• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.154-158
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• 1999

Purpose : The purpose of this study was to find the optimum TE value for enhancing $T_2^{*}$ weighting effect and minimizing the SNR degradation and to compare the BOLD effects according to the changes of TE in 1.5T and 3.0T MRI systems. Materials and Methods : Healthy normal volunteers (eight males and two females with 24-38 years old) participated in this study. Each volunteer was asked to perform a simple finger-tapping task (sequential opposition of thumb to each of the other four fingers) with right hand with a mean frequency of about 2Hz. The stimulus was initially off for 3 images and was then alternatively switched on and off for 2 cycles of 6 images. Images were acquired on the 1.5T and 3.0T MRI with the FLASH (fast low angle shot) pulse sequence (TR : 100ms, FA : $20^{\circ}$, FOV : 230mm) that was used with 26, 36, 46, 56, 66, 76ms of TE times in 1.5T and 16, 26, 36, 46, 56, 66ms of TE in 3.0T MRI system. After the completion of scan, MR images were transferred into a PC and processed with a home-made analysis program based on the correlation coefficient method with the threshold value of 0.45. To search for the optimum TE value in fMRI, the difference between the activation and the rest by the susceptibility change for each TE was used in 1.5T and 3.0T respectively. In addition, the functional $T_2^{*}$ map was calculated to quantify susceptibility change. Results : The calculated optimum TE for fMRI was $61.89{\pm}2.68$ at 1.5T and $47.64{\pm}13.34$ at 3.0T. The maximum percentage of signal intensity change due to the susceptibility effect inactivation region was 3.36% at TE 66ms in 1.5T 10.05% at TE 46ms in 3.0T, respectively. The signal intensity change of 3.0T was about 3 times bigger than of 1.5T. The calculated optimum TE value was consistent with TE values which were obtained from the maximum signal change for each TE. Conclusion : In this study, the 3.0T MRI was clearly more sensitive, about three times bigger than the 1.5T in detecting the susceptibility due to the deoxyhemoglobin level change in the functional MR imaging. So the 3.0T fMRI I ore useful than 1.5T.

• Journal of Korean Ophthalmic Optics Society
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• v.20 no.3
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• pp.377-384
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• 2015

Purpose: On this study, we measured and compared the dynamic stereoacuity by two-rods test (Howard-Dolman Test) and three-rods test. And we analyzed the correlation between PD and refractive error with dynamic stereoacuity. Methods: Dynamic stereoacuity of two-rods test and three-rods test at 2.5 m distance for 93 adults 93 (50 males, 43 females), mean age of $21.27{\pm}2.32$ (19~32) years old, were measured 5 times for two tests. Results: The mean of dynamic stereoacuity measured by two-rods test and three-rods test were $29.91{\pm}23.03sec$ of arc and $23.75{\pm}21.65sec$ of arc for total subjects, respectively. The mean of male and female were $36{\pm}22.38sec$ of arc and $22.28{\pm}23.79$, respectively. Three-rods test showed better dynamic stereoacuity than two-rods test, but there was no statistically significant difference (p>0.05). For the average standard deviation of PD between 60.63 mm~66.19 mm, dynamic stereoacuity fo two-rod test and three-rod test were $31.48{\pm}24.87sec$ of arc and $31.48{\pm}24.87sec$ of arc, respectively. The results showed statistically significant difference (p<0.05), but the relationship between dynamic stereoacuity and PD was not great. Comparison between two tests on the basis of refractive error, dynamic stereoacuity by three-rods test was better than by two-rods test with no significant difference between both tests (p>0.05) and there was little correlation between refractive error and two dynamic stereoacuity. Conclusions: Three-rods test showing lower stereoacuity than two-rods tests could measure the lower minimum threshold of dynamic stereoacuity. It was found that both tests can be applied to dynamic stereoacuity test as a standard test, and PD and refractive error was found that little effect upon the dynamic stereoacuity. PD and refractive error was found that little effect upon the dynamic stereoacuity.

• Korean Journal of Soil Science and Fertilizer
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• v.41 no.4
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• pp.260-266
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• 2008

Small lysimeter experiment under rain shelter plastic film house was conducted to investigate the effect of soil characteristics on the leaching and soil solution concentration of nitrate and phosphate. Three soils were obtained from different agricultural sites of Korea: Soil A (mesic family of Typic Dystrudepts), Soil B (mixed, mesic family of Typic Udifluvents), and Soil C (artificially disturbed soils under greenhouse). Organic-C contents were in the order of Soil C ($32.4g\;kg^{-1}$) > Soil B ($15.0g\;kg^{-1}$) > Soil A ($8.1g\;kg^{-1}$). Inorganic-N concentration also differed significantly among soils, decreasing in the order of Soil B > Soil C > Soil A. Degree of P saturation (DPS) of Soil C was 178%, about three and fifteen times of Soil B (38%) and Soil A (6%). Prior to treatment, soils in lysimeters (dia. 300 mm, soil length 450 mm) were tabilized by repeated drying and wetting procedures for two weeks. After urea at $150kg\;N\;ha^{-1}$ and $KH_2PO_4$ at $100kg\;P_2O_5\;ha^{-1}$ were applied on the surface of each soil, total volume of irrigation was 213 mm at seven occasions for 65 days. At 13, 25, 35, 37, and 65 days after treatment, soil solution was sampled using rhizosampler at 10, 20, and 30 cm depth and leachate was sampled by free drain out of lysimeter. The volume of leachate was the highest in Soil C, and followed by the order of Soils A and B, whereas the amount of leached nitrate had a reverse trend, i.e. Soil B > Soil A > Soil C. Soil A and B had a significant increase of the nitrate concentration of soil solution at depth of 10 cm after urea-N treatment, but Soil C did not. High nitrate mobility of Soil B, compared to other soils, is presumably due to relatively high clay content, which could induce high extraction of nitrate of soil matrix by anion exclusion effect and slow rate of water flow. Contrary to Soil B, high organic matter content of Soil C could be responsible for its low mobility of nitrate, inducing preferential flow by water-repellency and rapid immobilization of nitrate by a microbial community. Leached phosphate was detected in Soil C only, and continuously increased with increasing amount of leachate. The phosphate concentration of soil solution in Soil B was much lower than in Soil C, and Soil A was below detection limit ($0.01mg\;L^{-1}$), overall similar to the order of degree of P saturation of soils. Phosphate mobility, therefore, could be largely influenced by degree of P saturation of soils but connect with apparent leaching loss only more than any threshold of P accumulation.

• Journal of the Korean Society for Marine Environment & Energy
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• v.16 no.2
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• pp.71-81
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• 2013

Trace metal concentration in sediment cores from the outer sea of Lake Shihwa were determined to study the vertical profiles of metal concentrations and to evaluate the levels of metal contamination. Sediment pollution assessment was carried out using enrichment factor (EF) and geo-accumulation index (Igeo). The mean concentration of metals were 58.8 mg/kg for Cr, 10.3 mg/kg for Co, 22.8 mg/kg for Ni, 18.1 mg/kg for Cu, 74.0 mg/kg for Zn, 6.75 mg/kg for As, 0.14 mg/kg for Cd, 27.4 mg/kg for Pb and 0.026 mg/kg for Hg, respectively. The mean EF values for Cu, Zn, As, Cd and Hg were greater than 1.5 in sediment cores, indicating that these metals in sediments are slightly enriched by anthropogenic activities. The geo-accumulation index (Igeo) suggested unpolluted status for metals of sediments collected from outer see of Lake Shihwa. Igeo values for Cu and Hg nearby LNG station (site C, D, E) ranged from 1 to 2, indicating moderately to unpolluted pollution status for those metals. Even if the higher concentrations of trace metals nearby LNG station were observed, there is significantly positive relationship between Al and trace metals. Thus, the sediment grain size plays an important roles in influencing the distribution of trace metals in sediment cores from the outer sea of Lake Shihwa. Based on the comparison with sediment quality guidelines such as threshold effect level and probable effect level in Korea, the concentration of metals in sediments from outer sea of Lake Shihwa are likely to result in no harmful effects on sediment-dwelling organisms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.70-80
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• 2003

We report the first direct measurement of $CO_2$ flux over Kwangneung broadleaf deciduous forest, one of the tower flux sites in KoFlux network. Eddy covariance system was installed on a 30 m tower along with other meteorological instruments from June to August in 2002. Although the study site was non-ideal (with valley-like terrain), turbulence characteristics from limited wind directions (i.e., 90$\pm$45$^{\circ}$) was not significantly different from those obtained at simple, homogeneous terrains with an ideal fetch. Despite very low rate of data retrieval, preliminary results from our analysis are encouraging and worthy of further investigation. Ignoring the role of advection terms, the averaged net ecosystem exchange (NEE) of $CO_2$ ranged from -1.2 to 0.7 mg m$^{-2}$ s$^{-1}$ from June to August in 2002. The effect of weak turbulence on nocturnal NEE was examined in terms of friction velocity (u*) along with the estimation of storage term. The effect of low uf u* NEE was obvious with a threshold value of about 0.2 m s$^{-1}$ . The contribution of storage term to nocturnal NEE was insignificant; suggesting that the $CO_2$ stored within the forest canopy at night was probably removed by the drainage flow along the hilly terrain. This could be also an artifact of uncertainty in calculations of storage term based on a single-level concentration. The hyperbolic light response curves explained ＞80% of variation in the observed NEE, indicating that $CO_2$ exchange at the site was notably light-dependent. Such a relationship can be used effectively in filling up the missing gaps in NEE data through the season. Finally, a simple scaling analysis based on a linear flow model suggested that advection might play a significant role in NEE evaluation at this site.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1979.05a
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• pp.3.2-3
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• 1979

Bone conduction loss is one of the most common complication in chronic otitis media, and is mostly high frequency loss. Of 233 tympanomastoidectomy ears, 187 ears were considered eligible for this study. A histopathological change was examined in the natural otitis media of guinea pigs. It is our intention to analyze the pattern of bone conduction loss in chronic otitis media, and to correlate this findings with clinical and pathological changes in human and animal otitis media. l) In unilateral cases, a significant difference in bone conduction threshold was observed between normal and diseased ears, and between each frequency with significant interaction between 2KHz and 4KHz (p 0.01). 2) Using one way analysis of variance, mean bone conduction was compared with the duration of disease. We observed a significant difference (p 0.05) between each group of duration, except between 11-15 and 15-20 years group. 3) A comparison of bone conduction between stapes loss group and intact stapes group revealed significant t ratio (p 0.01) at each frequency. The effect of stapes loss on each frequency was evaluated, using one way analysis of variance. there were significant difference(p 0.05) between 250Hz and 500Hz. and between 2KHz and 4KHz. 4) A comparison of bone conduction between round window obliteration and nonobliteration group revealed significant t ratio (p 0.01) at each frequency. Using one way analysis of variance. the effect of round window obliteration was evaluated in each frequency. We observed significant difference (p 0.05) between 250Hz and 500Hz. and between 2KHz and 4KHz. 5) A comparison of bone conduction between cholesteatoma and non -cholesteatoma group revealed significant t ratio (p 0.01) only in 2KHz and 4KHz. No significant differency was observed in mean bone conduction. 6) In a histopathological study of natural otitis media in guinea pig, we observed inflammatory infiltration of the round window membrane, serofibrinous precipitate in the scala tympani, and degeneration of the organ of Corti most significant near the basal turn. These changes would explain high tone bone conduction loss in the process of chronic otitis media.

• Proceedings of the KOR-BRONCHOESO Conference
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• 1972.03a
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• pp.7-8
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• 1972

The effects of noise exposure are of two types: Nonauditory effects and auditory effects. Nonauditory effects of noise exposure are interference with communication by speech, sleeping and emotional behavior. The noise will cause the high blood pressure and rapid pulse, also that decrease the salivation and gastric juice. in experimentaly showed that the Corticoid hormon: Gonatotropic hormone were decrease and Thyrotropic hormoone is increase. Auditory effect of noise exposure. when the normal ear is exposed to noise at noise at hamful intensities (above 90㏈) for sufficiently long periods of time, a temoral depression of hearing results, disappearing after minutes or hours of rest. When the exposure longer or intesity greater is reached the Permanent threshold shift called noise-induced hearing loss. Hearing loss resulting from noise exposure presents legal as well as medical problems. The otologist who examines and evaluates the industrial hearing loss cases must be properly informed, not only concerning the otologic but also about the physical and legal aspects of the problems. The measurement of hearing ability is the most important part of a hearing conservation, both preplacement and periodic follow-up tests of hearing. The ideal hearing conservation program would be able to reduce or eliminate the hazardous noise at its source or by acoustic isolation of noisy working area and two ear protections (plugs and muff type) were developed for personal protection.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.223-233
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• 2015

In order to evaluate the pollution of heavy metals in offshore surface sediments around shipyards in Korea, surface sediment samples were collected at eleven stations around four major shipyards located in the southeastern coast of Korea in summer 2010 and nine kinds of heavy metals such as copper(Cu), zinc(Zn), cadmium(Cd), lead(Pb), chrome(Cr), arsenic(As), mercury(Hg), iron(Fe) and aluminum(Al) in sediments were analyzed. The concentrations of Cu at all sampling stations were in the range of 47.10~414.96 mg/kg and exceeded TEL(Threshold Effects Level) 20.6 mg-Cu/kg of Korean marine environmental standards for offshore sediments and ERL(Effect Range-Low) 34.0 mg-Cu/kg. The concentrations of Cu at seven stations around four shipyards were 65.18~414.96 mg/kg and exceeded PEL(Probable Effects Level) 64.4 mg-Cu/kg of Korean marine environmental standards for offshore sediments. The concentration of Cu at one station around B-shipyard was 414.96 mg/kg and exceeded ERM(Effect Range-Median) 270.0 mg-Cu/kg. The concentrations of Zn at all stations were in the range of 135.09~388.79 mg/kg which exceeded ERL 150.0 mg-Zn/kg. The concentrations of Zn at seven stations around four shipyards were 157.57~388.79 mg/kg and exceeded PEL 157.0 mg-Zn/kg. The concentration of Zn at one station around B-shipyard was 388.79 mg/kg and was approaching ERM 410.0 mg-Zn/kg. The concentrations of Cd at all stations were in the range of 0.11~0.54 mg/kg and were below TEL 0.75 mg-Cd/kg and ERL 1.2 mg-Cd/kg. The concentrations of Pb at all stations were in the range of 18.04~105.62 mg/kg. The concentrations of Pb at two stations around B-shipyard were 73.87~105.62 mg/kg which exceeded TEL 44.0 mg-Pb/kg and ERL 46.7 mg-Pb/kg, and were below PEL 119.0 mg-Pb/kg and ERM 218.0 mg-Pb/kg. The concentrations of Cr at all stations were in the range of 51.26~85.39 mg/kg. The concentration of Cr at one station around B-shipyard was 85.39 mg/kg and exceeded ERL 81.0 mg-Cr/kg. The concentrations of As at all stations were in the range of 8.70~22.15 mg/kg which exceeded ERL 8.2 mg-As/kg and were below ERM 70.0 mg-As/kg. The concentrations of As at eight stations around A-shipyard, B-shipyard and D-shipyard were 14.93~22.15 mg/kg which exceeded TEL 14.5 mg-As/kg and were below PEL 75.5 mg-As/kg. The concentrations of Hg at all stations were in the range of 0.02~0.35 mg/kg. The concentrations of Hg at three stations around A-shipyard were 0.11~0.13 mg/kg which were almost equal to TEL 0.11 mg-Hg/kg. Those at two stations around B-shipyard were 0.27~0.35 mg/kg which exceeded TEL 0.11 mg-Hg/kg and ERL 0.15 mg-Hg/kg, and were below PEL 0.62 mg-Hg/kg and ERM 0.71 mg-Hg/kg. The concentrations of Fe and Al at all stations were in the range of 2.90 3.66 % and 3.12 6.80 %, respectively. These results imply that heavy metals such as copper, zinc, lead, arsenic and mercury were likely to be transferred to marine environment from shipyards, especially from B-shipyard.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2335-2347
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• 2023

As medical facilities are usually built at urban areas, special concrete aggregates and evaluation methods are needed to optimize the design of concrete walls by balancing density, thickness, material composition, cost, and other factors. Carbon treatment rooms require a high radiation shielding requirement, as the neutron yield from carbon therapy is much higher than the neutron yield of protons. In this case study, the maximum carbon energy is 430 MeV/u and the maximum current is 0.27 nA from a hybrid particle therapy system. Hospital or facility construction should consider this requirement to design a special heavy concrete. In this work, magnetite is adopted as the major aggregate. Density is determined mainly by the major aggregate content of magnetite, and a heavy concrete test block was constructed for structural tests. The compressive strength is 35.7 MPa. The density ranges from 3.65 g/cm³ to 4.14 g/cm³, and the iron mass content ranges from 53.78% to 60.38% from the 12 cored sample measurements. It was found that there is a linear relationship between density and iron content, and mixing impurities should be the major reason leading to the nonuniform element and density distribution. The effect of this nonuniformity on radiation shielding properties for a carbon treatment room is investigated by three groups of Monte Carlo simulations. Higher density dominates to reduce shielding thickness. However, a higher content of high-Z elements will weaken the shielding strength, especially at a lower dose rate threshold and vice versa. The weakened side effect of a high iron content on the shielding property is obvious at 2.5 µSv=h. Therefore, we should not blindly pursue high Z content in engineering. If the thickness is constrained to 2 m, then the density can be reduced to 3.3 g/cm³, which will save cost by reducing the magnetite composition with 50.44% iron content. If a higher density of 3.9 g/cm³ with 57.65% iron content is selected for construction, then the thickness of the wall can be reduced to 174.2 cm, which will save space for equipment installation.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.