• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.151-159
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• 2021

Cost information in the Korean construction industry is mainly controlled by the government agencies. However, there have been wild-spread speculations among participants on the adequacy of these unit prices and difference with the actual market condition. Korean public-led unit prices are developed using mainly a top-down approach by a few designated public institutions. Due to the rapid fluctuations in market prices and high-volume of information, it is impossible for a few public institutions to properly consider market conditions. However, there are almost none private cost reference while many are available in other countries to supplement the public cost references. Needs for private cost references have recognized, and this study can be seen as a pilot study to support them. This study attempts to identify the problem areas of Korean cost references and to provide guidance by benchmarking other countries. This study has confirmed the need of developing market-driven cost references by employing a bottom-up approach in which a large number of various construction participants are fostered to provide their own cost information and share with others. It is envisioned that this study provides foundations for further study on the development on-line construction market platform based on abundant and appropriate cost information.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.115-121
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• 2021

This paper used big data and artificial intelligence technology to predict the rapidly increasing internet traffic. There have been various studies on traffic prediction in the past, but they have not been able to reflect the increasing factors that induce huge Internet traffic such as smartphones and streaming in recent years. In addition, event-like factors such as the release of large-capacity popular games or the provision of new contents by OTT (Over the Top) operators are more difficult to predict in advance. Due to these characteristics, it was impossible for an ISP (Internet Service Provider) to reflect real-time service quality management or traffic forecasts in the network business environment with the existing method. Therefore, in this study, in order to solve this problem, an Internet traffic collection system was constructed that searches, discriminates and collects traffic data in real time, separate from the existing NMS. Through this, the flexibility and elasticity to automatically register the data of the collection target are secured, and real-time network quality monitoring is possible. In addition, a large amount of traffic data collected from the system was analyzed by machine learning (AI) to predict future traffic of OTT operators. Through this, more scientific and systematic prediction was possible, and in addition, it was possible to optimize the interworking between ISP operators and to secure the quality of large-scale OTT services.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.320-329
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• 2021

In this paper, an empirical model of air bubble size to be applied to an air masker for reduction of underwater radiation noise is presented. The proposed model improves the divergence problem under the low-speed flow condition of the existing model derived using Rayleigh's jet instability model and simple continuity condition by introducing a jet flow velocity of air. The jet flow velocity of air is estimated using the bubble size where the liquid is quiescent. In a medium without flow, the size of the bubble is estimated by an empirical method where bubble formation regime is divided into a laminar-flow range, a transition range, and a turbulent-flow range based on the Reynolds number of the injected air. The proposed bubble size model is confirmed to be in good agreement with the Computational Fluid Dynamics (CFD) analysis result and the experimental results of the existing literature. Using the acoustic inversion method, the air bubble population is estimated from the insertion loss measured during the air injection experiment of the air- masker model in a large cavitation tunnel. The results of the experiments and the bubble size model are compared in the paper.

• Journal of Korean Theatre Studies Association
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• no.48
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• pp.421-446
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• 2012

The purpose of this paper is to shed light onto the historical significance and limitations of the Tsukiji Little Theater's modern performances. The Tsukiji Little Theater holds a position of great importance to the history of both Japanese and Korean modern theater. Some, however, are under the completely opposite impression. There are also mixed opinions about whether the Tsukiji Little Theater is a "model example" of the modern theatrical movement or a "bad example". Based on this controversy, we look into the definitive characteristics of the Tsukiji Little Theater based mostly on "the controversy over translated foreign plays", "the controversy of foreign plays versus original plays", "the value of kabuki" and "Shinpa as a rival". This paper looked into the differences in controversy over translated foreign plays in the Tsukiji Little Theater and the controversy in existing translated foreign plays. It mostly looks at the "casuistry of foreign plays" and the "cultural engineering theory of foreign plays"to get a grasp on the controversy surrounding existing translated foreign plays. Meanwhile, the "internally critical meaning" towards the original plays of renowned writers was strong in the controversy of foreign plays in the Tsukiji Little Theater. Kaoru Osanai defined the 1920s as a dark period, and persisted that because of the activity of the Shingeki movement, foreign plays were needed instead of low-level original plays. This study examines the characteristics of original plays and foreign plays publicly performed at the Tsukiji Little Theater to analyze the "controversy of translated foreign plays versus original plays". The Tsukiji Little Theater mostly put on shows with a strong sense of resistance or that defied the old times. This caused there to be a lot of emphasis put on the rebellious mindset towards old conventions and ideologies for most of the plays, both foreign and original, and the problem arises that little mind was paid to the integrity or beauty of the works. In looking at the "value of kabuki", this paper looked into Kaoru Osanai, who was deeply involved in kabuki actors. He evaluated traditional Japanese arts highly not because of the literary value of their scripts, but because he recognized the value of how they were performed. In order to create a new spectacle, music, dance and mime was taken in from countries around the world, and kabuki was regarded highly as a means of expression on stage. Finally, we also examine the recognized reasons for treating Shinpa as a rival. There is a relationship between these reasons and a complex about the audiences they drew. The Shinpa performances always had many spectators and were successful, but those at the Tsukiji Little Theater were so unpopular with the public that it was hard for them to financially run their theater group. The empty seats in their theater constantly made the modern intellectuals in the Shingeki movement feel inferior.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.58-76
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• 2019

As the number of reported injuries has tended to increase over time, large hospitalization expenditure from excessive medical treatments and hospitalization, and insurance frauds associated with moral hazard in minor collisions have caused a global societal problem. Many occupants of rear-ended vehicles involved in rear-end collisions complain of whiplash injury, which is also known as neck injury, without any anatomical and radiological evidence. With only clinical symptoms, stating that a whiplash injury is a type of injury defined by the Abbreviated Injury Scale would be difficult. Therefore, this study focuses on minor rear-end collisions, where the rear-ender vehicle collides with the rear-ended vehicle at rest. The mathematics dynamic model is employed to simulate a total of 100 rear-end collision scenarios based on various weights and collision speeds and identify how the weights and speeds of both vehicles influence the risk of whiplash injury in occupants involved in minor rear-end collisions. The possibility of an injury is very high when the same-weight vehicles are involved in accidents at collision speeds of 15 km/h or higher. The possibilities are 36% and 84% with collision speeds of 15 km/h and 20 km/h, respectively, if weights are disregarded.

• Korean Chemical Engineering Research
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• v.57 no.4
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• pp.512-518
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• 2019

To develop a membrane electrode assembly (MEA) with lower Pt loading and higher performance in proton exchange membrane fuel cells (PEMFCs), it is an important research issue to understand interfacial structure of Pt/C catalyst and ionomer and design the catalyst layer structure. In this study, we prepared short-side-chain Nafion-based ionomer dispersion using propylene glycol (PG) as a solvent instead of water which is commonly used as a solvent for commercially available ionomers. Cathode catalyst layers with different ionomer content from 20 to 35 wt% were prepared using the ionomer dispersion for the fabrication of four different MEAs, and their fuel cell performance was evaluated. As the ionomer content increased to 35 wt%, the performance of the prepared MEAs increased proportionally, unlike the commercially available water-based ionomer, which exhibited an optimum at about 25 wt%. Small size micelles and slow evaporation of PG in the ionomer dispersion were effective in proton transfer by inducing the formation of a uniformly structured catalyst layer, but the low oxygen permeability problem of the PG-based ionomer film should be resolved to improve the MEA performance.

• Journal of Korean Society of Disaster and Security
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• v.12 no.2
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• pp.15-24
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• 2019

In the previous study, the rainfall data of 1 hour, 6 hours and 3 days were used as the rainfall criterion according to the grade to trigger the debris flow in the highway area, using the rainfall data of Gangwon area and the rainfall time-series data at the spot where the debris flow occurred. In this study, we propose an early warning criterion of the highway debris flow triggering through appropriate combination of three rainfall criteria selected through previous studies and adjustments of rainfall criterion in the highway debris flow triggering. In addition, simulations were conducted using the time-series rainfall data of 2010~2012, which had a large amount of precipitation for the five sites where debris flows occurred in 2013. As a result of the study, the criteria for the early warning of highway unsteadiness on the highway were prepared. In case of the grade-based adjustment, it is preferable to apply the unified rating to the grade B. Also, if the fatigue of the monitoring is not a problem, adjusting it to A or S may be a way to positively cope with the occurrence of highway debris flow.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.179-184
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• 2019

In many countries, such as developing countries where electricity is scarce, small wind turbines in the form of Off Grid are an effective solution to solve power supply problems. In some countries, the expansion of power systems and the decline of electricity-intensive areas have led to the use of small wind power in urban road lighting, mobile communications base stations, aquaculture and seawater desalination. With this change, the size of the small wind power industry is expected to have greater potential than large-scale wind power. In the case of small wind power generators, the generator is controlled at a variable speed, and the voltage and current generated by the generator have many harmonic components. To solve this problem, the AC to DC converter to be studied in this paper is a three-phase step-up type converter with a single switch. The inductor current is controlled in discontinuous mode, and has a characteristic of having a unit power factor by eliminating the harmonic of the input current. The proposed converter is composed of LCL filter and three phase rectification boost converter at the input stage and a single phase full bridge for grid connection. It is a control system with energy storage system(ESS) that the system stabilization can be pursued against the electric power.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.