• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1496-1515
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• 2017

One of the most visible developments in Decision Support Systems (DSS) was the emergence of rule-based expert systems. Hence, despite their success in many sectors, developers of Medical Rule-Based Systems have met several critical problems. Firstly, the rules are related to a clearly stated subject. Secondly, a rule-based system can only learn by updating of its rule-base, since it requires explicit knowledge of the used domain. Solutions to these problems have been sought through improved techniques and tools, improved development paradigms, knowledge modeling languages and ontology, as well as advanced reasoning techniques such as case-based reasoning (CBR) which is well suited to provide decision support in the healthcare setting. However, using CBR reveals some drawbacks, mainly in its interrelated tasks: the retrieval and the adaptation. For the retrieval task, a major drawback raises when several similar cases are found and consequently several solutions. Hence, a choice for the best solution must be done. To overcome these limitations, numerous useful works related to the retrieval task were conducted with simple and convenient procedures or by combining CBR with other techniques. Through this paper, we provide a combining approach using the multi-criteria analysis (MCA) to help, the traditional retrieval task of CBR, in choosing the best solution. Afterwards, we integrate this approach in a decision model to support medical decision. We present, also, some preliminary results and suggestions to extend our approach.

• Journal of Distribution Science
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• v.19 no.12
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• pp.23-32
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• 2021

Purpose: By integrating multiple separate online, offline distribution channels, omnichannel distribution has modernized and revolutionized the retailing sector. Omnichannel distribution supports firms by delivering seamless shopping experiences for customers throughout all touchpoints of the shopping journey. This paper aims at exploring the impact of channel integration quality on customer experience and patronage intentions in the omnichannel distribution context. Research design, data and methodology: An online survey was taken with 351 omnichannel experienced shoppers by utilizing the structured questionnaire. The partial least square-structural equation modeling (PLS-SEM) and Smart PLS software were employed to analyze and test proposed hypotheses. Results: The findings reveal that channel integration quality dimensions including breadth of channel-service choice, transparency of channel-service configuration, content consistency, and process consistency, play crucial roles in the customer shopping experience. The perceived compatibility has been influenced by the integrated interactions in which content consistency and process consistency. The findings also demonstrate the positive and direct impact of perceived compatibility on customer experience, and both factors have substantial effects on customers' patronage intentions. Conclusions: This study sheds light on the literature on channel integration quality, omnichannel retailing experience and customer patronage. In addition, this study provides practical implications for omnichannel retailers in enhancing customer experience and patronage.

• Journal of Engineering Education Research
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• v.22 no.4
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• pp.32-42
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• 2019

This study is aim to the effects of job satisfaction on the major satisfaction of science and engineering college students and also analyzed the mediating effects of future outlook of job and major relevance in career choice. To do this, structural equation modeling(SEM) and multi-group SEM were applied to data from 2016 Graduate Occupational Mobility Survey(GOMS). In the results of this study, the major satisfaction, future outlook of job and major relevance were positive effects on job satisfaction and the mediating effects of future outlook of job and major relevance were verified. And results of analysis according to gender difference, the coefficient of woman was smaller than man. Among major satisfaction had a positive effect on job satisfaction, job satisfaction fell for women who value their relevance to the major when choosing a job. Based on such results, universities need to further strengthen their role in helping them enhance their expertise through skills and learning about their majors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.213-219
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• 2018

Mechanical components are to be produced with accurate dimensions in order to function properly in assemblies of a machine. Once designs of mechanical components are created, designers examine the designs by adopting many known experimental methods. A primary test method includes stress and strain evaluation of structural parts. In addition, fatigue test and vibration analysis are an important test method for mechanical components. Real experiments at a laboratory are established when products are manufactured. Since design changes should be done before producing the designs in factories, rapid modifications for new designs are required in production industries. FEM simulation is a proper choice for a design evaluation with speed at a detail stage in design process. This research focuses modeling and mechanical simulation of a mechanical component in order to ensure structural safety. In this paper, a universal joint, being used in driving axels of vehicles, is studied as a target component. A design model is created and tested in some ways by using commercial software of FEM. The designed component is being twisted to transmit heavy power and thus, torsional stress should be under strengths of the component's material. The next is fatigue analysis to convince fatigue cycles to be within the endurance limit of the material. Another test is a vibration analysis for rotational components. This research draws final conclusions from these test analyses and recommends whether the designed model is under safety condition in terms of mechanical structure.

• Journal of Distribution Science
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• v.18 no.12
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• pp.31-43
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• 2020

Purpose: This study examined how many determinant factors (service dimensions, food quality, and price perception) affect revisit intention. This practical concept is service quality (SERVQUAL), customer satisfaction, and repeated/revisit behavioral intention based on the theory of reasoned action (TRA). Research design, data and methodology: This research applied a hybrid mixed-method comprising exploratory and explanatory sequential design by Creswell (2014). The 400 responses were collected in four townships in Myanmar. This study drilled down to exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA) prior to test the hypothesized factor structure of all the variables resulted in the form of the goodness of fit. For further data analysis, structural equation modeling (SEM) was applied to test the relationships among the variables of the proposed model. Results: The results showed that perceived service quality, food quality, and price perception have direct effects on customer satisfaction and indirect effect on revisit intention. The perceived service quality has the most significant influence while the food quality has the least influence on customer satisfaction. Conclusions: The results are useful for the restaurant managers to better understand the significant strategic choice factors to improve higher quality service amongst restaurants both domestic and international under the stiff competition.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.817-825
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• 2022

A recent benchmarking effort, under the auspices of the Organization for Economic Cooperation and Development (OECD) Nuclear Energy Agency (NEA), has been made to evaluate the current state of modeling and simulation tools available to model fluoride salt-cooled high temperature reactors (FHRs). The FHR benchmarking effort considered in this work consists of several cases evaluating the neutronic parameters of a 2D prismatic FHR fuel assembly model using the participants' choice of simulation tools. Benchmark participants blindly submitted results for comparison with overall good agreement, except for some which significantly differed on cases utilizing a molybdenum-bearing control rod. Participants utilizing more recently updated explicit isotopic cross sections had consistent results, whereas those using elemental molybdenum cross sections observed reactivity differences on the order of thousands of pcm relative to their peers. Through a series of supporting tests, the authors attribute the differences as being nuclear data driven from using older legacy elemental molybdenum cross sections. Quantitative analysis is conducted on the control rod to identify spectral, reaction rate, and cross section phenomena responsible for the observed differences. Results confirm the observed differences are attributable to the use of elemental cross sections which overestimate the reaction rates in strong resonance channels.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.291-309
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• 2023

Longitudinal count data has been widely collected in biomedical research, public health, and clinical trials. These repeated measurements over time on the same subjects need to account for an appropriate dependency. The Poisson regression model is the first choice to model the expected count of interest, however, this may not be an appropriate when data exhibit over-dispersion or under-dispersion. Recently, Conway-Maxwell-Poisson (CMP) distribution is popularly used as the distribution offers a flexibility to capture a wide range of dispersion in the data. In this article, we propose a Bayesian CMP regression model to accommodate over and under-dispersion in modeling longitudinal count data. Specifically, we develop a regression model with random intercept and slope to capture subject heterogeneity and estimate covariate effects to be different across subjects. We implement a Bayesian computation via Hamiltonian MCMC (HMCMC) algorithm for posterior sampling. We then compute Bayesian model assessment measures for model comparison. Simulation studies are conducted to assess the accuracy and effectiveness of our methodology. The usefulness of the proposed methodology is demonstrated by a well-known example of epilepsy data.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.1-11
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• 2022

The study incorporates model uncertainty into the private equity (PE) valuation model (SWY model) (Sorensen et al., 2014) to evaluate how model uncertainty distorts the leverage and valuations of PE funds. This study applies a continuous-time model to PE project valuation, modeling the LPs' goal as multiplier preferences provided by Anderson et al. (2003), and assuming that LPs' aversion to model uncertainty causes endogenous belief distortions with entropy as a measure of model discrepancies. Concerns regarding model uncertainty, according to the theoretical model, have an unclear effect on LPs' risk attitude and GPs' decision, which is based on the value of the PE asset. It also demonstrates that model uncertainty lowers the certainty-equivalent valuation of the LPs. Finally, we compare the outcomes of the Full-spanning risk model with the Non-spanned risk model, and they match the intuitive economic reasoning. The most important implication is that model uncertainty will have negative effects on the LPs' certainty-equivalent valuation but has ambiguous effects on the portfolio allocation choice of liquid wealth. Our works contribute to two literature streams. The first is the literature that models the PE funds. The second is the literature introduces model uncertainty into standard finance models.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.2
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• pp.23-29
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• 2024

Purpose: This study aims to investigate consumer attitudes towards healthy foods, focusing on low-calorie options, and their impact on purchasing behavior. Methods: The study utilizes structural equation modeling, which incorporates statistical tools such as SPSS and AMOS for thorough analysis. This involves collecting data over a period of time and then inferring patterns and relationships through correlation and trend analysis. Results: The study found that attributes such as quality, price, functional value, and emotional value have a significant impact on customer satisfaction and repurchase intentions, but not on nutrition and brand. The study provides a comprehensive understanding of the factors that influence consumer attitudes and purchase behavior toward healthy indulgences in the context of low-calorie foods, and has important implications for both academic research and practical marketing strategies. Conclusions and Implications: This study provides new insights into consumer behavior theory by validating the impact of the perceived value of low-calorie products on attitudes and purchase behavior, which is of great academic value. It is also expected to provide useful information for the formulation of effective marketing strategies for low-calorie products and the development of products that meet consumer needs.

• Journal of the Korean Society for Precision Engineering
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• v.3 no.1
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• pp.40-49
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• 1986

Crack, craze and void are common defects which may be found in the bulk of polymeric materials such as either themoplastics or thermosets. The healing phenomena, autohesion, of these defects are known to be a intrinsic material property of various polymeric materials. However, only a few experimental and theoretical investigations on crack, void and craze healing phenomena for various polymeric materials have been reported up to date [1, 2, 3]. This may be partly due to the complications of healing processes and lacking of appropriate theoretical developments. Recently, some investigators have been urged to study the healing phenomena of various polymenic materials since the significance of the use of polymer based alloys or composites has been raised in terms of specific strength and energy saving. In the earlier published reports [1, 2, 3, 4], the crack and void healing velocity, healing toughness and some other healing mechanical and physical properties were measured experimentally and compared with predicted values by utilizing a simple model such as the reptation model under some resonable assumptions. It seems, however, that the general acceptance of the proposed modeling analyses is yet open question. The crack healing processes seem to be complicate and highly dependent on the state of virgin material in terms of mechanical and physical properties. Furthermore, it is also strongly dependent on the histories of crack, craze and void development including fracture suface morphology, the shape of void and the degree of disentanglement of fibril in the craze. The rate of crack healing may be a function of environmental factors such as healing temperature, time and pressure which gives different contact configurations between two separated surfaces. It seems to be reasonable to assume that the crack healing processes may be divided in several distinguished steps like stress relaxation with molecular chain arrangement, surface contact (wetting), inter- diffusion process and com;oete healing (to obtain the original strength). In this context, it is likely that we no longer have to accept the limitation of cumulative damage theories and fatigue life if it is probable to remove the defects such as crack, craze and void and to restore the original strength of polymers or polymer based compowites by suitable choice of healing histories and methods. In this paper, we wish to present a very simple and intuitive theoretical model for the prediction of healed fracture toughness of cracked or defective polymeric components. The central idea of this investigation, thus, may be the modeling of behavior of chain molecules under healing conditions including the effects of chain scission on the healing processes. The validity of this proposed model will be studied by making comparisons between theoretically predicted values and experimentally determined results in near future and will be reported elsewhere.