• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.97-108
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• 2011

Systems for underwater environment monitoring and natural resources can be considered as a part of digital convergence where real-time data transmission is possible with the help of underwater wireless sensor network (UWSN). One of key technologies required for the deployment of the systems is underwater acoustic micro modem. In this work, we design and implement an acoustic modem equipped with a commercial omnidirectional transducer. We also make experiments at the northern Han river for the verification of the developed modem. According to the experiments, the modem supports the working distance of 250 m and the data rate of 200 bps with a negligible bit error rate. It is expected that the acoustic modem can be used for various applications based on UWSN in a near future.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.7
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• pp.610-617
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• 2017

In the recent weapon system trend, it is required to develop small and low cost guidance missile to track and strike the enemy target effectively. Controling the such small drone typed weapon demands a integrated electronic device that equipped with not only a wireless network interface, a high resolution camera, various sensors for target tracking, and position and attitude control but also a high performance processor that integrates and processes those sensor outputs in real-time. In this paper, we propose the android smartphone as a solution for that and implement the guidance and control application of the missile. Furthermore, the performance of the implemented guidance and control application is analyzed through the simulation.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.70-77
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• 2017

Recently, Internet of Things (IoT) and deep learning techniques have affected video surveillance systems in various ways. The surveillance features that perform detection, tracking, and classification of specific objects in Closed Circuit Television (CCTV) video are becoming more intelligent. This paper presents real-time algorithm that can run in a PC environment using only a low power CPU. Traditional tracking algorithms combine background modeling using the Gaussian Mixture Model (GMM), Hungarian algorithm, and a Kalman filter; they have relatively low complexity but high detection errors. To supplement this, deep learning technology was used, which can be trained from a large amounts of data. In particular, an SRGB(Sequential RGB)-3 Layer CNN was used on tracked objects to emphasize the features of moving people. Performance evaluation comparing the proposed algorithm with existing ones using HOG and SVM showed move-in and move-out error rate reductions by 7.6 % and 9.0 %, respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.95-102
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• 2014

In this paper, we propose the high speed PLC-based automatic control system for a smart LED streetlight. The proposed the automatic control system were constructed of a power line modem part and monitoring part, streetlight controller part for the high speed communication frequency band and streetlight ballasts characterization and real-time remote control using a high-speed PLC network, and it was designed to meet to lighting grades conditions of KS road lighting standards. The proposed automatic control system were easy monitoring of the power consumption using PC through to the comparison result of the existing streetlight system. As a result, it was confirmed to the possibility of efficient operation for the real-time monitoring and maintenance by induction of reasonable power consumption through to the LED streetlight state checking and remote-control. In addition, we proved to improvement of expected effects for the power cost savings, the energy efficiency, and streetlight differentiation and advanced.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.32-45
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• 2013

Globally, intelligent vehicles and telematics research and development through the integration of IT technology in the vehicle are significant increasing. Real-time data communication for intelligent transportation system (ITS) is very important. It collects real-time data from the vehicle and provides the information collected from ITS center. We propose an effective and secure communication scheme for these communication procedures. In particular, our proposed SIP-based MVPN reduces signaling cost and has many advantages in security aspects. In addition, our proposed scheme performs the mobility management applying NEMO (Network Mobility) for the communication between the vehicles. In other words, we propose an ITS communication mechanism of SIP-based mobile VPN and V2V NEMO. Finally, our performance analysis show that the ITS of SIP-based MVPN is significantly reducing the handoff signaling cost.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.632-639
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• 2010

Ground Transportation is one of the most required field that users need positioning information Especially, more precise position can make smart traffic management possible and bring convenience to users. By advanced wireless network, cars can receive the GPS information of reference station in any tim e and any where. Thus land vehicles are possible to process precise positioning. In general, for precise positioning code and phase measurements are used. But receivers provide not only code and phase measurements but also doppler measurements and Doppler is direct measurement of velocity. In this paper, because velocity is very important information required in Ground Transportation, precise positioning for Ground Transportation is studied. For precise positioning RTK(Real-Time Kinematic) was used and double differenced doppler measurements were added, As a Result, positioning error by multipath and cycle slip was soften. However there still remained Positioning error. Thus smoothing technique using doppler measurement in position domain is used for softening positioning error.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.31-36
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• 2000

This paper describes the implementation and the evaluation of the speech recognition automatic exchange system. The system provides government or public offices, companies, educational institutions that are composed of large number of members and parts with exchange service using speech recognition technology. The recognizer of the system is a Speaker-Independent, Isolated-word, Flexible-Vocabulary recognizer based on SCHMM(Semi-Continuous Hidden Markov Model). For real-time implementation, DSP TMS320C32 made in Texas Instrument Inc. is used. The system operating terminal including the diagnosis of speech recognition DSP and the alternation of speech recognition candidates makes operation easy. In this experiment, 8 speakers pronounced words of 1,300 vocabulary related to automatic exchange system over wire telephone network and the recognition system achieved 91.5% of word accuracy.

• IMMUNE NETWORK
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• v.8 no.3
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• pp.82-89
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• 2008

Background: Although a skin test is the primary option for detecting allergen-specific IgE in clinics, the serum IgE immunoassay is also important because it allows for the diagnosis of allergy without any accompanying adverse effect on the patient. However, the low detection limit of IgE levels by immunoassay may restrict the use of the method in some occasions, and improving its sensitivity would thus have a significant implication in allergy-immunology clinics. Methods: In this study, we attempted to detect specific serum IgE by using immuno-polymerase chain reaction (IPCR) which combines the antigen-antibody specificity of enzyme-linked immunosorbent assays (ELISAs) with the amplification power of PCR. Results: Our results demonstrated that Blo t5-specific serum IgE can be detected by IPCR with a 100-fold higher sensitivity than ELISA, and cross-reactivity of serum IgE to other mite allergens is able to be analyzed by using only $0.3{\mu}l$ of serum sample. Use of real-time IPCR seemed to permit more convenient determination of specific serum IgE as well. Conclusion: We believe that IPCR can serve as a valuable tool in determining specific serum IgE, especially when the amount of serum sample is limited.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.5
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• pp.1002-1011
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• 2005

In this paper. we design and implement a bi-directional broadcasting system, so called return channel server, to allow users to participate in a broadcasting program by using a hi-directional interaction channel. To provide user participation in a program and reflect the user's opinions or responses in real time, the return channel server can be viewed as consisting of four major functional modules: a control module, network interface module, DBMS module, and real-time content authoring module. To construct a return channel server that has a service independent architecture, we designed a return channel server to include the hierarchical structure. The presented return channel server consists of two parts: an RCSAE(return channel server application environment) and RCSA(return channel server application). An RCSA is composed of an execution code and a parameter for executing the execution code. RCSA defines the procedures for providing a specific broadcasting program using the return channel server. On the other hand, an RCSAE provides the environment for the execution of RCSAS. By adopting RCSAE and RCSA, we construct the return channel server that has a service-independent architecture which are shown by the test.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.776-788
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• 2020

In this paper, a vehicle type recognition system using deep learning and a license plate recognition system are proposed. In the existing system, the number plate area extraction through image processing and the character recognition method using DNN were used. These systems have the problem of declining recognition rates as the environment changes. Therefore, the proposed system used the one-stage object detection method YOLO v3, focusing on real-time detection and decreasing accuracy due to environmental changes, enabling real-time vehicle type and license plate character recognition with one RGB camera. Training data consists of actual data for vehicle type recognition and license plate area detection, and synthetic data for license plate character recognition. The accuracy of each module was 96.39% for detection of car model, 99.94% for detection of license plates, and 79.06% for recognition of license plates. In addition, accuracy was measured using YOLO v3 tiny, a lightweight network of YOLO v3.