• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.869-877
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• 2018

The area of desert in East Asia is increasing every year, and it cause a great cost of social damage. Because desert is widely distributed and it is difficult to approach people, remote sensing using satellites is commonly used. But the study of desert area comparison is insufficient which is calculated by satellite sensor. It is important to recognize the characteristics of the desert area data that are calculated for each sensor because the desert area calculated according to the selection of the sensor may be different and may affect the climate prediction and desertification prevention measures. In this study, the desert area of Northeast Asia in 2001-2013 was calculated and compared using Moderate Resolution Imaging Spectroradiometer (MODIS) and Vegetation. As a result of the comparison, the desert area of Vegetation increased by $3,020km^2/year$, while in the case of MODIS, it decreased by $20,911km^2/year$. We performed indirect validation because It is difficult to obtain actual data. We analyzed the correlation with the occurrence frequency of Asian dust affected by desert area change. As a result, MODIS showed a relatively low correlation with R = 0.2071 and Vegetation had a relatively high correlation with R = 0.4837. It is considered that Vegetation performed more accurate desert area calculation in Northeast Asian desert area.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Journal of Periodontal and Implant Science
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• v.46 no.2
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• pp.116-127
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• 2016

Purpose: The objective of this study was to investigate the relationships between primary implant stability as measured by impact response frequency and the structural parameters of trabecular bone using cone-beam computed tomography(CBCT), excluding the effect of cortical bone thickness. Methods: We measured the impact response of a dental implant placed into swine bone specimens composed of only trabecular bone without the cortical bone layer using an inductive sensor. The peak frequency of the impact response spectrum was determined as an implant stability criterion (SPF). The 3D microstructural parameters were calculated from CT images of the bone specimens obtained using both micro-CT and CBCT. Results: SPF had significant positive correlations with trabecular bone structural parameters (BV/TV, BV, BS, BSD, Tb.Th, Tb.N, FD, and BS/BV) (P<0.01) while SPF demonstrated significant negative correlations with other microstructural parameters (Tb.Sp, Tb.Pf, and SMI) using micro-CT and CBCT (P<0.01). Conclusions: There was an increase in implant stability prediction by combining BV/TV and SMI in the stepwise forward regression analysis. Bone with high volume density and low surface density shows high implant stability. Well-connected thick bone with small marrow spaces also shows high implant stability. The combination of bone density and architectural parameters measured using CBCT can predict the implant stability more accurately than the density alone in clinical diagnoses.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.1-15
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• 2007

The objective of this paper is the establishment of finite element analysis frame work for pavement research. Finite element analysis results simulating various loading experiments are verified with sensor measurements obtained from the KHC Test Road. The accuracy of the finite element analysis can be supported by these efforts so that it helps spread out the finite element analysis to pavement research and design processes. The finite element model used in this research is the full 3D nonlinear model including concrete slab, lean concrete base, subbase, shoulder, dowel, and tie-bar. In order to accomplish the accurate verification, the loading condition and the pavement temperature distribution are exactly simulated with field measured data. The curling behavior and the strain distribution are compared with measured responses from the loading tests with a truck and the FWD. Strain and curling predictions from the concrete slab are matched well with measured responses but the strain prediction from the lean concrete base is not matched with measured response. In addition, the magnitude of permanent curling is evaluated with the finite element analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.347-350
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• 2018

In order for an IoT system to automatically make the house temperature pleasant for the user, the system needs to predict the optimal start-up time of air-conditioner or heater to get to the temperature that the user has set. Predicting the optimal start-up time is important because it prevents extra fee from the unnecessary operation of the air-conditioner and heater. This paper introduces an ANN(Artificial Neural Network) and an IoT system that predicts the cooling and heating time in households using air-conditioner and heater. Many variables such as house structure, house size, and external weather condition affect the cooling and heating. Out of the many variables, measurable variables such as house temperature, house humidity, outdoor temperature, outdoor humidity, wind speed, wind direction, and wind chill was used to create training data for constructing the model. After constructing the ANN model, an IoT system that uses the model was developed. The IoT system comprises of a main system powered by Raspberry Pi 3 and a mobile application powered by Android. The mobile's GPS sensor and an developed feature used to predict user's return.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.523-535
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• 2017

Local intelligent services aim at controlling local services such as cooling or lightening services in a certain local area, using Internet-of-Things (IoT) sensor data in the area. As the IoT paradigm has evolved, local intelligent services have gained increasing attention. However, most of the local intelligent service mechanism proposed so far do not directly take the users' presence and service preference information into account for controlling local services. This study proposes an individual presence-and-preference-based local service system (IPP-LISS). We present a intelligent service control algorithm and implement a prototype system of IPP-LISS. Typically, the intelligence part of IPP-LISS including the prediction models, is generated on remote server in the cloud because of their compute-intense aspect. However, this can cause huge data traffic between IoT devices and servers in the cloud. The emerging mobile edge computing technology will be a promising solution of this challenge of IPP-LISS. In this paper, we implement IPP-LISS in the cloud, and then, based on the implementation result, we discuss applying the mobile edge computing technology to the IPP-LISS application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.737-746
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• 2019

Most landslides in the country are shallow failures triggered by intense rainfall. Many researchers have revealed the possibility of predicting shallow failure through the volumetric water content (VWC). This study examined how to determine shallow failure using the gradient characteristics of the volumetric water content. For this, flume experiments were conducted using weathered granite soil. To confirm the saturation state of the surface layer under a rainfall intensity of 30 and 50mm/hr, VWC sensors were installed at depths of 10 and 20 cm on the upper, middle and lower slope. The test results showed that a shallow failure determination using VWC could be applied limitedly according to the slope degree. In addition, the effective cumulative rainfall due to the rainfall infiltration velocity is considered the main factor for the failure time. The failure prediction using the gradient of the VWC depends on the installation location and depth of the sensor. According to the experimental data, the measured value at 20 cm below the slope was most effective. Therefore, an analysis method of VWC and the method of selecting the installation location confirmed through this study can provide important data for presenting the measurement criteria using VWC in the future.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.683-689
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• 2017

We have carried out the development for hydraulic breaker which can be operated by optimal mode with ICT convergence technology. This developed system can predict the rock properties. Moreover, this system can maximize the energy efficient with intelligent control of hydraulic system. In order to provide the optimal impact force, this system can measure the descending depth of piston with the proximity sensor and discriminate the rock properties with the measuring data and control the piston stroke using solenoid valve eventually. In addition, we have developed the controller, display module and operating device for cascade (multi-level impact) system and applied the module which can communicate each system by wireless communications. In conclusion, the control system which can control the multi-level impact in accordance with strength of rocks has been developed and approved by several field tests.

• Current Optics and Photonics
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• v.2 no.3
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• pp.269-279
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• 2018

We are currently investigating the feasibility of a 1.6 m telescope with a laser-guide star adaptive optics (AO) system. The telescope, if successfully commissioned, would be the first dedicated adaptive optics observatory in South Korea. The 1.6 m telescope is an f/13.6 Cassegrain telescope with a focal length of 21.7 m. This paper first reviews atmospheric seeing conditions measured over a year in 2014~2015 at the Bohyun Observatory, South Korea, which corresponds to an area from 11.6 to 21.6 cm within 95% probability with regard to the Fried parameter of 880 nm at a telescope pupil plane. We then derive principal seeing conditions such as the Fried parameter and Greenwood frequency for eight astronomical spectral bands (V/R/I/J/H/K/L/M centered at 0.55, 0.64, 0.79, 1.22, 1.65, 2.20, 3.55, and $4.77{\mu}m$). Then we propose an AO system with a laser guide star for the 1.6 m telescope based on the seeing conditions. The proposed AO system consists of a fast tip/tilt secondary mirror, a $17{\times}17$ deformable mirror, a $16{\times}16$ Shack-Hartmann sensor, and a sodium laser guide star (589.2 nm). The high order AO system is close-looped with 2 KHz sampling frequency while the tip/tilt mirror is independently close-looped with 63 Hz sampling frequency. The AO system has three operational concepts: 1) bright target observation with its own wavefront sensing, 2) less bright star observation with wavefront sensing from another bright natural guide star (NGS), and 3) faint target observation with tip/tilt sensing from a bright natural guide star and wavefront sensing from a laser guide star. We name these three concepts 'None', 'NGS only', and 'LGS + NGS', respectively. Following a thorough investigation into the error sources of the AO system, we predict the root mean square (RMS) wavefront error of the system and its corresponding Strehl ratio over nine analysis cases over the worst ($2{\sigma}$) seeing conditions. From the analysis, we expect Strehl ratio >0.3 in most seeing conditions with guide stars.

• Food Science and Preservation
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• v.16 no.1
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• pp.1-7
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• 2009

Watermelons (Citrulus vulgaris Schrad) are usually sorted manually by weight, appearance, and acoustic impulse, so grading of maturity and internal quality is subject to inaccuracies. It was necessary to develop a nondestructive evaluation technique of internal watermelon quality to reduce human error. Thus, acoustic characteristics related to internal quality factors were analyzed. Among these factors, three (ripeness, presence of an internal cavity, and blood-colored flesh) were selected for evaluation. The number of peaks and the sum of peak amplitudes for watermelons with blood-colored flesh were lower than for normal fruits. The portable evaluation system has an impact mechanism, a microphone sensor, a signal processing board, an LCD panel, and a battery. A performance test was conducted in the field. The internal quality evaluation model showed 87% prediction accuracy. Validation was conducted on 72 samples. The accuracy of quality evaluation was 83%. The quality of samples was evaluated by an inspector using conventional methods (hitting the watermelon and listening to the sounds), and then compared with prototype results. The quality evaluation accuracy of the prototype was better than that of the inspector. This nondestructive quality evaluation system could be useful in the field, warehouse, and supermarket