• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.176-184
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• 2005

In this paper, we implemented an Elliptic Curve Cryptography(ECC) processor for Digital Transmission Contents Protection (DTCP), which is a standard for protecting various digital contents in the network. Unlikely to other applications, DTCP uses ECC algorithm which is defined over GF(p), where p is a 160-bit prime integer. The core arithmetic operation of ECC is a scalar multiplication, and it involves large amount of very long integer modular multiplications and additions. In this paper, the modular multiplier was designed using the well-known Montgomery algorithm which was implemented with CSA(Carry-save Adder) and 4-level CLA(Carry-lookahead Adder). Our new ECC processor has been synthesized using Samsung 0.18 m CMOS standard cell library, and the maximum operation frequency was estimated 98 MHz, with the size about 65,000 gates. The resulting performance was 29.6 kbps, that is, it took 5.4 msec to process a 160-bit data frame. We assure that this performance is enough to be used for digital signature, encryption and decryption, and key exchanges in real time environments.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.39-47
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• 2017

Although motorcycle safety studies to date have identified the causes of motorcycle accidents in general, very few have investigated postal motorcycle accidents by studying the delivery postmen's specific work environment. To better understand postal motorcyclists' driving behavior associated with their delivery workload, we developed a system using V-World platform which visualizes driving behavior in real time along the driver's delivery route throughout an entire work day. We conducted a field test to examine the feasibility of our system by involving six delivery postmen currently working in Songpa, Seocheongju, and Gangseo, respectively. To show the potential of our system for nationwide comparison of postal motorcyclists' driving behavior and their workloads, we present several sample analyses using the collected field data. Although ideally, postmen's workloads should be standardized nationwide, we found large variation depending on regional characteristics of work area which affects postmen's driving behavior.

• The Transactions of the Korea Information Processing Society
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• v.4 no.7
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• pp.1797-1803
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• 1997

Message handling function of the SS7(Signaling System N0.7) provides signaling traffic routing capabilities to transfer the signaling traffic to the destination nodes in the signaling network. This message handling function should be handled without any transfer delay for real time processing of large amount of signaling traffic for data communication service, and visual information service. In this paper, we suggest two routing algorithms working on the distributed message handling processors which were specially designed for message handling function. The one is an internal distributing algorithm for equal distribution of signaling traffic among the distributed message handling processors and the other is a distributing algorithm for distribution of signaling traffic in the multiple signaling routes. Both of algorithms are using signaling link selection codes labled in each signaling messages. It is shown that the suggested algorithms are very efficient for routing signaling traffic at the fault condition of signaling routes and the restoration of unavailable signaling routes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.192-197
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• 2020

Multivariate processes, such as large scale power plants or chemical processes are operated in very hazardous environment, which can lead to significant human and material losses if a fault occurs. On-line monitoring technology, therefore, is essential to detect system faults. In this paper, the ICA-based fault detection method is conducted using three different multivariate process data. Fault detection procedure based on ICA is divided into off-line and on-line processes. The off-line process determines a threshold for fault detection by using the obtained dataset when the system is normal. And the on-line process computes statistics of query vectors measured in real-time. The fault is detected by comparing computed statistics and previously defined threshold. For comparison, the PCA-based fault detection method is also implemented in this paper. Experimental results show that the ICA-based fault detection method detects the system faults earlier and better than the PCA-based method.

• Journal of IKEEE
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• v.28 no.2
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• pp.168-173
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• 2024

Speaker recognition refers to a technology that analyzes voice frequencies that are different for each individual and compares them with pre-stored voices to determine the identity of the person. Deep learning-based speaker recognition is being applied to many fields, and pet robots are one of them. However, the hardware performance of pet robots is very limited in terms of the large memory space and calculations of deep learning technology. This is an important problem that pet robots must solve in real-time interaction with users. Lightening deep learning models has become an important way to solve the above problems, and a lot of research is being done recently. In this paper, we describe the results of research on lightweight speaker recognition for pet robots by constructing a voice data set for pet robots, which is a specific command type, and comparing the results of models using residuals. In the conclusion, we present the results of the proposed method and Future research plans are described.

• Smart Media Journal
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• v.12 no.10
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• pp.71-84
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• 2023

Paralichthys olivaceus accounts for a large proportion, accounting for more than half of Korea's aquaculture industry. However, about 25-30% of the total breeding volume throughout the year occurs due to diseases, which has a very bad impact on the economic feasibility of fish farms. For the economic growth of Paralichthys olivaceus farms, it is necessary to quickly and accurately diagnose disease symptoms by automating the diagnosis of Paralichthys olivaceus diseases. In this study, we create training data using innovative data collection methods, refining data algorithms, and techniques for partitioning dataset, and compare the Paralichthys olivaceus disease symptom detection performance of four object detection deep learning models(such as YOLOv8, Swin, Vitdet, MvitV2). The experimental findings indicate that the YOLOv8 model demonstrates superiority in terms of average detection rate (mAP) and Estimated Time of Arrival (ETA). If the performance of the AI model proposed in this study is verified, Paralichthys olivaceus farms can diagnose disease symptoms in real time, and it is expected that the productivity of the farm will be greatly improved by rapid preventive measures according to the diagnosis results.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.559-563
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• 2015

Monitor of All-sky X-ray Image (MAXI) is a Japanese X-ray all-sky surveyer mounted on the International Space Station (ISS). It has been scanning the whole sky since 2009 during every 92-minute ISS rotation. X-ray transients are quickly found by the real-time nova-search program. As a result, MAXI has issued 133 Astronomer's Telegrams and 44 Gamma-ray burst Coordinated Networks so far. MAXI has discovered six new black holes (BH) in 4.5 years. Long-term behaviors of the MAXI BHs can be classified into two types by their outbursts; a fast-rise exponential-decay type and a fast-rise flat-top one. The slit camera is suitable for accumulating data over a long time. MAXI issued a 37-month catalog containing 500 sources above a ~0.6 mCrab detection limit at 4-10 keV in the region ${\mid}{b}{\mid}$ > $10^{\circ}$. The SSC instrument utilizing an X-ray CCD has detected diffuse soft X-rays extending over a large solid angle, such as the Cygnus super bubble. MAXI/SSC has also detcted a Ne emission line from the rapid soft X-ray nova MAXI J0158-744. The overall shapes of outbursts in Be X-ray binaries (BeXRB) are precisely observed with MAXI/GSC. BeXRB have two kinds of outbursts, a normal outburst and a giant one. The peak dates of the subsequent giant outbursts of A0535+26 repeated with a different period than the orbital one. The Be stellar disk is considered to either have a precession motion or a distorted shape. The long-term behaviors of low-mass X-ray binaries (LMXB) containing weakly magnetized neutron stars are investigated. Transient LMXBs (Aql X-1 and 4U 1608-52) repeated outbursts every 200-1000 days, which is understood by the limit-cycle of hydrogen ionization states in the outer accretion disk. A third state (very dim state) in Aql X-1 and 4U 1608-52 was interpreted as the propeller effect in the unified picture of LMXB. Cir X-1 is a peculiar source in the sense that its long-term behavior is not like typical LMXBs. The luminosity sometimes decreases suddenly at periastron. It might be explained by the stripping of the outer accretion disk by a clumpy stellar wind. MAXI observed 64 large flares from 22 active stars (RS CVns, dMe stars, Argol types, young stellar objects) over 4 years. The total energies are $10^{34}-10^{36}$ erg $s^{-1}$. Since MAXI can measure the spectrum (temperature and emission measure), we can estimate the size of the plasma and the magnetic fields. The size sometimes exceeds the size of the star. The magnetic field is in the range of 10-100 gauss, which is a typical value for solar flares.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.3
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• pp.147-160
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• 2020

A stochastic probabilistic model for harbor structures such as rubble-mound breakwater has been formulated by using the generalized Wiener process considering the nonlinearity of damage drift and its nonlinear uncertainty, by which the damage path with real-time can be tracked, the residual useful lifetime at some age can also be analyzed properly. The formulated stochastic model can easily calculate the probability of failure with the passage of time through the probability density function of cumulative damage. In particular, the probability density functions of residual useful lifetime of the existing harbor structures can be derived, which can take into account the current age, its present damage state and the future damage process to be occurred. By using the maximum likelihood method and the least square method together, the involved parameters in the stochastic model can be estimated. In the calibration of the stochastic model presented in this paper, the present results are very well similar with the results of MCS about tracking of the damage paths as well as evaluating of the density functions of the cumulative damage and the residual useful lifetime. MTTF and MRL are also evaluated exactly. Meanwhile, the stochastic probabilistic model has been applied to the rubble-mound breakwater. The related parameters can be estimated by using the experimental data of the cumulative damages of armor units measured as a function of time. The theoretical results about the probability density function of cumulative damage and the probability of failure are very well agreed with MCS results such that the density functions of the cumulative damage tend to move to rightward and the amounts of its uncertainty are increased as the elapsed time goes on. Thus, the probabilities of failure with the elapsed time are also increased sharply. Finally, the behaviors of residual useful lifetime have been investigated with the elapsed age. It is concluded for rubble-mound breakwaters that the probability density functions of residual useful lifetime tends to have a longer tail in the right side rather than the left side because of the gradual increases of cumulative damage of armor units. Therefore, its MRLs are sharply decreased after some age. In this paper, the special attentions are paid to the relationship of MTTF and MRL and the elapsed age of the existing structure. In spite of that the sum of the elapsed age and MRL must be equal to MTTF deterministically, the large difference has been shown as the elapsed age is increased which is due to the uncertainty of cumulative damage to be occurred in the future.

• Economic and Environmental Geology
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• v.52 no.4
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• pp.313-322
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• 2019

SAR (Synthetic Aperture Radar) remote sensing data is a very useful tool for near-real-time identification of landslide affected areas that can occur over a large area due to heavy rains or typhoons. This study aims to develop an effective algorithm for automatically delineating landslide areas from the polarimetric SAR data acquired after the landslide event. To detect landslides from SAR observations, reduction of the speckle effects in the estimation of polarimetric SAR parameters and the orthorectification of geometric distortions on sloping terrain are essential processing steps. Based on the experimental analysis, it was found that the IDAN filter can provide a better estimation of the polarimetric parameters. In addition, it was appropriate to apply orthorectification process after estimating polarimetric parameters in the slant range domain. Furthermore, it was found that the polarimetric entropy is the most appropriate parameters among various polarimetric parameters. Based on those analyses, we proposed an automatic landslide detection algorithm using the histogram thresholding of the polarimetric parameters with the aid of terrain slope information. The landslide detection algorithm was applied to the ALOS-2 PALSAR-2 data which observed landslide areas in Japan triggered by Typhoon in September 2011. Experimental results showed that the landslide areas were successfully identified by using the proposed algorithm with a detection rate of about 82% and a false alarm rate of about 3%.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.198-210
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• 2022

The southern strait of Jeju is a divergence point of the Tsushima Warm Current (TWC), and it is the starting point of the thermohaline circulation in the waters of the Korean Peninsula, affecting the size and frequency of marine disasters such as typhoons and tsunamis, and has a very important oceanographic impact, such as becoming a source of harmful organisms and radioactively contaminated water. Therefore, for an immediate response to these maritime disasters, real-time ocean observation is required. However, compared to other straits, in the case of southern Jeju, such wide area marine observations are insufficient. Therefore, in this study, surface current field of the southern strait of Jeju was calculated using High-Frequency radar (HF radar). the large surface current field is calculated, and post-processing and data improvement are carried out through APM (Antenna Pattern Measurement) and FOL (First Order Line), and comparative analysis is conducted using actual data. As a result, the correlation shows improvement of 0.4~0.7 and RMSE of about 1~19 cm/s. These high-frequency radar observation results will help solve domestic issues such as response to typhoons, verification of numerical models, utilization of wide area wave data, and ocean search and rescue in the future through the establishment of an open data network.