• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.251-260
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• 1998

The Holter monitoring system is a widely used noninvasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we design a high performance intelligent holter monitoring system which is characterized by the small-sized and the low-power consumption. The system hardware consists of one-chip microcontroller(68HC11E9), ECG preprocessing circuit, and flash memory card. ECG preprocessing circuit is made of ECG preamplifier with gain of 250, 500 and 1000, the bandpass filter with bandwidth of 0.05-100Hz, the auto-balancing circuit and the saturation-calibrating circuit to eliminate baseline wandering, ECG signal sampled at 240 samples/sec is converted to the digital signal. We use a linear recursive filter and preprocessing algorithm to detect the ECG parameters which are QRS complex, and Q-R-T points, ST-level, HR, QT interval. The long-term acquired ECG signals and diagnostic parameters are compressed by the MFan(Modified Fan) and the delta modulation method. To easily interface with the PC based analyzer program which is operated in DOS and Windows, the compressed data, that are compatible to FFS(flash file system) format, are stored at the flash memory card with SBF(symmetric block format).

• Journal of Home Health Care Nursing
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• v.5
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• pp.20-31
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• 1998

The purpose of this study was to develop the framework of community-based home care nursing delivery system, and to examine the validity of it. For these, home care nursing study team of College of Nursing, Seoul National University has studied home care nursing system since September, 1996, and has operated home care center since August, 1997. This study has been supported by the Korean Sience Foundation. We organized Committee of rules, and Clinical specialist consultant group for more efficient running of the home care center. In nursing station, research assistant controlled general work, and 5 home care nurses were hired for home visiting. We developed the Standards for operations, that included criteria for clients, central supply system of nursing materials, central management of nursing care cost, advertisement, patient referral system, and so forth. In our center, 108 patients enrolled, and neurologic disorders including cerebrovascular accident, and cancer were the most prevailing diseases. We tried to overcome the limitations of hopital -based home care, and to provide more accessible, efficient, safe, and stable home care nursing. Therefore, we were referred clients from patients and families, public health care center, industries, as well as from hospitals. Meanwhile, we developed home care recording system and assessment-intervention algorithm for various diseases for quality control and standardization. Also, we did continuing education, and tried to detect problems and to find solutions by regular meeting between the committee of rules and home care nurses. As the results of this study, several limitations of operation were found. First, it was difficult to manage and communicate with the doctor in the emergency situation, Second, we spent too much time for trasnsportation, because only five nurses covered all areas of Seoul and nearby cities. Third, preparation for special care of home care nurses were lacked. Forth, criteria for termination of care and frequency of home visit were ambiguous. Fifth, some difficulties were found in retrospective payment system. And finally, interconnection with home care machinery company were needed. Strategies for solving these problems were suggested.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.666-677
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• 2015

The importance of application traffic analysis for efficient network management has been emphasized continuously. Snort is a popular traffic analysis system which detects traffic matched to pre-defined signatures and perform various actions based on the rules. However, it is very difficult to get highly accurate signatures to meet various analysis purpose because it is very tedious and time-consuming work to search the entire traffic data manually or semi-automatically. In this paper, we propose a novel method to generate signatures in a fully automatic manner in the form of sort rule from raw packet data captured from network link or end-host. We use a sequence pattern algorithm to generate common substring satisfying the minimum support from traffic flow data. Also, we extract the location and header information of the signature which are the components of snort content rule. When we analyzed the proposed method to several application traffic data, the generated rule could detect more than 97 percentage of the traffic data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.819-830
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• 2017

An FM radio based PCL system is a passive radar technique for detecting the multiple moving targets from FM radio signals and tracking the trajectories of the targets by calculating the cross-correlation function of direct-path signal and target echo signals. However, the interference signals are received from a surveillance channel, which is designed to receive the target echo signals. Because of this problem, the target echo signals are masked by the strong interference signals and this makes it difficult to detect the true targets from the cross-correlation function. Adaptive filters are known as effective methods for suppressing the interference signals but there is a problem to present their accurate performances in the PCL system because many literatures used the cross-correlation function and the ratio of input and output power as a measure of the performance analysis. In this paper, a performance analysis method is proposed to evaluate the performance of interference cancellation algorithms. By using the property that each component of the filter weight vector is adjusted to suppress the specific interference signal, a performance measure of the interference signal suppression is defined by a function of adaptive filter weights. Based on the proposed method, we compare the performance of the adaptive filters used in the PCL system. Simulation results show that the proposed method can be very effective for evaluating the performance of interference cancellation algorithms.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.117-125
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• 2008

The Object tracking by real-time image analysis is one of the major concerns in computer vision and its application fields. The Object detection process of real-time images must be preceded before the object tracking process. To achieve the stable object detection performance in the exterior environment, adaptive background model generation methods are needed. The adaptive background model can accept the nature's phenomena changes and adapt the system to the changes such as light or shadow movements that are caused by changes of meridian altitudes of the sun. In this paper, we propose a robust background model generation method effective in an illegal parking auto-detection application area. We also provide a evaluation method that judges whether a moving vehicle stops or not. As the first step, an initial background model is generated. Then the differences between the initial model and the input image frame is used to trace the movement of object. The moving vehicle can be easily recognized from the object tracking process. After that, the model is updated by the background information except the moving object. These steps are repeated. The experiment results show that our background model is effective and adaptable in the variable exterior environment. The results also show our model can detect objects moving slowly. This paper includes the performance evaluation results of the proposed method on the real roads.

• Spatial Information Research
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• v.23 no.5
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• pp.1-7
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• 2015

Twitter has the fast propagation and diffusion of information compare to other SNS. Therefore, many researches about detecting real-time event using twitter are progressing. Twitter real-time event detecting system assumes every twitter user as a sensor and analyzes their written tweet in order to detect the event. Researches that are related to this twitter have already obtained good results but confronted the limits because of some problems. Especially, many existing researches are using the method that can trace an event location by using GPS coordinate. However, it can be suggested a definite limitation through the present user's skeptical responses about making personal location information public. Therefore, this paper suggests the method that traces the location information in tweet contents text without using the provided location information from twitter. Associated words were grouped by using the keyword that extracted in tweet contents text. The place that the events have occurred and whether the events have surely occurred are detected by this experiment using this algorithm. Furthermore, this experiment demonstrated the necessity of the suggested methods by showing faster detection compare to the other existing media.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.42-47
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• 2007

To reduce the chattering errors of reed switch sensors in the automatic remote measurement of water meter a reed switch sensor was analyzed and improved. The operation of reed switch sensors can be described as a mechanical contact switch by approximation of permanent magnet piece to generate an electrical pulse. The reed switch sensors are used mostly in measurement application to detect the rotational or translational displacement. To apply for water flow measurement devices, the reed switch sensors should keep high reliability. They are applied for the electronic digital type of water flow meters. The reed switch sensor is just mounted simply on the conventional mechanical type flow meter. A small magnet is attached on a pointer of the water meter counter rotor. Inside the reed sensor two steel leaf springs make mechanical contact and apart repeatedly as rotation of flow meter counter. The counting electrical contact pulses can be converted as the water flow amount. The MCU sends the digital flow rate data to the server using the wireless communication network. But the digital data is occurred difference or won by chattering noise. The reed switch sensor contains chattering error by it self at the force equivalent position. The vibrations such as passing vehicle near to the switch sensor installed location causes chattering. In order to reduce chattering error, most system uses just software methods, for example using filter algorithm and also statistical calibration methods. The chattering errors were reduced by changing leaf spring structure using mechanical characteristics.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.183-190
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• 2013

In this paper, we propose an improved anisotropic diffusion model for micro-crack detection in heterogeneously textured surface of polycrystalline solar wafers. Due to the nature of the image sensor, the gray-level of the diagonal micro-crack is non-uniform. Thus, the conventional algorithms can't fully detect diagonal micro-cracks when the number of iteration is not enough. However, the increasing of the iteration number leads to increase computation time and detects micro-crack thicker than the original micro-crack. In order to overcome this drawback, we use the gradient of north, south, east, and west directions as well as extended directions. To calculate the diffusion coefficients, we compare the gradients of conventional directions and extended directions and apply the larger gradient values to the coefficient function. This is because the proposed method reflects the information of diagonal micro-crack. Comparing to Tsai et al.'s and Ko and Rheem's, the proposed algorithm shows superior efficiency in detecting the diagonal micro-cracks with less iterations in the images of polycrystalline solar wafers. In addition, it also shows that the thickness of segmented micro-crack is similar to the orignal micro-crack.

• Journal of Radiation Protection and Research
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• v.42 no.3
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• pp.158-165
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• 2017

Background: Nuclear facilities in South Korea have generally adopted pressurized ion chambers to measure ambient gamma ray exposure rates for monitoring the impact of radiation on the surrounding environment. The rates assessed with pressurized ion chambers do not distinguish between natural and man-made radiation, so a further step is needed to identify the cause of abnormal variation. In contrast, using NaI(Tl) scintillation detectors to detect gamma energy rates can allow an immediate assessment of the cause of variation through an analysis of the energy spectra. Against this backdrop, this study was conducted to propose a more effective way to monitor ambient gamma exposure rates. Materials and Methods: The following methods were used to analyze gamma energy spectra measured from January to November 2016 with NaI detectors installed at the Korea Atomic Energy Research Institute (KAERI) dormitory and Hanbat University. 1) Correlations of the variation of rates measured at the two locations were determined. 2) The dates, intervals, duration, and weather conditions were identified when rates increased by $5nSv{\cdot}h^{-1}$ or more. 3) Differences in the NaI spectra on normal days and days where rates spiked by $5nSv{\cdot}h^{-1}$ or more were studied. 4) An algorithm was derived for automatically calculating the net variation of the rates. Results and Discussion: The rates measured at KAERI and Hanbat University, located 12 kilometers apart, did not show a strong correlation (coefficient of determination = 0.577). Time gaps between spikes in the rates and rainfall were factors that affected the correlation. The weather conditions on days where rates went up by $5nSv{\cdot}h^{-1}$ or more featured rainfall, snowfall, or overcast, as well as an increase in peaks of the gamma rays emitted from the radon decay products of $^{214}Pb$ and $^{214}Bi$ in the spectrum. This study assumed that $^{214}Pb$ and $^{214}Bi$ exist at a radioactive equilibrium, since both have relatively short half-lives of under 30 minutes. Provided that this assumption is true and that the gamma peaks of the 352 keV and 1,764 keV gamma rays emitted from the radionuclides have proportional count rates, no man-made radiation should be present between the two energy levels. This study proved that this assumption was true by demonstrating a linear correlation between the count rates of these two gamma peaks. In conclusion, if the count rates of these two peaks detected in the gamma energy spectrum at a certain time maintain the ratio measured at a normal time, such variation can be confirmed to be caused by natural radiation. Conclusion: This study confirmed that both $^{214}Pb$ and $^{214}Bi$ have relatively short half-lives of under 30 minutes, thereby existing in a radioactive equilibrium in the atmosphere. If the gamma peaks of the 352 keV and 1,764 keV gamma rays emitted from these radionuclides have proportional count rates, no man-made radiation should exist between the two energy levels.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.754-761
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• 2008

As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.