• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.163-173
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• 2016

Recently, massive amounts of stream data have been studied for distributed processing. In this paper, we propose an incremental stream data processing method based on in-memory in big data environments. The proposed method stores input data in a temporary queue and compare them with data in a master node. If the data is in the master node, the proposed method reuses the previous processing results located in the node chosen by the master node. If there are no previous results of data in the node, the proposed method processes the data and stores the result in a separate node. We also propose a job scheduling technique considering the load and performance of a node. In order to show the superiority of the proposed method, we compare it with the existing method in terms of query processing time. Our experimental results show that our method outperforms the existing method in terms of query processing time.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.211-216
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• 2017

This paper proposes image processing techniques that improve usability and performance in a diagnostic system of the contrast-enhanced ultrasonography. For a methodology for visualizing diagnostic parameter data in an ultrasonic medical image, an expression of transition time data with successive pixel values and a method of generating a lesion diagnostic parameter image with four categorized values are presented. We also introduce a MRF-based image enhancement technique to eliminate noises from generated parametric images. Such parametric image generation technique can overcome the difficulty of discriminating dynamic change in patterns in the ultrasonography. The technique clarifies the contour of the region in the original image and facilitates visual determination of the characteristics of the lesion through four colors. With regard to this MRF-based image enhancement, we define the energy function of consecutive pixel values and develop a technique to optimize it, and the usability of the proposed theory is examined through experiments with medical images.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.90-96
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• 2021

As real-time data of factories can be collected using various sensors, the adaptation of intelligent unmanned processing systems is spreading via the establishment of smart factories. In intelligent unmanned processing systems, data are collected in real time using sensors. The equipment is controlled by predicting future situations using the collected data. Particularly, a technology for the prediction of tool wear and for determining the exact timing of tool replacement is needed to prevent defected or unprocessed products due to tool breakage or tool wear. Directly measuring the tool wear in real time is difficult during the cutting process in milling. Therefore, tool wear should be predicted indirectly by analyzing the cutting load of the main spindle, current, vibration, noise, etc. In this study, data from the current and acceleration sensors; displacement data along the X, Y, and Z axes; tool wear value, and shape change data observed using Newroview were collected from the high-speed, two-edge, flat-end mill machining process of SKD11 steel. The support vector machine technique (machine learning technique) was applied to predict the amount of tool wear using the aforementioned data. Additionally, the prediction accuracies of all kernels were compared.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.3
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• pp.15-22
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• 2007

An automatic measurement system which collects experimental data at an unmanned station where the networking to the internet could not be accessed was developed. With a Robo-rail accessing to the unmanned station, wireless local networking between server PC at the Rob-rail and client PC at the unmanned station is possible within 30 m from an access point equipment located at the unmanned station. An algorithm for transferring the data file which is saved in the client PC at the unmanned station to the server PC in the Robo-rail was proposed. IEEE-1394 camera was used to collect the data at the client PC. An extracting program from the IEEE-1394 captured images to character data and number data was developed using image processing technique, which drastically reduces the size of data file comparing to that of the raw image file.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• Journal of National Security and Military Science
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• s.1
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• pp.191-229
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• 2003

Multi-sensor data fusion techniques combine evidences from multiple sensors in order to get more accurate and efficient meaningful information through several process levels that may not be possible from a single sensor alone. One of the most important parts in the data fusion system is the identification fusion, and it can be categorized into physical models, parametric classification and cognitive-based models, and parametric classification technique is usually used in multi-sensor data fusion system by its characteristic. In this paper, we propose a novel heuristic identification fusion method in which we adopt desirable properties from not only parametric classification technique but also cognitive-based models in order to meet the realtime processing requirements.

• Journal of the Korean Society for Railway
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• v.8 no.1
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• pp.1-5
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• 2005

This paper has presented the parallel cyclic redundancy check (CRC) technique that performs CRC computation in parallel superior to the conventional CRC technique that processes data bits serially. Also, it has showed that the implemented parallel CRC circuit has been successfully applied to the inductively coupled passive RFTD system working at a frequency of 13.56㎒ in order to process the detection of logical faults more fast and the system has been verified experimentally. In comparison with previous works, the proposed RFID system using the parallel CRC technique has been shown to reduce the latency and increase the data processing rates about 15％ In the results. Therefore, it seems reasonable to conclude that the parallel CRC realization in the RFID system offers a means of maintaining the integrity of data in the high speed RFID system.

• Journal of Korean Tunnelling and Underground Space Association
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• v.6 no.3
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• pp.247-258
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• 2004

Two 3-dimensional data processing techniques to predict the fractured zone ahead of a tunnel face by the tunnel seismic survey were proposed so that the geometric formation of the fractured zone could be estimated. The first 3-dimensional data processing technique was developed based on the principle of ellipsoid, The input data needed for the 3D migration can be obtained from the 2-dimensional tunnel seismic prediction (TSP) test where the TSP test should be performed in each sidewall of a tunnel. The second 3-dimensional migration technique that was developed based on the concept of wave travel plane was proposed. This technique can be applied when the TSP is operated with sources in one sidewall of a tunnel while the receivers are installed in both sidewalls. New migration technique was applied to an in-situ tunnelling site. The 3-dimensional migration was performed using measured TSP data and its results were compared with the geological investigation results that were monitored during tunnel construction. This comparison revealed that the proposed migration technique could reconstruct the discontinuity planes reasonably well.

• Journal of the Korean Institute of Navigation
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• v.19 no.4
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• pp.1-8
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• 1995

Although ship's draught information onboard is substantial for both the safety of navigation and the estimation of loaded cargoes, its accuracy depends, in conventional surveying method, on the skillfulness of observers and the condition of the sea surface round the vessel. To obtain more accurate information accessibly, measuring instruments with sophisticated sensors such as mechanical, electronic and ultrasonic transducers have been developed. However, they have still limitation in accuracy and in making up a system due to the complexity of processing signal. In this paper, we propose a new technique for analyzing ultrasonic pulse signal, in order to improve the measurement accuracy and simplify a remote sensing system of draught by ultrasonic waves. In this technique, pulse signal is translated into phase curve which is composed of the phase value defined in time domain. Then, the time interval between two signals different in waveform, is waveform, is analytically determined by calculating average time difference on phase curves. Also, analytical procedure can be carried out in real time with the successive five data sampled at T/4, for high speed digital processing with computer and A/D converter. This technique is useful for measuring draught under the influence of sea condition and for interfacing its data briefly to the integrated bridge system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.34-41
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• 2009

This paper investigates the issue of efficient reading for sensor data of semi-passive sensor tag. The Cold Chain management system requires complete sensor data without data loss and the short processing time of reading sensor tag data. However, reading the sensed data could be interfered by RF environment such as a jamming, obstacle and so on. This study found that it could lead to loss of the sensed data and takes much time to read it when data loss is occurred. To solve this problem, we propose the transaction processing mechanism that guarantees efficient reading of the sensed data. To do this, we present the technique of dynamic packet size and technique of data recovery to execute read transaction. These techniques improve the reliability of reading operation as well as speed up of read process for the large capacity data. This paper contributes to the improvement of efficient reading of sensed data without any loss of data and large time required.