adding the lower bits of the partial product, the input bit width of the final adder and whole delay of the critical path were reduced. The proposed MAC was applied into the DWT(Discrete Wavelet Transform) filtering operation for JPEG2000, and it showed the possibility for the practical application. Finally we identified the improved performance according to the comparison with the previous architecture in the aspect of hardware resource and delay.