• Korean Chemical Engineering Research
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• v.50 no.6
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• pp.980-987
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• 2012

Nonpoint source pollution causes leaks and overtopping, depending on the state of the sewer network as well as aggravates the pollution load of the aqueous water system as it is introduced into the sewer by wash-off. According, the need for efficient sewer monitoring system which can manage the sewage flowrate, water quality, inflow/infiltration and overflow has increased for sewer maintenance and the prevention of environmental pollution. However, the sewer monitoring is not easy since the sewer network is built in underground with the complex nature of its structure and connections. Sewer decontamination mechanism as well as pipe network monitoring and fault diagnosis of water network system on system analysis proposed in this study. First, the pollution removal pattern and behavior of contaminants in the sewer pipe network is analyzed by using sewer process simulation program, stormwater & wastewater management model for expert (XP-SWMM). Second, the sewer network fault diagnosis was performed using the multivariate statistical monitoring to monitor water quality in the sewer and detect the sewer leakage and burst. Sewer decontamination mechanism analysis with static and dynamic state system results showed that loads of total nitrogen (TN) and total phosphorous (TP) during rainfall are greatly increased than non-rainfall, which will aggravate the pollution load of the water system. Accordingly, the sewer outflow in pipe network is analyzed due to the increased flow and inflow of pollutant concentration caused by rainfall. The proposed sewer network monitoring and fault diagnosis technique can be used effectively for the nonpoint source pollution management of the urban watershed as well as continuous monitoring system.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1353-1366
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• 2015

These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1266-1271
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• 2022

Cats have strong wildness so they have a characteristic of hiding diseases well. The disease may have already worsened when the guardian finds out that the cat has a disease. It will be of great help in treating the cat's disease if the owner can recognize the cat's polydipsia, polyuria, and frequent urination more quickly. In this paper, 1) Efficient version of DeepLabCut for pose estimation, 2) YOLO v4 for object detection, 3) LSTM is used for behavior prediction, and 4) BoT-SORT is used for object tracking running on an artificial intelligence device. Using artificial intelligence technology, it predicts the cat's next, polyuria and frequency of urination through the analysis of the cat's behavior pattern from the home CCTV video and the weight sensor of the water bowl. And, through analysis of cat behavior patterns, we propose an application that reports disease prediction and abnormal behavior to the guardian and delivers it to the guardian's mobile and the server system.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.11-19
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• 2004

Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50％ or the relative power of theta waves more than 23％ was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3％ and Cohen's Kappa was 0.586 (p＜0.01). A significant portion (32％) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70％. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3％ in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.

• Journal of Internet Computing and Services
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• v.18 no.3
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• pp.71-83
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• 2017

In recent years, by utilizing the greatest strengths of process mining, the various research activities have been actively progressed to use auditing work of business organization. On the other hand, there is insufficient research on systematic and efficient analysis of massive data generated under big data environment using process mining, and proactive monitoring of risk management from audit side, which is one of important management activities of corporate organization. In this study, we intend to realize Hadoop-based internal audit integrated real-time monitoring system in order to detect the abnormal symptoms in prevent accidents in advance. Through the integrated real-time monitoring system for purchasing audit, we intend to realize strengthen the delivery management of purchasing materials ordered, reduce cost of purchase, manage competitive companies, prevent fraud, comply with regulations, and adhere to internal control accounting system. As a result, we can provide information that can be immediately executed due to enhanced purchase audit integrated real-time monitoring by analyzing data efficiently using process mining via Hadoop-based systems. From an integrated viewpoint, it is possible to manage the business status, by processing a large amount of work at a high speed faster than the continuous monitoring, the effectiveness of the quality improvement of the purchase audit and the innovation of the purchase process appears.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.58-68
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• 2011

As part of basic studies of monitoring carbon dioxide ($CO_2$) storage using electrical and seismic surveys, laboratory experiments have been conducted to measure resistivity and P-wave velocity changes due to the injection of $CO_2$ into water-saturated sandstone. The rock sample used is a cylinder of Berea sandstone. $CO_2$ was injected under supercritical conditions (10 MPa, $40^{\circ}C$). The experimental results show that resistivity increases monotonously throughout the injection period, while P-wave velocity and amplitude decrease drastically due to the supercritical $CO_2$ injection. A reconstructed P-wave velocity tomogram clearly images $CO_2$ migration in the sandstone sample. Both resistivity and seismic velocity are useful for monitoring $CO_2$ behaviour. P-wave velocity, however, is less sensitive than resistivity when the $CO_2$ saturation is greater than ~20%. The result indicates that the saturation estimation from resistivity can effectively complement the difficulty of $CO_2$ saturation estimations from seismic velocity variations. By combining resistivity and seismic velocity we were able to estimate $CO_2$ saturation distribution and the injected $CO_2$ behaviour in our sample.

• Korean Journal of Remote Sensing
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• v.34 no.2_2
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• pp.313-326
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• 2018

This paper introduces core techniques on ship detection and tracking based on a compact HF radar platform which is necessary to establish a wide-area surveillance network. Currently, most HF radar sites are primarily optimized for observing sea surface radial velocities and bearings. Therefore, many ship detection systems are vulnerable to error sources such as environmental noise and clutter when they are applied to these practical surface current observation purpose systems. In addition, due to Korea's geographical features, only compact HF radars which generates non-uniform antenna response and has no information on target information are applicable. The ship detection and tracking techniques discussed in this paper considers these practical conditions and were evaluated by real data collected from the Yellow Sea, Korea. The proposed method is composed of two parts. In the first part, ship detection, a constant false alarm rate based detector was applied and was enhanced by a PCA subspace decomposition method which reduces noise. To merge multiple detections originated from a single target due to the Doppler effect during long CPIs, a clustering method was applied. Finally, data association framework eliminates false detections by considering ship maneuvering over time. According to evaluation results, it is claimed that the proposed method produces satisfactory results within certain ranges.

• Journal of Periodontal and Implant Science
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• v.35 no.2
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• pp.413-426
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• 2005

수직 치근파절은 특이성을 나타내지 않기 때문에 치과의사가 정확한 진단을 하기 어렵다. 따라서 수직 치근파절의 임상적 특징, 진단적 증상을 파악하여 향후 근관치료된 치아나 치료되지 않은 치아에서 수직 치근파절의 유발인자와의 관련성 및 고찰을 통해 수직 치근파절의 예방 및 치료에 응용할 수 있을 것으로 생각된다. 연구대상은 조선대학교 부속치과병원 치주과에 내원한 환자 중 최근 2년간 144명의 환자에서 근관치료를 받았거나 받지 않았던 치아 중 임상적 및 방사선학적으로 수직 치근파절로 진단된 156개의 증례를 대상으로 하였다. 모든 불확실한 증례에서 수직 지근파절의 최종 진단은 외과적 탐지를 통해 이루어졌고, 금이 간 치아와 관련될 수 있는 치근파절의 증례의 경우는 제외되었다. 근관치료된 치아와 치료되지 않은 치아, 환자의 나이와 성별, 치아종류 및 파절된 치근부위, 자각증상의 유무를 기준으로 각각의 수치와 백분율로 분류하였다. 수직 치근파절의 증상과 증후별로 분류하였으며, 진단방법에 의한 분류, 치료방법에 따른 분류, 근관 치료 후 수직 치근파절이 발생한 기간에 따른 분류를 시행하고 통계분석을 하여 다음과 같은 결과를 얻었다. 1. 근관치료를 받지 않았던 치아의 수직 치근파절의 발생율은 58%였다. 2. 성별에 따른 발생률에 있어서 남성의 호발양상을 나타내었다. 3. 근관치료된 치아에 있어서 치료되지 않은 치아에 비해 호발연령이 낮았다. 4. 전치부의 수직 치근파절은 관찰되지 않았으며 특히, 강한 교합력을 필요로 히는 구치부에서의 높은 발생율을 나타냈다. 5. 수직 치근파절의 가장 주된 증상 및 증후는 깊은 치주낭 깊이였다. 6. 근관 치료 후 수직 치근파절이 발생한 기간은 평균 5.7년이었다. 7. 다수 증례에 있어서 3개 이하의 결손치를 가졌고, 자각증상이 나타났다. 이상의 결괴에서 한국인에 있어서 근관치료를 받지 않은 치아의 수직 치근파절은 드문 현상이 아님을 알 수 있었고 남성과 구치부에 있어서의 높은 발생율을 알 수 있었다. 그 이유로는 강한 교합력, 딱딱한 음식의 저작습관, 치조골 흡수에 따른 낮은 저항성, 골 유연성의 저하 등으로 여겨진다. 그러나, 수직 치근파절은 아직까지 정확한 진단을 내리기는 여전히 어려운 상태이며, 이를 위한 다양한 진단방법 및 더 나은 연구가 필수적이라 하겠다. 그리고, 향후 보다 많은 증례에 대한 분석, 치주질환에 이환되지 않은 경우의 분석, 치료 후 생존 기간에 대한 고찰 등도 필요하리라 사료된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.48-63
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• 2015

In this study, we introduce various hyperspectral data processing techniques for the monitoring of shallow and coastal waters to enlarge the application range and to improve the accuracy of the end results in Korea. Unlike land, more accurate atmospheric correction is needed in coastal region showing relatively low reflectance in visible wavelengths. Sun-glint which occurs due to a geometry of sun-sea surface-sensor is another issue for the data processing in the ocean application of hyperspectal imagery. After the preprocessing of the hyperspectral data, a semi-analytical algorithm based on a radiative transfer model and a spectral library can be used for bathymetry mapping in coastal area, type classification and status monitoring of benthos or substrate classification. In general, semi-analytical algorithms using spectral information obtained from hyperspectral imagey shows higher accuracy than an empirical method using multispectral data. The water depth and quality are constraint factors in the ocean application of optical data. Although a radiative transfer model suggests the theoretical limit of about 25m in depth for bathymetry and bottom classification, hyperspectral data have been used practically at depths of up to 10 m in shallow and coastal waters. It means we have to focus on the maximum depth of water and water quality conditions that affect the coastal applicability of hyperspectral data, and to define the spectral library of coastal waters to classify the types of benthos and substrates.