• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.163-172
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• 2022

Typical anti-jamming technologies based on array antennas, Space Time Adaptive Process (STAP) & Space Frequency Adaptive Process (SFAP), are very effective algorithms to perform nulling and beamforming. However, it does not perform equally well for all types of jamming signals. If the anti-jamming algorithm is not optimized for each signal type, anti-jamming performance deteriorates and the operation stability of the system become worse by unnecessary computation. Therefore, jamming classification technique is required to obtain optimal anti-jamming performance. Machine learning, which has recently been in the spotlight, can be considered to classify jamming signal. In general, performing supervised learning for classification requires a huge amount of data and new learning for unfamiliar signal. In the case of jamming signal classification, it is difficult to obtain large amount of data because outdoor jamming signal reception environment is difficult to configure and the signal type of attacker is unknown. Therefore, this paper proposes few-shot jamming signal classification technique using meta-learning and transfer-learning to train the model using a small amount of data. A training dataset is constructed by anti-jamming algorithm input data within the GNSS receiver when jamming signals are applied. For meta-learning, Model-Agnostic Meta-Learning (MAML) algorithm with a general Convolution Neural Networks (CNN) model is used, and the same CNN model is used for transfer-learning. They are trained through episodic training using training datasets on developed our Python-based simulator. The results show both algorithms can be trained with less data and immediately respond to new signal types. Also, the performances of two algorithms are compared to determine which algorithm is more suitable for classifying jamming signals.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.99-105
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• 2012

Given the numbers of smartphones, tablets and other mobile devices shipped every day, more and more users are relying on the cloud as the main driver for satisfying their computing needs, whether it is data storage, applications or infrastructure. Mobile cloud computing is simply cloud computing in which at least some of the devices involved are mobile. Each node is owned by a different user and is likely to be mobile. Using mobile hardware for cloud computing has advantages over using traditional hardware. These advantage include computational access to multimedia and sensor data without the need for large network transfer, more efficient access to data stored on other mobile devices and distributed ownership and maintenance of hardware. It is important to predict job execution time in mobile cloud computing because there are many mobile nodes with different capabilities. This paper analyzes the job execution time for mobile cloud computing in terms of network environment and heterogeneous mobile nodes using a mathematical model.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.4
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• pp.576-582
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• 2015

The efficiencies of thermal power system using fossil fuel depend on heat exchangers which extract energy from the exhaust gas before it is expelled to the atmosphere. To increase heat transfer efficiency it is very important to maintain the surface of heat exchanger as clean condition. The accepted skill of cleaning of fouled surface of heat exchanger is soot blowing. A high pressure jet of air is forced through the flat surface of plate to remove the deposit of fouling. There is, however, little knowledge of the fundamental principles of how the jet behave on the surface and how the jet actually removes the deposit. Therefore, the study focuses on the measuring of cleaning area and cleaning dwell time after accumulating the simulated deposit on the flat surface. The deposit test rig was built for the study and simulated deposit material is used after measuring the physical property of the each material by shearing stress test. Much data was obtained for the analysis by the parameters change such as the different jet speed, different inner pressure and variable distance of the jet from the test rig surface. The experimental data was compared with the theoretical equation and most of the data matches well except some extreme cases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1496-1502
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• 1998

In this paper, a real-time audio broadcasting service system which is robust to loaded traffic on the Internet is developed. For implementing reliable real-time data transfer, the transfer characteristics of TCP/IP and UDP/IP was compared and analyzed. For lost packet recovery, redundant audio data algorithm was used and interleaving technique was applied for scattering consecutive packet loss. Test results showed, when using TCP/IP, pause occurred during playback, and when using UDP/IP, a stable receive rate was noticeable but the quality of the sound was lower than that of uisng TCP/IP. The recovery rate using redundant audio data and interleaving technique is shown in Fig. 9 and the delay is shown in Fig 4.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.663-668
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• 2024

This paper applies statistical analysis methods in the time domain to the fault diagnosis of wafer transfer robots, and proposes a methodology to discern the critical characteristics of vibration and torque signals. Subsequently, principal component analysis (PCA) is applied to diminish the data's dimensionality, followed by the development of a fault diagnosis algorithm utilizing Euclidean distance and Hotelling's T-square statistics. The algorithm establishes decision boundaries to categorize failure states based on the observed data. Our findings indicate that data classification incorporating velocity parameters enhances diagnostic accuracy. This approach serves to enhance the precision and efficacy of fault diagnosis.

• Database Research
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• v.34 no.3
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• pp.137-147
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• 2018

A key to a well-performing human activity recognition (HAR) system through machine learning technique is the availability of a substantial amount of labeled data. Collecting sufficient labeled data is an expensive and time-consuming task. To build a HAR system in a new environment (i.e., the target domain) with very limited labeled data, it is unfavorable to naively exploit the data or trained classifier model from the existing environment (i.e., the source domain) as it is due to the domain difference. While traditional machine learning approaches are unable to address such distribution mismatch, transfer learning approach leverages the utilization of knowledge from existing well-established source domains that help to build an accurate classifier in the target domain. In this work, we propose a transfer learning approach to create an accurate HAR classifier with very limited data through the multitask neural network. The classifier loss function minimization for source and target domain are treated as two different tasks. The knowledge transfer is performed by simultaneously minimizing the loss function of both tasks using a single neural network model. Furthermore, we utilize the unlabeled data in an unsupervised manner to help the model training. The experiment result shows that the proposed work consistently outperforms existing approaches.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.279-284
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• 2019

This paper presents processing-node status-based message scattering and gathering algorithms for multi-processor systems on chip to reduce the communication time between processors. In the message-scattering part of the message-passing interface (MPI) scatter function, data transmissions are ordered according to the proposed linear algorithm, based on the processor status. The MPI hardware unit in the root processing node checks whether each processing node's status is 'free' or 'busy' when an MPI scatter message is received. Then, it first transfers the data to a 'free' processing node, thereby reducing the scattering completion time. In the message-gathering part of the MPI gather function, the data transmissions are ordered according to the proposed linear algorithm, and the gathering is performed. The root node receives data from the processing node that wants to transfer first, and reduces the completion time during the gathering. The experimental results show that the performance of the proposed algorithm increases at a greater rate as the number of processing nodes increases.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.44-49
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• 2011

The need of data transmission in oceans and other underwater mediums are increasing day by day, so as the research. The underwater medium is very different from that of air. Propagation of electromagnetic wave in water or underground is very difficult because of the conductivity of the propagation materials. In this case, we usually use acoustic signals as ultrasonic but, they are not easy to transfer long distance with coherent method because of time varying multipaths, Doppler effects and attenuations. So, we use non-coherent methods such as FSK or ASK to communicate between long distances. But, as the propagation speed of acoustic wave is very slow, BW of the channel is narrow. It is very hard to guaranty the enough speed for the transmission of digital image data. In previous studies, we proposed this data communication protocol theoretically. In this paper, an underwater channel is modeled and this protocol is tested in this channel condition. The results show that the protocol is 4-6 times faster than ASK. Some relations and results are shown depending on the data length, channel length, bit rate etc.

• Journal of Digital Contents Society
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• v.15 no.2
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• pp.137-145
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• 2014

In this paper, we focus on end-to-end transfer delay improvement by using erasure coding when delivering expediting message consisting of M packets in networks with high coefficient of variation of transfer time. In the scheme, M packets are divided into b groups with each having g packets. Each group is erasure coded with additional r packets and transmitted. Since the first arrived g packets among g+r packets completes the delivery of the group, the delivery time of the expediting message is reduced. For the scheme, we investigate the optimum group size and number of redundancy packets considering delivery delay reduction and additional transmission cost caused by using erasure coding. From the results of the investigation, we see that the proposed scheme is effective in networks having high variability of transfer time and would be very useful and practical especially for the case that expedited deliveries of messages are needed.

• Nuclear Engineering and Technology
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• v.38 no.6
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• pp.585-590
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• 2006

This paper describes the results of an irradiation test and the specifications of the pneumatic transfer system (PTS) in the NAA #3 irradiation hole at the HANARO research reactor, which was reinstalled after some modifications of the operation mode at the end of 2004. The outer and inner diameters of the PE transfer tube are 34.1 and 27.5 mm, respectively. PE rabbit was used for sample irradiation. The $N_2$ gas pressure of the PTS lines was adjusted to 0.75 bar. The average sending time to the reactor was $8.5{\pm}0.3$ s and the average receiving time back to the receiver was $3.2{\pm}0.2$ s. The internal and external temperature of the irradiation tube was measured in a range of 50 to $80^{\circ}C$ for a 40 s to 80 s irradiation time, respectively. The optimum irradiation time was estimated to be less than 80 s. The thermal, epithermal and fast neutron flux at 30 MW thermal power were $1.42{\pm}0.01{\times}10^{14},\;1.51{\pm}0.04{\times}10^{13}$ and $9.48{\pm}0.69{\times}10^{11} n{\cdot}cm^{-2}{\codt}s^{1-}$, respectively. The cadmium ratio was approximately 9.40. The data obtained will be applied to supplement user information and for reactor management.