• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.907-916
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• 2019

In this paper, we propose a new five-qubit multiple bit flip code that can completely protect the target qubit from all multiple bit flip errors using only CNOT gates. The proposed multiple bit flip codes can be easily extended to multiple phase flip codes by embedding Hadamard gate pairs in the root error section as in conventional single bit flip code. The multiple bit flip code and multiple phase flip code in this paper share the state vector error information by four auxiliary qubits. These four-qubit state vectors reflect the characteristic that all the multiple flip errors with Pauli X and Z corrections commonly include a specific root error. Using this feature, this paper shows that low-cost implementation is possible despite the QECC design for multiple-flip error correction by batch processing the detection and correction of Pauli X and Z root errors with only three CNOT gates. The five-qubit multiple bit flip code and multiple phase flip code proposed in this paper have 100% error correction rate and 50% error discrimination rate. All QECCs presented in this paper were verified using QCAD simulator.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.446-457
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• 2020

Crescentic sand bar in the coastal zone of eastern Korea is a common morphological feature and the rhythmic patterns exist constantly except for high wave energy events. However, four consecutive typhoons that directly and indirectly affected the East Sea of Korea from September to October in 2019 impacted the formation of longshore uniform sand bar and overall shoreline retreats (approx. 2 m) although repetitive erosion and accretion patterns exist near the shoreline. Widely used XBeach to predict storm erosions in the beach is utilized to investigate the morphological response to a series of storms and each storm impact (NE-E wave incidence). Several calibration processes for improved XBeach modeling are conducted by recently reported calibration methods and the optimal calibration set obtained is applied to the numerical simulation. Using observed wave, tide, and pre & post-storm bathymetries data with optimal calibration set for XBeach input, XBeach successfully reproduces erosion and accretion patterns near MSL (BSS = 0.77 (Erosion profile), 0.87 (Accretion profile)) and observed the formation of the longshore uniform sandbar. As a result of analysis of simulated total sediment transport vectors and bed level changes at each storm peak Hs, the incident wave direction contributes considerable impact to the behavior of crescentic sandbar. Moreover, not only the wave height but also storm duration affects the magnitude of the sediment transport. However, model results suggest that additional calibration processes are needed to predict the exact crest position of bar and bed level changes across the inner surfzone.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.1-12
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• 2021

In this paper, a new algorithm is proposed to estimate the damage location in the composite panel by extracting the elastic wave signal reflected from the damaged area. The guided elastic wave is generated by a piezoelectric actuator and sensed by a piezoelectric sensor. The proposed algorithm adopts a diagnostic approach. It compares the non-damaged signal with the damaged signal, and extract damage information along with sensor network and lamb wave group velocity estimated by signal correlation. However, it is difficult to clearly distinguish the damage location due to the nonlinear properties of lamb wave and complex information composed of various signals. To overcome this difficulty, the cumulative summation feature vector algorithm(CSFV) and a visualization technique are newly proposed in this paper. CSFV algorithm finds the center position of the damage by converting the signals reflected from the damage to the area of distance at which signals reach, and visualization technique is applied that expresses feature vectors by multiplying damage indexes. Experiments are performed for a composite panel and comparative study with the existing algorithms is carried out. From the results, it is confirmed that the damage location can be detected by the proposed algorithm with more reliable accuracy.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.11-22
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• 1999

Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

• Journal of IKEEE
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• v.25 no.2
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• pp.273-279
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• 2021

In this paper, we propose an algorithm that shortens the learning time by performing individual learning using partitioning the deep learning structure. The proposed algorithm consists of four processes: network classification origin setting process, feature vector extraction process, feature noise removal process, and class classification process. First, in the process of setting the network classification starting point, the division starting point of the network structure for effective feature vector extraction is set. Second, in the feature vector extraction process, feature vectors are extracted without additional learning using the weights previously learned. Third, in the feature noise removal process, the extracted feature vector is received and the output value of each class is learned to remove noise from the data. Fourth, in the class classification process, the noise-removed feature vector is input to the multi-layer perceptron structure, and the result is output and learned. To evaluate the performance of the proposed algorithm, we experimented with the Extended Yale B face database. As a result of the experiment, in the case of the time required for one-time learning, the proposed algorithm reduced 40.7% based on the existing algorithm. In addition, the number of learning up to the target recognition rate was shortened compared with the existing algorithm. Through the experimental results, it was confirmed that the one-time learning time and the total learning time were reduced and improved over the existing algorithm.

• Journal of Apiculture
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• v.35 no.1
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• pp.9-19
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• 2020

The questionnaire survey for Apis cerana beekeepers and professionals on improved native bee hives was carried out and we compared the temperature, relative humidity(RH), and weight changes of 4 improved hives(Chungju, Miryang, Hanam, and Suwon) from May 1, 2019 to January 31, 2020. Beekeepers need vertical feeder, hive stand, entrance block, and separating panel as hive accessory devices. The average temperatures within brood area were kept constantly (31.3~35.1℃) and the low daily variances of temperature (≤1℃) in Chungju hive among tested hives were observed. The daily temperature variances in the separated space and on the top of winter cluster were not different among 4 hives. In correlation between the temperature of brood area and the number of combs, Chungju hive showed the highest correlation(80.4%) and between the temperature on top of winter clusters and outside temperature, 4 hives showed high positive correlation(76.8~87.1%). RH of brood area(45~60%) in all hives were kept relatively low and constant compared to the outside RH(60~85%). The stablest RH on the top of winter cluster was observed in Suwon hives (65~75%) The highest cumulative weight increase among hives and the high positive correlation(65~67%) between the change of cumulative hive weight and combs number of hives were shown in the Miryang and Chungju. Based on these results, A. cerana bees are able to manage constant temperature and RH within hives area for their colony life, which also effected by the types of hive.

• Smart Media Journal
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• v.10 no.1
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• pp.16-24
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• 2021

The exiting word embedding methodology such as word2vec represents words, which only occur in the raw training corpus, as a fixed-length vector into a continuous vector space, so when mapping the words incorporated in the raw training corpus into a fixed-length vector in morphologically rich language, out-of-vocabulary (OOV) problem often happens. Even for sentence embedding, when representing the meaning of a sentence as a fixed-length vector by synthesizing word vectors constituting a sentence, OOV words make it challenging to meaningfully represent a sentence into a fixed-length vector. In particular, since the agglutinative language, the Korean has a morphological characteristic to integrate lexical morpheme and grammatical morpheme, handling OOV words is an important factor in improving performance. In this paper, we propose parallel Tri-LSTM sentence embedding that is robust to the OOV problem by extending utilizing the morphological information of words into sentence-level. As a result of the sentiment analysis task with corpus in Korean, we empirically found that the character unit is better than the morpheme unit as an embedding unit for Korean sentence embedding. We achieved 86.17% accuracy on the sentiment analysis task with the parallel bidirectional Tri-LSTM sentence encoder.

• 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.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.4
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• pp.356-363
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• 2020

The distribution of ticks and severe fever with thrombocytopenia syndrome virus (SFTSV) pathogens were investigated by collecting ticks from March to November 2018 in four environments (grass fields, copses, mountain roads, and tombs) in Jeju. Three thousand and ninety ticks were collected using a tick trap, and 1,569 ticks were collected using the flagging method. Of the 4,659 ticks collected, Haemaphysalis longicornis and Haemaphysalis flava accounted for 4,440 ticks (95.2%) and 219 ticks (4.7%), respectively. Nine hundred and fifty, 883, 847, and 410 ticks were collected from grass fields, copses, mountain roads, and tombs, respectively, using tick traps, whereas 704, 472, 197, and 196 ticks were collected from copses, mountain roads, tombs, and grass fields, respectively, using the flagging method. The largest fraction of ticks (2,978) was collected from April to August, and most were collected in May and June. Adult ticks comprised 94 percent of the total ticks from June to August. SFTSV was not detected in the 4,440 H. longicornis ticks or the 219 H. flava ticks collected in this study.