• 대한간호학회지
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• 제33권1호
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• pp.17-25
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• 2003

Purpose: The purpose of this study was to identified the male nurses' encounter in adapting themselves in the hospital settings dominated by the female nurses in number. Method: Data were collected through the in-depth interview of 16 male nurses and analysed through the grounded theory methodology. Result: The behaviors of have made tremendous for job-adaptation can be summarized as a series of struggles to consolidate their own ground. They have made tremendous efforts to hold their own ground in the nursing profession composed of a large numbers of female nurses, while they have experienced many difficulties and problems as minorities. They have struggled to adapt themselves professionally through efforts such as; challenging the social and professional barriers, identifying the job identity, empowering themselves through self-development and dedication, expanding their influence among colleagues. In spite of these efforts, they had the perception that nursing is not a lifelong occupation for them. Thus, they had tendency to find outlets of change to occupations. Conclusion: A specific strategy is needed to provide an environment that is helpful for males in integrating into and adapting to the nursing profession.

• 동아시아경상학회지
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• 제5권2호
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• pp.38-47
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• 2017

In today's highly unpredictable marketing environment, where the consumer demands and behaviors are continuously and rapidly changing therefore various factors of consumer impulse buying behavior are proving to be challenging for the existing and new business organizations. Shopping has become a relaxing and rejoicing activity for the consumers making impulsive buying as a socially acceptable and common practice. So by taking into account all these aspects, the objective of this study was to understand the factors affecting impulse buying behavior of the consumer. Store atmosphere and fashion involvement were selected as independent variables while consumer impulse buying behavior was taken as dependent variable for this study. Likewise, impulse buying behavior of consumers with different monthly household income was also analyzed in this study. Primary data was collected through a questionnaire from 250 respondents of district Faisalabad, and then it was analyzed by using various statistical techniques. The results indicated a significant positive impact of store atmosphere and fashion involvement on consumer impulse buying behavior. The study also revealed that among consumer groups with different household incomes; at least one group differed from others in impulse buying behavior. These results were consistent with previous literature. These results could provide information to the marketers and retailers for planning and execution of various marketing techniques. Moreover, educators could expand on the findings by developing new studies examining consumer impulse buying behavior.

• 대한임베디드공학회논문지
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• 제3권1호
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• pp.19-24
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• 2008

To reduce time-to-market, more and more embedded system developers and system-on-chip designers rely on microprocessor-based design methodology. ARM processor has been a major player in this industry over the last 10 years. However, there are many restrictions on developing embedded software using ARM processor in the early design stage. For those who are not familiar with embedded software development environment or who cannot afford to have an expensive embedded hardware equipment, testing their software on a real ARM hardware platform is a challenging job. To overcome such a problem, we have designed VMA (Virtual ARM Machine), which offers easier testing and debugging environment to ARM based embedded system developers. Major benefits that can be achieved by utilizing a virtual ARM platform are (1) reducing development cost, (2) lowering the entrance barrier for embedded system novices, and (3) making it easier to test and debug embedded software designs. Unlike many other purely software-oriented ARM simulators which are independent of real hardware platforms, VMA is specifically targeted on SYS-Lab 5000 ARM hardware platform, (designed by Libertron, Inc.), which means that VMA imitates behaviors of embedded software as if the software is running on the target embedded hardware as closely as possible. This paper will describe how VMA is designed and how VMA can be used to reduce design time and cost.

• ETRI Journal
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• 제43권1호
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

• BMB Reports
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• 제55권5호
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• pp.238-243
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• 2022

Autism or autism spectrum disorder (ASD) is a behavioral syndrome characterized by persistent deficits in social interaction, and repetitive patterns of behavior, interests, or activities. The gene encoding Methyl-CpG binding protein 2 (MeCP2) is one of a few exceptional genes of established causal effect in ASD. Although genetically engineered mice studies may shed light on how MeCP2 loss affects synaptic activity patterns across the whole brain, such studies are not considered practical in ASD patients due to the overall level of impairment, and are technically challenging in mice. For the first time, we show that hippocampal MeCP2 knockdown produces behavioral abnormalities associated with autism-like traits in rats, providing a new strategy to investigate the efficacy of therapeutics in ASD. Ketamine, an N-Methyl-D-aspartate (NMDA) blocker, has been proposed as a possible treatment for autism. Using the MeCP2 knockdown rats in conjunction with a rat model of valproic acid (VPA)-induced ASD, we examined gene expression and ASD behaviors upon ketamine treatment. We report that the core symptoms of autism in MeCP2 knockdown rats with social impairment recovered dramatically following a single treatment with ketamine.

• 한국지진공학회논문집
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• 제26권6호
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• pp.227-235
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• 2022

For a member model in nonlinear structural analysis, a lumped plastic model that idealizes its flexural bending, shear, and axial behaviors by springs with the nonlinear hysteretic model is widely adopted because of its simplicity and transparency compared to the other rigorous finite element methods. On the other hand, a challenging task in its numerical solution is to satisfy the equilibrium condition between nonlinear flexural bending and shear springs connected in series. Since the local forces between flexural and shear springs are not balanced when one or both springs experience stiffness changes (e.g., cracking, yielding, and unloading), the additional unbalanced force due to overshooting or undershooting each spring force is also generated. This paper introduces an iterative scheme for numerical solutions satisfying the equilibrium conditions between flexural bending and shear springs. The effect of equilibrium iteration on analysis results is shown by comparing the results obtained from the proposed method to those from the conventional scheme, where the equilibrium condition is not perfectly satisfied.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1892-1900
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• 2023

A protective oxide layer forms on the material surfaces of a Nuclear Power Plant during operation due to high temperature. These oxides can host radionuclides, the activated corrosion products of fission products, resulting in decommissioning workers' exposure. These deposited oxides are iron oxides such as Fe₃O₄, Fe₂O₃ and mixed ferrites such as nickel ferrites, chromium ferrites, and cobalt ferrites. Developing a new chemical decontamination technology for domestic CANDU-type reactors is challenging due to variations in oxide compositions from different structural materials in a Pressurized Water Reactor (PWR) system. The Korea Atomic Energy Research Institute (KAERI) has already developed a chemical decontamination process for PWRs called 'HyBRID' (Hydrazine-Based Reductive metal Ion Decontamination) that does not use organic acids or organic chelating agents at all. As the first step to developing a new chemical decontamination technology for the Pressurized Heavy Water Reactor (PHWR) system, we investigated magnetite dissolution behaviors in various HyBRID inorganic acidic solutions to assess their applicability to the PHWR reactor system, which forms a thicker oxide film.

• 한국분말재료학회지
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• 제30권3호
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• pp.223-232
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• 2023

Metal additive manufacturing (AM) has transformed conventional manufacturing processes by offering unprecedented opportunities for design innovation, reduced lead times, and cost-effective production. Aluminum alloy, a material used in metal 3D printing, is a representative lightweight structural material known for its high specific strength and corrosion resistance. Consequently, there is an increasing demand for 3D printed aluminum alloy components across industries, including aerospace, transportation, and consumer goods. To meet this demand, research on alloys and process conditions that satisfy the specific requirement of each industry is necessary. However, 3D printing processes exhibit different behaviors of alloy elements owing to rapid thermal dynamics, making it challenging to predict the microstructure and properties. In this study, we gathered published data on the relationship between alloy composition, processing conditions, and properties. Furthermore, we conducted a sensitivity analysis on the effects of the process variables on the density and hardness of aluminum alloys used in additive manufacturing.

• Educational Technology International
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• 제15권2호
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.

• 한국지진공학회논문집
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• 제27권6호
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• pp.275-281
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• 2023

The demand for high-strength steel is rising due to its economic efficiency. Low-cycle fatigue (LCF) tests have been conducted to investigate the nonlinear behaviors of high-strength steel. Accurate material models must be used to obtain reliable results on seismic performance evaluation using numerical analyses. This study uses the combined hardening model to simulate the LCF behavior of high-strength steel. However, it is challenging and complex to determine material model parameters for specific high-strength steel because a highly nonlinear equation is used in the model, and several parameters need to be resolved. This study used the particle swarm algorithm (PSO) to determine the model parameters based on the LCF test data of HSA 650 steel. It is shown that the model with parameter values selected from the PSO accurately simulates the measured LCF curves.