• The KIPS Transactions:PartC
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• v.17C no.2
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• pp.205-214
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• 2010

As network traffic is dramatically increasing due to the popularization of Internet, the need for application traffic classification becomes important for the effective use of network resources. In this paper, we present an application traffic classification method based on fixed IP-port information. A fixed IP-port is a {IP address, port number, transport protocol}triple dedicated to only one application, which is automatically collected from the behavior analysis of individual applications. We can classify the Internet traffic more accurately and quickly by simple packet header matching to the collected fixed IP-port information. Therefore, we can construct a lightweight, fast, and accurate real-time traffic classification system than other classification method. In this paper we propose a novel algorithm to extract the fixed IP-port information and the system architecture. Also we prove the feasibility and applicability of our proposed method by an acceptable experimental result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.791-799
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• 2008

An image recognition for surrounding conditions is very important in image transmission. In recently rears, as the information infrastructure is more general, the user-centered demands in which they want to identify by object's states image using wire or wireless environment have increased. However, existing mobile solution could be hard to expect high quality mage, because limitation of software processing according as network based on mobile terminal which has low band width supports software codec. To solve this weak point, this paper describes on hardware codec design based on MPEG-4 which is international video compression standard. Implemented system contains the embedded CPU for optimized design and it works high quality service as transmission speed and resolution in mobile circumstance.

• Journal of Radiation Industry
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• v.11 no.1
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• pp.13-18
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• 2017

Recently, the number of PET cyclotrons has increased in Korea. A cyclotron mainly produces $^{18}F$, which is used for the production of [$^{18}F$]FDG, a cancer diagnostic radiopharmaceutical. For radiation protection, the discharge control standard under the Nuclear Safety Act limits the radioactive concentration of $^{18}F$ in the exhaust discharged from a nuclear power utilization facility to below $2,000Bq\;m^{-3}$. However, the radioactive concentration of $^{18}F$ discharged during [$^{18}F$]FDG production at the cyclotron facility at Chosun University is maintained at about $1,500Bq\;m^{-3}$ on average, which is 75% of the concentration limit of the discharge control standard, and temporarily exceeds the standard as per the real-time monitoring results. This study evaluated the performance of the exhaust filter unit of the cyclotron facility at Chosun University by assessing the concentration of $^{18}F$ in the exhaust, and an experiment was conducted on the discharge reduction, where $^{18}F$ is discharged without reacting with the FDG precursors during [$^{18}F$]FDG synthesis and is immediately captured by the [$^{18}F$]FDG automatic synthesis unit. Based on the performance evaluation results of the exhaust filter at the cyclotron facility of Chosun University, the measured capture efficiency before and after the filter was found to be 92%. Furthermore, the results of the discharge reduction experiment, where the exhaust $^{18}F$ was immediately captured by the [$^{18}F$]FDG synthesizer, showed a very satisfactory 94.3% reduction in the concentration of discharge compared to the existing discharge concentration.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.157-165
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• 2010

In June 2010, Geostationary Ocean Color Imager (GOCI), the world's first ocean color observation satellite will be launched. GOCI is planned for use in real-time monitoring of the ocean environment around Korean Peninsula by daily analysis of ocean environment measurements of chlorophyll concentration, dissolved organic matter, and suspended sediments taken eight times per day for seven years. GOCI primary data will support a fishery information service and red tide forecasting, and ocean climate change research. In this paper, the development background of GOCI, user requirements, GOCI architecture, and the GOCI on-orbit operational concept are explained.

• International Journal of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.71-75
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• 2019

Sleep apnea is a disease that causes various complications, and the polysomnography is expensive and difficult to measure. The purpose of this study is to develop an unrestricted wearable monitoring system so that patients can be examined in a familiar environment. We used a method to detect sleep apnea events and to determine sleep satisfaction by non-constrained method using SpO2 measurement sensor and 3-axis acceleration sensor. Heart rate and SpO2 were measured at the finger using max30100. After acquiring the SpO2 data of the user in real time, the apnea measurement algorithm was used to transmit the number of apnea events of the user to the mobile phone using Bluetooth (HC-06) on the wrist. Using the three-axis acceleration sensor (mpu6050) attached to the upper body, the number of times of tossing and turning during sleep was measured. Based on this data, this algorithm evaluates the patient's tossing and turning during sleep and transmits the data to the mobile phone via Bluetooth. The power source used 9 volts battery to operate Arduino UNO and sensors for portability and stability, and the data received from each sensor can be used to check the various degree between sleep apnea and sleep tossing and turning on the mobile phone. Through thisstudy, we have developed a wearable sleep apnea measurement system that can be easily used at home for the problem of low sleep efficiency of sleep apnea patients.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.321-327
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• 2019

The purpose of this study is to develop a smart device-based Language Rehabilitation Program (LRP) to improve communication ability for the patients with language disability. The content of the LRP includes a variety of semantic categories and grammatical elements and consists of 17 semantic categories, 29 tasks and 3780 items to improve comprehension/production ability at word level, semantic category level, sentence level and discourse level. We developed LRP as a Windows-base management program and an Android-base language rehabilitation application. LRP was developed into an application for smart devices, providing real-time delivery of training contents, measurement and database of training task results, and patient progress and monitoring. A follow-up study will be conducted on the verification of the language rehabilitation effect using LRP by patients with language disability.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.61-65
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• 2016

Currently, a variety of Information and Communication Technology(ICT) is being broadly utilized for mental health. Especially, mobile application is one of the effective ICT, and several applications have been developed after the spread of smartphones. The mobile-based mental health has several strengths, such as better treatment accessibility and easier check-ups of symptoms or daily activities by real-time monitoring. Better follow-ups of treatment course, more customized feedback and better transportability enable patients to be more adherent. However, there are some limitations of mobile technology about the mental health, such as technical troubles of electric errors, data safety problems and personal information extrusion. Therefore, full considerations should be given during the development and provision of the technology. Most of all, mental health specialists should actively participate in the development process by incorporation of evidence-based experiences and assurance of good clinical qualities.

• Applied Chemistry for Engineering
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• v.32 no.6
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• pp.700-705
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• 2021

A portable and disposable pH sensor based on Ti wire was successfully developed for monitoring hydronium ion concentrations. A sensing electrode was prepared by electrochemically depositing iridium oxide onto a Ti wire, while a reference electrode was fabricated by coating Ag/AgCl ink on a Ti wire. Combining the two electrodes in the pH sensor enabled the collection of open circuit potential signals when the sensor was immersed in solutions of various pH values. The pH sensor exhibited excellent electrochemical sensing performance in terms of sensitivity, response time, repeatability, selectivity, and stability. To demonstrate point-of-measurement applications, the pH sensor was integrated with a wireless electronic module that could communicate with a mobile application. The portable pH sensor accurately measured pH changes in real samples. The results obtained were consistent with those of using a commercial pH meter.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.7-14
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• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.

• Tunnel and Underground Space
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• v.29 no.1
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• pp.1-11
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• 2019

This study investigated use cases of machine learning technology in domestic medical, manufacturing, finance, automobile, urban sectors and those in overseas mining industry. Through a literature survey, it was found that the machine learning technology has been widely utilized for developing medical image information system, real-time monitoring and fault diagnosis system, security level of information system, autonomous vehicle and integrated city management system. Until now, the use cases have not found in the domestic mining industry, however, several overseas projects have found that introduce the machine learning technology to the mining industry for improving the productivity and safety of mineral exploration or mine development. In the future, the introduction of the machine learning technology to the mining industry is expected to spread gradually.