• 천문학회지
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• 제35권1호
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• pp.35-40
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• 2002

Gaudi, Naber & Sackett pointed out that if an event is caused by a lens system containing more than two planets, all planets will affect the central region of the magnification pattern, and thus the existence of the multiple planets can be inferred by detecting additionally deformed anomalies from intensive monitoring of high magnification microlensing events. Unfortunately, this method has important limitations in identifying the existence of multiple planets and determining their parameters (the mass ratio and the instantaneous projected separation) due to the degeneracy of the resulting light curve anomalies from those induced by a single planet and the complexity of multiple planet lensing models. In this paper, we propose a new channel to search for multiple planets via microlensing. The method is based on the fact that the lensing light curve anomalies induced by multiple planets are well approximated by the superposition of those of the single planet systems where the individual planet-primary pairs act as independent lens systems. Then, if the source trajectory passes both of the outer deviation regions induced by the individual planets, one can unambiguously identify the existence of the multiple planets. We illustrate that the probability of successively detecting light curve anomalies induced by two Jovian-mass planets located in the lensing zone through this channel will be substantial. Since the individual anomalies can be well described by much simpler single planet lensing models, the proposed method has an important advantage of allowing one to accurately determine the parameters of the individual planets.

• Bulletin of the Korean Chemical Society
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• 제24권8호
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• pp.1211-1214
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• 2003

The anomalies that appear at every multiple of 15 ℃ in the viscosity of a thin liquid film of water and of water near solid interfaces are explained in this paper by comparing the thermal wavelength and molecular free volume of water, and quantum numbers are found. The possibility that these anomalies are related to the preferred and/or lethal temperatures of organisms is considered. The toxicity of heavy water (D₂O) can also be explained with this approach.

• Genomics & Informatics
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• 제15권3호
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• pp.82-86
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• 2017

Chromosomal microarray (CMA) is a high-resolution, high-throughput method of identifying submicroscopic genomic copy number variations (CNVs). CMA has been established as the first-line diagnostic test for individuals with developmental delay (DD), intellectual disability (ID), autism spectrum disorders (ASDs), and multiple congenital anomalies (MCAs). CMA analysis was performed in 42 Korean patients who had been diagnosed with unexplained DD, ID, ASDs, and MCAs. Clinically relevant CNVs were discovered in 28 patients. Variants of unknown significance were detected in 13 patients. The diagnostic yield was high (66.7%). CMA is a superior diagnostic tool compared with conventional karyotyping and fluorescent in situ hybridization.

• 대한임상검사과학회지
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• 제39권2호
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• pp.63-67
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• 2007

A ring, monosomy and marker chromosome 13 was found in a 14 months old male with multiple congenital anomalies which suggested the deletion 13 syndrome. He presented development retardation, mental retardation, syndactyly of thumbs, xeroderma, dyspnea, dyslogia and face deformity diagnosed by chromosomal analysis using synchronized G-banding technique which revealed of 46,XY,r(13)(p13q34)[48]/45,XY,-13[28]/46,XY,-13,+mar[13]. We report this case with a brief review of the correlation between clinical features and the observed 13 polymorphism chromosome.

• Neonatal Medicine
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• 제15권2호
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• pp.200-206
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• 2008

안면 기형, 삼각두, 뇌량 무형성, 감각 신경성 난청, 시각장애, 심기형, 심근병증, 폐동맥 고혈압, 배꼽 탈장과 생식기 기형이 있는 환아에게 동반된 9번 염색체 단완이질염색질 부위의 첨가를 발견하여 9번 염색체 p13 부위의 첨가와 연관된 다발성 기형의 발생을 보고하는 바이다.

• Smart Structures and Systems
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• 제29권1호
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• pp.129-140
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• 2022

The effectiveness of system identification, damage detection, condition assessment and other structural analyses relies heavily on the accuracy and reliability of the measured data in structural health monitoring (SHM) systems. However, data anomalies often occur in SHM systems, leading to inaccurate and untrustworthy analysis results. Therefore, anomalies in the raw data should be detected and cleansed before further analysis. Previous studies on data anomaly detection mainly focused on just single type of data anomaly for denoising or removing outliers, meanwhile, the existing methods of detecting multiple data anomalies are usually time consuming. For these reasons, recognising multiple anomaly patterns for real-time alarm and analysis in field monitoring remains a challenge. Aiming to achieve an efficient and accurate detection for multi-type data anomalies for field SHM, this study proposes a pattern-recognition-based data anomaly detection method that mainly consists of three steps: the feature extraction from the long time-series data samples, the training of a pattern recognition neural network (PRNN) using the features and finally the detection of data anomalies. The feature extraction step remarkably reduces the time cost of the network training, making the detection process very fast. The performance of the proposed method is verified on the basis of the SHM data of two practical long-span bridges. Results indicate that the proposed method recognises multiple data anomalies with very high accuracy and low calculation cost, demonstrating its applicability in field monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권4호
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• pp.671-690
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• 2010

The continuous growth of attacks in the Internet causes to generate a number of rules in security devices such as Intrusion Prevention Systems, firewalls, etc. Policy anomalies in security devices create security holes and prevent the system from determining quickly whether allow or deny a packet. Policy anomalies exist among the rules in multiple security devices as well as in a single security device. The solution for policy anomalies requires complex and complicated algorithms. In this paper, we propose a new method to remove policy anomalies in a single security device and avoid policy anomalies among the rules in distributed security devices. The proposed method classifies rules according to traffic direction and checks policy anomalies in each device. It is unnecessary to compare the rules for outgoing traffic with the rules for incoming traffic. Therefore, classifying rules by in-out traffic, the proposed method can reduce the number of rules to be compared up to a half. Instead of detecting policy anomalies in distributed security devices, one adopts the rules from others for avoiding anomaly. After removing policy anomalies in each device, other firewalls can keep the policy consistency without anomalies by adopting the rules of a trusted firewall. In addition, it blocks unnecessary traffic because a source side sends as much traffic as the destination side accepts. Also we explain another policy anomaly which can be found under a connection-oriented communication protocol.

• Neonatal Medicine
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• 제16권1호
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• pp.89-93
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• 2009

저자들은 당뇨병이 임신 초기부터 진단된 산모에서 출생한 신생아에서 작은 악안면, 우측소이증, 오른손의 손가락다지증, 오른쪽 눈물샘의 위치 이상이 동반된 상검판 기형, 근위부 공장폐쇄증을 지닌 사례와 수술 후 공장 부위의 협착증을 중재적 방사선 시술로 치료하였기에 문헌 고찰과 함께 보고하는 바이다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.236-241
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• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• 대한원격탐사학회지
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• 제17권2호
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• pp.183-188
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• 2001

The NOAA AVHRR remotely sensed SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the sea near korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple SST images, all of images must be consistent exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which automatically detects cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$3$^{\circ}C$ as a criterion of SST anomalies). The remotely sensed SST data are tuned by comparing remotely sensed data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel and the SST anomalies are studied by statistical method. It was found that the SST anomalies are rather persistent for one or two months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST. In the Markov lprocess model of SST anomalies, autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. The developed algorithm with automatic cloud pixel detection and rediction of future SST is expected to be incorporated to the operational real time service of SST around Korea.