• The Journal of the Society of Korean Medicine Diagnostics
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• v.19 no.3
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• pp.141-149
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• 2015

Objectives Recently the fuzzy logic is widely used in the decision making, identification, pattern recognition, optimization in various fields. In this study, we propose the fuzzy logic as the objective method of distinguishing hot and cold, the basis of diagnosis in Korean medicine. Methods We developed fuzzy inference system to distinguish whether the subjects had hot or cold. The cold and hot questionnaire of Korean traditional university textbook, the pulse rate and the DITI value of face used in the system. These three kinds of information were defined as 'fuzzy sets,' and 54 fuzzy rules were established on the basis of clinical practitioners' knowledge. The fuzzy inference was performed by using the Mamdani's method. To evaluate the usefulness of the fuzzy inference system, 200 cases of data measured in the Woosuk university hospital of oriental medicine were used to compare the determining hot, normal, cold results obtained from the experts and from the proposed system. Results As a result, 100 cases of "cold", 54 cases of "normal", and 34 cases of "hot" were matched between the experts and the proposed system. This fuzzy system showed the conformity degree of 94%(${\kappa}=0.853$). Conclusions In this study, we could express the process of distinguishing hot-cold using the fuzzy logic for objectification and quantification of hot-cold identification. This is the first study that introduce a fuzzy logic for distinguish pattern identification. The degree of the heat characteristic of the patients inferred by this system could provide a more objective basis for diagnosing the hot-cold of patients.

• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.6
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• pp.466-473
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• 2016

This study intended to find out the most substantial items in cold and heat pattern identification(CHPI) questionnaire based on usual symptoms through CHPI diagnosis and evaluation by experts. 120 participants, faculties of OO university, filled out CHPI questionnaire based on usual symptoms by the way of self-reporting. Then 2 Korean Medicine doctors independently diagnosed them whether they belonged to cold pattern identification(PI) or heat PI, and scored the result of it. Pearson correlation of 2 experts was 0.649 in cold PI and 0.605 in heat PI. Agreement was 75.8%(Kappa value 0.516) in cold PI and 74.2%(Kappa value 0.465) in heat PI. Pearson correlation of 2 experts was 0.649 in cold PI and 0.605 in heat PI. Agreement between two experts was 75.8%(Kappa value 0.516) in cold PI and 74.2%(Kappa value 0.465) in heat PI. Items of high correlation with experts' evaluation followed next: "do not usually like the cold", "usually like the warm", "usually feel cold" in cold PI and "do not usually like the hot", "usually feel hot", "usually feel burning sensation in the body" in heat PI. We could infer from that facts that experts give weight on 'subjective feeling of cold or heat in participants body' and 'preference on sensation of cold and heat'. We also expect this study to be an epidemiological foundation to disclose correlation between usual CHPI and diseases.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.1-8
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• 2015

Wear leveling techniques have been studied to prolong the lifetime of NAND flash memory. Most of studies have used Program/Erase(P/E) cycles as wear index for wear leveling. Unfortunately, P/E cycles could not predict the real lifetime of NAND flash blocks. Therefore, these algorithms have the limited performance from prolonging the lifetime when applied to the SSD. In order to apply the real lifetime, wear leveling algorithms, which use raw Bit Error Rate(rBER) as wear index, have been studied in recent years. In this paper, we propose CrEWL(Cold data identification using raw Bit error rate in Wear Leveling), which uses rBER as wear index to apply to the real lifetime. The proposed wear leveling reduces an overhead of garbage collections by using HBSQ(Hot Block Sequence Queue) which identifies hot data. In order to reduce overhead of wear leveling, CrEWL does not perform wear leveling until rBER of the some blocks reaches a threshold value. We evaluate CrEWL in comparison with the previous studies under the traces having the different Hot/Cold rate, and the experimental results show that our wear leveling technique can reduce the overhead up to 41% and prolong the lifetime up to 72% compared with previous wear leveling techniques.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.1-9
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• 2019

Hard disks, which have long been used as secondary storage in computing systems, are increasingly being replaced by solid state drives (SSDs), due to their relatively fast data input / output speeds and small, light weight. SSDs that use NAND flash memory as a storage medium are significantly different from hard disks in terms of physical operation and internal operation. In particular, there is a feature that data overwrite can not be performed, which causes erase operation before writing. In order to solve this problem, a hot data for frequently updating a data for a specific page is distinguished from a cold data for a relatively non-hot data. Hot data identification helps to improve overall performance by identifying and managing hot data separately. Among the various hot data identification methods known so far, there is a technique of recording consecutive write requests by using a Bloom filter and judging the values by hot data. However, the Bloom filter technique has a problem that a new bit array must be generated every time a set of items is changed. In addition, since it is judged based on a continuous write request, it is possible to make a wrong judgment. In this paper, we propose a method using a counting filter for accurate hot data verification. The proposed method examines consecutive write requests. It also records the number of times consecutive write requests occur. The proposed method enables more accurate hot data verification.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.1273-1274
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• 2006

Chemically pure, hydride/dehydride titanium powders were cold pre-compacted then extruded at $850^{\circ}C$ and $\sim450MPa$ under argon. The extrusions were 100% dense with a narrow band of surface porosity and equiaxed microstructure of similar magnitude to the starting material. The tensile properties of the bars were better than conventionally extruded CP titanium bar product. Outcomes from this study have assisted in the identification of a number of key characteristics important to the extrusion of titanium from pre-compacted CP titanium powders, allowing the elimination of canning and hot isostatic pressing (HIPping) of billets prior to extrusion as per conventional PM processes.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.1
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• pp.224-228
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• 2006

The pattern identification of exterior-interior syndrome and cold-heat syndrome is one of the diagnostic methods using most frequently in Oriental medicine. There was no systematic studies analyzing the characteristics of the 'exterior-interior and cold-heat' between healthy and disease group. In this study, cold-heat pattern, blood pressure, pulse rate, height and weight are recorded from 100 healthy subjects and 196 disease subjects with age ranging from 30 to 59 years. To analyze the differences between healthy and disease group, we used the descriptive statistics. And linear regression function, linear support vector machine and bayesian classifier were used for distinguishing healthy group from disease group. The score of both exterior-heat and interior-cold in healthy group is higher than the score in disease group. This means that if one belongs to the disease group, his(or her) exterior gets cold and his interior gets hot. And also, these result have no relevance to age. But, the attempt to classify healthy group from disease group with a exterior-interior and cold-heat and other vital signs did not have good performance. It mean that even though they have a different trend each other, only these kinds of information couldn't classify healthy group and disease group.

• Biomedical Science Letters
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• v.29 no.4
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• pp.256-262
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• 2023

The purpose of this study is to investigate microbial contamination in water purifiers from two universities (A and B) in Chungcheong region and to evaluate about the harmfulness of the isolated bacteria to the human. The degree of microbiological contamination of six water purifiers at university A was investigated three times from July 2018 to September 2019, and nine water purifiers at university B were investigated in 2023. The isolated bacteria were biochemically identified using an API kit and Vitek-2 system, and then the bacteria were identified to the species level using MALDI-TOF MS. In addition, the possibility of human infection of the isolated bacteria was evaluated through a literature search. In July 2018 and September 2019, the number of bacteria isolated inside the faucet was below the acceptable standard for hot water, but exceed for cold water in all water purifiers. In January and September 2019, bacteria exceeding the acceptable standards were isolated nine times from the cold water of six water purifies (a total of 12 water purifiers). Bacteria identified by MALDI-TOF MS included anaerobic bacteria (Clostridium novyi, Clostridium themopalmarium etc.), Gram-positive bacilli (Microbacterium testaceum, Arthrobacter woluwensis etc.), and Gramnegative bacilli (Acinetobacter nosocomialis, Comamonas kerstersii etc.), which are difficult identify by biochemical methods. In conclusion, bacteria exceeding the acceptable standard were isolated from the cold water of most of the water purifiers. Most of the isolated bacteria were low-pathogenic bacteria from natural environment, but opportunistic bacteria that can cause infection in humans were also isolated from some water purifiers.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.5
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• pp.321-328
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• 2017

In this study, vortex tube system model is developed to predict the temperature of the hot and the cold sides. The vortex tube model is developed based on the system identification method, and the model utilized in this work to design the vortex tube is ARX type (Auto-Regressive with eXtra inputs). The derived polynomial model is validated against experimental data to verify the overall model accuracy. It is also shown that the derived model passes the stability test. It is confirmed that the derived model closely mimics the physical behavior of the vortex tube from both the static and dynamic numerical experiments by changing the angles of the low-temperature side throttle valve, clearly showing temperature separation. These results imply that the system identification based modeling can be a promising approach for the prediction of complex physical systems, including the vortex tube.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.2
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• pp.47-55
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• 2021

In order to ensure the fact that eight principle pattern differentiation is used clinically as a basic guideline for Korean medicine practice, the definition, role and method of yin-yang pattern differentiation with its case report were explored at first. Yinyang Pattern Differentiation is a method of discriminating human tendencies or morbidity based on the yin and yang characteristics expressed in living bodies. And yin and yang are the two contrasting characteristics and aspects of the interaction when certain physical conditions that have a lasting effect on the human physiological metabolic function are correlated with the morbidity. Specific methods of yinyang pattern differentiation can be divided into several types of yin and yang indicators. First, time and space factors like day and night, hot and cold seasons, above and below, topographical districts. Second, colors and pulse and their/or relative clearness and muddiness, hardness and softness, moving and resting. Third, diagnose yin and yang patterns through distinguishing the true and false of a fever and cold in an emergency phase such as increase of brain pressure and shock state. Fourth, general characteristics of the propensity and constitution of a subject such as body type, speech, behavior, and physiological metabolism. And for clinical use, these were summarized again as a symptom indicators of physical signs and color, pulse, tongue and questionnaire indicators of propensity, body type, and space-time characteristics. Conclusively, it was confirmed that yinyang pattern differentiation has its own diagnostic significance which is distinct from exterior-interior, cold-heat and deficiency-excess pattern differentiation.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.