• Journal of Korean Institute of Industrial Engineers
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• v.7 no.1
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• pp.5-11
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• 1981

In the case of numerical implementation, the exact solution method for the M/M/s system where customers demand multiple server use [2] reveals limitations, if a system has large number of servers or types of customers. This is due to the huge matrices involved in the course of the calculations. This paper offers an approximation scheme for such cases. Capitalizing the characteristics of the service rate curve of the system, this method approximates the service rate as a piecewise linear function. With the service rates obtained from the linear function for each number of customers n (n=0. 1. 2,$\cdots$), ${\mu}(n)$, steady-state probabilities and measures of performance are found treating this system as an ordinary M/M/s system. This scheme performs well when the traffic intensity of a system is below about 0.8. Some numerical examples are presented.

• Earthquakes and Structures
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• v.2 no.1
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• pp.25-42
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• 2011

This paper discusses a mechanical model for the vulnerability assessment of old masonry building aggregates that takes into account the uncertainties inherent to the building parameters, to the seismic demand and to the model error. The structural capacity is represented as an analytical function of a selected number of geometrical and mechanical parameters. Applying a suitable procedure for the uncertainty propagation, the statistical moments of the capacity curve are obtained as a function of the statistical moments of the input parameters, showing the role of each one in the overall capacity definition. The seismic demand is represented by response spectra; vulnerability analysis is carried out with respect to a certain number of random limit states. Fragility curves are derived taking into account the uncertainties of each quantity involved.

• Korean Journal of Occupational Health Nursing
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• v.21 no.2
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• pp.134-144
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• 2012

Purpose: The purpose was to investigate the relations among job-stress, self-efficacy, and depression of nurses. Methods: The data were collected from a random sample of 213 nurses working in two general hospitals of a local area. A self-reported questionnaire was used to assess the level of job-stress, self-efficacy, and depression. Results: The mean score of job-stress was 49.1 and the score of job demand was the highest. The mean score of self-efficacy was 3.4, and depression was 18.2. The prevalence of depression was very high. The job-stress and depression were negatively correlated with self-efficacy. Hierarchial multiple regression showed that the self-efficacy and the high job demand, lack of reward, and organizational injustice of job-stress explained 53% of the variance for the nurses' depression. Conclusion: The findings indicated that the self-efficacy and job stress, especially job demand, organizational injustice, and lack of reward contributed to the depression. In order to prevent and decrease the depression, the developing programs to improve self-efficacy are needed.

• KIEAE Journal
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• v.8 no.6
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• pp.11-20
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• 2008

Modern society is an era that demands higher standards of living, and accordingly healthier living conditions due to fast economic growth. This society is being confronted by the necessity to find strategies to promote and manage health condition in everyday living environment. The current 'wellbeing' trend which pursues holistic health including physical, psychological and social health has accelerated the demand for healthy environment. In this context, this study intended to identify health friendly planning features based on consumer's demand. Web survey technique was used as main research methodology. Stratified random sampling was used with age being used as the strata valuable. Two hundred and eleven data were analyzed using SPSS statistical package. As results, awareness about health housing and hierarchy of important planning features were empirically identified. Furthermore, significant differences in some planning features according to the age were scrutinized. Major health friendly features demanded by consumers were found ventilation, non-toxic material, view of nature, space in which family can gather, protection of their privacy. Consumers' recognitions and demands varied according to age. The older the resident was, the higher the demands appeared. The results are expected to be used as a reference to explore and develop strategies for future healthy housing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• Safety and Health at Work
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• v.13 no.4
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• pp.469-474
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• 2022

Background: Nowadays, counter-productive work behaviors (CWBs) have turned into a common and costly position for many organizations and especially health centers. Therefore, the study was carried out to examine and compare the demand-control-support (DCS) and effort-reward imbalance (ERI) models as predictors of CWBs. Methods: The study was cross-sectional. The population was all nurses working in public hospitals in Hamadan, Iran of whom 320 were selected as the sample based on simple random sampling method. The instruments used were Job Content Questionnaire, Effort-Reward Imbalance Questionnaire, and Counterproductivity Work Behavior Questionnaire. Data were analyzed using correlation and regression analysis in SPSS18. Results: The findings indicated that both ERI and DCS models could predict CWB (p ≤ 0.05); however, the DCS model variables can explain the variance of CWB-I and CWB-O approximately 8% more than the ERI model variables and have more power in predicting these behaviors in the nursing community. Conclusion: According to the results, job stress is a key factor in the incidence of CWBs among nurses. Considering the importance and impact of each component of ERI and DCS models in the occurrence of CWBs, corrective actions can be taken to reduce their incidence in nurses.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.92-98
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• 1988

In this paper a model is developed for an inventory system in which the number of units of acceptable quality in a replenishment lot is uncertain and the demand. during the stockout period is back ordered and. also under the same condition an inventory model with experdited stockout is developed. It is assumed that the fraction of the acceptable quality in a replenishment lot is a random variable whose probability distribution is known. The optimal replenishment policy is synthesized for such a system. A numerical example is used to illustrate the theory.

• Proceedings of the Technology Innovation Conference
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• 2003.02a
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• pp.173-190
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• 2003

Demand forecasting is essential in establishing national and corporate strategy as well as the management of their resource. We forecast demand for multi-generation product using discrete choice model combining diffusion model The discrete choice model generally captures consumers'valuation of the product's qualify in the framework of a cross-sectional analysis. We incorporate diffusion effects into a discrete choice model in order to capture the dynamics of demand for multi-generation products. As an empirical application, we forecast demand for worldwide DRAM (dynamic random access memory) and each of its generations from 1999 to 2005. In so doing, we use the method of 'Technological Forecasting'for DRAM Density and Price of the generations based on the Moore's law and learning by doing, respectively. Since we perform our analysis at the market level, we adopt the inversion routine in using the discrete choice model and find that our model performs well in explaining the current market situation, and also in forecasting new product diffusion in multi-generation product markets.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.3 s.357
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• pp.43-51
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• 2007

OneNAND flash combines the advantages of NAND and NOR flash, and has become an alternative to the former. But the advanced features of OneNAND flash are not utilized effectively in demand paging systems designed for NAND flash. We propose delayed dual buffering, a demand paging system which fully exploits the random-access I/O interface and dual page buffers of OneNAND flash demand paging system. It effectively reduces the time of page transfer from the OneNAND page buffer to the main memory. On average, it achieves and 28.5% reduction in execution time and 4.4% reduction in paging system energy consumption.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.77-77
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• 2011

These days, a growing demand for memory device is filled up with the flash memory and the dynamic random access memory (DRAM). Although DRAM is a reasonable solution for current demand, the universal novel memory with high density, high speed and nonvolatility, needs to be developed. Among various new memories, the magnetic random access memory (MRAM) device is considered as one of good candidate memories because of excellent features including high density, high speed, low operating power and nonvolatility. The etching of MTJ stack which is composed of magnetic materials and insulator such as MgO is one of the vital process for MRAM. Recently, MgO has attracted great interest in the MTJ stack as tunneling barrier layer for its high tunneling magnetoresistance values. For the successful realization of high density MRAM, the etching process of MgO thin films should be investigated. Until now, there were some works devoted to the investigations on etch characteristics of MgO thin films. Initially, ion milling was applied to the etching of MgO thin films. However, ion milling has many disadvantages such as sidewall redeposition and etching damage. High density plasma etching containing the magnetically enhanced reactive ion etching and high density reactive ion etching have been employed for the improvement of etching process. In this work, inductively coupled plasma reactive ion etching (ICPRIE) system was adopted for the improvement of etching process using MgO thin films and etching gas mixes of $CH_4$/Ar and $CH_4$/$O_2$/Ar have been employed. The etch rates are measured by a surface profilometer and etch profiles are observed using field emission scanning emission microscopy (FESEM). The effects of gas concentration and etch parameters such as coil rf power, dc-bias voltage to substrate, and gas pressure on etch characteristics will be systematically explored.