Proceedings of the Korea Water Resources Association Conference
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2023.05a
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pp.174-174
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2023
The impact of global warming on the south Asian summer monsoon is of critical importance for the large population of this region. This study aims to investigate the future changes of the precipitation extremes during pre-monsoon and monsoon, across this region in a more organized regional structure. The study area is divided into six major divisions based on the Köppen-Geiger's climate structure and 10 sub-divisions considering the geographical locations. The future changes of extreme precipitation indices are analyzed for each zone separately using five indices from ETCCDI (Expert Team on Climate Change Detection and Indices); R10mm, Rx1day, Rx5day, R95pTOT and PRCPTOT. 10 global climate model (GCM) outputs from the latest CMIP6 under four combinations of SSP-RCP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are used. The GCMs are bias corrected using nonparametric quantile transformation based on the smoothing spline method. The future period is divided into near future (2031-2065) and far future (2066-2100) and then the changes are compared based on the historical period (1980-2014). The analysis is carried out separately for pre-monsoon (March, April, May) and monsoon (June, July, August, September). The methodology used to compare the changes is probability distribution functions (PDF). Kernel density estimation is used to plot the PDFs. For this study we did not use a multi-model ensemble output and the changes in each extreme precipitation index are analyzed GCM wise. From the results it can be observed that the performance of the GCMs vary depending on the sub-zone as well as on the precipitation index. Final conclusions are made by removing the poor performing GCMs and by analyzing the overall changes in the PDFs of the remaining GCMs.
Proceedings of the Korea Water Resources Association Conference
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2023.05a
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pp.314-314
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2023
Extreme climate events can have a large impact on human life by hampering social, environmental, and economic development. Global circulation models (GCMs) are the widely used numerical models to understand the anticipated future climate change. However, different GCMs can project different future climates due to structural differences, varying initial boundary conditions and assumptions about the physical phenomena. The multi-model ensemble (MME) approach can improve the uncertainties associated with the different GCM outcomes. In this study, a comprehensive rating metric was used to select the best-performing GCMs out of 11 CMIP5 and 13 CMIP6 GCMs, according to their skills in terms of four temporal and five spatial performance indices, in replicating the 21 extreme climate indices during the baseline (1975-2017) in South Korea. The MME data were derived by averaging the simulations from all selected GCMs and three top-ranked GCMs. The random forest (RF) algorithm was also used to derive the MME data from the three top-ranked GCMs. The RF-derived MME data of the three top-ranked GCMs showed the highest performance in simulating the baseline extreme climate which was subsequently used to project the future extreme climate indices under both the representative concentration pathway (RCP) and the socioeconomic concentration pathway scenarios (SSP). The extreme cold and warming indices had declining and increasing trends, respectively, and most extreme precipitation indices had increasing trends over the period 2031-2100. Compared to all scenarios, RCP8.5 showed drastic changes in future extreme climate indices. The coasts in the east, south and west had stronger warming than the rest of the country, while mountain areas in the north experienced more extreme cold. While extreme cold climatology gradually declined from north to south, extreme warming climatology continuously grew from coastal to inland and northern mountainous regions. The results showed that the socially, environmentally and agriculturally important regions of South Korea were at increased risk of facing the detrimental impacts of extreme climatology.
Proceedings of the Microbiological Society of Korea Conference
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2001.11a
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pp.39-45
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2001
Extremophiles are unique microorganisms that are adapted to survive in ecological niches such as high or low temperatures, extremes of pH, high salt concentrations and high pressure. These unusual microorganisms have unique biochemical features which can be exploited for use in the biotechnological industries. Due to the high biodiversity of extremophilic archaea and bacteria and their existence in various biotopes a variety of biocatalysts with different physicochemical properties have been discovered. The extreme molecular stability of their enzymes, membranes and the synthesis of unique organic compounds and polymers make extremophiles interesting candidates for basic and applied research. Some of the enzymes from extremophiles, especially hyperthermophilic marine microorganisms (growth above $85^{\circ}C$), have already been purified in our laboratory. These include the enzyme systems from Pyrococcus, Pyrodictium, Thermococcus and Thermotoga sp. that are involved in polysacharide modification and protein bioconversion. Only recently, the genome of the thermoalkaliphilic strain. Anaerobranca gottschalkii has been completely sequenced providing a unique resource of novel biocatalysts that are active at high temperature and pH. The gene encoding the branching enzyme from this organism was cloned and expressed in a mesophilic host and finally characterized. A novel glucoamylase was purified from an aerobic archaeon which shows optimal activity at $90^{\circ}C$ and pH 2.0. This thermoacidophilic archaeon Picrophilus oshimae grows optimally at pH 0.7 and $60^{\circ}C$. Furthermore, we were able to detect thermoactive proteases from two anaerobic isolates which are able to hydrolyze feather keratin completely at $80^{\circ}C$ forming amino acids and peptides. In addition, new marine psychrophilic isolates will be presented that are able to secrete enzymes such as lipases, proteases and amylases possessing high activity below the freezing point of water.
Blocking refers to a class of weather phenomena appearing in the mid and high latitudes, whose characteristics are blocked airflow of persistence. Frequently found over the Pacific and Atlantic regions of the Northern Hemisphere, blocking affects severe weather in the surrounding areas with different mechanisms depending on the type of blocking patterns. Along with lots of studies about persistent weather extremes focusing on the specific types of blocking, a new categorization using Rossby wave breaking has emerged. This study aims to apply this concept to the classification of blockings over the Pacific and examine how different wave breakings specify the associated cold weather in the Korean peninsula. At the same time, we investigate a strongly developing ridge around the Pacific by designing a new detection algorithm, where a reversal method is modified to distinguish ridge-type blocking patterns. As result, Kamchatka blocking (KB) and strong ridge over the Central Pacific are observed the most frequently during 20 years (2001~2020) of the studied period, and anomalous low pressures with cold air over the Korean Peninsula are accompanied by blocking events. When it considers the Rossby wave breaking, cyclonic wave-breaking is dominant in KB, which generates low-pressure anomalies over the Korean Peninsula. However, KB with anticyclone wave breaking appears with the high-pressure anomalies over the Korean Peninsula and it generates the warm temperature anomaly. Lastly, the low-pressure anomalies are also generated by the strong ridge over the Central Pacific, which persists for approximately three days and give a significant impact on cold surge on the Korean Peninsula.
Proceedings of the Korea Water Resources Association Conference
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2022.05a
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pp.152-152
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2022
Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.
Back ground : Arm span measurements provide a practical substitute for standing height to predict normal spirometric values in subjects unable to stand or those with a skeletal deformity such as kyphoscoliosis. The relationship between arm span and height has previously been reported as either a fixed ratio unaffected by age or as a regression equation in which the ratio varies as a function of age. The fixed ratio or regression equation is known to be specific for sex and race. Methods : We studied the relationship between standing height, arm span, and age in 381 Korean adult female subjects (ages 20 to 69 yrs) sampled in a general population. Results : The mean ratio for arm span to height is 1.004. Multiple linear analysis found arm span and age to be predictive of standing height (p=0.0001, $r^2$=0.76). We performed the analysis of the difference between the predicted height using either fixed ratio or regression equation and actual height. At the extremes of arm span and age, the ratio method either underestimated(at smaller arm span or younger age) or overestimated(at larger arm span or older age) as compared with actual height (p=0.0001). Conclusion : This results indicate that the estimated height using the fixed ratio method provides a less acceptable method of estimating height for the prediction of lung volumes in the Korean adult women when compared with the regression equations, especially at the extremes of stature or age.
Proceedings of the Korean Institute of Intelligent Systems Conference
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1993.06a
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pp.975-976
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1993
This talk presents the overview of the author's research and development activities on fuzzy inference hardware. We involved it with two distinct approaches. The first approach is to use application specific integrated circuits (ASIC) technology. The fuzzy inference method is directly implemented in silicon. The second approach, which is in its preliminary stage, is to use more conventional microprocessor architecture. Here, we use a quantitative technique used by designer of reduced instruction set computer (RISC) to modify an architecture of a microprocessor. In the ASIC approach, we implemented the most widely used fuzzy inference mechanism directly on silicon. The mechanism is beaded on a max-min compositional rule of inference, and Mandami's method of fuzzy implication. The two VLSI fuzzy inference chips are designed, fabricated, and fully tested. Both used a full-custom CMOS technology. The second and more claborate chip was designed at the University of North Carolina(U C) in cooperation with MCNC. Both VLSI chips had muliple datapaths for rule digital fuzzy inference chips had multiple datapaths for rule evaluation, and they executed multiple fuzzy if-then rules in parallel. The AT & T chip is the first digital fuzzy inference chip in the world. It ran with a 20 MHz clock cycle and achieved an approximately 80.000 Fuzzy Logical inferences Per Second (FLIPS). It stored and executed 16 fuzzy if-then rules. Since it was designed as a proof of concept prototype chip, it had minimal amount of peripheral logic for system integration. UNC/MCNC chip consists of 688,131 transistors of which 476,160 are used for RAM memory. It ran with a 10 MHz clock cycle. The chip has a 3-staged pipeline and initiates a computation of new inference every 64 cycle. This chip achieved an approximately 160,000 FLIPS. The new architecture have the following important improvements from the AT & T chip: Programmable rule set memory (RAM). On-chip fuzzification operation by a table lookup method. On-chip defuzzification operation by a centroid method. Reconfigurable architecture for processing two rule formats. RAM/datapath redundancy for higher yield It can store and execute 51 if-then rule of the following format: IF A and B and C and D Then Do E, and Then Do F. With this format, the chip takes four inputs and produces two outputs. By software reconfiguration, it can store and execute 102 if-then rules of the following simpler format using the same datapath: IF A and B Then Do E. With this format the chip takes two inputs and produces one outputs. We have built two VME-bus board systems based on this chip for Oak Ridge National Laboratory (ORNL). The board is now installed in a robot at ORNL. Researchers uses this board for experiment in autonomous robot navigation. The Fuzzy Logic system board places the Fuzzy chip into a VMEbus environment. High level C language functions hide the operational details of the board from the applications programme . The programmer treats rule memories and fuzzification function memories as local structures passed as parameters to the C functions. ASIC fuzzy inference hardware is extremely fast, but they are limited in generality. Many aspects of the design are limited or fixed. We have proposed to designing a are limited or fixed. We have proposed to designing a fuzzy information processor as an application specific processor using a quantitative approach. The quantitative approach was developed by RISC designers. In effect, we are interested in evaluating the effectiveness of a specialized RISC processor for fuzzy information processing. As the first step, we measured the possible speed-up of a fuzzy inference program based on if-then rules by an introduction of specialized instructions, i.e., min and max instructions. The minimum and maximum operations are heavily used in fuzzy logic applications as fuzzy intersection and union. We performed measurements using a MIPS R3000 as a base micropro essor. The initial result is encouraging. We can achieve as high as a 2.5 increase in inference speed if the R3000 had min and max instructions. Also, they are useful for speeding up other fuzzy operations such as bounded product and bounded sum. The embedded processor's main task is to control some device or process. It usually runs a single or a embedded processer to create an embedded processor for fuzzy control is very effective. Table I shows the measured speed of the inference by a MIPS R3000 microprocessor, a fictitious MIPS R3000 microprocessor with min and max instructions, and a UNC/MCNC ASIC fuzzy inference chip. The software that used on microprocessors is a simulator of the ASIC chip. The first row is the computation time in seconds of 6000 inferences using 51 rules where each fuzzy set is represented by an array of 64 elements. The second row is the time required to perform a single inference. The last row is the fuzzy logical inferences per second (FLIPS) measured for ach device. There is a large gap in run time between the ASIC and software approaches even if we resort to a specialized fuzzy microprocessor. As for design time and cost, these two approaches represent two extremes. An ASIC approach is extremely expensive. It is, therefore, an important research topic to design a specialized computing architecture for fuzzy applications that falls between these two extremes both in run time and design time/cost. TABLEI INFERENCE TIME BY 51 RULES {{{{Time }}{{MIPS R3000 }}{{ASIC }}{{Regular }}{{With min/mix }}{{6000 inference 1 inference FLIPS }}{{125s 20.8ms 48 }}{{49s 8.2ms 122 }}{{0.0038s 6.4㎲ 156,250 }} }}
An, Soon-Il;Ha, Kyung-Ja;Seo, Kyong-Hwan;Yeh, Sang-Wook;Min, Seung-Ki;Ho, Chang-Hoi
Journal of Climate Change Research
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v.2
no.4
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pp.237-251
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2011
This study presents a review on the recent climate change over the Korean peninsula, which has experienced a significant change due to the human-induced global warming more strongly than other regions. The recent measurement of carbon dioxide concentrations over the Korean peninsula shows a faster rise than the global average, and the increasing trend in surface temperature over this region is much larger than the global mean trend. Recent observational studies reporting the weakened cold extremes and intensified warm extremes over the region support consistently the increase of mean temperature. Surface vegetation greenness in spring has also progressed relatively more quickly. Summer precipitation over the Korean peninsula has increased by about 15% since 1990 compared to the previous period. This was mainly due to an increase in August. On the other hand, a slight decrease in the precipitation (about 5%) during Changma period (rainy season of the East Asian summer monsoon), was observed. The heavy rainfall amounts exhibit an increasing trend particularly since the late 1970s, and a consecutive dry-day has also increased primarily over the southern area. This indicates that the duration of precipitation events has shortened, while their intensity became stronger. During the past decades, there have been more stronger typhoons affecting the Korean peninsula with landing more preferentially over the southeastern area. Meanwhile, the urbanization effect is likely to contribute to the rapid warming, explaining about 28% of total temperature increase during the past 55 years. The impact of El Nino on seasonal climate over the Korean peninsula has been well established - winter [summer] temperatures was generally higher [lower] than normal, and summer rainfall tends to increase during El-Nino years. It is suggested that more frequent occurrence of the 'central-Pacific El-Nino' during recent decades may have induced warmer summer and fall over the Korean peninsula. In short, detection and attribution studies provided fundamental information that needed to construct more reliable projections of future climate changes, and therefore more comprehensive researches are required for better understanding of past climate variations.
This thesis examined interpreting methodology of Do Won Lew Seung Kug(1923~2011) is based on the principle of Juhng-yaug. His lifelong academic aim was searching for the theory that enables global community to co-exist peacefully through humanitarianism that leads to reconciliation and mutual benefits. The research of the history of Korean thoughts provided him with the clue for his theory. According to Do Won, Korean thoughts pursue the Juhng-yaug's value of 'Yin and Yang accordance' rather than the I-Ching's value of 'suppress Yin and elevate Yang'. He furthermore asserts the concept of the middle (中), which harmonizes the two extremes by human beings as main agents, has been consistently observed from the action of divination during the ancient period through Juhng-yaug in the late 19th century. Do Won identifies 'human maturity that integrates the extremely conflicting insistences and values and seeks to be reconciled' as the basic character of Korean thoughts. He explains 'Hongikingan[弘益人間, becoming beneficial to the human world] is the idea that embraces the conflicting values symbolized by heaven and the earth. He also illuminates that Choe Chi Won(崔致遠)'s created Poongliu Do by integrating heterogeneity among Confucianism, Buddhim, and Daoism and it was attainable through the various works of mature human beings. Both Toe Gye' s philosophy of Ingeuk(人極, the Great Ultimate of Person) and the concept of Innaecheon(人乃天, Human Being right is Heaven) of Donghak are excellent examples of Humanitarianism that sublate two extremes. In Korea, the prototype of this thought has penetrated its entire history in the various circumstances of the period. The grand finale is Juhng-yaug of which the pursued values are 'Yin and Yang accordance' and mature humanitarianism revealed by the thoughts of the Person of the Central Ultimate (皇極人,至人) and Central Ultimate (皇極). Therefore, Humanitarianism in Korean thoughts clearly makes its appearance by the time of Juhng-yaug and it functions as a keyword to illuminate the entire history of Korean thoughts in reverse.
Journal of Korean Society of Occupational and Environmental Hygiene
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v.11
no.2
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pp.161-168
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2001
The types of exposure data needed in an industry-based study depend on the diseases of interest and the study design to be used. The best situation occurs when we have quantified personal exposure estimates for the agents of interest, the least informative case occurs when we have only knowledge of the fact of employment in a plant, industry, or trade where exposure probability is high. Exposure information for most industry-based studies falls somewhere between these tow extremes. Job exposure matrices(JEM) are designed to link information on occupation with information on exposure to specific workplace hazards. Some forms of systematic error of bias may be less likely to occur in studies that utilize job-exposure matrices to indirectly infer exposures from job titles than in studies that assess exposures by asking subjects about their past exposure. JEM can be used effectively in industry-based studies for historic cohort studies, case-control study to assist with the retrospective assessment of occupational exposures among workers whose individual exposure histories are unavailable. JEM generally consist of a computerized database that links information about job categories and likely exposures. These two major axes may be stratified by calendar time. This article reviews the design of JEM in support of industry-based studies. Specific matrices may find broader applicability along with the increasing availability of detailed hygienic data.
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