• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.72-77
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• 2009

In this paper, a 3.2Gb/s clock and data recovery (CDR) circuit for a high-speed serial data communication without the reference clock is described This CDR circuit consists of 5 parts as Phase and frequency detector(PD and FD), multi-phase Voltage Controlled-Oscillator(VCO), Charge-pumps (CP) and external Loop-Filter(KF). It is adapted the PD and FD, which incorporates a half-rate bang-bang type oversampling PD and a half-rate FD that can improve pull-in range. The VCO consists of four fully differential delay cells with rail-to-rail current bias scheme that can increase the tuning range and tuning linearity. Each delay cell has output buffers as a full-swing generator and a duty-cycle mismatch compensation. This materialized CDR can achieve wide pull-in range without an extra reference clock and it can be also reduced chip area and power consumption effectively because there is no additional Phase Locked- Loop(PLL) for generating reference clock. The CDR circuit was designed for fabrication using 0.18um 1P6M CMOS process and total chip area excepted LF is $1{\times}1mm^2$. The pk-pk jitter of recovered clock is 26ps at 3.2Gb/s input data rate and total power consumes 63mW from 1.8V supply voltage according to simulation results. According to test result, the pk-pk jitter of recovered clock is 55ps at the same input data-rate and the reliable range of input data-rate is about from 2.4Gb/s to 3.4Gb/s.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.4
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• pp.6-11
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• 2015

In this study, we surveyed analysis of ADS-B ground trajectory data using non-aviation approval public data. For analysis used non-aviation public data and commercial ADS-B receiver. The study result is available using ADS-B ground trajectory data for airfield surveillance on limited range. Also, to confirmed of available using non-aviation public data for aviation research.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.47-54
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• 2013

Climate change is the most direct threatening factors in sustaining agricultural productivity. It is necessary to reduce the damages from the natural hazards such as flood, drought, typhoons, and snowstorms caused by climate change. Through the vulnerability assessment to adapt the climate change, it is possible to analyze the priority, feasibility, effect of the reduction policy. For the vulnerability assessment, broad amount of weather data for each meterological station are required. Making the database management system for the meteorologic data could troubleshoot of the difficulties lie in handling and processing the weather data. In this study, we generated the meteorologic data retrieval system (MetSystem) for climate change vulnerability assessment. The user interface of MetSystem was implemented in the web-browser so as to access to a database server at any time and place, and it provides different query executions according to the criteria of meteorologic stations, temporal range, meteorologic items, statistics, and range of values, as well as the function of exporting to Excel format (*.xls). The developed system is expected that it will make it easier to try different analyses of vulnerability to natural hazards by the simple access to meteorologic database and the extensive search functions.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.62-65
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• 2003

When a mobile robot moves around autonomously without man-made corrupted bye landmarks, it is essential to recognize the placement of surrounding objects especially for self localization, obstacle avoidance, and target classification and localization. To recognize the environment we use many Kinds of sensors, such as ultrasonic sensors, laser range finder, CCD camera, and so on. Among the sensors, ultra sonic sensors(sonar)are unexpensive and easy to use. In this paper, we analyze the sonar data and propose a method to recognize features of indoor environment. It is supposed that the environments are consisted of features of planes, edges, and corners, For the analysis, sonar data of plane, edge, and corner are accumulated for several given ranges. The data are filtered to eliminate some noise using the Kalman filter algorithm. Then, the data for each feature are compared each other to extract the character is ties of each feature. We demonstrate the applicability of the proposed method using the sonar data obtained form a sonar transducer rotating and scanning the range information around a indoor environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.427-435
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• 2023

Cardinality estimation is used in wide range of applications and a fundamental problem processing a large range of data. While the internet moves into the era of big data, the function addressing cardinality estimation use only on-chip cache memory. To use memory efficiently, there have been various methods proposed. However, because of the noises between estimator, which is data structure per flow, loss of accuracy occurs in these algorithms. In this paper, we focus on minimizing noises. We propose multiple data structure that each estimator has the number of estimated value as many as the number of structures and choose the minimum value, which is one with minimum noises, We discover that the proposed algorithm achieves better performance than the best existing work using the same tight memory, such as 1 bit per flow, through experiment.

• Spatial Information Research
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• v.21 no.4
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• pp.7-14
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• 2013

Recently, R&D(Research and Development) is processing actively on range search in the road network environments. However, the existing representative range search techniques have shortcomings in that the greater the number of POI's, the more increased storage space or the more increased search time due to inefficient search process. Accordingly, In this paper, we proposed a range search technique using QRMP(QR-tree using Middle Point) to solve the problems of conventional range search techniques. In addition, we made a formula to obtain the total size of the storage space for QRMP and proved the excellence of the range search technique proposed in this paper through the experiment using actual road networks and POI data.

• PNF and Movement
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• v.12 no.3
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• pp.159-165
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• 2014

Purpose: The purpose of this study was to investigate the effect of early ankle exercise with functional electrical stimulation(FES) on spasticity, strength and active range of motion of ankle in patients with stroke. Methods: This study included 21 patients with stroke, who were performed early ankle exercise combined FES. The exercise program comprised 5 sessions of 30 minutes per week for 4 weeks. The spasticity, strength and active range of motion of ankle were evaluated before and after training. The spasticity was measured by modified ashworth scale(MAS), strength of ankle was measured by hand-held dynamometer and active range of motion of ankle dorsi-flexion was measured by goniometer. All data were analyzed using SPSS 18.0. Results: Significant differences were observed the subjects for strength of ankle and active range of motion. The results of the study were as follow: strength of ankle was significantly increased subjects(p<.001) and active range of motion was significantly increased subjects(p<.001). Conclusion: Ankle is very important part of body in stroke patients. early ankle exercise with FES is effective for improvement of strength of ankle and active range of motion in patients with stroke. ealry ankle exercise with FES about stroke patient is very useful and effective. It is effective in clinical practice.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.539-543
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• 2005

The research presented in this paper enables real-time 3D modeling to help make construction processes ultimately faster, more predictable and safer. Initial research efforts used an emerging sensor technology and proved its usefulness in the acquisition of range information for the detection and efficient representation of static and moving objects. Based on the time-of-flight principle, the sensor acquires range and intensity information of each image pixel within the entire sensor's field-of-view in real-time with frequencies of up to 30 Hz. However, real-time working range data processing algorithms need to be developed to rapidly process range information into meaningful 3D computer models. This research ultimately focuses on the application of safer heavy equipment operation. The paper compares (a) a previous research effort in convex hull modeling using sparse range point clouds from a single laser beam range finder, to (b) high-frame rate update Flash LADAR (Laser Detection and Ranging) scanning for complete scene modeling. The presented research will demonstrate if the FlashLADAR technology can play an important role in real-time modeling of infrastructure assets in the near future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.