• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.3 s.333
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• pp.43-50
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• 2005

In this paper, quaternary logic gates using Down literal circuit(DLC) has been designed, and then synchronous Quaternary un/down counter using those gates has been proposed The proposed counter consists of T-type quaternary flip flop and 1-of-2 threshold-t MUX, and T-type quaternary flip flop consists of D-type quaternary flip flop and quaternary logic gates(modulo-4 addition gates, Quaternary inverter, identity cell, 1-of-4 MUX). The simulation result of this counter show delay time of 10[ns] and power consumption of 8.48[mW]. Also, assigning the designed counter to MVL(Multiple-valued Logic) circuit, it has advantages of the reduced interconnection and chip area as well as easy expansion of digit.

• Advances in Traditional Medicine
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• v.5 no.1
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• pp.1-15
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• 2005

Ginseng is a popular medicinal plant highly valued throughout the world. Asian ginseng is one of the most common species of ginseng. It has long occupied a significant position in oriental medicine and has been justified its name as the 'king herb'. As a nutritional supplement, ginseng is an extremely common and popular herbal medicine in the United States and Canada in recent decades. The multiple constituents of ginseng possess equally multifaceted pharmacological actions as demonstrated by numerous studies. Ginseng root and its constituents influenced the central nervous system, endocrine, cardiovascular, gastrointestinal system, sexual, renal organ and immune system, etc. One important action is its anti-hyperglycemic effect. Previous studies on ginseng demonstrate that only the root of ginseng has been used in the treatment of diabetes, while the other parts of ginseng plant were always neglected. Recently, we analyzed the constituents of ginseng berry, leaf and discovered that ginseng berry, leaf extracts and its total ginsenosides have the ability to reduce hyperglycemia and body weight and increase the peripheral glucose utilization in obese or diabetic ob/ob or db/db mice. Our data suggest that all parts of ginseng plant, including root, berry, leaf and stem exhibit potent anti-hyperglycemic and anti-obese effects and may provide an opportunity to develop a novel class of anti-diabetic agents.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.6
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• pp.42-49
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• 2000

In this paper, we propose the parallel ternary logic circuit design algorithm to DCG Property with 2$^n$ nodes. To increase circuit integration, one of the promising approaches is the use of multiple-valued logic(MVL). It can be useful methods for the realization of compact integrated circuit, the improvement of high velocity signal processing using parallel signal transmission and the circuit design algorithm to optimize and satisfy the circuit property. It is all useful method to implement high density integrated circuit. In this paper, we introduce matrix equation to satisfy given DCG with 2$^n$ nodes, and propose the parallel ternary logic circuit design process to circuit design algorithm. Also, we propose code assignment algorithm to satisfy for the given DCG property. According to the simulation result of proposed circuit design algorithm, it have the following advantage ； reduction of the circuit signal lines, computation time and costs.

• Korean Journal of Environmental Biology
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• v.32 no.4
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• pp.306-310
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• 2014

The brown seaweed Sargassum fusiforme is an edible and highly valued in Korea. During the summer season, phytal organisms graze heavily on young algal blades and holdfastsof the species and substantially reduce harvestable biomass. Here, in this study, we investigated the effects of pH (range: 2~13) and salinity (range: 0~44 psu) on the removal of two major phytal animals, Caprella scaura and Gammaropsis utinomi, associated with S. fusiforme. We also examined the optimum quantum yield (Fv/Fm) of algae in the same experimental conditions to quantify the tolerance of algae to acid and salinity treatments. It was observed that the phytal animals showed more than 80% mortality at pH lower that pH 4 and the extreams of salinity (0~10 psu and 44 psu) after a 5 min of immersion. However, the quantum yield of S. fusiforme was not significantly different from controls within the pH 3~11 range, and the 0~44 psu salinity range. Precisely, if the pH and salinity conditions outside these ranges were used in comercial Sargassum culture, the removal of the animal species would be higher, but with reduced quantum yield of algae. Taken together, our study results indicated that the pH and salinity treatments could allow multiple harvests from the same holdfast of S. fusiforme.

• Culinary science and hospitality research
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• v.18 no.5
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• pp.165-175
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• 2012

Investment in training by a company can lead to the retention and motivation of its valued staff and promote high self-fulfillment by providing career development. The objectives of this research were (a) to test the perceived satisfaction with a training based on respondents' socio-demographic characteristics, (b) to investigate training motivation factors affecting employees' training satisfaction, (c) to assess how training motivation factors affect the employees' satisfaction, and (d) to indicate the relationship between training satisfaction and the employees' job satisfaction. Additionally, by developing an employees' training motivation model and conducting multiple regression analysis, two types of motivation factors, intrinsic motivation and extrinsic motivation, were shown to be positively related to employees' training satisfaction. Subsequently, this employees' training satisfaction was a significant determinant factor for improving job satisfaction.

• Structural Engineering and Mechanics
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• v.55 no.6
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• pp.1261-1278
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• 2015

Due to their low intrinsic damping, stay cables in cable-stayed bridges have often exhibited unanticipated and excessive vibrations which result in increasing maintenance frequency and disruption to normal operations of the entire bridges. Mitigation of undesired cable vibration can be achieved by attaching an external damping device near the anchorage. High Damping Rubber (HDR) dampers have many advantages such as compact size, better aesthetics, easy maintenance, temperature stability, and cost benefits; therefore, they have been widely used to increase cable damping. Although a single damper has been shown to reduce cable vibrations, it is not the most effective method due to geometric constraints. This paper proposes the use of two HDR dampers to improve effectiveness and robustness in suppressing cable vibration. Oscillation parameters of the cable-dampers system were investigated in detail by modeling the stay cable as a taut string and each HDR damper as complex-valued impedance and by using an analytical formulation of the complex eigenvalue problem. The problem of two HDR dampers arbitrarily located along a cable is solved and the solution is discussed. Asymptotic formulas to calculate the damping ratios of the cable with two HDR dampers installed near the anchorage(s) are proposed and compared with the exact solutions. Further, a design example is presented in order to justify the methodology. The results of this study show that when the two HDR dampers are installed close to each other on the same end of the cable, some interaction between the dampers leads to reduced damping ratio. When the dampers are on the opposite ends of the cable, they are effective in increasing damping ratio and can provide better vibration reduction to multiple modes.

• Journal of Engineering Education Research
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• v.24 no.6
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• pp.3-19
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• 2021

This study aimed to introduce a case study of a basic engineering design course using the ENACT model for fostering social responsibility of engineers, and to investigate the educational effects of the course. Since the ENACT model was designed to encourage STEM college students to pursue responsible problem solving based on their understanding of socioscientific issues, we assumed that it would be beneficial for engineering students to foster their social responsibility as well as their understanding of science/engineering-related issues. A total of 49 engineering students who enrolled in the course participated in the study. Data included students' course artifacts, reflection papers, and responses to survey questionnaires. Results indicated that the students became more aware of nature of science and technology after the program, and began to solve the problems while considering the views of multiple stakeholders. They highly valued the experience of communicating with others as engaging in the civic activities. They also expressed high satisfaction and feeling of achievement on the course learning. We expect the ENACT model to be an effective teaching guideline that fosters the social responsibility of engineering students and furthermore, engineering ethics.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• Journal of Korean Academy of Fundamentals of Nursing
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• v.6 no.3
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• pp.493-506
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• 1999

The purpose of the study is to evaluate the effectiveness and competence level of trainees of Cardiopulmonary resuscitation training targeted for nursing students. 70 nursing students of Y nursing college are recruited as subjects from Dec. 1st, 1998 through Dec. 8th. 1998. For the pre-test. demographic data related to CPR and knowledge of CPR were evaluated. For the post-test, the next week of pre-test, three difference groups of subjects were tested their knowledge of CPR. CPR training was designed by two components which were 90 mins lecture and demonstration by one professor and individual practice using two educational models with two professors. As the tool of measurement estimating pre or post knowledge of CPR. questionnaires were developed based on self-diagnosis questionnaires of American Heart Association(AHA). The questionnaires were multiple choices (50 questions) and open end questions regarding CPR process. Each multiple choices questions valued 2 points (Score varied min. 0 point to max 100 points.). Collected data were computerized and analyzed by SPSS-WIN. Frequency and percentage of each questions analyzed. The differences of the knowledge and competency level of subjects between pre and post test was analyses by paired t-test. The followings are research outcome. 1. In the pre-test, 95% of subjects answered that they already knew what CPR was. but only 82% described correctly what CPR was. 49% learned CPR before, and 80s5 of them learned at high school. 2. 37 questions scores increases, and 10 questions scores decreased. 3 questions didnt change their score. After getting training, ratio of 80% correct score significantly increased 4 times. 3. In post-test. knowledge level of trainees increased compared to that of pre-test. (t=-15.075, p=.000) 4. Competence level also increased (t=-14.86, p=.00). In result, after getting CPR training, most CPR knowledge increased except open the air tract, toddler CPR, and alternative behavior when the air tract is blocked. CPR training needs to extend the educational scope not only CPR lecture but also psychomotor skill practice. CPR trainees are in need of appropriate feedback as well as enough opportunities of skill practice.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.55-71
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• 2013

The prediction model is the main factor affecting the performance of a knowledge-based system for bankruptcy prediction. Earlier studies on prediction modeling have focused on the building of a single best model using statistical and artificial intelligence techniques. However, since the mid-1980s, integration of multiple techniques (hybrid techniques) and, by extension, combinations of the outputs of several models (ensemble techniques) have, according to the experimental results, generally outperformed individual models. An ensemble is a technique that constructs a set of multiple models, combines their outputs, and produces one final prediction. The way in which the outputs of ensemble members are combined is one of the important issues affecting prediction accuracy. A variety of combination schemes have been proposed in order to improve prediction performance in ensembles. Each combination scheme has advantages and limitations, and can be influenced by domain and circumstance. Accordingly, decisions on the most appropriate combination scheme in a given domain and contingency are very difficult. This paper proposes a confidence-based selection approach as part of an ensemble bankruptcy-prediction scheme that can measure unified confidence, even if ensemble members produce different types of continuous-valued outputs. The present experimental results show that when varying the number of models to combine, according to the creation type of ensemble members, the proposed combination method offers the best performance in the ensemble having the largest number of models, even when compared with the methods most often employed in bankruptcy prediction.