• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.6
• /
• pp.678-686
• /
• 2019

In this study, marine heat waves on coastal waters of Republic of Korea were detected using satellite-based Sea Surface Temperature Anomaly (SSTA). The detected results were compared with the warm water issues reported by the National Institute of Fisheries Science (NIFS). Marine heat waves detection algorithm using SSTA based on a threshold has proposed. The threshold value was defined as 2℃ for caution and 3℃ for warning issues, respectively. Daily averaged SST data from July to September of 2017-2018 were used to generate SSTA. The satellite-based detection results were classified into nine areas according to the place names used in the NIFS warm water issues. In the comparison of frequency of marine heat waves occurrence to each area with the warm water issue, most areas in the southern coast showed a similar pattern, that is probably NIFS uses spatially well distributed buoys. On the other hand, other sea areas had about two times more satellite detection results. This result seems to be because NIFS only considers the water temperature data measured at limited points. The results of this study are expected to contribute to the development of a satellite-based warm/cold water monitoring system in coastal waters.

• Journal of Korea Water Resources Association
• /
• v.53 no.4
• /
• pp.273-283
• /
• 2020

Quantitative forecasting of groundwater levels for the assessment of groundwater variation and vulnerability is very important. To achieve this purpose, various time series analysis and machine learning techniques have been used. In this study, we developed a prediction model based on LSTM (Long short term memory), one of the artificial neural network (ANN) algorithms, for predicting the daily groundwater level of 11 groundwater wells in Hankyung-myeon, Jeju Island. In general, the groundwater level in Jeju Island is highly autocorrelated with tides and reflected the effects of precipitation. In order to construct an input and output variables based on the characteristics of addressing data, the precipitation data of the corresponding period was added to the groundwater level data. The LSTM neural network was trained using the initial 365-day data showing the four seasons and the remaining data were used for verification to evaluate the fitness of the predictive model. The model was developed using Keras, a Python-based deep learning framework, and the NVIDIA CUDA architecture was implemented to enhance the learning speed. As a result of learning and verifying the groundwater level variation using the LSTM neural network, the coefficient of determination (R²) was 0.98 on average, indicating that the predictive model developed was very accurate.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.7
• /
• pp.23-35
• /
• 2013

This paper proposes an effective technique that is used to automatically extract feature vectors from vibration signals for fault classification systems. Conventional mel-frequency cepstral coefficients (MFCCs) are sensitive to noise of vibration signals, degrading classification accuracy. To solve this problem, this paper proposes spectral envelope cepstral coefficients (SECC) analysis, where a 4-step filter bank based on spectral envelopes of vibration signals is used: (1) a linear predictive coding (LPC) algorithm is used to specify spectral envelopes of all faulty vibration signals, (2) all envelopes are averaged to get general spectral shape, (3) a gradient descent method is used to find extremes of the average envelope and its frequencies, (4) a non-overlapped filter is used to have centers calculated from distances between valley frequencies of the envelope. This 4-step filter bank is then used in cepstral coefficients computation to extract feature vectors. Finally, a multi-layer support vector machine (MLSVM) with various sigma values uses these special parameters to identify faulty types of induction motors. Experimental results indicate that the proposed extraction method outperforms other feature extraction algorithms, yielding more than about 99.65% of classification accuracy.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.5
• /
• pp.76-87
• /
• 2014

Today the energy consumption of ICT networks is about 10% of the worldwide power consumption and is predicted to increase remarkably in the near future. For this reason, this paper studies energy saving strategies assuring the network-level QoS. In the strategies, the energy consumption of NIC(network interface card) on both endpoint of links decreases by selecting links and making them sleep when the total traffic volume of the IP network is lower than a threshold. In this paper, we propose a heuristic routing algorithm based on so-called delegating/delegated routers, and evaluate its characteristics using computer simulation considering network-level QoS. The selection of sleep links is determined in terms of the number of traffic paths (called min_used path) or the amount of traffics(called min_used traffic) through those kinks. To our experiment, the min_used traffic method shows a little better energy saving but the increased path length compared to the min_used path method. Those two methods have better energy saving characteristics than the random method. This paper confirms that the delegating/delegated router-based routing algorithm results in energy saving effects and sustains network-level QoS in IP networks.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.49 no.1
• /
• pp.16-22
• /
• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.36C no.12
• /
• pp.11-19
• /
• 1999

Fractal image compression algorithm has been studied mostly not in the view of hardware but software. However, a general processor by software can't decode fractal compressed images in real-time. Therefore, it is necessary that we develop a fast dedicated hardware. However, design examples of dedicated hardware are very rare. In this paper, we designed a quadtree fractal-based compressed image decoder which can decode $256{\times}256$ gray-scale images in real-time and used two power-down methods. The first is a hardware-optimized simple post-processing, whose role is to remove block effect appeared after reconstruction, and which is easier to be implemented in hardware than non-2' exponents weighted average method used in conventional software implementation, lessens costs, and accelerates post-processing speed by about 69%. Therefore, we can expect that the method dissipates low power and low energy. The second is to design a power dissipation in the multiplier can be reduced by about 28% with respect to a general array multiplier which is known efficient for low power design in the size of 8 bits or smaller. Using the above two power-down methods, we designed decoder's core block in 3.3V, 1 poly 3 metal, $0.6{\mu}m$ CMOS technology.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.75-84
• /
• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.47 no.1
• /
• pp.15-21
• /
• 2010

This paper proposes the multimedia fingerprinting code insertion algorithm when video content is distributed in P2P environment, and designs the collusion codebook SRP(Small RISC Processor) embedded system for the collusion attack prevention. In the implemented system, it is detecting the fingerprinting code inserted in the video content of the client user in which it requests an upload to the web server and in which if it is certified content then transmitted to the streaming server then the implemented system allowed to distribute in P2P network. On the contrary, if it detects the collusion code, than the implemented system blocks to transmit the video content to the streaming server and discontinues to distribute in P2P network. And also it traces the colluders who generate the collusion code and participates in the collusion attack. The collusion code of the averaging attack is generated with 10% of BIBD code v. Based on the generated collusion code, the codebook is designed. As a result, when the insert quantity of the fingerprinting code is 0.15% upper in bitplane 0~3 of the Y(luminance) element of I-frame at the video compression of ASF for a streaming service and MP4 for an offline offer of video content, the correlation coefficient of the inserted original code and the detected code is above 0.15. At the correlation coefficient is above 0.1 then the detection ratio of the collusion code is 38%, and is above 0.2 then the trace ratio of the colluder is 20%.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.12
• /
• pp.157-163
• /
• 2017

The object segmentation approach has the merit of reducing the processing cost required to detect moths of interest, because it applies a moth detection algorithm to the segmented objects after segmenting the objects individually in the moth image. In this paper, an object segmentation method for moth detection in pheromone trap images is proposed. Our method consists of preprocessing, thresholding, morphological filtering, and object labeling processes. Thresholding in the process is a critical step significantly influencing the performance of object segmentation. The proposed method can threshold very elaborately by reflecting the local properties of the moth images. We performed thresholding using global and local versions of Ostu's method and, used the proposed method for the moth images of Carposina sasakii acquired on a pheromone trap placed in an orchard. It was demonstrated that the proposed method could reflect the properties of light and background on the moth images. Also, we performed object segmentation and moth classification for Carposina sasakii images, where the latter process used an SVM classifier with training and classification steps. In the experiments, the proposed method performed the detection of Carposina sasakii for 10 moth images and achieved an average detection rate of 95% of them. Therefore, it was shown that the proposed technique is an effective monitoring method of Carposina sasakii in an orchard.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.1
• /
• pp.33-42
• /
• 2016

In Korea, the address-point matching technique has been used to provide geocoding services. In fact, this technique brings the high positional accuracy. However, the quality of geocoding result can be limited, since it is significantly affected by data quality. Also, it cannot be used for the 3D address geocoding and the reverse geocoding. In order to alleviate issues, the paper has implemeted proposed geocoding methods, based on street-based addresses matching technique developed by US census bureau, for street-based addresses in Korea. Those proposed geocoding methods are illustrated in two ways; (1) street address-matching method, which of being used for not only 2D addresses representing a single building but also 3D addresses representing indoor space or underground building, and (2) reverse geocoding method, whichas converting a location point to a readable address. The result of street-based address geocoding shows 82.63% match rates, while the result of reverse geocoding shows 98.5% match rates within approximately 1.7(m) the average position error. According to the results, we could conclude that the proposed geocoding techniques enable to provide the LBS(Location Based Service). To develop the geocoding methods, the study has perfoermed by ignoring the parsing algorithms for address standardization as well as the several areas with unusual addresses, such as sub-urban areas or subordinate areas to the roads, etc. In the future, we are planning the improved geocoding methods for considering these cases.