• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.497-504
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• 2018

This paper studies about the Oriental Medical Expert System, based on Open Source Drools for rule engine processing, which contains scalability, availability, and modifiability. The system is developed with the Spring MVC framework and Ajax for stable services of the Web-based Medical Expert System. The diagnosis and treatment process of this Medical Expert system provides a service that provides the general users to accesses the web with a series of questionnaires. In order to compensate for the asynchronous communication between clients and services, and also for the complicated JDBC weaknesses, we applied the data handling in JSON to reduce the servers' loads, and also the Mybatis framework to improve the performance of the RDBMS, respectively. In addition, as the number of users increases to cope with the maximum available services of the web-based system, the load balancing structure using Nginx has been developed to solve the server traffic problems and the service availability has been increased. The experimental results show the stable services by approving the scalability test.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.465-472
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• 2021

In this paper, we present an approach for detection of adverse drug reactions from drug reviews to compensate limitations of the spontaneous adverse drug reactions reporting system. Considering negative reviews usually contain adverse drug reactions, sentiment analysis on drug reviews was performed and extracted negative reviews. After then, MedDRA dictionary and named entity recognition were applied to the negative reviews to detect adverse drug reactions. For the experiment, drug reviews of Celecoxib, Naproxen, and Ibuprofen from 5 drug review sites, and analyzed. Our results showed that detection of adverse drug reactions is able to compensate to limitation of under-reporting in the spontaneous adverse drugs reactions reporting system.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.199-205
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• 2021

The distributing board in directly installed on the ground or the bottom surface of the building, and when vibrations such as earthquakes or external shocks occur, the possibility of damage or malfunction of electric components such as internal power devices, wiring, and protection relays increases. Recently, the need for a seismic type distributing board is increasing, and research and development of a distributing board having a vibration damping function and product launch are being conducted. In this paper, an IoT-based data collection device system capable of measuring vibration and environmental data of distributing board was designed and implemented. When vibration occurred on the distributing board, data was stored and visualized in the MySQL DB through Node-RED for monitoring and data storage using the MQTT protocol for reliable messaging transmission. The test was conducted by attaching the IoT device of the distributing board, and data was collected in real-time and monitored through Node-RED.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.143-150
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• 2021

There is a need for an artificial intelligent technology that can reduce various types of safety accidents by analyzing the risk factors that cause safety accidents in industrial site. In this paper, user safety profiling methods are proposed that can prevent safety accidents in advance by specifying and modeling user information data related to safety accidents. User information data is classified into normal and abnormal conditions through deep learning based artificial intelligence analysis. As a result of verifying user safety profiling technology using more than 10 types of industrial field data, 93.6% of user safety profiling accuracy was obtained.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.35-46
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• 2011

Future Internet should support more efficient mobility management, flexible traffic engineering and various emerging new services. So, lots of traffic engineering techniques have been suggested and developed, but it's impossible to apply them on the current running commercial Internet. To overcome this problem, OpenFlow protocol was proposed as a technique to control network equipments using network controller with various networking applications. It is a software defined network, so researchers can verify their own traffic engineering techniques by applying them on the controller. In addition, for high-speed packet processing in the OpenFlow network, programmable NetFPGA card with four 1G-interfaces and commercial Procurve OpenFlow switches can be used. In this paper, we implement an OpenFlow test-bed using hardware-accelerated NetFPGA cards and Procurve switches on the KREONET, and implement CSPF (Constraint-based Shortest Path First) algorithm, which is one of popular QoS routing algorithms, and apply it on the large-scale testbed to verify performance and efficiency of multimedia traffic engineering scheme in Future Internet.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.436-450
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• 2005

Existing B2B, B2C computer systems and applications that executed business trans-actions were the client- server based architecture which consists of heterogeneous hardware and software including personal computers and mainframes. Due to the active boom of electronic business, integration and compatibility of exchanged data, applications and hardwares have emerged as hot issue. This paper designs and implements a message transport system and a document transformation system in order to solve the interoperability problem of integrated logistics system in e-Business when doing electronic business. Message transport system integrated ebMS 2.0 which is standard business message exchange format of ebXML, the international standard electronic commerce framework, and JMS of J2EE enable to ensure reliable messaging. The document transformation system could convert non-standard XML documents into standard XML documents and provide the web services after integrating message system. Using suggested business scenario and various test data, our message oriented system preyed to be interoperable and stable. We participated ebXML messaging interoperability test organized by ebXML Asia Committee ITG in oder to evaluate and certify the suitability for message system.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.57-65
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• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• Journal of KIISE:Software and Applications
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• v.29 no.8
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• pp.573-583
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• 2002

Pattern recognition process is made up of the feature extraction in the pre-processing, the pattern clustering by training and the recognition process. This paper presents the F-LVQ (Fuzzy Learning Vector Quantization) pattern classification model which is optimized by the fuzzy membership function for the OCR(Optical Character Recognition) system. We trained 220 numeric patterns of 22 Hangul and English fonts and tested 4840 patterns whose forms are changed variously. As a result of this experiment, it is proved that the proposed model is more effective and robust than other typical LVQ models.

• Electronics and Telecommunications Trends
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• v.24 no.3
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• pp.24-31
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• 2009

IMT-Advanced 무선전송 시스템 단말모뎀 플랫폼은 다중 반송파 변조 기술, 채널 부호화 기술, 셀 탐색/동기 기술 등 핵심이 되는 요소 기술인 고속 무선 전송 기술을 구현할 수 있는 하드웨어 구조, 기능 및 인터페이스를 설계 제작하였다. 상기 단말모뎀 플랫폼에서는 기저대역 모뎀 물리계층 기능인 변조, 복조, 부호, 복호, 동기를 위한 각각의 FPGA가 실장되는 Daughter Board 형태로 구성되어 L1 기저대역 모뎀 장치에 실장된다. 그리고 PHY 계층(L1)부터 MAE 계층(L2), RRC 계층(L3)까지의 하드웨어 및 소프트웨어 수행을 지원한다. 4G용 단말모뎀을 개발하기 위하여 상용화 이전에 LTE-Advanced 테스트 베드용 단말모뎀 플랫폼을 개발하여 20 MHz 대역폭을 적용 3 km/h의 저속 이동속도에서는 최대 110 Mbps를 수신하고, 최대 55 Mbps를 송신한다. 그리고 120 km/h의 고속 이동속도에서는 최대 55 Mbps를 수신하고, 최대 28 Mbps를 송신한다. 상기 성능을 만족하는 단말모뎀 플랫폼이 개발되면 IMT-Advanced 단말모뎀 플랫폼 기술을 확보하게 된다. 따라서 이동통신 분야에서 기술적인 우위와 시장 선점을 위하여 요소기술 IPR을 확보하고, IMT-Advanced의 표준화 과정에서 이를 국제 표준으로 반영하여 로열티 창출 효과 및 기술 경쟁력을 확보하게 될 것이다. 아울러, LTE 사용자들은 대용량의 고속, 멀티미디어 송 수신을 가능하게 하는 기술로 2010년 이후 가상 현실 서비스, 3D 게임, 센싱 등 사물과 사물이 통신하는 유비쿼터스 서비스로 발전할 것으로 전망한다.