• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.22 no.3
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• pp.103-117
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• 2017

This note provides technical guide on three issues associated with establishing and automatically running regional ocean forecasting systems: (1) a strategy for continuous production of hourly-interval three-day ocean forecast data, (2) the daily download of ocean and atmospheric forecasting data (i.e., HYCOM and NOAA/NCEP GFS data), which are provided by outside institutions and used as initial condition, surface forcing, and boundary data for regional ocean models, and (3) error notifications to numerical model managers through the Short Message Service (SMS). Guidance on dealing with these three issues is illustrated via solutions implemented by the Korea Hydrographic and Oceanographic Agency, since in embarking on this project we found that this procedural information was not readily available elsewhere. This technical guide is based on our experiences and lessons learned during the process of establishing and operating regional ocean forecasting systems for the East Sea and the Yellow and East China Seas over the 5 year period of 2012-2016. The fundamental approach and techniques outlined in this guide are of use to anyone wanting to establish an automatic regional and coastal ocean forecasting system.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.5
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• pp.451-457
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• 2016

To improve security in the data communication field, many studies on the application of chaotic signals to encryption have been conducted in recent years. In this study, a new security protocol where the initial value sensitivity and noise similarity of chaotic signals have been applied to an RFID communication channel was designed. In the case of chaotic systems, if the initial values become identical, the same signals are generated at the same time after that point even though the two systems have been calculated independently. Therefore, an unpredictable security channel can be produced based on such characteristics. However, a security channel can be produced only when an initial value is shared in advance, and thus there is a potential problem of infringement during the transmission of the initial value. To resolve this problem, a method in which a certain proportion of new chaotic signals are applied to two chaotic systems for communication and are then synchronized after some time was proposed. This new method can conceal the initial value, and thus can resolve the problem of the existing communication method using chaotic signals. The designed method was verified with the encryption and decryption of images. It is expected that a more secure RFID system could be established by applying the communication protocol proposed in this study to insecure RFID communication channels.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.99-104
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• 2012

The United States will proceed with the effort to modernize the GPS system, and one of its main content is to provide L5 signal. L5 will be transmitted in a radio band reserved exclusively for aviation safety services. And, L5, in combination with L1, will improve the position accuracy via ionospheric correction and robustness via signal redundancy. However, The acquisition processing time of L5 takes longer than that of L1 as the code length of L5 is 10 times longer than that of L1. To reduce this acquisition processing time, a higher number of correlators in the aquisition module should be used. However, there is a problem that this causes increase in the complexity of the correlator configuration and the computation power. So, in this paper, we propose L5 signal tracking scheme using tracking results in the GPS L1/L5 receiver. The proposed scheme could reduce the hardware complexity as the GPS L5 signal acquisition module is not needed, and provide fast and stable tracking of L5 signal by aiding L1 tracking results such as PRN, the code phase synchronization, and the Doppler frequency. The feasibility of the proposed scheme is demonstrated through simulation results.

• Geophysics and Geophysical Exploration
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• v.20 no.1
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• pp.43-48
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• 2017

The applicability of refraction survey has been tested using a wave glider widely used in long-term ocean observations around the world. To record seismic refractions, a single channel streamer with metal weight and a seismic recording system were mounted on the wave glider. We used GPS precise time synchronization signal and radio frequency (RF) communication to synchronize shot and recorder triggers and to control acquired data quality in real time. When the wave glider is positioned close to the set point, a 2,000 J sparker is exploded along the designed track at 2 second intervals. Through the test survey, we were able to successfully acquire refractions from the subsurface.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.555-564
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• 2016

This paper proposes a time slot allocation scheme for military patrol environments. This proposal comes from analysis of traffic properties in a military patrol environment. In the near future, robots are expected to explore enemy grounds and measure threat, taking the place of human patrol. In order to control such robots, control messages must be extremely accurate. One mistake from the control center could cause a tragedy. Thus, high reliability must be guaranteed. Another goal is to maintain a continual flow of multimedia data sent from patrol robots. That is, QoS (Quality of Service) must be guaranteed. In order to transmit data while fulfilling both attributes, the per-path based centralized TDMA slot allocation scheme is recommended. The control center allocates slots to robots allowing synchronization among robots. Slot allocation collisions can also be avoided. The proposed scheme was verified through the ns-3 simulator. The scheme showed a higher packet delivery ratio than the algorithm in comparison. It also performed with shorter delay time in the downlink traffic transmission scenario than the algorithm in comparison.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3C
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• pp.302-313
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• 2010

In this paper, we propose an enhanced AGC (Automatic Gain Control) structure and P-SCH detection method for initial cell search in 3GPP (3rdGenerationPartnershipProject) LTE (Long Term Evolution) FDD(Frequency Division Duplex) / TDD (Time Division Duplex) dual mode system. Since TDD frame structure consists of uplink subframe and downlink subframe, conventional AGC structure causes P-SCH detection performance degradation by increase of AGC variation due to signal power difference between uplink and downlink subframe. Also, P-SCH detection performance is degraded by distortion of P-SCH correlation characteristic in frequency offset and multipath fading channel environments. Therefore, we propose an AGC structure which can minimize P-SCH detection performance degradation with stable operation in 3GPP LTE TDD mode as well as FDD mode. Also we propose a P-SCH detection method which can reduce distortion of correlation chareteristics in frequency offset and multipath fading environments and obtain good P-SCH detection performance. Simulation results show that the proposed AGC structure and P-SCH detection method have stable AGC operation and excellent P-SCH detection performance for 3GPP LTE TDD / FDD dual mode downlink receiver in various channel environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1364-1373
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• 2016

Ultra High Definition Television (UHDTV) has attracted much attention as one of next generation broadcasting services. For the commercialization of UHD broadcasting service, standardization groups including the DVB (Digital Video Broadcasting) and the ATSC (Advanced Television Systems Committee) have decided to adopt the Orthogonal Frequency Division Multiplexing (OFDM) for signal transmission. However, when the carrier frequency is not properly synchronized at the receiver, inter-symbol interference (ISI) and inter-carrier interference (ICI) may occur. In order to avoid performance degradation resulting from ISI or ICI, receivers should synchronize the carrier frequency by using preambles and pilot symbols. However, there only few published literature dealing with the frequency offset estimation methods regarding the next generation terrestrial broadcasting. In this respect, this paper proposes a method to estimate timing and fractional frequency offset for the ATSC 3.0 system by using a preamble bootstrap symbol. The proposed detector can detect the fractional frequency offset by adding a complex conjugate product on the conventional estimator where only timing offset can be estimated.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.439-452
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• 2014

This paper suggests the method to extend service area by using the transmit offset delay in T-DMB single frequency network (SFN). In general, synchronization of the transmit time of all site can be done by using the reference clock of GPS, which dose not reflect the details geographical characteristics and transmit specifications of each site. Applying the site-specific transmit offset delay, we could extend the service area of SFN T-DMB. Applying the transmit offset delay, it is found that the signal quality in the region of weak receive field strength was improved and upto 4~8 km service area expansion was achieved by satisfying the minimum field strength ($45dB{\mu}V/m$) recommended by the Korea Communications Commission (KCC). Site-specific offset delay was calculated considering the geographic service area characteristics, distribution of electric field strength between neighboring sites and site-specific service target area. Experiments were carried out in order to analyze impact of calculated offset delay on the T-DMB SFN and also to confirm that the offset delay extends T-DMB service coverage. The experiment was done in metropolitan T-DMB service areas.

• Information Systems Review
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• v.17 no.2
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• pp.101-132
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• 2015

National technical qualifications to enhance an individual's vocational skills, the competitiveness of companies and countries have an important function to improve. Especially 'qualifications' will have a signal function to show objectively measure an individual's ability with the 'Education' The "knowledge necessary for the performance of their duties. Technology will gain knowledge about such assessment or recognition is based on certain criteria and procedures." Learning to qualify are being made through a smart learning a lot. Due to the revolution of the Internet in recent years with the development of information and communication technologies are entering into a knowledge society, the importance of information and knowledge. This contemporary smart learning education system is continuing to rapidly growing in pace with the changing time and space constraints, without teaching and learning is taking place. The purpose of this study is the ARCS motivation theory can determine a representative theory of human motivation factors and basic psychological needs dealing with the human nature of the psychological needs Interactivity and immersive learning, and to validate the empirical causality Affecting the continued use of smart learning through fun. Specifically, attention, relevance, confidence in the ARCS motivation, see their effect on the learning flow through the satisfaction we analyze empirically. Through this national technical qualifications smart learner's learning by supporting the implicit synchronization of students in learning are the degree of continued use. Therefore, to achieve the objectives of national technical qualifications and skills through a smart learning can contribute to the activation of the development and certification of course industry.