• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.12-21
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• 2012

IEEE 802.11 MAC protocol standard, DCF(CSMA/CA), is originally designed to ensure the fair channel access between mobile nodes sharing the local wireless channel. It has been, however, revealed that some misbehavior nodes transmit more data than other nodes through artificial means in hot spot area spreaded rapidly. The misbehavior nodes may modify the internal process of their MAC protocol or interrupt the MAC procedure of normal nodes to achieve more data transmission. This problem has been referred to as a selfish node problem and almost literatures has proposed methods of analyzing the MAC procedures of all mobile nodes to detect the selfish nodes. However, these kinds of protocol analysis methods is not effective at detecting all kinds of selfish nodes enough. This paper address this problem of detecting selfish node using Tsallis-Entropy which is a kind of statistical method. Tsallis-Entropy is a criteria which can show how much is the density or deviation of a probability distribution. The proposed algorithm which operates at a AP node of wireless LAN extracts the probability distribution of data interval time for each node, then compares the one with a threshold value to detect the selfish nodes. To evaluate the performance of proposed algorithm, simulation experiments are performed in various wireless LAN environments (congestion level, how selfish node behaviors, threshold level) using ns2. The simulation results show that the proposed algorithm achieves higher successful detection rate.

• Journal of Korean Neurosurgical Society
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• v.48 no.5
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• pp.391-398
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• 2010

Objective : This study was designed to validate the cell trafficking efficiency of the in vivo bioluminescence image (BLI) study in the setting of transplantation of the luciferase expressing bone marrow-derived mesenchymal stem cells (BMSC), which were delivered at each different time after transient middle cerebral artery occlusion (MCAO) in a mouse model. Methods : Transplanting donor BMSC were prepared by primary cell culture from transgenic mouse expressing luciferase (LUC). Transient focal infarcts were induced in 4-6-week-old male nude mice. The experiment mice were divided into five groups by the time of MSC transplantation : 1) sham-operation group, 2) 2-h group, 3) 1-day group, 4) 3-day group, and 5) 1-week group. BLI for detection of spatial distribution of transplanted MSC was performed by detecting emitted photons. Migration of the transplanted cells to the infarcted area was confirmed by histological examinations. Differences between groups were evaluated by paired t-test. Results : A focal spot of bioluminescence was observed at the injection site on the next day after transplantation by Signal intensity of bioluminescence. After 4 weeks, the mean signal intensities of 2-h, 1-day, 3-day, and 1-week group were $2.6{\times}10^7{\pm}7.4{\times}10^6$. $6.1{\times}10^6{\pm}1.2{\times}10^6$, $1.7{\times}10^6{\pm}4.4{\times}10^5$, and $8.9{\times}10^6{\pm}9.5{\times}10^5$, respectively. The 2-h group showed significantly higher signal intensity (p<0.01). The engrafted BMSC showed around the infarct border zones on immunohistochemical examination. The counts of LUC-positive cells revealed the highest number in the 2-h group, in agreement with the results of BLI experiments (p<0.01). Conclusion : In this study, the results suggested that the transplanted BMSC migrated to the infarct border zone in BLI study and the higher signal intensity of LUC-positive cells seen in 2 hrs after MSC transplantation in MCAO mouse model. In addition, noninvasive imaging in real time is an ideal method for tracking stem cell transplantation. This method can be widely applied to various research fields of cell transplantation therapy.

• Research in Plant Disease
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• v.13 no.1
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• pp.71-73
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• 2007

Field disease incidences of squash virus diseases in Jeonnam province were estimated to be 76.1% and of delayed planting on August-September (retarding culture) and on February-March (semi-forcing culture) on glass house were 55.0% and 0%, respectively, in 2000. Disease incidences of individual squash plant within a field were 100% and 3.6%, respectively, in wild culture and retarding culture. Total of 61 samples suspected to be infected with viruses were collected in 2000 and tested by RT-PCR using specific oligonulceotide primer sets designed for the detection of Cucumber green mottle mosaic virus (CGMMV), Kyuri green mottle mosaic virus (KGMMV), Zucchini yellow mosaic virus (ZYMV), Papaya ring spot virus (PRSV), Watermelon mosaic virus (WMV), and Cucumber mosaic virus (CMV). Each specific primer set for WMV, ZYMV, and PRSV amplified expected size of DNA fragments from 16, 10, and 2 samples in wild culture, respectively. Double or triple infection were observed in 7 samples tested. In contrast, each specific primer set for WMV, ZYMV, and PRSV confirmed virus infection from 7, 6, and 6 samples, respectively, in samples collected from semi-forcing culture. Double infection of WMV and PRSV was observed in only one sample. However, no DNA fragment was amplified from RT-PCR using CGMMV, KGMMV, and CMV specific oligonucleotide primer sets indicating no CGMMV, KGMMV, or CMV infection in squash fields in Jeonnam province in 2000.

• Journal of the Korean Society of Radiology
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• v.9 no.6
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• pp.369-374
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• 2015

In this study we proposed a texture feature analysis algorithm that distinguishes between a normal image and a diseased image using CT images of some brain hemorrhage patients, and generates both Eigen images and test images which can be applied to the proposed computer aided diagnosis system in order to perform a quantitative analysis for 6 parameters. And through the analysis, we derived and evaluated the recognition rate of CT images of brain hemorrhage. As the results of examining over 40 example CT images of brain hemorrhage, the recognition rates representing a specific texture feature-value are as follows: some appeared to be as high as 100% including average gray level, average contrast, smoothness, and Skewness while others showed a little low disease recognition rate: 95% for uniformity and 87.5% for entropy. Consequently, based on this research result, if a software that enables a computer aided diagnosis system for medical images is developed, it will lead to the availability for the automatic detection of a diseased spot in CT images of brain hemorrhage and quantitative analysis. And they can be used as computer aided diagnosis data, resulting in the increased accuracy and the shortened time in the stage of final reading.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.581-584
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• 2009

Recently, the cameras which used for observation are installed in children protection area and local crime prevention area in order to protect life and property and by its work being recognized and are installed more. Normal cameras have cost problem to observe multiple area and detail, because they can observe only one place. PTZ camera can observe multiple area by moving focus by schedule or remote control, but it can't automatically move the focus of it to the place where event occurred, because it can't recognize the place. In this study, we can monitor multiple area effectively, by installing a wireless sensor node equipped with temperature, lighting, gas and human detection sensor to each area, to monitor many place low-price and actively and to move the focus of PTZ camera to preset position, and send recorded video to the user, when the various sensor data received from wireless sensors in observation area are to be determined abnormal by analyzing. In addition, at night we can record a scene using infrared, but to reduce power consumption of lighting system which are installed to improve resolution, it supplies power to the lighting system when event occurred. So we were able to implement low power green monitoring system.

• Korean Journal of Optics and Photonics
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• v.28 no.3
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• pp.116-121
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• 2017

In this paper, a Raman spectrometer is designed to detect chemicals contaminating the ground. The system is based on Raman spectroscopy, which is spectral analysis of scattered light from chemicals, induced by a laser. The system consists of a transmitting-optics module with a laser to induce Raman-scattered light from the sample, a receiving-optics module to collect the scattered light, and a spectrograph to separate the collected light into a wavelength spectrum. The telescope, a part of the receiving-optics module, is designed to produce a focal spot in the same position for variable measurement distances using the code V simulator, considering the distance change between the system and the road. The Raman spectra of 12 chemicals on a glass surface and on a concrete sample were measured. Intensity differences between the Raman spectra acquired on a glass surface and on a concrete sample were observed, but the characteristics of the spectra according to the chemicals on them were similar. Additionally, the Raman spectrum of PTFE (polytetrafluoroethylene) was measured at various distances. The measured and simulated optical throughputs were similar. In conclusion, it is confirmed that with this system the Raman spectrum can be measured, irrespective of the distance change.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.04a
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• pp.54-54
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• 2019

Apple (Malus domestica) is one of the most economically important fruits in Korea. But virus infection has decreased sustainable production of apple and caused the serious problems such as yield loss and poor fruit quality. Virus or viroid infection including Apple chlorotic leaf spot virus (ACLSV), Apple stem pitting virus (ASPV), Apple stem grooving virus (ASGV), Apple mosaic virus (ApMV) and Apple scar skin viroid (ASSVd) has been also reported in Korea. In many cases, apple is infected with virus and viroid with no specific symptoms, the damage caused by the virus are unaware significantly. In our research, we tried to eliminate viruses in the rootstock for the disease-free seedlings of the apple dwarfing rootstock M.9 and M.26. The method of virus elimination was meristem culture, heat($37^{\circ}C$, 6weeks) treatment and chemistry($Ribavirin^{(R)}$) treatment. The analytical methods commonly used for the detection of virus is Enzyme-linked Immuno-Sorbent Assay(ELlSA) and Reverse Transcription-polymerase Chain Reaction(RT-PCR). RT-PCR method was more 30% sensitive than ELISA method. Efficiency of method eliminate virus appeared meristem method > heat treatment > chemistry treatment. The higher acquisition rate of disease-free seedlings is 30~40% on meristem treatment. In meristem treatment, the apple dwarfing rootstock M.9 gained infection ratio of ACLSV, ASPV and ASGV were 45%, 60% and 50% respectively. In the apple dwarfing rootstock M.26, infection ratio of ACLSV, ASPV and ASGV were 40%, 55%, 55%, respectively. Based on our results, it was found that most effective method of disease-free seedlings apple dwarfing rootstocks was by meristem treatment than heat method and chemistry treatment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.77-83
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• 2020

The heat treatment facility is in a situation where the scope of application of the remote IOT system is expanding due to the harsh environment caused by high heat and long working hours among the root industries. In this heat treatment process environment, the IOT middleware is required to play a pivotal role in interpreting, managing and controlling data information of IoT devices (sensors, etc.). Until now, the system controlled by the heat treatment remotely was operated with the command of the operator's batch system without overall monitoring of the site situation. However, for the safety and precise control of the heat treatment facility, it is necessary to control various sensors and recognize the surrounding work environment. As a solution to this, the heat treatment safety support system presented in this paper proposes a support system that can detect the access of the work manpower to the heat treatment furnace through thermal image detection and operate safely when ordering work from a remote location. In addition, an OPEN CV-based deterioration analysis system using DNN deep learning network was constructed for faster and more accurate recognition than general fixed hot spot monitoring-based thermal image analysis. Through this, we would like to propose a system that can be used universally in the heat treatment environment and support the safety management specialized in the heat treatment industry.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.85-96
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• 2023

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.203-217
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• 2024

The Land Use, Land-Use Change and Forestry (LULUCF) sector of the National Greenhouse Gas Inventory is crucial for obtaining data on carbon sinks, necessitating accurate estimations. This study analyzes cases of countries applying the LULUCF sector at the Tier 3 level to propose enhanced methodologies for carbon sink estimation. In nations like Japan and Western Europe, satellite spatial information such as SPOT, Landsat, and Light Detection and Ranging (LiDAR)is used alongside national statistical data to estimate LULUCF. However, in Korea, the lack of land use change data and the absence of integrated management by category, measurement is predominantly conducted at the Tier 1 level, except for certain forest areas. In this study, Space-borne LiDAR Global Ecosystem Dynamics Investigation (GEDI) was used to calculate forest canopy heights based on Relative Height 100 (RH100) in the cities of Icheon, Gwangju, and Yeoju in Gyeonggi Province, Korea. These canopy heights were compared with the 1:5,000 scale forest maps used for the National Inventory Report in Korea. The GEDI data showed a maximum canopy height of 29.44 meters (m) in Gwangju, contrasting with the forest type maps that reported heights up to 34 m in Gwangju and parts of Icheon, and a minimum of 2 m in Icheon. Additionally, this study utilized Ordinary Least Squares(OLS)regression analysis to compare GEDI RH100 data with forest stand heights at the eup-myeon-dong level using ArcGIS, revealing Standard Deviations (SDs)ranging from -1.4 to 2.5, indicating significant regional variability. Areas where forest stand heights were higher than GEDI measurements showed greater variability, whereas locations with lower tree heights from forest type maps demonstrated lower SDs. The discrepancies between GEDI and actual measurements suggest the potential for improving height estimations through the application of high-resolution remote sensing techniques. To enhance future assessments of forest biomass and carbon storage at the Tier 3 level, high-resolution, reliable data are essential. These findings underscore the urgent need for integrating high-resolution, spatially explicit LiDAR data to enhance the accuracy of carbon sink calculations in Korea.