• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.209-240
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• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Journal of Preventive Medicine and Public Health
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• v.52 no.3
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• pp.154-160
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• 2019

Objectives: Stillbirth is a common adverse pregnancy outcome that represents a distressing and traumatic event for women and their partners. The aim of this study was to identify factors associated with stillbirth in ever-pregnant women in Nepal. Methods: This study utilized the individual women's dataset from the Nepal Demographic and Health Survey, conducted in 2016. The dependent variable of interest was whether women had at least 1 stillbirth during their lifetime. The associations between independent variables and the dependent variable of the study were analyzed using a multiple logistic regression model. Results: Among 8918 ever-pregnant women aged 15-49 years, 488 had experienced at least 1 stillbirth during their lifetime, representing 5.5% of the total. After adjusting each factor for the confounding effects of other factors, maternal age, maternal education, place of residence, and sub-region remained significantly associated with having experienced stillbirth. Conclusions: Stillbirth continues to be a major problem among women, especially those with higher maternal age, those who are illiterate, and residents of certain geographical regions. To minimize stillbirth in Nepal, plans and policies should be focused on women with low education levels and residents of rural areas, especially in the western mountain and far-western hill regions.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.331-337
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• 2022

Smart learning is augmented with digital, context-aware, and adaptable technologies to encourage students to learn better and faster. To ensure that digital learning is successful and that implementation is efficient, it is critical that the dimensions of digital learning are arranged correctly and that interactions between the various elements are merged in an efficient and optimal manner. This paper builds and discusses a basic framework for smart learning in the digital age, aimed to improve students' abilities and performance in learning. The proposed framework consists of five dimensions: Teacher, Technology, Learner, Digital content, and Evaluation. The Teacher and Learner dimensions operate on two levels: (a) an abstract level to fit in knowledge and skills or interpersonal characteristics and (b) a concrete level in the form of digital devices used by teachers and learners. Moreover, this paper proposes asynchronous online course delivery model. An Arabic smart learning platform has been developed, based on these smart learning core dimensions and the asynchronous online course delivery model, because despite the official status of this language in many countries, there is a lack of Arabic platforms to teach Arabic. Moreover, many non-native Arabic speakers around the world have expressed an interest in learning it. The Arabic digital platform consists of over 70 lessons classified into three competence levels: beginner, intermediate, and advanced, delivered by Arabic experts and Arabic linguists from various Arab countries. The five dimensions are described for the Arabic platform in this paper. Learner dimension is the Arabic and non-Arabic speakers, Teacher dimension is Arabic experts and Arabic linguistics, Technology dimension consists of technology for Arabic platform that includes web design, cloud computing, big data, etc. The digital contents dimension consists of web-based video, records, etc. The evaluation dimension consists of Teachers rating, comments, and surveys.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.163-173
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• 2015

In this paper, it shows optimal inventory level of bicycle sharing service terminal by maintaining the lowest costs. As the interest to environment and exhaustion of resource increases globally, investment to sustainable transportation increases around advanced countries and interest to efficient transportation, managing and consuming of vehicle increases also. Vehicle sharing service is a model of rental car where customer rent cars for short periods of time often by the hour and its users are increasing for the reason that it is more convenient than car rent. In addition, bicycle sharing service is one of the major parts in vehicle sharing program and many of country are already managing it. This paper proposes optimal inventory levels of vehicle sharing service's terminal by using simulation calculating operation costs of vehicle sharing service.

• Journal of Service Research and Studies
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• v.2 no.2
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• pp.35-43
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• 2012

Data mining is an interest area in all field around us not in any specific areas, which could be used applications in a number of areas heavily. In other words, it is used in the decision-making process, data and correlation analysis in hidden relations, for finding the actionable information and prediction. But some of the data sets contains many missing values in the variables and do not exist a large number of records in the data set. In this paper, missing values are handled in accordance with the model tree algorithm. Cholesterol value is applied for predicting. For the performance analysis, experiments are approached for each treatment. Through this, efficient alternative is presented to apply the missing data.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.73-87
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• 2016

Combining power generation and water production by desalination is economically advantageous. Most desalination projects use fossil fuels as an energy source, and thus contribute to increased levels of greenhouse gases. Environmental concerns have spurred researchers to find new sources of energy for desalination plants. The coupling of nuclear power production with desalination is one of the best options to achieve growth with lower environmental impact. In this paper, we will per-form a sensitivity study of coupling nuclear power to various combinations of desalination technology: {1} thermal (MSF [Multi-Stage Flashing], MED [Multi-Effect Distillation], and MED-TVC [Multi-Effect Distillation with Thermal Vapour Compression]); {2} membrane RO [Reverse Osmosis]; and {3} hybrid (MSF-RO [Multi-Stage Flashing & Reverse Osmosis] and MED-RO [Multi-Effect Distillation & Reverse Osmosis]). The Korean designed reactor plant, the APR1400 will be modeled as the energy production facility. The economical evaluation will then be executed using the computer program DEEP (Desalination Economic Evaluation Program) as developed by the IAEA. The program has capabilities to model several types of nuclear and fossil power plants, nuclear and fossil heat sources, and thermal distillation and membrane desalination technologies. The output of DEEP includes levelized water and power costs, breakdowns of cost components, energy consumption, and net saleable power for any selected option. In this study, we will examine the APR1400 coupled with a desalination power plant in the Kingdom of Saudi Arabia (KSA) as a prototypical example. The KSA currently has approximately 20% of the installed worldwide capacity for seawater desalination. Utilities such as power and water are constructed and run by the government. Per state practice, economic evaluation for these utilities do not consider or apply interest or carrying cost. Therefore, in this paper the evaluation results will be based on two scenarios. The first one assumes the water utility is under direct government control and in this case the interest and discount rate will be set to zero. The second scenario will assume that the water utility is controlled by a private enterprise and in this case we will consider different values of interest and discount rates (4%, 8%, & 12%).

• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.109-114
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• 2003

There is an emergence of Internet applications that have real-time requirements. These applications require IP to support guaranteed capacity, higher priority and lower packet loss rate. To address this, the Internet Engineering Task Force (IETF) is developing a set of protocols and standards for Integrated Services on the Internet. Using RSVP and policies to manage the allocation of network resources in order to provide different levels of service is a topic of great interest to service providers. Currently, it is not possible to dynamically reallocate resources during an application's session. This paper discusses how policies in conjunction with new service class can provide a more enhanced network resource allocation by allowing for this dynamic reallocation.

• Research in Mathematical Education
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• v.8 no.1
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• pp.1-18
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• 2004

Current interest in mathematics learning that focuses on understanding, mathematical reasoning and meaning making underscores the need to develop ways of analyzing classrooms that foster these types of learning. In this paper, the author show that the constructs of social and socio-mathematical norms, which grew out of taking a symbolic interactionist perspective, and Toulmins scheme for argumentation, as elaborated for mathematics education by Krummheuer [The ethnology of argumentation. In: The emergence of mathematical meaning: Interaction in classroom cultures (1995, pp. 229-269). Hillsdale, NJ: Erlbaum], provide us with means to analyze aspects of explanation, justification and argumentation in mathematics classrooms, including means through which they can be fostered. Examples from a variety of classrooms are used to clarify how these notions can inform instruction at all levels, from the elementary grades through university-level mathematics.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.210-214
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• 2002

Association rule mining is an exploratory learning task to discover some hidden dependency relationships among items in transaction data. Quantitative association rules denote association rules with both categorical and quantitative attributes. There have been several works on quantitative association rule mining such as the application of fuzzy techniques to quantitative association rule mining, the generalized association rule mining for quantitative association rules, and importance weight incorporation into association rule mining fer taking into account the users interest. This paper introduces a new method for generalized fuzzy quantitative association rule mining with importance weights. The method uses fuzzy concept hierarchies fer categorical attributes and generalization hierarchies of fuzzy linguistic terms fur quantitative attributes. It enables the users to flexibly perform the association rule mining by controlling the generalization levels for attributes and the importance weights f3r attributes.

• Journal of Korean Society for Quality Management
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• v.8 no.1
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• pp.3-7
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• 1980

In many industrial processes, there are more than two responses (i.e., yield, percent impurity, etc.) of interest, and it is desirable to determine the optimal levels of the factors (i.e., temperature, pressure, etc.) that influence the responses. Suppose the response relationships are assumed to be approximated by second-order polynomial regression models. The problems considered in this paper is, first, to propose how to select polynomial terms to fit the multivariate regression surfaces for a given set of data, and, second, to propose how to analyze the data to obtain an optimal operating condition for the factors. The proposed techniques were applied for empirical process optimization in a tire company in Korea. This case is presented as an illustration.