• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.113-121
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• 2012

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

• Korean Journal of Microbiology
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• v.52 no.2
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• pp.236-241
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• 2016

The Schizosaccharomyces pombe $sdu1^+$ gene, belonging to the PPPDE superfamily of deubiquitinating enzyme (DUB) genes, was previously shown to encode a protein with ubiquitin C-terminal hydrolase (UCH) activity and to participate in the response against oxidative and nitrosative stresses. This work focused on the reactive oxygen species (ROS)-dependent regulation of the S. pombe $sdu1^+$ gene. UCH activities, encoded by the $sdu1^+$ gene, were attenuated in the S. pombe cells exposed to $H_2O_2$, superoxide radical-generating menadione (MD), and nitric oxide (NO)-generating sodium nitroprusside (SNP). Reduced glutathione (GSH) and its precursor N-acetylcysteine (NAC) were able to significantly enhance the UCH activities in the absence or presence of $H_2O_2$. However, the influences of both GSH and NAC on the ROS levels in the absence or presence of $H_2O_2$ were opposite to their effects on the UCH activities under the same conditions. The UCH activities in the Sdu1-overexpressing S. pombe cells were also diminished under exposure to $H_2O_2$, MD and SNP, but still remained to be higher than those in the vector control cells. In brief, it is proposed that the S. pombe $sdu1^+$ gene is regulated by ROS in a negative manner, the meaning of which largely remains elusive.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Korean Journal of Microbiology
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• v.55 no.2
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• pp.103-111
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• 2019

DNA methylation is involved in diverse processes in bacteria, including maintenance of genome integrity and regulation of gene expression. CcrM, the DNA methyltransferase conserved in Alphaproteobacterial species, carries out $N^6$-adenine or $N^4$-cytosine methyltransferase activities using S-adenosyl methionine as a co-substrate. Celeribacter marinus IMCC12053 from the Alphaproteobacterial group was isolated from a marine environment. Single molecule real-time sequencing method (SMRT) was used to detect the methylation patterns of C. marinus IMCC12053. Gibbs motif sampler program was used to observe the conversion of adenosine of 5'-GANTC-3' to $N^6$-methyladenosine and conversion of $N^4$-cytosine of 5'-GpC-3' to $N^4$-methylcytosine. Exocyclic DNA methyltransferase from the genome of strain IMCC12053 was chosen using phylogenetic analysis and $N^4$-cytosine methyltransferase was cloned. IPTG inducer was used to confirm the methylation activity of DNA methylase, and cloned into a pQE30 vector using dam-/dcm- E. coli as the expression host. The genomic DNA and the plasmid carrying methylase-encoding sequences were extracted and cleaved with restriction enzymes that were sensitive to methylation, to confirm the methylation activity. These methylases protected the restriction enzyme site once IPTG-induced methylases methylated the chromosome and plasmid, harboring the DNA methylase. In this study, cloned exocyclic DNA methylases were investigated for potential use as a novel type of GpC methylase for molecular biology and epigenetics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.35-42
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• 2019

Nut fasteners that require ultra-precise control are required in the overall manufacturing industry including electronic products that are currently developing with the automobile industry. Important performance factors when tightening nuts include loosening due to insufficient fastening force, breakage due to excessive fastening, Tightening torque and angle are required to maintain and improve the assembling quality and ensure the life of the product. Nut fasteners, which are now marketed under the name Nut Runner, require high torque and precision torque control, precision angle control, and high speed operation for increased production, and are required for sophisticated torque control dedicated to high output BLDC motors and nut fasteners. It is demanded to develop a high-precision torque control driver and a high-speed, low-speed, high-response precision speed control system, but it does not satisfy the high precision, high torque and high speed operation characteristics required by customers. Therefore, in this paper, we propose a control technique of BLDC motor variable speed control and nut runner based on vector control and torque control based on coordinate transformation of d axis and q axis that can realize low vibration and low noise even at accurate tightening torque and high speed rotation. The performance results were analyzed to confirm that the proposed control satisfies the nut runner performance. In addition, it is confirmed that the pattern is programmed by One-Stage operation clamping method and it is tightened to the target torque exactly after 10,000 [rpm] high speed operation. The problem of tightening torque detection by torque ripple is also solved by using disturbance observer Respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.651-658
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• 2021

Because bolts with anti-loosening coatings are used mainly for joining safety-related components in automobiles, accurate automatic screening of these coatings is essential to detect defects efficiently. The performance of the convolutional neural network (CNN) used in a previous study [Identification of bolt coating defects using CNN and Grad-CAM] increased with increasing number of data for the analysis of image patterns and characteristics. On the other hand, obtaining the necessary amount of data for coated bolts is difficult, making training time-consuming. In this paper, resorting to the same VGG16 model as in a previous study, transfer learning was applied to decrease the training time and achieve the same or better accuracy with fewer data. The classifier was trained, considering the number of training data for this study and its similarity with ImageNet data. In conjunction with the fully connected layer, the highest accuracy was achieved (95%). To enhance the performance further, the last convolution layer and the classifier were fine-tuned, which resulted in a 2% increase in accuracy (97%). This shows that the learning time can be reduced by transfer learning and fine-tuning while maintaining a high screening accuracy.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.697-705
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• 2020

This paper deals with an analysis of crustal movement for the sourthern part of Korean peninsula using GNSS (Global Navigation Satellite System) data. An earthquake of more than 5.0 occurred in the southeastern region of the Korean Peninsula, and it is necessary to evaluate the risk of earthquakes in various ways.In order to reveal long-term tectonic movement patten in Pohang and Gyeongju provinces, we derived crustal movement parameters related with elastic theory. We used GAMIT/GLOBK for analyzing seven-year interval GNSS data of CORS (Continuously Operating Reference Stations). The azimuth of velocity vectors trended generally about 110° with an mean magnitude of 31mm/yr.The main characteristics of the strain change for seven-year in Korea obtaind from our study. Direction of the principal axis of the maximum compression is ENE-WSW as a whole, through there are some exceptions. The mean rate of the maximum shear strain change is (0.11±0.07)μ/yr, that is approximately one third that of Chubu district, Central Japan. Taking into account our results, the mean rate of maximum shear in southern part of Korean peninsula is considered as reasonable. The mean azimuth of principal strain is about (85.4°±26.8°). There are some exceptions of azimuth because the average azimuth differ from the left and right side in Yangsan fault which are about (73.2°±21.5°) and (105.2°±17.0°) respectively, It is noteworthy that the high seismicity areas in the southern part of Korea peninsula almost coincides with the area of large strain rate. As a conclusion, it could be stated that the our study represents the characteristics of crustal deformation in the southern part of peninsula, and contributes to the researches on earthquake disaster management.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.449-456
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• 2021

An intrusion detection system is a technology that detects abnormal behaviors that violate security, and detects abnormal operations and prevents system attacks. Existing intrusion detection systems have been designed using statistical analysis or anomaly detection techniques for traffic patterns, but modern systems generate a variety of traffic different from existing systems due to rapidly growing technologies, so the existing methods have limitations. In order to overcome this limitation, study on intrusion detection methods applying various machine learning techniques is being actively conducted. In this study, a comparative study was conducted on data preprocessing techniques that can improve the accuracy of anomaly detection using NGIDS-DS (Next Generation IDS Database) generated by simulation equipment for traffic in various network environments. Padding and sliding window were used as data preprocessing, and an oversampling technique with Adversarial Auto-Encoder (AAE) was applied to solve the problem of imbalance between the normal data rate and the abnormal data rate. In addition, the performance improvement of detection accuracy was confirmed by using Skip-gram among the Word2Vec techniques that can extract feature vectors of preprocessed sequence data. PCA-SVM and GRU were used as models for comparative experiments, and the experimental results showed better performance when sliding window, skip-gram, AAE, and GRU were applied.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.133-140
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• 2023

The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.347-357
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• 2003

This paper describes on the suppression of sea clutter on marine radar display using a cell-averaging CFAR(constant false alarm rate) technique, and on the analysis of radar echo signal data in relation to the estimation of ARPA functions and the detection of the shadow effect in clutter returns. The echo signal was measured using a X -band radar, that is located on the Pukyong National University, with a horizontal beamwidth of $$3.9^{\circ}$$, a vertical beamwidth of $20^{\circ}$, pulsewidth of $0.8 {\mu}s$ and a transmitted peak power of 4 ㎾ The suppression performance of sea clutter was investigated for the probability of false alarm between $l0-^0.25;and; 10^-1.0$. Also the performance of cell averaging CFAR was compared with that of ideal fixed threshold. The motion vectors and trajectory of ships was extracted and the shadow effect in clutter returns was analyzed. The results obtained are summarized as follows；1. The ARPA plotting results and motion vectors for acquired targets extracted by analyzing the echo signal data were displayed on the PC based radar system and the continuous trajectory of ships was tracked in real time. 2. To suppress the sea clutter under noisy environment, a cell averaging CFAR processor having total CFAR window of 47 samples(20+20 reference cells, 3+3 guard cells and the cell under test) was designed. On a particular data set acquired at Suyong Man, Busan, Korea, when the probability of false alarm applied to the designed cell averaging CFAR processor was 10$^{-0}$.75/ the suppression performance of radar clutter was significantly improved. The results obtained suggest that the designed cell averaging CFAR processor was very effective in uniform clutter environments. 3. It is concluded that the cell averaging CF AR may be able to give a considerable improvement in suppression performance of uniform sea clutter compared to the ideal fixed threshold. 4. The effective height of target, that was estimated by analyzing the shadow effect in clutter returns for a number of range bins behind the target as seen from the radar antenna, was approximately 1.2 m and the information for this height can be used to extract the shape parameter of tracked target..