• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.175-182
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• 1995

Despite the simplicity of processing, a conventional autocorrelation function (ACF) method for the precise determination of fetal heart rate (FHR) has many problems. In case of weak or noise corrupted Doppler ultrasound signal, the ACF method is very sensitive to the threshold level and data window length. It is very troublesome to extract FHR when there is a data loss. To overcome these problems, the high resolution pitch detection algorithm was adopted to estimate the FHR. This method is more accurate, robust and reliable than the ACF method. With a lot of calculation, however, it is impossible to process real time FHR estimation. This paper is presented a new FHR estimation algorithm for real time processing and studied the real time FHR monitoring system by high resolution pitch detection algorithm.

• Convergence Security Journal
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• v.3 no.3
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• pp.51-57
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• 2003

The Real-time DBMS must provide the keeping, fabrication and control function which the data where the user requsets for processing inside the hour when it is restricted, it is quick most and safely[3]. In order lide this to take chare of the real-time control and fabrication function, details recording (log) of the control processing is very important in accomplished transactions from inside the Real-time DBMS. In this proposal, it sees recording which is like this in base and it proposes the new recovery function for transactions log. This recovery technique which it sees used the concept of the LIFO (Last-In-First-Out) method with basic. The proposed technique will becomes the technique which it will be able and to record to process efficiently with a same attribute and the continuous transactions log.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3785-3793
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• 2000

Effective synchronization specification model which can specify temrxlral relationship among media resolving asynchronous problem due to variable network delay is necessary in a distributed multimedia system. Therefore in this paper, we propose RTPN(Real- Time Petri Net) synchronization specification model based on Petri Net for multimedia application in a distributed real time environment. The proposed RTPN model supplies a tlexible decsription of the temporal relationship among various media objects by defining primary key media and relative key media according to delay and importance among media. Firing rule is instantly executed by firing function based on QoS values which supports intra-media and inter-media syncbronization. And asynchronous control algorithm for resynchronization of presentation level is possible more effective supporting of QoS.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.99-102
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• 2003

In this paper, we have developed a system for monitoring and processing the real time sensor data in remote site through Internet. For realizing this system, measurement equipment and protocol are used to transmit the measurement data to remote server and to process measurement data. In server part, the received data from remote site sensor is converted to text or graphic charts for user. The measurement device in sensor part receives the sensor data form sensor and store the received data to its internal memory for transmitting data to server part through Internet. Also the measurement device can receive data form server. The temperature sensor is corrected to the measurement device located in laboratory and the measurement device measures temperature of laboratory which can be confirmed by user through Internet. We have developed a server program working on the Linux to store measurement data from measurement device to server memory. The program is use for SNMP(Simple Network Management Protocol) to exchange data with measurement device. Also the program changes the measurement data into text and graphic charts for user display. The program is use apache PHP program for user display and inquiry. The real time temperature measurement system can be applly for many parts of industry and living.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.359-366
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• 2003

We propose a real-time stereoscopic image conversion method that can generate stereoscopic image with different perspective depth using motion parallax from 2-D image and offer realistic 3-D effect regardless of the direction and velocity of the moving object in the 2-D image. The stereoscopic image is generated by computing the motion parallax between adjacent two 2-D images using the proposed method for motion detection, region segmentation and depth map generation. The proposed method is suitable for real-time stereoscopic conversion processing on various image formats. It has been verified the proposed method by comparing between the stereoscopic image of the proposed method and that of MTD.

• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.10-21
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• 2016

Images taken from outdoor are degraded quality by fog or haze, etc. In this paper, we propose a method that provides the visibility improved images through fog or haze removal. We proposed haze removal method that uses brightness transform based on atmospheric scatter coefficient rate with local histogram equalization. To calculate the transmission rate that indicate fog rate in original image, we use atmospheric scatter coefficient rate based on quadratic equations about haze model. And primary brightness transformed image can be obtained by using the obtained transmission rate. Also we use local histogram equalization with proposed brightness transform for effectively image visibility enhancement. Unlike existing methods, our method can process real-time with stable and effect image visibility enhancement. Proposed method use only the luminance images processed by good performance surveillance systems because it represents the real-time processing is required, black-box, digital camera and multimedia equipment is applicable. Also because it shows good performance only with the luminance images processed, Surveillance systems, black boxes, digital cameras, and multimedia devices etc, that require real-time processing can be applied.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.225-233
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• 2004

A novel real-time color gamut mapping method is described. The color gamut mapping method that is used for enhancing the color reproduction quality between PC monitor and printer devices is adopted for digital TV display quality enhancement. The high definition digital TV display devices operate at the clock speed of around 70MHz ～ 150MHz and permit several nano seconds for real-time gamut mapping. Thus, the concept of three-dimensional reduced resolution look-up table is introduced for real-time processing. The required hardware can be greatly reduced by look-up table resolution adjustment. The proposed hardware architecture is successfully implemented in FPGA and ASIC and also successfully adopted in digital TV display quality enhancement purposes.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.30-38
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• 2008

At past, but smaller enterprises had operated each business automation system about office, at present, are making use of integration ERP information system that take advantage of accessible web technology in outside environment. In this research we took smaller enterprise's example, constructed ERP system that real-time processing is available to supply ERP information to customer by real time and to handle business in outside site. With construction result of this system, we verified efficiency of system and customers' satisfaction etc of customer's complaint solution, business productivity elevation, economical curtailment and so on through various kinds quantitative estimation.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.