• The Korean Journal of Community Living Science
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• v.21 no.2
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• pp.191-200
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• 2010

The purpose of this study was to research the differences between gender roles and creativity. This study was done based on 178 pre-service teachers who were from the Department of Early Childhood Education in Universities around the Busan area. The researchers have collected statistical data by questioning pre-service teachers about creative thinking tests, creative personality tests, and gender role identification awareness tests. The data was interpreted by the Paerson's Simple Product-moment Correlation Coefficient method, the one-way ANOVA method, and the $Sch\acute{e}ffe$ Post-hoc comparison method. According to this study, the group perceived of high androgyny type group showed the highest level in important factors of creative thinking, such as fluency, elaborateness, ness, and openness. This result meant that the more a pre-service teacher was aware of the identity of gender roles, the more she or he thought creatively. Additionally, the acceptance of authority, an element of the creative personality factor, showed the highest level in a high feminity type group. On the other hand, self confidence, inquisitiveness, and disciplined imagination showed the highest level in a group which perceived the identity of androgyny type roles.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.4
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• pp.580-585
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• 2016

The objective of this study was to determine cow characteristics and farm management factors during the dry period associated with early postparturient intramammary infection (IMI) and subsequent clinical mastitis (CM). Data were collected three times: before drying off (P1), during the dry period (P2), and 5 to 14 days after calving (P3), using questionnaires and farm investigation. Milk samples were aseptically collected for bacterial identification at P1 and P3. Factors associated with IMI and CM were analyzed using multiple logistic regression models. The final model showed that IMI in early postpartum was significantly associated with full insertion of dry cow antibiotic, dry cows in barns with a combination of tie and free stalls, body condition score (BCS) in dry period and after calving, and milk yield before drying off. For IMI cows, factors significantly associated with clinical expression of mastitis were having daily barn cleaning, teat disinfected with alcohol before administration of dry cow therapy, BCS before drying off, milk yield before drying off, and days in milk at drying off. In conclusion, both cow and farm management factors are associated with the IMI rate and subsequent expression of clinical signs of mastitis in early postpartum cows.

• Journal of Gastric Cancer
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• v.21 no.1
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• pp.4-15
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• 2021

Recently, endoscopic screening systems have enabled the diagnosis of gastric cancer in the early stages. Early gastric cancer (EGC) is typically characterized by a shallow invasion depth and small size, which can hinder localization of EGC tumors during laparoscopic surgery. Here, we review nine recently reported tumor localization methods for the laparoscopic resection of EGCs. Preoperative dye or blood tattooing has the disadvantage of spreading. Preoperative 3-dimensional computed tomography reconstruction is not performed in real time during laparoscopic gastrectomy. Thus, they are considered to have a low accuracy. Intraoperative portable abdominal radiography and intraoperative laparoscopic ultrasonography methods can provide real-time feedback, but these methods require expertise, and it can be difficult to define the clips in some gastric regions. Despite a few limitations, intraoperative gastrofibroscopy provides real-time feedback with high accuracy. The detection system using an endoscopic magnetic marking clip, fluorescent clip, and radio-frequency identification detection system clip is considered highly accurate and provides real-time feedback; we expect a commercial version of this setup to be available in the near future. However, there is not yet an easy method for accurate real-time detection. We hope that improved devices will soon be developed and used in clinical settings.

• Journal of Oral Medicine and Pain
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• v.21 no.2
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• pp.225-242
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• 1996

The author studied to determine the sex and age of 8 ancient human skeletal remains, which had excavated from ancient tombs located in Yeanri, Kimhae. Some kinds of personal identification methods their skulls and teeth were used for this study and the results were obtained as follows : 1. Sex determination was possible in ancient teeth from 4th to 5th century, using detection of X-Y homologous amelogenin gene by polymerase chain reaction. 2. DNA analysis proved that the materials examined were all male, but which always did not coincide with the results from other methods for sex determination including comparison of sexual differentiation of cranium and teeth and use of discriminant functions in the dental measurement. 3. There was little difference of the estimated ages between the methods by regression of pulp cavity and attrition in teeth. The ages from these two methods always did not coincide with ones from evaluation closure of cranial and palatal sutures. 4. Sex and age of the materials were determined as follows ; $\cdot$ Y9 was estimated to be male in early sixties. $\cdot$ Yl2 was estimated to be male in late twenties to early thirties. $\cdot$ Y37 was estimated to be male in early forties. $\cdot$ Y70 was estimated to be male in early sixties. $\cdot$ Y87 was estimated to be male in late forties. $\cdot$ Y109 was estimated to be male in early forties. $\cdot$ Yl29 was estimated to be male in late thirties to early forties. $\cdot$ Yl42 was estimated to be male in late fifties to early sixties.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.1-18
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• 2017

Recently, identification of the extremely stressed condition of children is an essential skill for real-time recognition of a dangerous situation because incidents of children have been dramatically increased. In this paper, therefore, we present a model based on machine learning techniques for stress status identification of a child by using bio-signals such as voice and heart rate that are major factors for presenting a child's emotion. In addition, a smart band for collecting such bio-signals and a mobile application for monitoring child's stress status are also suggested. Specifically, the proposed method utilizes stress patterns of children that are obtained in advance for the purpose of training stress status identification model. Then, the model is used to predict the current stress status for a child and is designed based on conventional machine learning algorithms. The experiment results conducted by using a real-world dataset showed that the possibility of automated detection of a child's stress status with a satisfactory level of accuracy. Furthermore, the research results are expected to be used for preventing child's dangerous situations.

• ETRI Journal
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• v.30 no.2
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• pp.183-193
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• 2008

In this paper, we propose quality of service mechanisms for flow-based routers which have to handle several million flows at wire speed in high-speed networks. Traffic management mechanisms are proposed for guaranteed traffic and non-guaranteed traffic separately, and then the effective harmonization of the two mechanisms is introduced for real networks in which both traffic types are mixed together. A simple non-work-conserving fair queuing algorithm is proposed for guaranteed traffic, and an adaptive flow-based random early drop algorithm is proposed for non-guaranteed traffic. Based on that basic architecture, we propose a dynamic traffic identification method to dynamically prioritize traffic according to the traffic characteristics of applications. In a high-speed router system, the dynamic traffic identification method could be a good alternative to deep packet inspection, which requires handling of the IP packet header and payload. Through numerical analysis, simulation, and a real system experiment, we demonstrate the performance of the proposed mechanisms.

• Korean Journal of Clinical Laboratory Science
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• v.38 no.3
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• pp.158-165
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• 2006

Although Mycobacterium tuberculosis complex strains remain responsible for the majority of diseases caused by mycobacterial infections worldwide, the increase in HIV infections has allowed for the emergence of other non-tuberculous mycobacteria as clinically significant pathogens. However, Mycobacterium species has a long period of incubation, and requires serious biochemical tests such as niacin, catalase, and nitrate test that are often tedious. The development of rapid and accurate diagnostics can aid in the early diagnosis of disease caused by Mycobacterium. The current DNA amplification and hybridization methods that have been developed target several genes for the detection of mycobacterial species such as hps65, 16S rDNA, rpoB, and dnaj. These methods produce rapid and accurate results. In this study, PCR-restriction fragment length polymorphism analysis(PCR-RFLP) based on the region of the rpoB gene was used to verify the identification of non-tuburculosis Mycobacterium species. A total of 8 mycobacterial reference strains and 13 clinical isolates were digested with restriction enzymes such as Msp I in this study. The results of using this process clearly demonstrated that all 13 specimens were identified by rpoB gene PRA method. The PCR-RFLP method based on the rpoB gene is a simple, rapid, and accurate test for the identification of Mycobacterium.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.1024-1031
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• 2019

The Molten Salt Fast Reactor (MSFR) with its liquid circulating fuel and its fast neutron spectrum calls for a new safety approach including technological neutral methodologies and analysis tools adapted to early design phases. In the frame of the Horizon2020 program SAMOFAR (Safety Assessment of the Molten Salt Fast Reactor) a safety approach suitable for Molten Salt Reactors is being developed and applied to the MSFR. After a description of the MSFR reference design, this paper focuses on the identification of the Postulated Initiating Events (PIEs), which is a core part of the global assessment methodology. To fulfil this task, the Functional Failure Mode and Effect Analysis (FFMEA) and the Master Logic Diagram (MLD) are selected and employed separately in order to be as exhaustive as possible in the identification of the initiating events of the system. Finally, an extract of the list of PIEs, selected as the most representative events resulting from the implementation of both methods, is presented to illustrate the methodology and some of the outcomes of the methods are compared in order to highlight symbioses and differences between the MLD and the FFMEA.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.799-808
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• 2017

Failure of a redundant long-span bridge is often described by innumerable failure modes, which make the structural system reliability analysis become a computationally intractable work. In this paper, an innovative procedure is proposed to efficiently identify the dominant failure modes and quantify the structural reliability for a long-span bridge system. The procedure is programmed by ANSYS and MATLAB. Considering the correlation between failure paths, a new branch and bound operation criteria is applied to the traditional stage critical strength branch and bound algorithm. Computational effort can be saved by ignoring the redundant failure paths as early as possible. The reliability of dominant failure mode is computed by FORM, since the limit state function of failure mode can be expressed by the final stage critical strength. PNET method and FORM for system are suggested to be the suitable calculation method for the bridge system reliability. By applying the procedure to a CFST arch bridge, the proposed method is demonstrated suitable to the system reliability analysis for long-span bridge structure.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.401-405
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• 1993

This paper presents a neuro adaptive control method for nonlinear dynamical systems based on artificial neural network systems. The proposed neuro adaptive controller consists of 3 layers artificial neural network system and parallel PD controller. At the early stage in learning or identification process of the system characteristics the PD controller works mainly in order to compensate for the inadequacy of the learning process and then gradually the neuro contrller begins to work instead of the PD controller after the learning process has proceeded. From the simulation studies the neuro adaptive controller is seen to be robust and works effectively for nonlinear dynamical systems from a practical applicational points of view.