• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.247-252
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• 2013

An intelligent light emitting diode (LED) dimming system is designed and implemented for energy-saving lighting systems. An LED light bulb is powered by an LED driver controlled by a microcontroller using pulse width modulation (PWM) signals. By changing the duty cycle of the PWM signals, the LED driver generates a driving current of up to 1,000 mA. The current consumption by the LED light bulb exhibits a very linear characteristic that indicates that the level of LED dimming can be finely tuned. Multiple sensors-lighting intensity and ultrasonic range sensors-are combined with the LED dimming system to realize an automatically controllable LED lighting system. The light intensity sensor is capable of sensing ambient light. The ultrasonic range sensor can detect objects from 0.15 to 5.6 m at a resolution of 0.0254 m. The collected information by the light intensity and ultrasonic range sensors is processed by the microcontroller that in turn automatically controls the brightness of the LED light bulb. The algorithm of the software for the LED dimming system is also described.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1136-1149
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• 2018

With the increasing of urban electricity demand, making the most use of the power cable carrying capacity has become an important task in power grid system. Contrary to the rated ampacity obtained under extremely conservative conditions, this paper presents the various steady value of cable ampacity by using the changing surrounding parameters under operation, which is based on cable ampacity calculation equation under the IEC-60287 standard. To some degree, the cable ampacity analysis of actual surroundings improves the transmission capacity of cables. This paper reveals the factors that influence cable ampacity such as insulating layer thickness, allowable long-term conductor temperature, the ambient temperature, soil thermal resistance coefficient, and so on, then gives the class of the influence of these parameters on the ampacity, which plays a great role in accurately calculating the real-time ampacity and improving the utilization rate of cable in the complex external environment condition. Furthermore, the transient thermal rating of the cable is analyzed in this paper, and temperature variation of the conductor under different overload conditions is discussed, which provides effective information for the operation and control of the system.

• Earthquakes and Structures
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• v.22 no.2
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• pp.185-201
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• 2022

Structural Health Monitoring (SHM) is used to provide reliable information about the structure's integrity in near realtime following extreme incidents such as earthquakes, considering the inevitable aging and degradation that occurs in operating environments. This paper experimentally investigates an integrated wireless sensor network (Wi-SN) based monitoring technique for damage detection in concrete structures. An effective SHM technique can be used to detect potential structural damage based on post-earthquake data. Two novel methods are proposed for damage detection in reinforced concrete (RC) building structures including: (i) Jerk Energy Method (JEM), which is based on time-domain analysis, and (ii) Modal Contributing Parameter (MCP), which is based on frequency-domain analysis. Wireless accelerometer sensors are installed at each story level to monitor the dynamic responses from the building structure. Prior knowledge of the initial state (immediately after construction) of the structure is not required in these methods. Proposed methods only use responses recorded during ambient vibration state (i.e., operational state) to estimate the damage index. Herein, the experimental studies serve as an illustration of the procedures. In particular, (i) a 3-story shear-type steel frame model is analyzed for several damage scenarios and (ii) 2-story RC scaled down (at 1/6th) building models, simulated and verified under experimental tests on a shaking table. As a result, in addition to the usual benefits like system adaptability, and cost-effectiveness, the proposed sensing system does not require a cluster of sensors. The spatial information in the real-time recorded data is used in global damage identification stage of SHM. Whereas in next stage of SHM, the damage is detected at the story level. Experimental results also show the efficiency and superior performance of the proposed measuring techniques.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1006-1011
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• 2004

Recently, technical trend in machine tools is focused on enhancing of speed, accuracy and reliability. Such high speed usually results in thermal displacement and structural deformation. To minimize such thermal effect, most precision machine tools adopt high precision cooling system. This study proposes a temperature control for an oil cooler system using PI control with fuzzy logic. In a cooler system, the refrigerant flow rate is controlled by rotational speed of the compressor, where the outlet oil temperature is selected as the control variable. The fuzzy control rules iteratively correct PID parameters to minimize the error, difference between the outlet temperature and the reference one. Here, the ambient temperature is used as the reference one. To show the effectiveness of the proposed method, a series of experiments are conducted for an oil cooler system of machine tools, and the results are compared with the ones of a conventional PID control. The experimental results show that the proposed method has advantages of smaller overshoot and smaller steady state error.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.4
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• pp.285-296
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• 1997

The suspended particulate matters had been collected on quartz fiber fiters by a cascade impactor having 9 size stages for 4 years (Sep. 1991 to Dec. 1995) in Kyung Hee University-Suwon Campus. Membrane filters were used to collected the particulate matters on each stage. The weight concentration on each stage was obtained by a microbalance and further chemical element levels were determined by an x-ray fluorescence system. Based on these chemical information, our study focused on applying the target transformation factor analysis (TTFA), a receptor model, to identify aerosol sources and to apportion quantitatively their mass contribution. There are total of 63 ambient data sets. Each data set consists of the 8 size-ranged subdata sets characterized by 16 elemental variables. By the results, four to five sources were extracted from each size range and some sources reappeared in other size ranges. Then total of 8 source profiles were statistically generated from all the ranges, such as oil burning source, soil source, field burning source, gasoline related source, coal burning source, marine source, glass related source, and unknown sources. Apportioning aerosol mass to each source was intensively examined by investigating emission inventories near the study area. The results showed that soil particle source was the most significant contributor. However, coal and oil burning sources were the major anthropogenic ones. The study finally proposed some air quality control strategies to achieve the clean air quality in Suwon area.

• International Journal of Highway Engineering
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• v.20 no.2
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• pp.127-135
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• 2018

PURPOSES : This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS : Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS : Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.2
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• pp.105-115
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• 1994

This study was conducted to assess the health risk of carcinogenic heavy metals such as arsenic, nickel, chromium and cadmium Ambient concentrations of these metals were measured bimonthly, during May 1987 to March 1988. Respirable Particle concentrations of As, Ni, Cr, Cd in traffic area(Shinchon) were 16ng/㎥, 43ng/㎥, 4.2ng/㎥, 6.6ng/㎥, respectively, and in residential area(Bulkwang) were 25ng/㎥, 32ng/㎥, 4.7ng/㎥, 8.9ng/㎥, respectively. Carcinogenic risk of each metal was calculated by multiplication of ambient concentration and unit risk of the metal which was referred to recent version of Integrated Risk Information System(IRIS). Sum of the risk from these for metals was 9.8$\times$10$^{-5}$ as individual risk in traffic area and 13.9$\times$10$^{-5}$ in residential area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.423-443
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• 2009

We present the design and implementation of a unique sensing and actuation application -- the Illuminator: a sensor network-based intelligent light control system for entertainment and media production. Unlike most sensor network applications, which focus on sensing alone, a distinctive aspect of the Illuminator is that it closes the loop from light sensing to lighting control. We describe the Illuminator's design requirements, system architecture, algorithms, implementation and experimental results. The system uses the Illumimote, a multi-modal and high fidelity light sensor module well-suited for wireless sensor networks, to satisfy the high-performance light sensing requirements of entertainment and media production applications. The Illuminator system is a toolset to characterize the illumination profile of a deployed set of fixed position lights, generate desired lighting effects for moving targets (actors, scenic elements, etc.) based on user constraints expressed in a formal language, and to assist in the set up of lights to achieve the same illumination profile in multiple venues. After characterizing deployed lights, the Illuminator computes optimal light settings at run-time to achieve a user-specified actuation profile, using an optimization framework based on a genetic algorithm. Uniquely, it can use deployed sensors to incorporate changing ambient lighting conditions and moving targets into actuation. Experimental results demonstrate that the Illuminator handles various high-level user requirements and generates an optimal light actuation profile. These results suggest that the Illuminator system supports entertainment and media production applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12B
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• pp.1435-1443
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• 2009

In this paper, an energy harvesting sensor network system is modeled and simulated by using the DEVS (Discrete Event System Specification) formalism. The system is composed of a sink (master) node, which is battery or mains powered, and a set of sensor (slave) nodes, each of which harvests ambient energy and converts it into electrical energy. For simulation, (i) the behavior of energy harvesting and storing circuits of the slave node is partitioned into a set of piecewise continuous segments and then each segment is represented as a discrete state; (ii) the interaction among the master node and components of the slave node is investigated preciously; and (iii) the investigated result is modeled and simulated by using the DEVS formalism.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1815-1817
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• 2010

TMSM을 통한 검진 및 센싱 결과를 바탕으로 다량의 복잡한 의료 정보를 지능적으로 통합하는 의료서비스 방식과 앰비언트 정보 시스템을 통한 시각화 시스템은 환자의 상태를 실시간으로 모니터링하며, 환자의 응급상황에 대하여 보다 유연하고 조기 적으로 대처할 수 있게 하여 정보 인지적 부담을 덜고, 인적, 진단 비용을 절약할 수 있다.