• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1606-1616
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• 2004

This paper introduces a technique for generating an appropriate template signal via modeling of minimum-phase stable ARMA (Auto-Regressive Moving Average) system for coherent impulse communication systems. It has been well known that the transmitted impulse signal becomes deformed because of dispersive and resonant characteristics. Accordingly, in spite of using ideal template signal at the correlator, these impairments degrade overall performance attributed to low level of coherence. To increase the degree of coherence, our proposed scheme realizes A3U system derived by Gaussian pulse signal, which simulates the overall characteristic of transfer function in between transmit and receive wideband antennas so as to generate an appropriate template signal in a form of output. The performance of proposed scheme will be shown in results from computer simulations to verify its affirmative impact on impulse communication system with regarding several distinctively shaped antennas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.30-40
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• 2022

Electrocardiogram (ECG) signal's shape and characteristic varies through each individual, so it is difficult to classify with one neural network. It is difficult to classify the given data directly, but if corresponding normal beat is given, it is relatively easy and accurate to classify the beat by comparing two beats. In this study, we classify the ECG signal by generating the reference normal beat through the template cluster, and combining with the input ECG signal. It is possible to detect abnormal beats of various individual's records with one neural network by learning and classifying with the imaged ECG beats which are combined with corresponding reference normal beat. Especially, various neural networks, such as GoogLeNet, ResNet, and DarkNet, showed excellent performance when using the comparative learning. Also, we can confirmed that GoogLeNet has 99.72% sensitivity, which is the highest performance of the three neural networks.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.21 no.1
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• pp.28-34
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• 1985

This paper describes that the characteristic of movement and the performance of the directional system of the liquid magnetic compass analyze and investigate in the kinds of compass and the coefficient of viscosity of the liquid of compass, which the horizontal magnetic field of the geo-magnetic is varied from the equator to the polar region (0.39 gauss-0.03 gauss) by use of apparatus generating artificial magnetic fields. The results are as follows; 1. It is confirmed that the measured values and the calculated values on the characteristic of damping curve by the type of compass and coefficient of viscosity has almost agree with one another. 2. As the horizontal magnetic force geo-magnetic field approaches around the equator (0.39 gauss), the horizontal magnetic field get near the polar region (0.03 gauss), its period is to be longer and the compass card prove not to be more stabilized. 3. The coefficient of viscosity of the liquid in the A, B, C, D and E compasses used in the experiment is estimated 0.03 poises, 0.02 poises, 0.02 poises, 0.015 poises and 0.048 poises respectively by computer simulation.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.19-31
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• 2022

In Machine learning, we usually divide the entire data into training data and test data, train the model using training data, and use test data to determine the accuracy and generalization performance of the model. In the case of models with low generalization performance, the prediction accuracy of newly data is significantly reduced, and the model is said to be overfit. This study is about a method of generating training data based on central limit theorem and combining it with existed training data to increase normality and using this data to train models and increase generalization performance. To this, data were generated using sample mean and standard deviation for each feature of the data by utilizing the characteristic of central limit theorem, and new training data was constructed by combining them with existed training data. To determine the degree of increase in normality, the Kolmogorov-Smirnov normality test was conducted, and it was confirmed that the new training data showed increased normality compared to the existed data. Generalization performance was measured through differences in prediction accuracy for training data and test data. As a result of measuring the degree of increase in generalization performance by applying this to K-Nearest Neighbors (KNN), Logistic Regression, and Linear Discriminant Analysis (LDA), it was confirmed that generalization performance was improved for KNN, a non-parametric technique, and LDA, which assumes normality between model building.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.11a
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• pp.12.1-12.1
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• 2009

Nano-hydroxyapatite (N-HAp)has shown the pivotal role in producing bone-regenerative materials since it has similarity to natural bone minerals in terms of size, morphology, and the composition. Currently, the combination of biopolymers and N-HAp is recognizedas an attractive approach in generating hybrid scaffolds for bone tissueengineering. Surface engineering is an important issue since it determines whether cells can effectively adhere and proliferate on porous scaffolds. We aim to develop a synthetic approach to porous 3D scaffolds by immobilizing N-HAp on pore surfaces. The discrete nano-level anchoring of N-HAp on the scaffold pore surface is achieved using surface-repellent stable colloidal N-HAp with surface phosphate functionality. This rational surface engineering enables surface-anchored N-HAp to express its overall intrinsic bioactivity,since N-HAp is not phase-mixed with the polymers. The porous polymer scaffolds with surface-immobilized N-HAp provide more favorable environments thanconventional bulk phase-mixed polymer/N-HAp scaffolds in terms of cellular interaction and growth. In vitro biological evaluation using alkalinephosphatase activity assay supports that immobilized N-HAp on pore surfaces of polymer scaffolds contributed to the more enhanced in vitro osteogenicpotential. Besides, the scaffolds with surface-exposed N-HAp provide favorable environments for enhanced in vivo bone tissue growth, estimated by characteristic biomarkers of bone formation such as collagen. The results suggest that newly developed hybrid scaffolds with surface-immobilized N-HApmay serve as a useful 3D substrate with pore surfaces featuring excellent bonetissue-regenerative properties. Acknowledgement. This research was supported by a grant (code #: 2009K000430) from 'Center for Nanostructured Materials Technology' under '21st Century Frontier R&D Programs' of the Ministry of Education, Science and Technology, Korea.

• Journal of Korea Game Society
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• v.12 no.5
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• pp.67-78
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• 2012

Summed area table allows filtering of arbitrary-width box regions for every pixel in constant time per pixel. This characteristic makes it beneficial in image processing applications where the sum or average of the surrounding pixel intensity is required. Although calculating the summed area table of an image data is primarily a memory bound job consisting of row or column-wise summation, previous works had to endure excessive access to the high latency global memory in order to exploit data parallelism. In this paper, we propose an efficient algorithm for generating the summed area table in the GPGPU environment where the input is decomposed into square sub-images with intermediate data that are propagated between them. By doing so, the global memory access is almost halved compared to the previous methods making an efficient use of the available memory bandwidth. The results show a substantial increase in performance.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.5
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• pp.27-33
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• 2003

G-code, another name of ISO6983, has been a popular commanding language for operating machine tools. This G-code, however, limits the usage of today's fast evolving high-performance hardware. For intelligent machines, the communications between machine and CAD/CAM departments become important, but the loss of information during generating G-code makes the production department isolated. The new standard for operating machine tools, named STEP-NC is just about to be standardized as ISO14649. As this new standard stores CAD/CAM information as well as operation commands of CNC machines, and this characteristic makes this machine able to exchange information with other departments. In this research, the new CNC machine operated by STEP-NC was built and tested. Unlike other prototypes of STEP-NC milling machines, this system uses the STEP-NC file in XML file form as data input. This machine loads information from XML file and deals with XML file structure. It is possible for this machine to exchange information to other databases using XML. The STEP-NC milling machines in this research loads information from the XML file, makes tool paths for two5D features with information of STEP-NC, and machines automatically without making G-code. All software is programmed with Visual $C^{++}$, and the milling machine is built with table milling machine, step motors, and motion control board for PC that can be directly controlled by Visual $C^{++}$ commands. All software and hardware modules are independent from each other; it allows convenient substitution and expansion of the milling machine. Example 1 in ISO14649-11 having the full geometry and machining information and example 2 having only the geometry and tool information were used to test the automatic machining capability of this system.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.243-248
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• 2014

The permanent magnet linear synchronous motors facilitate maintenance, for it is structurally simple compare to rotating machine and has lots of advantage such as a precision control, high speed, high thrust and so on. However, it causes an increase of material cost because of structural characteristics that need to arranges the armature on the full length of transportation lines. Thus, in order to resolve this problem, we propose the discontinuous arrangement method of the armature but the edge always exists due to the structure when the armature is arranged discontinuously. Due to this edge, the cogging force is greatly generated and it causes thrust force ripple generating noise, vibration and decline of performance. Therefore, in this paper, we examined the characteristic of end edge according to the skew angle through 3-D numerical analysis using finite element method(FEM) and improved the operation characteristics.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.157-162
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• 2020

In recent years, laser induced graphene process have been intensively studied for eco-friendly electronic device such as flexible electronics or thin film based energy storage devices because of its simple and effective process. In order to increase the performance and efficiency of an electronic device using such a graphene patterned structure, it is essential to study an optimized laser patterning condition as small as possible linewidth while maintaining the graphene-specific 2-dimensional characteristics. In this study, we analyzed to find the optimal line pattern by using a Ti:sapphire femtosecond laser based photo-thermal reduction process. we tuned intensity and scanning speed of laser spot for generating effective graphene characteristic and minimum thermal effect. As a result, we demonstrated the reduced graphene pattern of 30㎛ in linewidth by using a focused laser beam of 18㎛ in diameter.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.564-568
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• 2011

Microblogs became popular information delivery ways due to the spread of smart phones. They have the characteristic of reflecting the interests of users more quickly than other medium. Particularly, in case of the subject which attracts many users, microblogs can supply rich information originated from various information sources. Nevertheless, it has been considered as a hard problem to obtain useful information from microblogs because too much noises are in them. So far, various methods are proposed to extract and track some subjects from particular documents, yet these methods do not work effectively in case of microblogs which consist of short phrases. In this paper, we propose a graph-based topic extraction and partitioning method to understand interests of users about a certain keyword. The proposed method contains the process of generating a keyword graph using the co-occurrences of terms in the microblogs, and the process of splitting the graph by using a network partitioning method. When we applied the proposed method on some keywords. our method shows good performance for finding a topic about the keyword and partitioning the topic into sub-topics.