• Childhood Kidney Diseases
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• v.7 no.2
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• pp.189-196
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• 2003

Purpose : Ureteral duplication is a common urologic anomaly and early diagnosis may prevent irreversible renal damage. We thus aimed to evaluate the benefits of prenatal sonography in early detection. Methods : We retrospectively studied 55 children with duplicated systems who were admitted to Severance Hospital, Yonsei University, Seoul, Korea from January 1998 to July 2003. Results : The mean age at diagnosis was 2.3 years old. 89% of the children had complete duplicated ureter. 47% of the children visited the hospital with an initial complaint of abnormal prenatal sonographic findings. Among these patients, 70.8% had DMSA defects. The mean differential renal function(DRF) in the DMSA scan was 48.2% in the group diagnosed prenatally. In the postnatally-diagnosed group, DMSA defects were found in 67.7% patients and the mean DRF was 45.5%. Conclusion : In comparison with the past studies, the mean age at diagnosis is becoming younger, and the proportion of abnormal prenatal sonography as an initial complaint larger. Other clinical manifestations were similar. The difference of the renal damage between the prenatally diagnosed group and the postnatally diagnosed group was not statistically significant. A multi-center study may help to prove the importance of prenatal sonography in early diagnosis and treatment of ureteral duplication. (J Korean Soc Pediatr Nephrol 2003;7:189-196)

• Fire Science and Engineering
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• v.31 no.5
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• pp.44-52
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• 2017

This paper is based on a study of the response characteristics of photoelectric type smoke detector chambers according to dust color. Due to an amendment to the Fire Safety Codes to automatic fire alarm systems and visual alarm device, the installation of indoor smoke detectors has become mandatory, but in Korea there is still insufficient research on the non-operation or false alarms that could arise in indoor environments by indoor dust and other environmental conditions etc. In light of this, for this study, research was conducted on the indoor adaptability of smoke detector under various colors of fiber dust that were judged to occur most frequently in among the common indoor dust, photoelectric smoke detector with the lattice-type smoke detection chamber that the smoke detector which is most popular in the country was used, and four colors of fiber dust (brown, white, gray and black) were used the test dusts for carrying out dust and sensitivity testing. Also, the voltage of the photocell part of the smoke chamber was measured, and the scattering phenomenon in the chamber was observed. The result of the testing showed that all four dust types were suitable for dust and sensitivity testing under conditions of pollution A. Yet, there were occasions, at pollution B or C, where the brown, white and gray dust would cause fail alarm during operation testing. And black dust was confirmed to cause non-operation during operation testing. In the case of brown and white dust, the voltage measurement result of the photocell part of the smoke chamber confirmed that the voltage increases as the pollution level increases, and in the case of gray and black dust, the voltage decreases.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.7
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• pp.221-228
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• 2020

Part-of-Speech (POS) tagged corpus is a collection of electronic text in which each word is annotated with a tag as the corresponding POS and is widely used for various training data for natural language processing. The training data generally assumes that there are no errors, but in reality they include various types of errors, which cause performance degradation of systems trained using the data. To alleviate this problem, we propose a novel method for detecting errors in the existing POS tagged corpus using the classifier of XGBoost and cross-validation as evaluation techniques. We first train a classifier of a POS tagger using the POS-tagged corpus with some errors and then detect errors from the POS-tagged corpus using cross-validation, but the classifier cannot detect errors because there is no training data for detecting POS tagged errors. We thus detect errors by comparing the outputs (probabilities of POS) of the classifier, adjusting hyperparameters. The hyperparameters is estimated by a small scale error-tagged corpus, in which text is sampled from a POS-tagged corpus and which is marked up POS errors by experts. In this paper, we use recall and precision as evaluation metrics which are widely used in information retrieval. We have shown that the proposed method is valid by comparing two distributions of the sample (the error-tagged corpus) and the population (the POS-tagged corpus) because all detected errors cannot be checked. In the near future, we will apply the proposed method to a dependency tree-tagged corpus and a semantic role tagged corpus.

• Korean Journal of Remote Sensing
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• v.14 no.4
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• pp.376-391
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• 1998

Images from satellites will have 1 to 3 meter ground resolution and will be very useful for analyzing current status of earth surface. An image processing system named GeoWatch with more intelligent image processing algorithms has been designed and implemented to support the detailed analysis of the land surface using high-resolution satellite imagery. The GeoWatch is a valuable tool for satellite image processing such as digitizing, geometric correction using ground control points, interactive enhancement, various transforms, arithmetic operations, calculating vegetation indices. It can be used for investigating various facts such as the change detection, land cover classification, capacity estimation of the industrial complex, urban information extraction, etc. using more intelligent analysis method with a variety of visual techniques. The strong points of this system are flexible algorithm-save-method for efficient handling of large size images (e.g. full scenes), automatic menu generation and powerful visual programming environment. Most of the existing image processing systems use general graphic user interfaces. In this paper we adopted visual program language for remotely sensed image processing for its powerful programmability and ease of use. This system is an integrated raster/vector analysis system and equipped with many useful functions such as vector overlay, flight simulation, 3D display, and object modeling techniques, etc. In addition to the modules for image and digital signal processing, the system provides many other utilities such as a toolbox and an interactive image editor. This paper also presents several cases of image analysis methods with AI (Artificial Intelligent) technique and design concept for visual programming environment.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.101-116
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• 1995

The fact that the demands on traffic data collection are imposed by economic and safety considerations raisese the question of the potential for complementing existing traffic data collection programs with satellite data. Evaluating and monitoring traffic characteristics is becoming increasingly important as worsening congestion, declining economic situations, and increasing environmental sensitivies are forcing the government and municipalities to make better use of existing roadway capacities. The present system of using automatic counters at selected points on highways works well from a temporal point of view (i.e., during a specific period of time at one location). However, the present system does not cover the spatial aspects of the entire road system (i.e., for every location during specific periods of time); the counters are employed only at points and only on selected highways. This lack of spatial coverage is due, in part, to the cost of the automatic counters systems (fixed procurement and maintenance costs) and of the personal required to deploy them. The current procedure is believed to work fairly well in the aggregate mode, at the macro level. However, at micro level, the numbers are more suspect. In addition, the statistics only work when assuming a certain homogenity among characteristics of highways in the same class, an assumption that is impossible to test whn little or no data is gathered on many of the highways for a given class. In this paper, a remote sensing system as complement of the existing system is considered and implemented. Since satellite imagery with high resolution is not available, digitized panchromatic imagery acquired from an aircraft platform is utilized for initial test of the feasibility and performance capability of remote sensing data. Different levels of imagery resolutions are evaluated in an attempt to determine what vehicle types could be classified and counted against a background of pavement types, which might be expected in panchromatic satellite imagery. The results of a systematic study with three different levels of resolutions (1m, 2m and 4m) show that the panchromat ic reflectances of vehicles and pavements would be distributed so similarly that it would be difficult to classify systematically and analytically remotely sensing vehicles on pavement within panchromatic range. Anaysis of the aerial photographs show that the shadows of the vehicles could be a cue for vehicle detection.

• Food Engineering Progress
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• v.15 no.1
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• pp.75-79
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• 2011

Analytical methods for food antioxidants including ascorbic acid, erythorbic acid, ascorbyl palmitate (AP), and ascorbyl stearate (AS), were validated using high performance liquid chromatography. Validation parameters such as linearity, limit of detection (LOD), limit of quantification (LOQ), and recovery were tested using lard and cider as food model systems. Linearity of ascorbic acid and erythorbic acid were both higher than ($R^2$> 0.99), LOD of these compounds were 0.46 and 0.48 ${\mu}g/mL$, respectively and LOQ were 1.39 and 1.45 ${\mu}g/mL$, respectively. The recovery rates of these compounds were 86.35-94.78% and 84.76-95.02%, respectively. However, the concentration of AP and AS decreased in methanol stock solution. Four other solvents including ethanol, acetonitrile, mixture of methanol and acetonitrile, and mixture of ethanol and acetonitrile were tested to increase the stability of AP and AS under room temperature and refrigerated temperature. Ethanol provided better stability of AP and AS under both room and refrigerated temperature. This study can help to accurately analyze the content of ascorbic acid and its derivatives in processed foods.

• Korean Journal of Breeding Science
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• v.40 no.1
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• pp.26-30
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• 2008

Normal soybean seed contains three lipoxygenase isozymes called L-1, L-2, and L-3, respectively, which are responsible for the generation of undesirable grassy-beany flavors. Simple and effective methods for the detection of lipoxygenase isozymes were developed in soybean seeds. Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) has been tried in separating these isozymes. It was done effectively on 7.5% separating gel and 4.5% stacking gel. However, no reliable method has been developed specifically for separating L-3, L-13 and L-23. Visual judging methods were based on the bleaching activities of lipoxygenase in contact with methylene blue and ${\beta}$-carotene. Sodium linoleate bleaching method was adopted to determine L-1 and L-2. Carotene bleaching and spectrophotometric methods were used to determine L-3. These systems were very rapid within one minute, furthermore only required a small piece of cotyledon (below 10 mg) and the other part could be used for generation advance after analysis. It was demonstrated that 200 seed samples could be analyzed per day by one laboratory assistant. The combination of visual judging methods and electrophoresis is suitable for breeding programs. It took 6.5 hours for analysis of 100 seed samples by one person.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1260-1268
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• 2018

To improve fuel performance and specific characteristics of long storage and moving through fuel systems additives should be added in kerosene type aviation turbine fuel (AVTUR) such as antioxidant, fuel system icing inhibitor (FSII), electric conductivity improvers and so on. The dosage of additives has to be analyzed qualitatively and quantitatively due to inspect the quality of abnormal fuel and distinguish other petroleum products. Multi-dimensional GC-MS (MDGC-MS) with Deans switching technique are applied the determination of antioxidant and FSII, which are added with AVTUR containing complex mixture of hydrocarbons. Antioxidant and FSII in the range of 2.5-20 mg/L was quantitatively and qualitatively analyzed using MDGC-MS and the detection limit was about twice as low as that of the 1-dimensional GC-MS results. The method in this study has been higher peak resolution compared with GC-MS and could be simultaneously analyzed different two additives without sample pre-treatment.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.73-80
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• 2021

In this paper, we propose a packet processing method capable of handling large-capacity traffic over 20Gbps using multi-core and huge page memory approaches. As ICT technology advances, the global average monthly traffic is expected to reach 396 exabytes by 2022. With the increase in network traffic, cyber threats are also increasing, increasing the importance of traffic analysis. Traffic analyzed as an existing high-cost foreign product simply stores statistical data and visually shows it. Network administrators introduce and analyze many traffic analysis systems to analyze traffic in various sections, but they cannot check the aggregated traffic of the entire network. In addition, since most of the existing equipment is of the 10Gbps class, it cannot handle the increasing traffic every year at a fast speed. In this paper, as a method of processing large-capacity traffic over 20Gbps, the process of processing raw packets without copying from single-core and basic SMA memory approaches to high-performance packet reception, packet detection, and statistics using multi-core and NUMA memory approaches suggest When using the proposed method, it was confirmed that more than 50% of the traffic was processed compared to the existing equipment.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.27-32
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• 2020

Along with the aging of the population, the number of dementia patients is increasing, and the social and economic burden is also increasing. Currently, the effective way to manage dementia patients is to identify patients with dementia early. However, in rural and island areas where medical staff are scarce, there is a problem that it is difficult to visit a hospital and get an early examination. Therefore, we propose a remote early detection system for dementia to solve the problems. The remote dementia early diagnosis system is a system that allows a patient to receive examination and treatment from a remote dementia expert using remote medical technology based on real-time image communication. The remote early diagnosis system for dementia consists of a local client system used by medical staff at health centers in the island, an image server that transmits, stores and manages images, and an expert client used by remote dementia experts. The local client subsystem satisfies the current medical law's remote collaboration by allowing the patient to use it with the health center's medical staff. In addition, expert clients are used by dementia experts, and can store/manage patient information, analyze patient history information, and predict the degree of dementia progression in the future.