• Journal of Chest Surgery
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• v.25 no.12
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• pp.1455-1460
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• 1992

Anomalous drainage of the right superior vena cava into the left atrium is a very rare congenital cardiac anomaly. Recently a patient with this venous anomaly was surgically corrected and forms the basis of this report. Patient findings were as follows: The patient has no other symptom but cyanosis which prompted cardiac evaluation Chest PA and electrocariogram were usual. Cross-sectional echocardiogram showed normally connected heart without intracardiac defect, Inferior vena cava drained normally into right atrium and coronary sinus was not dilated. Contrast, given into the right atrium, appeared in the left atrium This rare venous anomaly was confirmed by surgery. Surgical correction consisted of division of superior vena cava above the junction of left atrium and reanastomosis into right atrial appendage. Postoperative digital subtracion angiography confirmed the successful repair. She has doing well for 6months since operation. Systemic venous anomalies without intracardiac defect are very rare. However this anomalies should be considered in the differential diagnosis of cyanosis. The successfully corrected case is reported and literature is reviewed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.587-595
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• 1999

The fundamental reason why inheritance anomaly occurs is that for a concurrent object, when synchronization code is not properly separated from the method code, the extension of code to produce a derived class may force the change of both the synchronization code and the method code in the super class, and inheritance is integrated inheritance in a simple and satisfactory way within a concurrent object-oriented language. The main emphasis on how to avoid or minimize inheritance anomaly. Therefore, in this paper we propose a new model, object model, and will minimizes the problem of inheritance anomaly found in concurrent object-oriented programming languages using Behavior Equation.

• YAKHAK HOEJI
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• v.22 no.4
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• pp.233-237
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• 1978

We studied on the separation of $\alpha$- and $\beta$-chain globins, the conditions of paper electrophoresis and mobility of globins in paper electrophoresis to determine their chain anomaly. Acidic-acetone mothod of Wilson and Smith was found to be more effecient for separating $\alpha$- and $\beta$chain globions than trichloroacetic acid method of Hayashi. The conditions of paper electrophoresis were current of 20v/cm and 0.6mA/cm for three hours at room temperature. In paper electroporesis, the mobility of $\alpha$- -chain globin towards the cathode was greater than that of $\beta$-chain globin. The results showed tha tchain anomaly of $\alpha$- and $\beta$-chain globins can be determined by the method of paper electrophoresis.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.750-757
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• 1999

The protocol conformance testing is to check whether an implementation of a protocol conforms to its specification. And it is important to improve the interoperability of protocol and the efficiency of cost. In general, protocol is composed of the control flow representing observable behaviors and the data flow representing internally used variables. Until now, research for generation of test suite has been realized only consideration the control flow of protocol or separation control flow from data flow. Case of considering control flow, contents of test was simple and definite. Length of test was short. But it was of little application, and it didn't manage each kind errors in data flow. Therefore, we must generate test case that can manage control and data flow. So, anomaly of variable must be removed for efficient conformance testing. Therefore in this dissertation, we proposed algorithm which can remove anomaly of variable for efficient conformance testing. And it showed that anomaly of variable was got rid of applying this algorithm to real protocol.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1412-1417
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• 2007

Magnetic anomaly generated around a ship is mainly due to the permanent magnetization(PM) and induced magnetization (IM) remaining on the hull. It is very difficult to predict the direction and its magnitude of the permanent magnetization distributed over the hull, that is caused by mechanical or thermal stress. In this paper, an effective method is proposed to separate two components, the one produced by PM and the other by IM, from the underwater earth field signal distorted by the ferromagnetic material of the ship. The method can easily provide the two kinds of magnetic anomaly through exploiting experimental results and 3D electromagnetic field analyses even though the PM distribution on the hull is not known. To validate the proposed method, a model ship is manufactured and tested. The results would be of much help to basis research for securing safe navigation of a ship against dangerous factors in underwater.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1413-1414
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• 2003

Interannual variability in the patterns of satellitederived pigment concentrations, sea-level height anomaly, sea surface temperature anomaly, and zonal wind anomaly are observed during the 2002-2003 El Ni${\tilde{n}}$o. The largest spatial extent of the phytoplankton bloom was recovery from El Ni${\tilde{n}}$o over the equatorial Pacific. The evolution towards a warm episode (El Ni${\tilde{n}}$o) started from spring of 2002 and continued during January 2003, while equatorial Sea Surface Temperature Anomaly (SSTA) remained greater than +1$^{\circ}$C in the central equatorial Pacific. The EOS (Earth Observing System) and OSMI (Ocean Scanning Multispectral Imager) data are used for detection of dramatic changes in the patterns of pigment concentration during El Ni${\tilde{n}}$o.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.277-283
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• 2021

This paper addresses the problem of vision-based mask filter inspection for mask production systems. Machine learning-based approaches can be considered to solve the problem, but they may not be applicable to mask filter inspection if normal and anomaly mask filter data are not sufficient. In such cases, handcrafted image processing methods have to be considered to solve the problem. In this paper, we propose a hierarchical correlation-based approach that combines handcrafted image processing methods to detect anomaly mask filters. The proposed approach combines image rotation, cropping and resizing, edge detection of mask filter parts, average blurring, and correlation-based decision. The proposed approach was tested and analyzed with real mask filters. The results showed that the proposed approach was able to successfully detect anomalies in mask filters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• ETRI Journal
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• v.41 no.5
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• pp.684-695
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• 2019

In a cloud environment, performance degradation, or even downtime, of virtual machines (VMs) usually appears gradually along with anomalous states of VMs. To better characterize the state of a VM, all possible performance metrics are collected. For such high-dimensional datasets, this article proposes a feature extraction algorithm based on unsupervised fuzzy linear discriminant analysis with kernel (UFKLDA). By introducing the kernel method, UFKLDA can not only effectively deal with non-Gaussian datasets but also implement nonlinear feature extraction. Two sets of experiments were undertaken. In discriminability experiments, this article introduces quantitative criteria to measure discriminability among all classes of samples. The results show that UFKLDA improves discriminability compared with other popular feature extraction algorithms. In detection accuracy experiments, this article computes accuracy measures of an anomaly detection algorithm (i.e., C-SVM) on the original performance metrics and extracted features. The results show that anomaly detection with features extracted by UFKLDA improves the accuracy of detection in terms of sensitivity and specificity.

• Kosin Medical Journal
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• v.33 no.3
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• pp.463-467
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• 2018

The hepatic artery can have numerous variations. However, a common hepatic artery originating from the left gastric artery and the entire hepatic blood supply furnished by the left gastric artery is an extremely rare anomaly. We encountered this anomaly in a patient with advanced gastric cancer. A surgeon should recognize this image appearance and identify the anomaly. Without knowledge of this anomaly and given the strategy for extensive lesser sac dissection generally employed during gastric cancer surgery, a surgeon could easily inadvertently divide this vessel, resulting in critical liver damage. We report a case of common hepatic artery originating from left gastric artery and review of the literatures.