• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.211-216
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• 2016

Worldwide casualties caused by earthquakes, floods, fire or other disaster has been increasing. So many researchers are being actively done technical studies to ensure golden-time. In this paper if a disaster occurs, use the IoT technologies in order to secure golden-time and transmits the message after to find the user of the accident area first. When the previous job is finished, gradually finds a user of the surrounding area and transmits the message. For national emergency information, OPEN API of Korea Meteorological Administration was used. To collect detailed information on a relevant area in real time, this study established the system that connects and integrates Crowd Sensing technology with BLE (Bluetooth Low Energy) Beacon technology. Up to now, the CBS based on base station has been applied. However, this study designed and mapped DB in the integration of Beacon based user positioning and national administrative address system in order to estimate local users. In this experiment, the accuracy and speed of information dif6fusion algorithm were measured with a rise in the number of users. The experiments were conducted in a manner that increases the number of users by one thousand and was measured the accuracy and speed of the message spread transfer algorithm. Finally, became operational in less than one second in 20,000 users, it was confirmed that the notification message is sent.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.387-394
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• 2019

In this study, in order to evaluate the damage and deterioration of the track components of sleeper floating track (STEDEF), the field samples(specimens) were taken from the serviced line over 20 years old, and the track components were visually inspected, and investigated by laboratory tests and finite element analysis. As a result of visual inspection, the damage of the rail pad and fastener was slight, but the rubber boot was worn and torn at the edges of bottom. The resilience pads were clearly examined for thickness reduction and fatigue hardening layer. As a result of spring stiffness test of rail pad and resilience pad, the deterioration of rail pad was insignificant, but the deterioration of resilience pad exceeded design standard value. Therefore resilience pad was directly affected by train passing tonnage. As a result of comparing the deterioration state of the field sample and the numerical analysis result, the stress and displacement concentration position of the finite element model and the damage position of the field sample were coincident.

• Korean Chemical Engineering Research
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• v.59 no.3
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• pp.417-428
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• 2021

The combustion characteristics of anthracite, which follow a complex process with low reactivity, must be considered through the dynamic behavior of circulating fluidized bed (CFB) boilers. In this study, computational fluid dynamics (CFD) simulation was performed to analyze the combustion characteristics of anthracite in a pilot scale 0.1 MW_th Oxy-fuel circulating fluidized bed (Oxy-CFB) boiler. The 0.1MW_th Oxy-CFB boiler is composed of combustor (0.15 m l.D., 10 m High), cyclone, return leg, and so on. To perform CFD analysis, a 3D simulation model reactor was designed and used. The anthracite used in the experiment has an average particle size of 1,070 ㎛ and a density of 2,326 kg/m³. The flow pattern of gas-solids inside the reactor according to the change of combustion environment from air combustion to oxygen combustion was investigated. At this time, it was found that the temperature distribution in air combustion and oxygen combustion showed a similar pattern, but the pressure distribution was lower in oxygen combustion. addition, since it has a higher CO₂ concentration in oxygen combustion than in air combustion, it can be expected that carbon dioxide capture will take place actively. As a result, it was confirmed that this study can contribute to the optimized design and operation of a circulating fluidized bed reactor using anthracite.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.134-139
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• 2021

Currently, the autonomous vehicle market is commercializing a level 3 autonomous vehicle, but it still requires the attention of the driver. After the level 3 autonomous driving, the most notable aspect of level 4 autonomous vehicles is vehicle stability. This is because, unlike Level 3, autonomous vehicles after level 4 must perform autonomous driving, including the driver's carelessness. Therefore, in this paper, we propose the Emergency-notification and Driver-response Confirmation System(EDCS) for an autonomousvehicle safety that notifies the driver of an emergency situation and recognizes the driver's reaction in a situation where the driver is careless. The EDCS uses the emergency situation delivery module to make the emergency situation to text and transmits it to the driver by voice, and the driver response confirmation module recognizes the driver's reaction to the emergency situation and gives the driver permission Decide whether to pass. As a result of the experiment, the HMM of the emergency delivery module learned speech at 25% faster than RNN and 42.86% faster than LSTM. The Tacotron2 of the driver's response confirmation module converted text to speech about 20ms faster than deep voice and 50ms faster than deep mind. Therefore, the emergency notification and driver response confirmation system can efficiently learn the neural network model and check the driver's response in real time.

• Journal of Convergence for Information Technology
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• v.9 no.1
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• pp.45-53
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• 2019

We face problems from excessive information served with websites in this rapidly changing information era. We find little information useful and much useless and spend a lot of time to select information needed. Many websites including search engines use web crawling in order to make data updated. Web crawling is usually used to generate copies of all the pages of visited sites. Search engines index the pages for faster searching. With regard to data collection for wholesale and order information changing in realtime, the keyword-oriented web data collection is not adequate. The alternative for selective collection of web information in realtime has not been suggested. In this paper, we propose a method of collecting information of restricted web sites by using Web crawling distributed monitoring system (R-WCMS) and estimating collection time through detailed analysis of data and storing them in parallel system. Experimental results show that web site information retrieval is applied to the proposed model, reducing the time of 15-17%.

• Applied Chemistry for Engineering
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• v.30 no.4
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• pp.408-414
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• 2019

In this study, an antioxidant was extracted from dandelion leaves using traditional hot water and ultrasonic extraction methods. In order to optimize the extraction yield and total flavonoid, an antioxidant, Box-Behnken design (BBD) model among response surface analysis methods was used. In the case of hot water extraction, the extraction temperature and time as well as the ratio of alcohol/ultrapure water were set as variables, and for the ultrasonic extraction, the ultrasonic survey century and irradiation time and the ratio of alcohol/ultrapure water were variables. Optimum extraction conditions in the hot water extraction method were the extraction temperature and time of $45.76^{\circ}C$ and 1.75 h and the ratio of alcohol/ultrapure water of 41.92 vol.%. While for the ultrasonic extraction method the survey century of 512.63 W, the ratio of alcohol/ultrapure water of 56.97 vol.% and the extraction time of 20.79 min were optimum conditions. Expected reaction yield and flavonoid content values under the optimized condition were calculated as 22.09 wt.% and 28.98 mg QE/mL dw, respectively. In addition, the error value of less than 3% was obtained validating our optimization process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.203-209
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• 2019

In this work, a new land-specific resistance measuring device (GM) and a measuring probe (Grounding Rod) are connected to the WENNER quadrant as power-line communication (PLC). In groups of two (P1,P2) probes, five to ten probes are installed in series on the ground at intervals of 1m, 2m, 4m, 8m, and 16m, respectively. If the PLC signal from the GMD is detected by the receiver of the Probe 1 (P1) for measurement, the minute voltage and current for measurement flow from the PSD (power supply) attached to the probe to the ground, and then, through the soil between P1 and P2, enters the Probe 1 (P2). The resistance value is then measured by the principle of voltage drop due to ground resistance. Measure the earth resistance every T seconds up to 1 trillion and store the measured data on the Arduino Server mounted on the main equipment. Stored measurement data can be derived from formulas by Ohm's Law and from inherent resistance (here,). Data obtained in real time will be linked to CDGES programs installed on Main PC, enabling data analysis and real-time monitoring of the ground environment on land. In addition, a three-dimensional display is possible with 3D graph support by identifying seasonal characteristics such as temperature and humidity of land (soils). The limitations of the study will require specific application measures of Test Bed for commercial access to a model that has been developed and operated experimentally.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.87-96
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• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.709-719
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• 2021

Recent progress in analysis and flight simulation methods enables wider use of a virtual certification and reduces number of certification flight tests. Aerodynamic database (AeroDB) is one of the most important components for the flight simulation. It is composed of aerodynamic coefficients at a range of flight conditions and control deflections. This paper proposes and efficient method for construction of AeroDB that combines Gaussian Process based Variable Fidelity Modeling with adaptive sampling algorithm. A case study of virtual certification of a F-16 fighter is presented. Four AeroDB were constructed using different number and distribution of high-fidelity data points. The constructed database is then used to simulate gliding, short pitch, and roll response. Compliance with certification regulations is then checked. The case study demonstrates that the proposed method can significantly reduce number of high-fidelity data points while maintaining high accuracy of the simulation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.