• Earthquakes and Structures
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• v.19 no.2
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• pp.129-144
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• 2020

In this study, the idea of damping force linearly proportional to horizontal isolation displacement is implemented into sloped rolling-type bearings in order to meet different seismic performance goals. In addition to experimentally demonstrating its practical feasibility, the previously developed analytical model is further modified to be capable of accurately predicting its hysteretic behavior. The numerical predictions by using the modified analytical model present a good match of the shaking table test results. Afterward, several sloped rolling-type bearings designed with linearly variable damping force are numerically compared with a bearing designed with conventional constant damping force. The initial friction damping force adopted in the former is designed to be smaller than the constant one adopted in the latter. The numerical comparison results indicate that when the horizontal isolation displacement does not exceed the designed turning point (or practically when subjected to minor or frequent earthquakes that seldom have a great displacement demand for seismic isolation), the linearly variable damping force design can exhibit a better acceleration control performance than the constant damping force design. In addition, the former, in general, advantages the re-centering performance over the latter. However, the maximum horizontal displacement response of the linearly variable damping force design, in general, is larger than that of the constant damping force design. It is particularly true when undergoing a horizontal isolation displacement response smaller than the designed turning point and designing a smaller value of initial friction damping force.

• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.513-528
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• 2014

The landscape of Christian higher education is changing. Students once spent most of their time in a traditional classroom with a professor, but now they take online and hybrid courses (face to face and online). Some students complete their entire degree in a fully online program. Nearly every type of college in the United States offers online courses. Online learning has clearly moved from a fad to a fixture, and nowhere is that more apparent than at one of the largest universities in the country. As the demand for online course and programs increase, teachers and administrators in Christian universities and colleges face new challenges. Even though some teachers and administrators still believe online education is inferior to traditional face-to-face learning, we found no statistically significant differences in standard measures of learning outcomes between students in the traditional classes and students in the hybrid-online format classes. In this situation, since online education will develop continuously, Christian universities should utilize it variously through complete understanding and research about it predicting the future of online education style.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.217-228
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• 2018

Since the real estate reporting system was first introduced, about 2 million real estate transaction per year have been reported over the last 10 years with an increasing demand for real estate price estimates. This study looks at the applicability and superiority of the regression-kriging method to derive effective real transaction prices estimation on the location where information about real transaction is unavailable. Several issues on predicting the real estate price are discussed and illustrated using the real transaction reports of Jinju, Gyeongsangnam-do. Results have been compared with a simple regression model in terms of the mean absolute error and root square error. It turns out that the regression-kriging model provides a more effective estimation of land price compared to the simple regression model. The regression-kriging method adequately reflects the spatial structure of the term that is not explained by other characteristic variables.

• The Journal of Information Systems
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• v.29 no.3
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• pp.35-52
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• 2020

Purpose Local governments in each region actively hold local festivals for the purpose of promoting the region and revitalizing the local economy. Existing studies related to local festivals have been actively conducted in tourism and related academic fields. Empirical studies to understand the effects of latent variables on local festivals and studies to analyze the regional economic impacts of festivals occupy a large proportion. Despite of practical need, since few researches have been conducted to predict the number of visitors, one of the criteria for evaluating the performance of local festivals, this study developed a model for predicting the number of visitors through various observed variables using a machine learning algorithm and derived its implications. Design/methodology/approach For a total of 593 festivals held in 2018, 6 variables related to the region considering population size, administrative division, and accessibility, and 15 variables related to the festival such as the degree of publicity and word of mouth, invitation singer, weather and budget were set for the training data in machine learning algorithm. Since the number of visitors is a continuous numerical data, random forest, Adaboost, and linear regression that can perform regression analysis among the machine learning algorithms were used. Findings This study confirmed that a prediction of the number of visitors to local festivals is possible using a machine learning algorithm, and the possibility of using machine learning in research in the tourism and related academic fields, including the study of local festivals, was captured. From a practical point of view, the model developed in this study is used to predict the number of visitors to the festival to be held in the future, so that the festival can be evaluated in advance and the demand for related facilities, etc. can be utilized. In addition, the RReliefF rank result can be used. Considering this, it will be possible to improve the existing local festivals or refer to the planning of a new festival.

• Journal of the Korea Concrete Institute
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• v.21 no.1
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• pp.75-84
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• 2009

An analytical model for predicting the shear strength of prestressed concrete beams without shear reinforcement was developed, on the basis of the existing strain-based shear strength model. It was assumed that the compression zone of intact concrete in the cross-section primarily resisted the shear forces rather than the tension zone. The shear capacity of concrete was defined based on the material failure criteria of concrete. The shear capacity of the compression zone was evaluated along the inclined failure surface, considering the interaction with the compressive normal stress. Since the distribution of the normal stress varies with the flexural deformation of the beam, the shear capacity was defined as a function of the flexural deformation. The shear strength of a beam was determined at the intersection of the shear capacity curve and the shear demand curve. The result of the comparisons to existing test results showed that the proposed model accurately predicted the shear strength of the test specimens.

• Journal of IKEEE
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• v.24 no.2
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• pp.543-549
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• 2020

As the importance of security increases in various fields, research on a random number generator (RNG) used for generating an encryption key, has been actively conducted. A high-quality RNG is essential to generate a high-performance encryption key, but the initial pseudo-random number generator (PRNG) has the possibility of predicting the encryption key from the outside even though a large amount of hardware resources are required to generate a sufficiently high-performance random number. Therefore, the demand of high-quality true random number generator (TRNG) generating random number through various noises is increasing. This paper examines and compares the representative TRNG methods based on metastable-based and ring-oscillator-based TRNGs. We compare the methods how the random sources are generated in each TRNG and evaluate its performances using NIST SP 800-22 tests.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.215-221
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• 2020

The paradigm of agriculture is also changing to address the problem of food shortages due to the increase of the world population, climate conditions that are increasingly subtropical, and labor shortages in rural areas due to aging population. With the development of Information Communication Technology (ICT), our daily lives are changing rapidly and heralds a major change in agricultural management. In a hyper-connected society, the introduction of high-tech into traditional Agriculture of the past is absolutely necessary. In the development process of Agriculture, the first generation produced by hand, the second generation applied mechanization, and the third generation introduced automation. The fourth generation is the current ICT operation and the fifth generation is artificial intelligence. This paper investigated Smart Farm that increases productivity through convergence of Agriculture and ICT, such as smart greenhouse, smart orchard and smart Livestock. With the development of sustainable food production methods in full swing to meet growing food demand, Smart Farming is emerging as the solution. In overseas cases, the Netherlands Smart Farm, the world's second-largest exporter of agricultural products, was surveyed. Agricultural automation using Smart Farms allows producers to harvest agricultural products in an accurate and predictable manner. It is time for the development of technology in Agriculture, which benchmarked cases of excellence abroad. Because ICT requires an understanding of Internet of Things (IoT), big data and artificial intelligence as predicting the future, we want to address the status of theory and actual Agriculture and propose future development measures. We hope that the study of the paper will solve the growing food problem of the world population and help the high productivity of Agriculture and smart strategies of sustainable Agriculture.

• Journal of the Korea Society of Computer and Information
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• v.19 no.8
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• pp.19-26
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• 2014

Analysis of influential factors on water consumption in households will help predicting the water demand of end-use in household and give an explanation to cause on the change of trend. In this research, the data are gathered by radio telemetry system which is combined electronic flow-meter and wireless communication system in 140 household in Korea. Using this data, we estimate for each residential type to determine liter per capita day. we used real data to predict bathtub and washbowl water-uses and compared the ordinary least square regression model and autoregressive regression error model. The results of this study can be applied in the planning stages of water and waste water facilities.

• Korean Journal of Computational Design and Engineering
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• v.21 no.3
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• pp.252-266
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• 2016

An architectural pre-design, which is conducted prior to the architecture design, supports fundamental configuration during the entire AEC project by predicting the cost, demand, etc., of the building, and is therefore gaining importance. In particular, the massing calculation of the pre-design phase should be prioritized, as it is fundamental to architectural outline. However, most architects depend on only their experience and intuition while conceptualizing an integrated framework of design conditions, including the building code and requirements for the massing calculation of the object. Therefore, many difficulties arise in terms of performing appropriate tasks. Thus, the purpose of this study is to implement a knowledge-based BIM for explicitly representing the design knowledge, which is the basis of decision making for an architect while performing the massing calculation. In particular, the 3D knowledge relevant to a project can be provided and accumulated in the massing calculation by the BIM system; this facilitates an integral understanding. Consequently, the approximate result of massing calculation in 3D BIM environment, through both the knowledge-based BIM template and plug-in, can be swiftly provided to the architect. In addition, the architect can invent various alternatives, estimate resulting costs, and reuse the accumulated knowledge in future BIM design processes.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.3
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• pp.45-52
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• 2016

This study is to predict the biogas production and the content analysis of the organic wastes of three islands located in the City of I. Content analysis for a total of six sections, including pH, BOD, COD, three components (Moisture, Ash, Combustibles)was conducted on the specimens of organic wastes from the representative spots of three islands. From the analysis result of organic waste, it is confirmed that more than $1,750,000m^3$ of methane gas per year will be generated through the calculation of the total methane generation for the COD value. Therefore, if the incineration facility for the organic waste in island region is converted into a biogas production facilities which is non-incineration facility, it seems that the organic waste of efficient utilization is available.