• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.328-333
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• 2012

Current differential GPS (DGPS) system consists of reference station (RS), integrity monitor (IM), and control station (CS). The RS computes the pseudorange corrections (PRC) and generates the RTCM messages for broadcasting. The IM receives the corrections from the RS broadcasting and verifies that the information is within tolerance. The CS performs realtime system status monitoring and control of the functional and performance parameters. The primary function of a DGPS integrity monitor is to verify the correction information and transmit feedback messages to the reference station. However, the current algorithms for integrity monitoring have the limitations of integrity monitor functions for satellite outage or anomalies. Therefore, this paper focuses on the detection and identification methods of satellite anomalies for maritime DGPS RSIM. Based on the function analysis of current DGPS RSIM, it first addresses the limitation of integrity monitoring functions for DGPS RSIM, and then proposes the detection and identification method of satellite anomalies. In addition, it simulates an actual GPS clock anomaly case using a GPS simulator to analyze the limitations of the integrity monitoring function. It presents the brief test results using the proposed methods for detection and identification of satellite anomalies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.647-648
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• 2009

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.41-47
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• 2012

MANET has vulnerable structure on security owing to structural characteristics as follows. MANET consisted of moving nodes is that every nodes have to perform function of router. Every node has to provide reliable routing service in cooperation each other. These properties are caused by expose to various attacks. But, it is difficult that position of environment intrusion detection system is established, information is collected, and particularly attack is detected because of moving of nodes in MANET environment. It is not easy that important profile is constructed also. In this paper, conformal predictor - support vector machine(CP-SVM) based intrusion detection technique was proposed in order to do more accurate and efficient intrusion detection. In this study, IDS-agents calculate p value from collected packet and transmit to cluster head, and then other all cluster head have same value and detect abnormal behavior using the value. Cluster form of hierarchical structure was used to reduce consumption of nodes also. Effectiveness of proposed method was confirmed through experiment.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.32-39
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• 2023

This paper provides a comprehensive overview of UAV classification, tracking, and detection, offering researchers a clear understanding of these fundamental concepts. It elucidates how classification categorizes UAVs based on attributes, how tracking monitors real-time positions, and how detection identifies UAV presence. The interconnectedness of these aspects is highlighted, with detection enhancing tracking and classification aiding in anomaly identification. Moreover, the paper emphasizes the relevance of simulations in the context of drones and UAVs, underscoring their pivotal role in training, testing, and research. By succinctly presenting these core concepts and their practical implications, the paper equips researchers with a solid foundation to comprehend and explore the complexities of UAV operations and the role of simulations in advancing this dynamic field.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.853-861
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• 2010

Experimental conditions are set with environmental factors which can affect ship navigation. In FTS simulation, infinite simulation can be theoretically tested with no time constraint but the simulated result with the same experimental condition is repeated due to mathematical model. RTS simulation can give more resonable results but costs at lest 30 minutes for only experimental time. The mixture of two simulation methods using probability density function has been proposed: some of experimental conditions in which ship-handling is most difficult are selected with FTS and are tested in RTS. It has drawback that it does not consider the navigation route but aggregated track index. In this paper, anomaly detection approach is suggested to select some experimental conditions of FTS simulation which are most difficult in ship-handling during the navigation route. An empirical result has been shown.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.411-418
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• 2020

In the field of information security, IDS(Intrusion Detection System) is normally classified in two different categories: signature-based IDS and anomaly-based IDS. Many studies in anomaly-based IDS have been conducted that analyze network traffic data generated in cyberspace by machine learning algorithms. In this paper, we studied pre-processing methods to overcome performance degradation problems cashed by rare classes. We experimented classification performance of a Machine Learning algorithm by reconstructing data set based on rare classes and semi rare classes. After reconstructing data into three different sets, wrapper and filter feature selection methods are applied continuously. Each data set is regularized by a quantile scaler. Depp neural network model is used for learning and validation. The evaluation results are compared by true positive values and false negative values. We acquired improved classification performances on all of three data sets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.103-111
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• 2023

This paper proposes a new data correction technique that transforms anomalies in time series data into normal values. With the recent development of IT technology, a vast amount of time-series data is being collected through sensors. However, due to sensor failures and abnormal environments, most of time-series data contain a lot of anomalies. If we build a predictive model using original data containing anomalies as it is, we cannot expect highly reliable predictive performance. Therefore, we utilizes the LSTM-GAN model to detect anomalies in the original time series data, and combines DTW (Dynamic Time Warping) and GAN techniques to replace the anomaly data with normal data in partitioned window units. The basic idea is to construct a GAN model serially by applying the statistical information of the window with normal distribution data adjacent to the window containing the detected anomalies to the DTW so as to generate normal time-series data. Through experiments using open NAB data, we empirically prove that our proposed method outperforms the conventional two correction methods.

• Childhood Kidney Diseases
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• v.1 no.1
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• pp.67-72
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• 1997

Purpose : Congenital urinary tract anomaly is the most common anomaly in the childhood and progress to chronic renal failure and growth retardation. Therefore, early diagnosis arid treatment of urinary tract anomaly are important. Method : We reviewed medical records of 124 patients who had urinary tract anomalies on radiologic studies from Jan. 1986 to Dec. 1996. We analyzed demography and clinical characteristics of urinary tract anomalies. Results : 1) The age distributions were as follows ; 61 cases of 124 patients (49%) were under 1 year, 11 cases (8.8%) from 1 to 3 years, 20 cases (16%) from 4 to 6 years, 10 cases (8%) from 7 to 9 years, 9 cases (7.2%) from 10 to 12 years, 10 cases (8%) from 13 to 15 years, and 3 cases (2.4%) from 16 to 18 years. 2) Chief complaints in patients with urinary tract anomalies were fever, flank pain, prenatally diagnosed hydronephrosis, abdominal mass, dysuria and hematuria. 3) Of 124 patients, 68 cases(54.8%) were combined with urinary tract infection, and main causative organism was E.coli, and the most frequently associated anomaly was vesicoureteral reflux. 4) Most of the urinary tract anomalies were VUR, UPJ obstruction, congenital hydronephrosis and double ureter in order of sequence. 5) Whereas the frequency of simple urinary tract anomaly was 87.9%, that of complex anomaly was 12%. 6) Operative corrections were needed in 47 cases and 7 cases were progressed to renal insufficiency. Conclusion : We emphasize that early detection of urinary tract anomaly, appropriate treatment and regular follow-up are needed.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.95-101
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• 2019

Entering the era of the 4^th Industrial Revolution and the Internet of Things, various services are growing rapidly, and various researches are actively underway. Among them, research on abnormal behaviors on various devices that are being used in the IoT is being conducted. In a hyper-connected society, the damage caused by one wrong device can have a serious impact on the various connected systems. In this paper, We propose a technique to cope with the problem that the threats caused by various abnormal behaviors such as anti-debugging scheme, anomalous process detection method and back door detection method on how to increase the safety of the device and how to use the device and service safely in such IoT environment.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.12a
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• pp.15-25
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• 2007

Gravity method could be one of the most effective tool for evaluating the soundness of basement which is directly correlated with density and its variations. Moreover, Gravimeter is easy to handle and strong to electromagnetic noises. But, gravity anomaly due to the target structures in engineering and environmemtal applications are too small to detect, comparing to the external changes, such as, elevation, topography, and regional geological variations. Gravity method targeting these kinds of small anomaly sources with high precision usually called microgravity. Microgravimetry with precision and accuracy of few ${\mu}Gal$, can be achieved by the recent high-resolution gravimeter, careful field acquisition, and sophisticated processing, analysis, and interpretation routines. This paper describes the application of the microgravity, such as, density structure of a rock fill dam, detection of abandoned mine-shaft, detection and mapping of karstic cavities in limestone terrains, and time-lapse gravity for grout monitoring. The case studies show how the gravity anomalies detect the location of the targets and reveal the geologic structure by mapping density distributions and their variations.