• Journal of Advanced Navigation Technology
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• v.21 no.3
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• pp.306-311
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• 2017

In the future ubiquitous network, information will collect data from various sensors in the field. Since the sensor nodes are equipped with small, often irreplaceable, batteries with limited power capacity, it is essential that the network be energy-efficient in order to maximize its lifetime. In this paper, we propose an effective network routing method that can operate with low power as well as the transmission of data and information obtained from sensor networks, and identified the number of sensors with the best connectivity to help with the proper placement of the sensor. These purposes of this research are the development of the sensor middle-ware to integrate the maritime information and the proposal of the routing algorithm for gathering the maritime information of various sensors. In addition, for more secure ship navigation, we proposed a method to construct a sensor network using various electronic equipments that are difficult to access in a ship, and then construct a communication system using NMEA(the national marine electronics association), a ship communication standard, in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.375-381
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• 2019

Structural health monitoring to determine structural conditions at an early stage and to efficiently manage the energy requirements of buildings using systems that collects relevant data, is under active investigation. Structural monitoring requires cutting-edge technology in which construction, sensing, and ICT technologies are combined. However, the scope of application is limited because expensive sensors and specialized technical skills are often required. In this study, a Raspberry Pi module, one of the most widely used single board computers, a Lora module that is capable of long-distance communication at low power, and a high-performance accelerometer are used to construct a wireless edge computing system that can monitor building response over an extended time period. In addition, the Raspberry Pi module utilizes an edge computing algorithm, and only meaningful data is obtained from the vast amount of acceleration data acquired in real-time. The raw data acquired using Wi-Fi communication are compared to the Laura data to evaluate the accuracy of the data obtained using the system.

• Journal of Advanced Marine Engineering and Technology
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• v.19 no.1
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• pp.60-70
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• 1995

In the field of marine transportation the energy saving is one of the most important factors for profit. In order to reduce the fuel oil consumption the ship's propulsion efficiency must be increased as much as possible. The propulsion efficiency depends upon a combination of an engine and a propeller. The propeller has better efficiency as lower rotational speed. This situation led the engine manufacturers to design the engine that has lower speed, longer stroke and a small number of cylinders. Consequently the variation of rotational torque became larger than before because of the longer delay-time in the fuel oil injection process and an increased output per cylinder. As this new trends the conventional mechanical-hydrualic governors for engine speed control have been replaced by digital speed controllers which adopted the PID control or the optimal control algorithm. But these control algorithms have not enough robustness to suppress the variation of the delay-time and the parameter pertubation. In this paper we consider the delay-time and the perturbation of engine parameters as the modeling uncetainties. Next we design the controller which has zero offset in steady state engine speed, based on the two-degree-of-freedom control theory and $\mu$-synthesis. Thd validity of the controller is investigated through the response simulation. We use a personal computer and an analog computer as the digital controller and the engine (plant) part respectively. And, we certify that the designed controller maintains its performance even though the engine parameters may vary.

• Journal of Drive and Control
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• v.10 no.4
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• pp.1-6
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• 2013

With aggravation of environmental contamination and energy resource exhaustion, Hybrid Electric Vehicles (HEV) that can be economically operated with low fuel consumption are receiving greater attention. For performance improvement of such HEV, the development of efficient transmission can be seen as one of core technologies such as performance of components and driving strategy. Dual clutch transmission (DCT) is actively studied as a transmission type for HEV due to its advantages of having excellent power transmission efficiency based on manual transmission characteristic, resolving the problem of power interruption, and realizing driving convenience of automatic transmission (AT). In this paper, one diesel HEV equipped with 6-Speed DCT, modelled using MATLAB/Simulink, and a performance simulator developed for this vehicle are introduced. Driving simulation with driving cycles such as FTP75 and NYCC was performed using the developed performance simulator, and the simulated results regarding state of charge and fuel economy, when AT and DCT are applied to this diesel hybrid vehicle respectively, are compared. This performance simulator can be utilized to develop a control algorithm for improving the fuel economy of HEV with DCT.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.461-467
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• 2019

As the convergence solutions become more common, the use of Arduino and Raspberry Pi boards has been increasing. These control boards has to be executed under power blackout. In this environment, we take advantage of solar power system to overcome the power out. In this paper, we poposed a effficient power control strategy. Our experimental device is a DSLR shooting device executed based a predesigned interval time. The control module of our experimental device is the compound system of Raspberry Pi and Arduino boards. Arduino board send the force signals to wake up Raspberry Pi. We developed a new control strategy algorithm for the efficient use of solar power energy. In this paper, we mesured the efficiency of solar enery consuming of our system. We programmed a control system to send DSLR shooting signals. In experimentals, we ensured a stable consuming of electricity during 10 days. In the end, it was found that the consumption power of the Raspberry was reduced by about 81% when the Aduino was combined to save power.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.1-9
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• 2020

In this paper, we propose Dynamic Rank Subsetting (DRAS) technique that enhances the energy-efficiency and the performance of memory system through the data compression. The goal of this technique is to enable a partial chip access by storing data in a compressed format within a subset of DRAM chips. To this end, a memory rank is dynamically configured to two independent sub-ranks. When writing a data block, it is compressed with a data compression algorithm and stored in one of the two sub-ranks. To service a memory request for the compressed data, only a sub-rank is accessed, whereas, for a memory request for the uncompressed data, two sub-ranks are accessed as done in the conventional memory systems. Since DRAS technique requires minimal hardware modification, it can be used in the conventional memory systems with low hardware overheads. Through experimental evaluation with a memory simulator, we show that the proposed technique improves the performance of the memory system by 12% on average and reduces the power consumption of memory system by 24% on average.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.137-142
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• 2021

The Internet of Things (IoT) paradigm is at the forefront of present and future research activities. The huge amount of sensing data from IoT devices needing to be processed is increasing dramatically in volume, variety, and velocity. In response, cloud computing was involved in handling the challenges of collecting, storing, and processing jobs. The fog computing technology is a model that is used to support cloud computing by implementing pre-processing jobs close to the end-user for realizing low latency, less power consumption in the cloud side, and high scalability. However, it may be that some resources in fog computing networks are not suitable for some kind of jobs, or the number of requests increases outside capacity. So, it is more efficient to decrease sending jobs to the cloud. Hence some other fog resources are idle, and it is better to be federated rather than forwarding them to the cloud server. Obviously, this issue affects the performance of the fog environment when dealing with big data applications or applications that are sensitive to time processing. This research aims to build a fog topology job scheduling (FTJS) to schedule the incoming jobs which are generated from the IoT devices and discover all available fog nodes with their capabilities. Also, the fog topology job placement algorithm is introduced to deploy jobs into appropriate resources in the network effectively. Finally, by comparing our result with the state-of-art first come first serve (FCFS) scheduling technique, the overall execution time is reduced significantly by approximately 20%, the energy consumption in the cloud side is reduced by 18%.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.81-89
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• 1996

It is very important for ultrasonic test method to evaluate the integrity of the class I components in nuclear power plants. However, as the rltrasonic test is affected by internal structures and configurations of test materials, backscattering, that is, time invariant noise is generated in large grain size materials. Due to the above reason, the received signal results in low signal to noise(S/N) ratio. Split spectrum processing(SSP) technique is effective to suppress the grain noise. The conventional SSP technique. however, has been applied to unique algorithm. This paper shows that MPO(minimization and polarity threshold) algorithm which two algorithms are applied simulatancously, was utilized, the signal processing time was shorten by using the new constant-Q SSP with the FIR filter which frequency to bandwidth ratio is constant and the optimum parameters were analysed for the signal processing to longitudinal wave and shear wave with the same requirements of inspection on nuclear power plant site. Moreover, the new ultrasonic test instrument, the reference block of the same product form and material specification, stainless stell test specimens and copper test specimens block of the same fabricated for the application of new SSP technique. As the result of experimental test with new ultrasonic test instrument and test specimens, the signal to noise ratio was improved by appying the new SSP technique.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.1 s.53
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• pp.89-97
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• 2007

Parameters including the seismic sources and the elastic wave propagation characteristics were analysed using the observed ground motions from 12 Fukuoka region earthquakes. The Levenberg-Marquardt algorithm was applied to invert all the variables non-linearly and simultaneously with S wave energy in fiequency domain. Average stress drop of 12 events and local attenuation parameter $\kappa$ under seismic stations were estimated to about 79.2-bar and 0.043 respectively. Regional attenuation parameter, Qo and ${\eta}$, were also estimated to be about 248.1 and 0.558 respectively. Low value of Qo seems to caused by inhomogeneous tectonic characteristics between Japan island and southern Korean peninsula. $\kappa$ values are much higher than that characterizing EUS (Eastern United States) region, and nearly similar to that of WUS (Western Waited States) region. If the informations on site specific amplification of all the seismic stations are known, $\kappa$ values can be estimated more precisely. All the values including the seismic sources and the site and crustal scale propagation characteristics can be used as seismic design parameters.

• Journal of IKEEE
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• v.22 no.2
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• pp.495-498
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• 2018

In this paper, we propose an DAP system for dose evaluation of medical and industrial X-ray generator. Based on the DAP measurement technique using the Ion-Chamber, the proposed system can clearly measure the exposure radiation dose generated by the diagnostic X-ray apparatus. The hardware part of the DAP measures the amount of charge in the air that is captured by an X-ray. The high-speed processing algorithm part for cumulative radiation dose measurement through microcurrent measures the amount of charge captured by X-ray at a low implementation cost (power) with no input loss. The wired/wireless transmission/reception protocol part synchronized with the operation of the X-ray generator improves communication speed. The PC-based control program part for interlocking and aging measures the amount of X-ray generated in real time and enables measurement graphs and numerical value monitoring through PC GUI. As a result of evaluating the performance of the proposed system in an accredited testing laboratory, the measured values using DAP increased linearly in each energy band (30, 60, 100, 150 kV). In addition, since the standard deviation of the measured value at the point of 4 division was ${\pm}1.25%$, it was confirmed that the DAP showed uniform measurements regardless of location. It was confirmed that the normal operation was not less than ${\pm}4.2%$ of the international standard.