• Journal of Chest Surgery
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• v.37 no.3
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• pp.235-244
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• 2004

Anatomic correction of the transposition of the great arteries (TGA) or Taussig-Bing anomaly by means of the arterial switch operation is now accepted as the therapeutic method of choice. This retrospective study was conducted to evaluate the risk factors for operative deaths and the efficacy of technical modification of the coronary transfer. 85 arterial switch operations for TGA or Taussig-Bing anomaly which were performed by one surgeon from 1994 to July 2002 at Dong-A university hospital were included in this retrospective study Multivariate analysis of perioperative variables for operative mortality including technical modification of the coronary transfer was peformed. Overall postoperative hospital mortality was 20.0% (17/85). The mortality before 1998 was 31.0% (13/42), but reduced to 9.3% (4/43) from 1998. The mortality in the patients with arch anomaly was 61.5% (8/13), but 12.5% (9/72) in those without arch anomaly. In patients who underwent an open coronary reimplantation technique, the operative mortality was 28.1% (18/64), but 4.8% (1/21) in patients undergoing a technique of reimplantation coronary buttons after neoarotic reconstruction. Risk factors for operative death from multivariated analysis were cardiopulmonary bypass time ($\geq$ 250 minutes), aortic cross-clamping time ($\geq$ 150 minutes), aortic arch anomaly, preoperative event, and open coronary reimplantation technique. Operative mortality has been reduced with time. Aortic arch anomaly and preoperative events were important risk factors for postoperative mortality. However atypical coronary artery patterns did not work as risk factors. We think that the technical modification of coronary artery transfer played an important role in reducing the postoperative mortality of arterial switch operation.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.355-364
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• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• 한국IT서비스학회:학술대회논문집
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• 2008.11a
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• pp.445-448
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• 2008

최근의 비디오 영상을 사용한 상황 판단 기법들은 사용자의 인식과 판단에 의존하고 있을 뿐만아니라 실시간 대응이 어렵다는 단점이 있었다. 따라서 본 논문에서는 순차패턴을 이용하여 실시간으로 영상에 나타나는 객체들의 비정상 행위를 탐지하는 자동화 방법을 제안한다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.157.1-157
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• 2001

A new methodology is presented to diagnose faults in equipment plasma. This is accomplished by using neural networks as a pattern recognizer of radio frequency(rf) impedance match data. Using a realtime match monitor system, the match data were collected. The monitor system consisted mainly of a multifunction board and a signal flow diagram coded by Visual Designer. Plasma anomaly was effectively represented by electrical match positions. Twenty sets of fault-symptom patterns were experimentally simulated with experimental variations in process factors, which include rf source power, pressure, Ar and O$_2$ flow rates. As the inputs to neural networks, two means and standard deviations of positions were used ...

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.3
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• pp.135-149
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• 2008

Traditional attack detection schemes based on packets or flows have very high computational complexity. And, network based anomaly detection schemes can reduce the complexity, but they have a limitation to figure out the pattern of the distributed global scale network attack. In this paper, we propose an efficient and fast method for detecting distributed global-scale network attack symptoms in high-speed backbone networks. The proposed method is implemented at the aggregate traffic level. So, our proposed scheme has much lower computational complexity, and is implemented in very high-speed backbone networks. In addition, the proposed method can detect attack patterns, such as attacks in which the target is a certain host or the backbone infrastructure itself, via collaboration of edge routers on the backbone network. The effectiveness of the proposed method are demonstrated via simulation.

• Economic and Environmental Geology
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• v.32 no.2
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• pp.141-150
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• 1999

The granitic rocks are distributed in the northeastern Gyeongsang basin, and are subdivided into the Youngduk, Younghae, Jangsadong and Onjeong granite. Based on the chondrite normalized patterns of REE by primitive mantle, the Jangsadong granite is more negative Eu anomaly than other granites. On the patterns of trace and rare earcth elements normalized by primitive mantle, Sr, P, Nd, Sm and Ti contents of t도 Youngduk and Younghae granites are higher than those of Jangsadong and Onjeong granites. Based on K-Ar ages, the Youngduk granite is 166.5 Ma for biotite, Younghae granite is 158.7 to 178.0 Ma for hornblende, Jangsadong granite is 113.8 to 118.4 Ma for K-feldspar and hornblende, and Onjeong granite is 67.4 Ma for biotite. Thus, geochemical and geochronological results suggest two plutonic episodes :the Youngduk-Younghae granites and Jangsadong-Onjeong granites suggest two plutonic episodes : the Youngduk-Younghae granites and Jangsadong-Onjeong granites. Jurassic plutonism cooled faster than Cretacous plutonism in the study area.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.525-532
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• 2003

This paper describes intrusion detection rule management using mobile agents. Intrusion detection can be divided into anomaly detection and misuse detection. Misuse detection is best suited for reliably detecting known use patterns. Misuse detection systems can detect many or all known attack patterns, but they are of little use for as yet unknown attack methods. Therefore, the introduction of mobile agents to provide computational security by constantly moving around the Internet and propagating rules is presented as a solution to misuse detection. This work presents a new approach for detecting intrusions, in which mobile agent mechanisms are used for security rules propagation. To evaluate the proposed approach, we compared the workload data between a rules propagation method using a mobile agent and a conventional method. Also, we simulated a rules management using NS-2 (Network Simulator) with respect to time.

• Economic and Environmental Geology
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• v.17 no.1
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• pp.49-55
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• 1984

This paper describes three-dimensional (3-D) standard curves for conductive dipping buried bodies in induced polarization (IP) method. Dipole-dipole IP responses for the dipping bodies are calculated by the numerical modeling technique using an integral equation solution. Dip angles of the bodies are 0, 20, 45, 70 and 90 degrees, respectively. The horizontal (0-degree dip) and vertical (90-degree dip) bodies produce symmetrical patterns of IP responses. The dipping bodies of 20, 45 and 70 degrees, however, produce asymmertical patterns, with the highest IP contours dipping in the direction opposite to the bodies in pseudo-sections. The most remarkable asymmetrical pattern appears in the model of 20-degree dip. It is difficult to distinguish the body of 70-degree dip from that of 90-degree dip on the basis of dipole-dipole IP data. The IP pattern in pseudo-sections varies when the line moves away from the center of the body along strike, with the anomaly deeper and smaller in amplitude. IP maps seem to be more useful than IP pseudo-sections in predicting the location of target.

• Journal of the Korean Geographical Society
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• v.43 no.5
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• pp.701-714
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• 2008

This study examines the prevailing synoptic-scale mechanisms favorable for long-lived summer Persistent Positive Temperature Anomalies (PPTAs) as well as winter PPTAs in the United States. Such long-lived PPTAs usually occur in the south-central region of the United States in summer, but in the southwestern part of the United States in winter. Composite analyses of surface and pressure level data demonstrate that the formation of both winter and summer PPTAs is closely related to the movement of subtropical high pressure systems in the Pacific Ocean and Atlantic Ocean, respectively. The occurrence of long-lived summer PPTAs usually coincides with an extremely stable atmospheric condition caused by persistent blocking by mid- to upper-tropospheric anticyclones. Significant surface forcing is also easily identified through relatively high Bowen ratios at the surface. Warm air advection is, however, weak and appears to be an insignificant element in the formation of long-lived summer PPTAs. On the other hand, synergistic warming effects associated with adiabatic heating under an anticyclonic blocking system as well as significant warm air advection characterize the favorable synoptic environments for long-lived winter PPTAs. However, the impact of surface forcing mechanisms on winter PPTAs is insignificant.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.125-144
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• 2022

When a variable message signs (VMS) system displays false information related to traffic safety caused by malicious attacks, it could pose a serious risk to drivers. If the normal message patterns displayed on the VMS system are learned, it would be possible to detect and respond to the anomalous messages quickly. This paper proposes a method for detecting anomalous messages by learning the normal patterns of messages using a bi-directional generative pre-trained transformer (GPT) network. In particular, the proposed method was trained using the normal messages and their system parameters to minimize the corresponding negative log-likelihood (NLL) values. After adequate training, the proposed method could detect an anomalous message when its NLL value was larger than a pre-specified threshold value. The experiment results showed that the proposed method could detect malicious messages and cases when the system error occurs.