• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2109-2119
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• 2001

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-2 bit-steam is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algorithm has two important steps, namely the motion vectors extraction from MPEG-2 bit-stream and the watershed algorithm. The algorithm extracts objects using user\`s assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object, the user can intervene to correct the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracts processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tacking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask, and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-2 bit-stream to the object-based MPEG-4 input.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.91-102
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• 2004

In this paper, a fast information extraction algorithm for object-based MPEG-4 application from MPEG-1,2 is proposed. For object-based MPEG-4 conversion, we need to extract such information as object-image, shape-image, macro-block motion vector, and header information from MPEG-1,2 bit-stream. If we use the extracted information, fast conversion for object-based MPEG-4 is possible. The proposed object extraction algerian has two important steps, namely the motion vector extraction from MPEG-1,2 bit-stream and the watershed algerian The algorithm extracts objects using user's assistance in the intra frame and tracks then in the following inter frames. If we have an unsatisfactory result for a fast moving object the user can intervene to connect the segmentation. The proposed algorithm consist of two steps, which are intra frame object extracting processing and inter frame tracking processing. Object extracting process is the step in which user extracts a semantic object directly by using the block classification and watersheds. Object tracking process is the step of the following the object in the subsequent frames. It is based on the boundary fitting method using motion vector, object-mask and modified watersheds. Experimental results show that the proposed method can achieve a fast conversion from the MPEG-1,2 bit-stream to the object-based MPEG-4 input.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.365-372
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• 2022

Compared to sensors mainly used in human activity recognition (HAR) systems, inertial measurement unit (IMU) sensors are small and light, so can achieve lightweight system at low cost. Therefore, in this paper, we propose a binary neural network (BNN) based gait pattern analysis system using IMU sensor, and present the design and implementation results of an FPGA-based accelerator for computational acceleration. Six signals for gait are measured through IMU sensor, and a spectrogram is extracted using a short-time Fourier transform. In order to have a lightweight system with high accuracy, a BNN-based structure was used for gait pattern classification. It is designed as a hardware accelerator structure using FPGA for computation acceleration of binary neural network. The proposed gait pattern analysis system was implemented using 24,158 logics, 14,669 registers, and 13.687 KB of block memory, and it was confirmed that the operation was completed within 1.5 ms at the maximum operating frequency of 62.35 MHz and real-time operation was possible.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.1-8
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• 2020

Recently, the number of APT(Advanced Persistent Threats) attack using malware has been increasing, and research is underway to prevent and detect them. While it is important to detect and block attacks before they occur, it is also important to make an effective response through an accurate analysis for attack case and attack type, these respond which can be determined by analyzing the attack group of such attacks. Therefore, this paper propose a framework based on genetic algorithm for analyzing malware and understanding attacker group's features. The framework uses decompiler and disassembler to extract related code in collected malware, and analyzes information related to author through code analysis. Malware has unique characteristics that only it has, which can be said to be features that can identify the author or attacker groups of that malware. So, we select specific features only having attack group among the various features extracted from binary and source code through the authorship clustering method, and apply genetic algorithm to accurate clustering to infer specific features. Also, we find features which based on characteristics each group of malware authors has that can express each group, and create profiles to verify that the group of authors is correctly clustered. In this paper, we do experiment about author classification using genetic algorithm and finding specific features to express author characteristic. In experiment result, we identified an author classification accuracy of 86% and selected features to be used for authorship analysis among the information extracted through genetic algorithm.

• Journal of Korean Society of Forest Science
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• v.83 no.4
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• pp.441-449
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• 1994

The two reflective channels(red and near infrared spectrum) of advanced very high resolution radiometer(AVHRR) data were used to classify primary vegetation cover types in the Korean Peninsula. From the NOAA-11 satellite data archive of 1991, 27 daytime scenes of relatively minimum cloud coverage were obtained. After the initial radiometric calibration, normalized difference vegetation index(NDVI) was calculated for each of the 27 data sets. Four or five daily NDVI data were then overlaid for each of the six months starting from February to November and the maximum value of NDVI was retained for every pixel location to make a monthly composite. The six bands of monthly NDVI composite were nearly cloud free and used for the computer classification of vegetation cover. Based on the temporal signatures of different vegetation cover types, which were generated by an unsupervised block clustering algorithm, every pixel was classified into one of the six cover type categories. The classification result was evaluated by both qualitative interpretation and quantitative comparison with existing forest statistics. Considering frequent data acquisition, low data cost and volume, and large area coverage, it is believed that AVHRR data are effective for vegetation cover type mapping at regional scale.

• Radiation Oncology Journal
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• v.15 no.2
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• pp.167-174
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• 1997

Purpose : The main Purpose of this study is to develop new payment rates for services of Radiation Oncology, considering costs of treating patients. Material and Methods : A survey of forty hospitals has been conducted in order to analyze the costs of treating patients. Before conducting the survey, we evaluated and reclassified the individual service items currently using as Payments units on the fee-for-service reimbursement system. This study embodies the analysis of replies received from the twenty four hospitals. The survey contains informations about the hospitals' costs of 1995 for the reclassified service items on Radiation Oncology. After we adjust the hospital costs by the operating rate of medical equipment, we compare the adjusted costs with the current Payment rates of individual services. Results : The current payment rates were 5.05-6.58 times lower than the adjusted costs in treatment planning services, 2.22 times lower in block making service, 1.57-2.86 times lower in external beam irradiation services, 3.82-5.01 times lower in intracavitary and interstitial irradiation and 1.12-2.55 times lower in total body irradiation. Conclusion : We could conclude that the current payment system on Radiation Oncology does not only reflect the costs of treating patients appropriately but also classify the service items correctly. For an example, when the appropriate costs and classification are applied to TBI, the payment rates of TBI should be increased five times more than current level.

• Journal of architectural history
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• v.20 no.6
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• pp.77-98
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• 2011

The aim of this study is to identify the floor plan types of folk houses or traditional vernacular dwellings found in Nagan Folk Village located in Joellanamdo province. Examining the floor plans appeared among 36 vernacular folk houses presumably built in the 19th century in the village by means of the changes in the number of bays of Anche, the mail block of the house, the study was also able to construct a spatial compositional process of floor plan development. The floor plan examination revealed that the basic floor plan type in Nagan folk housing was '一' shape, a typical southern dwelling based on the existing classification. This basic type is consisted of three bays or rooms: Jeongji (kitchen), Anbang (large room), and Jageunbang (small room). New spaces or rooms are added to this three room house to expand the house as the residential functions become more complex, such as more living and storage spaces. The expansion appears to have two direction. On the one hand, it has been taken place by inserting Marea, an open wooden floor living space between Anbang and Jageunbang to meet the extended living demand. On the other, Jeongjibang, a second kitchen/storage has been attached to Jeongji outward for extra cooking and storage. This two-way expansion shows the trend of symmetric expansion between cooking, storing space and dwelling space. It can be implied that the arrangement of house rooms has been structurally formulated and shared by the farmer-builders in the 19th century in Nagan village who appeared to be influenced by fixed images for housing.

• Journal of Chest Surgery
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• v.22 no.4
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• pp.620-629
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• 1989

A clinical analysis of 138 cases of ventricular septal defect operated on from 1983 to June 1988 at the department of Thoracic and Cardiovascular Surgery, School of Medicine, Chung-nam National University was done. The following results were obtained. 1. The VSD were 27.6 % and 41.0 % respectively of 500 open heart surgery cases and 334 congenital heart disease. 2. The range of age when the VSD was repaired was 3 months to 45 years, the mean age was 10.4 years and the 53.6 % of patients were under 7 years. The sex ratio was 6:4 in males favor. 3. The two common symptoms were frequent upper respiratory infection and dyspnea whose frequency was 62.5 % and 58.7% respectively. 4. 52% of the patients was below 25 percentile of the standard body weight. 5. The most common chest PA findings were cardiomegaly and increased pulmonary vascularity. 6. On anatomical classification, perimembranous type was most common [65.5%], subpulmonary arterial type was 27.6 %, perimembranous plus subpulmonary arterial type was 3.4 % multiple VSD was 0.8 % and LV-RA defect was 2.6 %. 7. Associated cardiac anomalies were founded in 39 cases [35.5 %] and PDA and aortic valve prolapse were most common associated anomalies and extracardiac anomalies were founded in 6.7 % of patients. 8. Mean extracorporeal circulation time was 68 min. and mean aortic cross-clamping time was 42 min. 9. The postoperative complications developed in 26 % of patients and the most common one was minor wound infection. 10. Right bundle branch block developed in 54.8% of the patients who had right ventriculotomy, 40.0% of the patients who had right atriotomy and 10.5% of the patients who had pulmonary arteriotomy. 11. The overall operative mortality was 5.1 % and the operative mortality of the patients who body weigh under 10 Kg was 23.8%.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.47-54
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• 2005

One of the standard procedures of discontinuity survey is the joint set identification from the population of field orientation data. Discontinuity set identification is fundamental to rock engineering tasks such as rock mass classification, discrete element analysis, key block analysis. and discrete fracture network modeling. Conventionally, manual method using contour plot had been widely used for this task, but this method has some short-comings such as yielding subjective identification results, manual operations, and so on. In this study, the method of discontinuity set identification using genetic algorithm was introduced, but slightly modified to handle the orientation data. Finally, based on the genetic algorithm, we developed a FORTRAN program, Genetic Algorithm based Clustering(GAC) and applied it to two different discontinuity data sets. Genetic Algorithm based Clustering(GAC) was proved to be a fast and efficient method for the discontinuity set identification task. In addition, fitness function based on variance showed more efficient performance in finding the optimal number of clusters when compared with Davis - Bouldin index.