• Smart Structures and Systems
• /
• v.6 no.3
• /
• pp.263-275
• /
• 2010

In the last decade, wireless sensor networks have emerged as a promising technology that could accelerate progress in the field of structural monitoring. The main advantages of wireless sensor networks compared to conventional monitoring technologies are fast deployment, small interference with the surroundings, self-organization, flexibility and scalability. These features could enable mass application of monitoring systems, even on smaller structures. However, since wireless sensor network nodes are battery powered and data communication is the most energy consuming task, transferring all the acquired raw data through the network would dramatically limit system lifetime. Hence, data reduction has to be achieved at the node level in order to meet the system lifetime requirements of real life applications. The objective of this paper is to discuss some general aspects of data processing and management in monitoring systems based on wireless sensor networks, to present a prototype monitoring system for civil engineering structures, and to illustrate long-term field test results.

• Information Systems Review
• /
• v.7 no.1
• /
• pp.275-295
• /
• 2005

Changes in business environment caused by globalization of the world economy and the beginning of the knowledge society forced hospitals to equip with tools for the enhanced competitiveness. In other words, hospitals must aim three targets such as acquisition of advanced medical skills and equipments, improvement of service level for patients, and achievement of superior managerial performance simultaneously. This study has been done to suggest a way to reduce the possibility of hospital bill claim reduction as an alternative for the achievement of superior managerial performance. If the reduction rate of hospital bill claim is high, it will put negative impact on the hospital's revenue stream and hospital's reliability. Thus, if they want to stay competitive, hospitals need to device ways to cut the reduction rate as much as possible. In this study, a prototype system has been developed and implemented to check the possibility to cut the reduction rate through deep analysis of causes of reduction. The prototype first developed utilizing data mining techniques and the relation rules algorithm. Then the prototype was tested its performance using the D hospital's live data.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.4
• /
• pp.112-120
• /
• 2012

In this paper, we manufactured the wireless video stream system after we scanned EMI(Electro Magnetic Interference)noise in the system. and then, we analysed the noise frequency in the interface, circuit and PCB(Printed Circuit Board). we suggested EMI noise reduction technique. The applied reduction method is low pass filtering, the internal layer placement for high speed video data line and optimization of the system ground condition. the manufactured system improved about 2 ~ 20[dB] margin for EMI limit 40[dBuV/m] at 30 ~ 230[MHz] and 47[dBuV/m] at 230 ~ 1000[MHz].

• Proceedings of the KSR Conference
• /
• 2004.06a
• /
• pp.1142-1147
• /
• 2004

In this study, two damage detection techniques are applied to the railway tunnel liner based on the static deformation data. Models based on uniform reduction of stiffness and smeared crack concept are both employed, and the efficiency and relative advantage are compared with each other. Numerical analyses are performed on the idealized tunnel structure and the effect of white noise, common in most measurement data, is also investigated to better understand the suitability of the proposed models. As a result, model 1 based on uniform stiffness reduction method is shown to be relatively insensitive to the noise, while model 2 with the smeared crack concept is proven to be easily applied to the field situation since the effect of stiffness reduction is rather small. Finally, real deformation data of a rail tunnel in which health monitoring system is in operation are introduced to find the possible damage and it is shown that the prediction shows quite satisfactory result.

• Proceedings of the IEEK Conference
• /
• 2002.06b
• /
• pp.101-104
• /
• 2002

This paper propose that is algorithm of power dissipation reduction in the high level synthesis design for DSP(Digital Signal Processor), as the portable terminal system recently demand high power dissipation. This paper obtain effect of power dissipation reduction and switching activity that increase correlation of operands as input data of function unit. The algorithm search loop or repeatedly data to the input operands of function unit. That can be reduce the power dissipation using the new low power high level synthesis algorithm. In this Paper, scheduling operation search same nodes from input DFG(Data Flow Graph) with correlation coefficient of first input node and among nodes. Function units consist a multiplier, an adder and a register. The power estimation method is added switching activity for each bits of nodes. The power estimation have good efficient using proposed algorithm. This paper result obtain more Power reduction of fifty percents after using a new low power algorithm in a function unit as multiplier.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.18 no.10
• /
• pp.1172-1180
• /
• 2007

OFDM system has very good high spectral efficiency and the robustness to the frequency-selective fading. Because of the high PAPR, OFDM signals can be distorted in nonlinear HPA(High Power Amplifier). So, to overcome the nonlinear distortion, it is very important to reduce the IMD value. With respect to the BER performance, IMD reduction method is better than the PAPR reduction method. However, IMD reduction method has much more system complexity because of the additional FFT processor in transmitter. In this paper, we study the OFDM communication system based on the IMD reduction method using SPW method. A new IMD reduction method is proposed to reduce the computational complexity. SPW method is to divide the input OFDM data into several sub-blocks and to multiply phase weighting values with each sub-blocks for the reduction of PAPR or IMD. Unlike the conventional method, the system size and computational complexity can be reduced.

• The KIPS Transactions:PartC
• /
• v.12C no.4 s.100
• /
• pp.511-518
• /
• 2005

The conventional OFDM (Orthogonal Frequency Division Multiplexing) modulation can be combined with WHT (Walsh-Hadamard Transform) to reduce PAPR (Peak-to-Average Power Ratio) and improve BER (Bit Error Rate) performance. However, this WHT-based OFDM system still suffers a relatively high PAPR. Therefore, we suggest a new technique, called DGT (Data Grouping Technique) and design an OFDM system employing it and WHT to further decrease PAPR without the BER performance degradation. h salient property of DGT is the independence of the side information which is inherently a principal drawback of the well-known PAPR reduction techniques for OFDM system as well as WHT-based OFDM. The simulation programs have been also performed to verify the validity of the proposed system.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.21 no.11
• /
• pp.997-1004
• /
• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.861-864
• /
• 2011

Since national GHG reduction target by 2020 has been presented in Korea, the role of railroad has been reinforced within transport system due to the allocation of reduction target into sector. So, it is necessary to manage activity data systematically for the calculation of GHG emission in railroad. Now, the activity data of diesel consumption for NIR(National Inventory Report) are provided from oil supply and demand statistics. On the other hands, the activity data collected directly from railroad operating companies are used for GHG & Energy Target Management Act. This study aimed to assess the GHG emissions using two kinds of activity data related to the diesel consumption of railroad in 2009 and 2010. As a result, GHG emissions based on oil supply and demand statistics was 636 thousands ton $CO_{2e}$, but the activity data collected from railroad operating companies showed 649 thousands ton $CO_{2e}$ in 2009. Also, the gap of $CO_{2e}$ emission was increased in 2010. These trends were caused because oil supply and demand statistics included total diesel sales volume during 1 year and the activity data collected from railroad operating companies were the amount of diesel consumption only at railcar operation and maintenance step. In conclusion, it is important to develop the management and verification system of activity data with high reliability to substitute oil supply and demand statistics in railroad sector.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.61 no.11
• /
• pp.1706-1712
• /
• 2012

The Beta-ray absorption method (BAM) gives a good solution for measuring the mass concentration of atmospheric particles(PM10 and PM2.5). To determine particular matters (PM) concentration, a ratio of the number of detected beta-ray intensity passing through the clean filter and the dust-sampled filter is used. These intensity data measured in air pollution monitoring such as PM10 and PM2.5 usually contained the additive noise(thermal noise, power supply noise and etc.). Therefore, the estimation performance of mass concentration can be deteriorated by these noises. In this paper, we present a new noise reduction method that is essentially required to develope an automatic continuous PM monitoring system using beta-ray absorption method. By combining the block data averaging technique and curve fitting, in the proposed method, the additive noise can be reduced in the measured data. To evaluate the performance of the proposed method, computer simulations were performed with computer generated signals as the input.