• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.451-454
• /
• 2005

Recently, many methods to analyze signal have been proposed and representative methods are the Fourier transform and wavelet transform. In these methods, the Fourier transform represents signal with combination cosine and sine at all locations in the frequency domain. However, it doesn't provide time information that particular frequency occurs in signal and depends on only the global feature of the signal. So, to improve these points the wavelet transform which is capable of multiresolution analysis has been applied to many fields such as speech processing, image processing and computer vision. And the wavelet transform, which uses changing window according to scale parameter, presents time-frequency localization. In this paper, we proposed a new approach using a wavelet of cosine and sine type and analyzed features of signal in a limited point of frequency-time plane.

• The KIPS Transactions:PartB
• /
• v.16B no.1
• /
• pp.47-54
• /
• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

• Journal of Sensor Science and Technology
• /
• v.21 no.2
• /
• pp.135-143
• /
• 2012

Arterial stiffness is causing the serious problems for human who is suffered from hypertension and metabolic syndrome. So it is important that measure the arterial stiffness for early prevention. Many researches point out that pulse wave velocity(PWV) is the reliable and simple method to predict arterial stiffness. In this paper, we developed the sensing parts that detect the pulse wave and ECG by using piezoelectric film and conductive textile with elastic band. Our system could detect 3ch pulse wave and ECG. Simultaneously, our algorithm extracts the features for calculating the delays among pulse waves. The delays are the significant parameter to estimate PWV, thus we design the experiment for evaluating the performance of our sensing parts. The reference is PP-1000(HanByul Meditech, Korea) that is good for performance evaluation. As a result, the start point of the pulse wave was the most reliable feature for comparing with PP-1000(r=0.691, P=0.00). The results between two operators showed that there is only a slight difference in the reproducibility of the devices. In conclusion, we assume that the suggested sensor could be more comfortable and faithful method for arterial stiffness.

• Journal of Power Electronics
• /
• v.11 no.3
• /
• pp.360-368
• /
• 2011

This paper proposes an active frequency with a positive feedback in the d-q frame anti-islanding method suitable for a robust phase-locked loop (PLL) algorithm using the FFT concept. In general, PLL algorithms for grid-connected PV PCS use d-q transformation and controllers to make zero an imaginary part of the transformed voltage vector. In a real grid system, the grid voltage is not ideal. It may be unbalanced, noisy and have many harmonics. For these reasons, the d-q transformed components do not have a pure DC component. The controller tuning of a PLL algorithm is difficult. The proposed PLL algorithm using the FFT concept can use the strong noise cancelation characteristics of a FFT algorithm without a PI controller. Therefore, the proposed PLL algorithm has no gain-tuning of a PI controller, and it is hardly influenced by voltage drops, phase step changes and harmonics. Islanding prediction is a necessary feature of inverter-based photovoltaic (PV) systems in order to meet the stringent standard requirements for interconnection with an electrical grid. Both passive and active anti-islanding methods exist. Typically, active methods modify a given parameter, which also affects the shape and quality of the grid injected current. In this paper, the active anti-islanding algorithm for a grid-connected PV PCS uses positive feedback control in the d-q frame. The proposed PLL and anti-islanding algorithm are implemented for a 250kW PV PCS. This system has four DC/DC converters each with a 25kW power rating. This is only one-third of the total system power. The experimental results show that the proposed PLL, anti-islanding method and topology demonstrate good performance in a 250kW PV PCS.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.11
• /
• pp.2662-2670
• /
• 1997

High speed network makes possible to transfer not only the test data but also multimedia data such as audio, image, and moving pictures and etc. In a multimedia applications, as a multimedia storage system, it is necessary to use a disk array to store and retrieve data by real time. It is important feature to various disk array parameters as a storage system on a real VOD system, such as configuration method of each disks and allocation method of multimedia data. In this paper, various parameters for the disk array are decided to be used for the video-on-demand system application by simulations in two ways. The real and simulation measurement are compared and analyzed on the performance. Simulation results shows that RAID level 5 and 256KB as striping unit and 185KB as data requests size per seconds are suitable parameter for the disk array architecture which provides MPEG-1 files with a rate of 1.5Mbps in two measurements of real and simulation.

• Journal of Soil and Groundwater Environment
• /
• v.19 no.2
• /
• pp.25-37
• /
• 2014

The volcanic type of geothermal water is linked intimately to active or potentially active volcanoes and takes place near the plate boundaries. In contrast to the volcanic type, the geothermal water in Korea has a non-volcanic origin. Korea's geothermal water is classified into the residual magma (RM) type and deep groundwater (DG) type according to the criterion of $35^{\circ}C$. This study reviewed the relationship between the physical and chemical features of the 281 geothermal water sources in South Korea in terms of the specific capacity, water temperature, and chemical compositions of two different basements (igneous rock and metamorphic rock) as well as the geological structures. According to the spatial relationship between the geothermal holes and geological faults, the length of the major fault is considered a key parameter determining the movement to a deeper place and the temperature of geothermal water. A negligible relationship between the specific capacity (Q/s) and temperature was found for both the RM type and DG type with the greater specific capacities of the RM- and DG-igneous types than the RM- and DG-metamorphic types. No relationship was observed between Q/s and the chemical constituents ($K^+$, $Na^+$, $Ca^{2+}$, $Mg^{2+}$, $Zn^{2+}$, $Cl^-$, $SO_4{^{2-}}$, $HCO_3{^-}$, and $SiO_2$) in the DG-igneous and DG-metamorphic types. Furthermore, weak relationship between temperature and chemical constituents was found for both the RM type and DG type.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.681-686
• /
• 2012

This paper studied the speech parameters less affected by the human emotion for the development of the robust emotional speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient, root-cepstral coefficient, PLP coefficient and frequency warped mel-cepstral coefficient in the vocal tract length normalization method were used as feature parameters. And CMS (Cepstral Mean Subtraction) and SBR(Signal Bias Removal) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using frequency warped RASTA mel-cepstral coefficient in the vocal tract length normalized method, its derivatives and CMS as a signal bias removal showed the best performance.

• Korean Journal of Remote Sensing
• /
• v.25 no.2
• /
• pp.95-105
• /
• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.11
• /
• pp.29-39
• /
• 2019

As mobile robot applications increase in real life, the need of low cost autonomous driving are gradually increasing. We propose a novel vision-based real-time lane detection and tracking system that supports autonomous driving of mobile robots in constrained tracks which are designed considering indoor driving conditions of mobile robots. Considering the processing of lanes with various shapes and the pre-adjustment of operation parameters, the system structure with multi-operation modes are designed. In parameter tuning mode, thresholds of the color filter is dynamically adjusted based on the geometric property of the lane thickness. And in the unstable input mode of curved tracks and the stable input mode of straight tracks, lane feature pixels are adaptively extracted based on the geometric and temporal characteristics of the lanes and the lane model is fitted using the least-squared method. The track centerline is calculated using lane models and the motion model is simplified and tracked by a linear Kalman filter. In the driving experiments, it was confirmed that even in low-performance robot configurations, real-time processing produces the accurate autonomous driving in the constrained track.

• Biomedical Engineering Letters
• /
• v.8 no.4
• /
• pp.365-371
• /
• 2018

Uninterrupted monitoring of multiple subjects is required for mass causality events, in hospital environment or for sports by medical technicians or physicians. Movement of subjects under monitoring requires such system to be wireless, sometimes demands multiple transmitters and a receiver as a base station and monitored parameter must not be corrupted by any noise before further diagnosis. A Bluetooth Piconet network is visualized, where each subject carries a Bluetooth transmitter module that acquires vital sign continuously and relays to Bluetooth enabled device where, further signal processing is done. In this paper, a wireless network is realized to capture ECG of two subjects performing different activities like cycling, jogging, staircase climbing at 100 Hz frequency using prototyped Bluetooth module. The paper demonstrates removal of baseline drift using Fast Fourier Transform and Inverse Fast Fourier Transform and removal of high frequency noise using moving average and S-Golay algorithm. Experimental results highlight the efficacy of the proposed work to monitor any vital sign parameters of multiple subjects simultaneously. The importance of removing baseline drift before high frequency noise removal is shown using experimental results. It is possible to use Bluetooth Piconet frame work to capture ECG simultaneously for more than two subjects. For the applications where there will be larger body movement, baseline drift removal is a major concern and hence along with wireless transmission issues, baseline drift removal before high frequency noise removal is necessary for further feature extraction.