• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.179-186
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• 2004

The purpose of this study is to implement web-based quality cost management system to measure the performance of quality improvement activities in the business firms. Developed WQCMS(Web-based Q-Cost Management System) have ability to collect and analyze quality data generated from various different departments in the inside or outside of the enterprise without any limitations, if end-users are able to access wide area network. It provides the capability to integrate quality information from database and to generate various easy analysis reports to management's needs using built-in analysis tool modules with real-time. The proposed system was developed using Microsoft's .Net technology, ASP.NET and MS-SQL Server 2000. By web-enabling Q-cost management system, the effectiveness of the system management and utilization was realized by easiness of information integration and economical efficiency.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.149-156
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• 2011

Transmission delay and packet loss induced by a communication network can degrade the control performance and, even make the system unstable. This paper presents a method for compensating transmission delay and packet loss in a networked control system for unmanned underwater vehicle. The proposed method is based on Lagrange interpolation in order to satisfy the requirements of simplicity and model-independency. In this work, the lost/delayed data are estimated in real time by only using the past data without requiring any mathematical model of the controlled system. Consequently, the proposed method can be implemented independent of the controlled system, and also it can achieve fast and accurate compensation performance. The performance of the proposed technique is evaluated by numerical simulations with an unmanned underwater vehicle.

• ETRI Journal
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• v.43 no.5
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• pp.775-786
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• 2021

To translate in real time, a simultaneous translation system should determine when to stop reading source tokens and generate target tokens corresponding to a partial source sentence read up to that point. However, conventional attention-based neural machine translation (NMT) models cannot produce translations with adequate latency in online scenarios because they wait until a source sentence is completed to compute alignment between the source and target tokens. To address this issue, we propose a reinforced learning (RL)-based attention mechanism, the reinforced attention mechanism, which allows a neural translation model to jointly train the stopping criterion and a partial translation model. The proposed attention mechanism comprises two modules, one to ensure translation quality and the other to address latency. Different from previous RL-based simultaneous translation systems, which learn the stopping criterion from a fixed NMT model, the modules can be trained jointly with a novel reward function. In our experiments, the proposed model has better translation quality and comparable latency compared to previous models.

• Neurospine
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• v.15 no.4
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• pp.306-322
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• 2018

This review introduces the current technique of photoacoustic imaging as it is applied in imaging-guided surgery (IGS), which provides the surgeon with image visualization and analysis capabilities during surgery. Numerous imaging techniques have been developed to help surgeons perform complex operations more safely and quickly. Although surgeons typically use these kinds of images to visualize targets hidden by bone and other tissues, it is nonetheless more difficult to perform surgery with static reference images (e.g., computed tomography scans and magnetic resonance images) of internal structures. Photoacoustic imaging could enable real-time visualization of regions of interest during surgery. Several researchers have shown that photoacoustic imaging has potential for the noninvasive diagnosis of various types of tissues, including bone. Previous studies of the surgical application of photoacoustic imaging have focused on cancer surgery, but photoacoustic imaging has also recently attracted interest for spinal surgery, because it could be useful for avoiding pedicle breaches and for choosing an appropriate starting point before drilling or pedicle probe insertion. This review describes the current instruments and clinical applications of photoacoustic imaging. Its primary objective is to provide a comprehensive overview of photoacoustic IGS in spinal surgery.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.161-168
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• 2018

Recently, the bio-sensing information systems for collecting and analysing human body information of a patient in real time in the field of medical information and healthcare information service are continuously increasing. Specially, various wearable devices such as a wrist, a garment, and a skin attachment type for supporting health information of a mobile user are rapidly increasing. Until now, there is no patch-type biometric information service model. Therefore, this paper presents a biometric information system model and the application examples to support biometric information sensing and health information service of mobile user with digital patch system as a new biometric information system. As a result, through this research, research issues based on digital patch system are searched to suggest the direction of continuous research.

• International journal of advanced smart convergence
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• v.8 no.1
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• pp.82-86
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• 2019

We aim to use public data different from the remote BEMS energy diagnostics technology and already established and then switch the conventional operation environment to a big-data-based integrated management environment to operate and build a building energy management environment of maximized efficiency. In Step 1, various network management environments of the system integrated with a big data platform and the BEMS management system are used to collect logs created in various types of data by means of the big data platform. In Step 2, the collected data are stored in the HDFS (Hadoop Distributed File System) to manage the data in real time about internal and external changes on the basis of integration analysis, for example, relations and interrelation for automatic efficient management.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.289-293
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• 2019

This paper presents a remote patient monitoring system for diagnostic pure-tone audiometry. A pure-tone audiometer was developed for basic hearing screening; its performance was evaluated according to international standards in terms of linearity, accuracy, and total harmonic distortion. Pure-tone audiometry has a maximum hearing level of 104.9 dB HL that is comparable with other commercial products. The audiometer shows satisfactory linearity with a deviation of ${\pm}0.4dB$, an accuracy of ${\pm}0.025%$, and a total harmonic distortion (THD) of 0.21%. The remote patient monitoring systems include remote control devices based on wide area network (WAN) connections and an audiometer connected in series. Through experimentation, we successfully performed real-time diagnostic communication without delay in transferring audiometric data. This system is expected to supply domestic equipment in the audiometric market and to improve the quality of life of patients in non-clinical environments.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.537-539
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• 2019

Recently, large-scale fires have been generated as urban buildings have become more and more density. Especially, the expansion of smoke in buildings due to high-rise is an problem, and the smoke is the main cause of death in fires. Therefore, in this paper, the image-based smoke detection is proposed through deep learning-based artificial intelligence techniques to prevent possible damage if existing detectors are not detected. In addition, the detection model was not configured simply through only the smoke data set, but the data set in the haze form was additionally composed together to compensate for the accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5252-5268
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• 2018

To support a large-scale Hadoop cluster, Hadoop heartbeat messages are designed to deliver the significant messages, including task scheduling and completion messages, via piggybacking to reduce the number of messages received by the NameNode. Although Hadoop is designed and optimized for high-throughput computing via batch processing, the real-time processing of large amounts of data in Hadoop is increasingly important. This paper evaluates Hadoop's performance and costs when the heartbeat period is controlled to support latency sensitive applications. Through an empirical study based on Hadoop 2.0 (YARN) architecture, we improve Hadoop's I/O performance as well as application performance by up to 13 percent compared to the default configuration. We offer a guideline that predicts the performance, costs and limitations of the total system by controlling the heartbeat period using simple equations. We show that Hive performance can be improved by tuning Hadoop's heartbeat periods through extensive experiments.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.52.2-52.2
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• 2019

Global map of solar surface magnetic field, such as the synoptic map or daily synchronic frame, does not tell us real-time information about the far side of the Sun. A deep-learning technique based on Conditional Generative Adversarial Network (cGAN) is used to generate farside magnetograms from EUVI $304{\AA}$ of STEREO spacecrafts by training SDO spacecraft's data pairs of HMI and AIA $304{\AA}$. Farside(or backside) data of daily synchronic frames are replaced by the Ai-generated magnetograms. The new type of data is used to calculate the Potential Field Source Surface (PFSS) model. We compare the results of the global field with observations as well as those of the conventional method. We will discuss advantage and disadvantage of the new method and future works.