• Journal of Biomedical Engineering Research
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• v.38 no.6
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• pp.321-329
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• 2017

This paper presents a bone metastasis Detection algorithm on abdominal computed tomography images for early detection using fully convolutional neural networks. The images were taken from patients with various cancers (such as lung cancer, breast cancer, colorectal cancer, etc), and thus the locations of those lesions were varied. To overcome the lack of data, we augmented the data by adjusting the brightness of the images or flipping the images. Before the augmentation, when 70% of the whole data were used in the pre-test, we could obtain the pixel-wise sensitivity of 18.75%, the specificity of 99.97% on the average of test dataset. With the augmentation, we could obtain the sensitivity of 30.65%, the specificity of 99.96%. The increase in sensitivity shows that the augmentation was effective. In the result obtained by using the whole data, the sensitivity of 38.62%, the specificity of 99.94% and the accuracy of 99.81% in the pixel-wise. lesion-wise sensitivity is 88.89% while the false alarm per case is 0.5. The results of this study did not reach the level that could substitute for the clinician. However, it may be helpful for radiologists when it can be used as a screening tool.

• Journal of Pharmacopuncture
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• v.17 no.3
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• pp.40-49
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• 2014

Objectives: The gastric ulcer is a common disorder of the stomach and duodenum. The basic physiopathology of a gastric ulcer results from an imbalance between some endogenous aggressive and cytoprotective factors. This study examined whether Ganoderma lucidum pharmacopuncture (GLP) would provide protection against acute gastric ulcers in rats. Methods: Sprague-Dawley rats were divided randomly into 4 groups of 8 rats each: normal, control, normal saline (NP) and GLP groups. The experimental acute gastric ulcer was induced by using an EtOH/HCl solution and the normal group received the same amount of normal saline instead of ethanol. The NP and the GLP groups were treated once with injections of saline and GLP, respectively. Two local acupoints were used: CV12 (中脘) which is the alarm point of the Stomach Meridian, and ST36 (足三里), which is the sea point of the Stomach Meridian. The stomachs from the rats in each group were collected and analyzed for gross appearance and histology. Also, immunohistochemistry staining for BAX, Bcl-2 and TGF-${\beta}1$ was performed. Results: Histological observations of the gastric lesions in the control group showed comparatively extensive damage of the gastric mucosa and necrotic lesions had penetrated deeply into the mucosa. The lesions were long, hemorrhagic, and confined to the glandular portions. The lesions were measured microscopically by using the clear depth of penetration into the gastric mucosal surface. The length and the width of the ulcer were measured and the inhibition percentage was calculated. Wound healing of the acute gastric ulcer was promoted by using GLP, and significant alterations of indices in gastric mucosa were observed. Such protection was shown by gross appearance, histology and immunohistochemistry staining for BAX, Bcl-2 and TGF-${\beta}1$. Conclusion: These results suggest that GLP administered at CV12 and ST36 can provide significant protection to the gastric mucosa against an ethanol-induced acute gastric ulcer.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.12
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• pp.2175-2185
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• 2000

Respiration rate should be a reasonable state variable for the activated sludge and could be used to simulate the performance of the activated sludge process. Toxic materials are classified into three groups, competitive, noncompetitive and uncompetitive. They increase/decrease the half saturation coefficient or specific growth rate. that means decreasing of the substrate removal capacity. In this research, a pilot-scale activated sludge process was operated under extended aeration method, and a representative noncompetitive inhibitor, acidic wastewater was applied to establish a respirometry-based toxicity model. Using this model. the correlation coefficient between measured and calculated respiration rate was 0.96 when acidic wastewater(pH 3.9~5.5) was introduced continuously to the aeration tank. Even though respiration rate was decreased by toxic effect of acidic wastewater, effluent substrate concentration represented to COD was deteriorated just a little bit. It might be caused by the low ratio of readily biodegradable substrate in the input substrate. Reduction of respiration rate by decreasing of input substrate concentration was much lower than that by acidic wastewater, and hence it was estimated that the possibility of false toxic alarm caused by decreasing of substrate concentration should be low.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.105-117
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• 2010

The topographical depressions in urban areas, the lack in drainage capability, sewage backward flow, road drainage, etc. cause internal inundation, and the increase in rainfall resulting from recent climate change, the rapid urbanization accompanied by economic development and population growth, and the increase in an impervious area in urban areas deteriorate the risk of internal inundation in the urban areas. In this study, the vulnerability of internal inundation in urban areas is analyzed and SWMM model is applied into Oncheoncheon watershed, which represents urban river of Busan, as a target basin. Based on the results, the representative storm sewers in individual sub-catchments is selected and the risk of vulnerability to internal inundation due to rainfall in urban streams is analyzed. In order to analyze the risk and vulnerability of internal inundation, capacity is applied as an index indicating the volume of a storm sewer in the SWMM model, and the risk of internal inundation is into 4 steps. For the analysis on the risk of internal inundation, simulation results by using a SMMM model are compared with the actual inundation areas resulting from localized heavy rain on July 7, 2009 at Busan and comparison results are analyzed to prove the validity of the designed model. Accordingly, probabilistic rainfall at Busan was input to the model for each frequency (10, 20, 50, 100 years) and duration (6, 12, 18, 24hr) at Busan. In this study, it suggests that the findings can be used to preliminarily alarm the possibility of internal inundation and selecting the vulnerable zones in urban areas.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.51-56
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• 2016

In this paper, we propose an Arduino-based plant monitoring system. The proposed system is based on the Arduino platform, using an environmental sensor and a pressure sensor for measuring temperature, humidity and illuminance in order to monitor the state of the environment and the facilities of the plant. Monitoring data are transmitted to a ZigBee coordinator connected to a server through a radio frequency transceiver. When using a pressure sensor and the environment sensor data stored on the host server, checking the pressure in the environment of the plant and equipment is intended to report any alarm status to the administrator. Using a grid line-based key distribution scheme, the authentication node dynamically generates a data key to protect the monitoring information. Applying a ZigBee wireless sensor network does not require additional wiring for the actual implementation of a plant monitoring system. Possible working-environment monitoring of an efficient plant can help analyze the cause of any failure by backtracking the working environment when a failure occurs. In addition, it is easy to expand or add a sensor function using the Arduino platform and an expansion board.

• KIISE Transactions on Computing Practices
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• v.23 no.6
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• pp.371-378
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• 2017

In modern society, awareness of diabetes is growing with an increase in the elderly population and an increase in the incidence of diabetes. In particular, diabetic patients can suddenly develop hypoglycemic shock; therefore, it is important to measure blood glucose periodically. However, self-monitoring blood glucose meters are difficult to carry and it is difficult to manage the value. To solve these problems, the blood glucose measurement system has been developed as a sensor attached to the body or as one of the functions of smart devices, but it has not been commercialized. In this paper, we propose a smart band with a blood glucose measurement function. If a user enters a schedule to measure blood glucose level, such as before/after meals, in the app, he/she can receive a measurement alarm from the band. The user can measure the blood glucose level at any time using the band, and the measured value is transmitted and managed by the app including behavior history such as before/after meals and the time. This will help the user to manage, diagnose and prevent health problems. The system has been tested using two medical device-certified products, and each blood glucose measurement value has been confirmed to be more accurate.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.271-280
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• 2017

In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.

• Food Science and Preservation
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• v.10 no.1
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• pp.28-31
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• 2003

For safe storage of agricultural products in the cold storage house, accurate monitoring of temperature, humidity and gas conditions is necessary. This study was conducted to develop an environmental monitoring and warning system for the cold storage house to improve safety of storage. The system developed in this study is able to monitor temperature, humidity and $CO_2$concentration in the storage house and to send alarm signal to the farmer by telephone and beeper when abnormal conditions have been occurred in the storage house. And the developed system use internet network so we can supervise storage conditions in the home. From the results of the performance test, it was found that the temperature and relative humidity can be controlled within the range of 0.5$^{\circ}C$ and $\pm$2 percent. And farmer's response was fair.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.703-711
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• 2018

Water distribution system (WDS) pipe bursts are caused from excessive pressure, pipe aging, and ground shift from temperature change and earthquake. Prompt detection of and response to the failure event help prevent large-scale service interruption and catastrophic sinkhole generation. To that end, this study proposes a improved Western Electric Company (WECO) method to improve the detection effectiveness and efficiency of the original WECO method. The original WECO method is an univariate Statistical Process Control (SPC) technique used for identifying any non-random patterns in system output data. The improved WECO method multiples a threshold modifier (w) to each threshold of WECO sub-rules in order to control the sensitivity of anomaly detection in a water distribution network of interest. The Austin network was used to demonstrated the proposed method in which normal random and abnormal pipe flow data were generated. The best w value was identified from a sensitivity analysis, and the impact of measurement frequency (dt = 5, 10, 15 min etc.) was also investigated. The proposed method was compared to the original WECO method with respect to detection probability, false alarm rate, and averaged detection time. Finally, this study provides a set of guidelines on the use of the WECO method for real-life WDS pipe burst detection.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.246-252
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• 2016

Since thermal power plant (TPP) equipment is operated under very high pressure and temperature, failures of the equipment give rise to severe losses of life and property. To prevent the losses, fault detection method is, therefore, absolutely necessary to identify abnormal operating conditions of the equipment in advance. In this paper, we present Mahalanobis distance (MD) based fault detection method for steam boiler tube in TPP. In the MD-based method, it is supposed that abnormal data samples are far away from normal samples. Using multivariate samples collected from normal target system, mean vector and covariance matrix are calculated and threshold value of MD is decided. In a test phase, after calculating the MDs between the mean vector and test samples, alarm signals occur if the MDs exceed the predefined threshold. To demonstrate the performance, a failure case due to boiler tube leakage in 200MW TPP is employed. The experimental results show that the presented method can perform early detection of boiler tube leakage successfully.