Search results

The purpose of this paper is to establish an automated microscopic imaging database system using a set of Radio Frequency Identification (RFID) management functions to provide a secure storage for hispathology images.

The automated microscopy imaging system is composed mainly of four parts, which include: first, tissue biopsy image acquisition system, second, image processing system, third, RFID system, and fourth, SQL database system. The system has two modes of operation to store and manage hispathology images. First, the hispathology slide undergoes fluorescence staining before acquiring images directly from an external CCD camera connected to the system. Second, the hispathogical slides that have undergone fluorescence staining undergo another microscopic imaging system, and the contents are extracted into a digitized image archive and imported to the system. Also, the system not only acquires images but also performs functions such as displacement correction, image superimposition, and calculation of the total number of fluorescence points. The two methods mentioned above produce the hispathology image files and are tagged using an RFID string index to establish and manage the database system.

The results demonstrated that in the impurities were effectively eliminated in the red fluorescence staining after binarization processing. However, the blue ones remained the same and to solve this problem an adjustable threshold allows users to select the appropriate threshold. Using an additional eigenvalue code to the RFID string provides better encryption mechanism for the patient files and any attempt to tamper the file can easily be detected through the comparison of the eigenvalues.

This paper proposes a novel method to implement a more comprehensive, safe, fast, and automated management system for hispathological images using RFID management and image processing techniques. Additional security is provided by including eigenvalues as encryption mechanisms in the Tag string of the RFID.

The purpose of this paper is to investigate the effects of an exercise education intervention on exercise behavior, depression and fatigue status of chronic kidney disease (CKD) patients.

This was a pilot study using an exercise education program as an intervention for CKD patients. The authors used the transtheoretical model (TTM) to design the exercise education programs. A total of 94 subjects diagnosed with CKD at a medical center in Taiwan participated in this quasi‐experimental study. Subjects were randomly divided into the experimental group (n=45) and the control group (n=49). The education program included written materials and teaching activities designed to encourage participants to initiate and continue regular exercise. Both groups took the pre‐test and post‐test containing a depression inventory, a fatigue scale and an exercise behavior inventory.

The findings indicated that changes in the exercise behavior, depression and fatigue status of the experimental group were statistically significant after the exercise education intervention compared with the control group.

The paper demonstrates that exercise education intervention can be administered by nursing staff, or a health educator, to encourage patients to exercise in order to enhance their quality of care.

The purpose of this paper is to study how relationship marketing can reduce cognitive dissonance in post-purchase stage and, thereby, increase customer satisfaction and encourage loyalty under mediating roles of trust and cognitive dissonance.

Based on a survey on consumers of cell phones, the authors tested the effects of relationship marketing on cognitive dissonance and then customer satisfaction, behavioural, and attitudinal loyalty, using structural equation modelling.

The results indicate that, thanks to relationship marketing, consumers undertook less cognitive dissonance in post-purchase stage. Thus, as consumers faced less cognitive dissonance, they represented more satisfaction and thereby behavioural and attitudinal loyalty. Additionally, the study confirmed the mediating role of trust and cognitive dissonance.

The results show that when brands and retailers make their ties with their customers stronger and encourage trust, they can discourage cognitive dissonance in post-purchase stage and thereby encourage customer satisfaction and behavioural and attitudinal loyalty.

Literature on post-purchase behaviour and cognitive dissonance shows how cognitive dissonance can reduce post-purchase satisfaction. Our research adds to the literature of both relationship marketing and post-purchase behaviour.

With the development of economy, China’s OFDI constantly increase in recent year. Meanwhile, OFDI has spillover effect on economic development and technological development of home country. Thus, accurate OFDI prediction is a prerequisite for the effective development of international investment strategies. The purpose of this paper is to predict China’s OFDI accurately using a novel multivariable grey prediction model with Fourier series.

This paper applied a multivariable grey prediction model, GM(1,N), to forecast China’s OFDI. In order to improve the prediction accuracy and without changing local characteristics of grey model prediction, this paper proposed a novel grey prediction model to improve the performance of the traditional GM(1,N) model by combining with residual modification model using GM(1,1) model and Fourier series.

The coefficients indicate that the export and GDP have positive influence on China’s OFDI, and, according to the prediction result, China’s OFDI shows a growing trend in next five years.

This paper proposed an effective multivariable grey prediction model that combined the traditional GM(1,N) model with a residual modification model in order to predict China’s OFDI. Accurate forecasting of OFDI provides reference for the Chinese Government to implement international investment strategies.

This work seeks to analyze the heat transfer phenomena of anisotropic thermal conductivity fabrics containing electric conductive yarns.

A numerical program, based on a spectral element method, is used to assess the heating fabric with a temperature control model. The study determines suitable parameters for the fabric by evaluating the temperature uniformity on the fabric surface. Effective thermal conductivities of the fabric are obtained by comparing the experimental and numerical results with each other, using a nonlinear least‐square fitting method.

The results indicate that employing high effective thermal conductivity of non‐electric conductive yarns in a direction perpendicular to electric conductive yarns helps to increase temperature uniformity. However, the effect of the high effective thermal conductivity of electric conductive yarns is not evident. Adopting a short distance between the electric conductive yarns and a thick fabric is also beneficial in increasing temperature uniformity. If the heating fabric is applied in a place where there is easy energy transfer between the surface of the fabric and moving air, collocation with high heating power is needed to maintain the temperature. Choosing an appropriate heating source is essential when considering temperature uniformity and energy savings using a temperature controller.

The findings will be useful in the design of heating fabrics.

Understanding the computer-virus propagation is quite essential for the construction and development of anti-virus policy. While researches about the anti-virus policy have been extensively investigated, the viewpoint from sociological perspective is relatively ignored. Therefore, this paper aims to explore the dynamics of computer-virus propagation and evaluate the effectiveness of anti-virus policies through the sociological perspective.

This research constructs a virus-propagation model based on the susceptible-exposed-infective-recovered epidemic concept to simulate and explore the dynamic behavior of multipartite computer viruses through the tool of system dynamics. The effectiveness of various anti-virus policies is then evaluated via this model.

The frequency of media contact has a significant effect on the virus infection rate. The effectiveness of user self-prevention relies on the usefulness of the virus signatures. The reporting/alarm process can enhance the capability of anti-virus software company and the detected intensity of new threat. The quarantine policy can effectively reduce the spread of computer virus.

Individuals should strengthen the self-awareness of information security to reduce the negative impact. Managers should construct and implement the information security norm to regulate the behavior of staff. Anti-virus software companies should strengthen the capability of their automatic reporting/alarm mechanism to early detect the exceptional conditions and control new threats in time.

Information security management research is still in the growth phase, but it is critically important to establish the groundwork for understanding of computer viruses and the effectiveness of anti-virus policy from assorted perspectives. The major contribution of research is to explore the propagation of multipartite computer viruses and study how to prevent their destruction from the sociological and technical perspectives.

No carbon gas is released into the atmosphere in electricity production with wind energy. Therefore, this type of energy is significantly environmentally friendly. On the other hand, thanks to wind energy investments, a country can produce its own energy. This reduces the country’s foreign dependency on energy. Due to these positive aspects, increasing wind energy investments is very important for both the social and economic development of the country. The aim of this study is to define the most appropriate government support to improve wind energy investments. In this context, four different criteria are defined in this regard by making a detailed literature review. In the analysis process, fuzzy AHP methodology is considered. Within this framework, the comparative evaluations of three different experts are obtained. The findings indicate that providing loans with low-interest rate is the most appropriate government support for the wind energy investors. Additionally, it is also defined that tax deduction is another important issue for this purpose. However, it is also identified that appropriate location supply and purchase guarantee of the product produced have lower importance in comparison with the others. It is strongly recommended that governments should provide loans to the wind energy investors. This strategy can minimize the problem of high initial cost so that it can be much easier to attract the attention of the investors.

In the face of complex and challenging economic and business environments, developing and implementing approaches to predict bankruptcy has become important for firms. Bankruptcy prediction can be regarded as a grey system problem because while factors such as the liquidity, solvency and profitability of a firm influence whether it goes bankrupt, the precise manner in which these factors influence the discrimination between failed and non-failed firms is uncertain. In view of the applicability of multivariate grey prediction models (MGPMs), this paper aimed to develop a grey bankruptcy prediction model (GBPM) based on the GM (1, N) (BP-GM (1, N)).

As the traditional GM (1, N) is designed for time series forecasting, it is better to find an appropriate permutation of firms in the financial data as if the resulting sequences are time series. To solve this challenging problem, this paper proposes GBPMs by integrating genetic algorithms (GAs) into the GM (1, N).

Experimental results obtained for the financial data of Taiwanese firms in the information technology industries demonstrated that the proposed BP-GM (1, N) performs well.

Among artificial intelligence (AI)-based techniques, GBPMs are capable of explaining which of the financial ratios has a stronger impact on bankruptcy prediction by driving coefficients.

Applying MGPMs to a problem without relation to time series is challenging. This paper focused on bankruptcy prediction, a crucial issue in financial decision-making for businesses, and proposed several GBPMs.

During the current global epidemic, e-learning and mobile learning have been rapidly developed in the field of entrepreneurship education. The effect of these learning methods remains to be confirmed. The purpose of this paper is to explore the effect of mobile business simulation games in entrepreneurship education.

From May 2020 to July 2020, the authors adopted a quasi-experimental design to explore the effect of mobile business simulation games in entrepreneurship education. The authors set up an experimental group to participate in mobile business simulation games, with a total of 105 students, and set up a control group of 100 students. At the beginning and end of the experiment, data on entrepreneurial attitude, self-efficacy, entrepreneurial intention and other related variables were collected. Paired sample T-test and regression analysis were used to analyze the results.

The authors found that mobile business simulation games can improve entrepreneurial attitudes and self-efficacy, but cannot change entrepreneurial intentions. The paired sample T-test in the experimental group showed that the entrepreneurial attitude and entrepreneurial self-efficacy of the participants were significantly improved, but the entrepreneurial intention did not change significantly. The above three variables did not change significantly in the control group. The research results also show that flow experience is very important in mobile business simulation games, which can improve entrepreneurial attitude and entrepreneurial self-efficacy.

The authors’ findings confirm the positive effects of mobile business simulation games in entrepreneurship education, which can improve entrepreneurial attitudes and entrepreneurial self-efficacy. But the disadvantage of mobile business simulation games is that they cannot increase entrepreneurial intention. In addition, the flow experience needs to be valued in mobile business simulation games. The research in this paper has implications for how mobile learning can be used in entrepreneurship education during the COVID-19 pandemic. In addition, research is of great value on how mobile business simulation games can be improved.

Drawing upon the theory of conservation of resources to argue the importance of job stress as an important variable that mediates the person-organization (P-O) fit-job satisfaction relationship, and supervisor support as an important moderating variable that moderates the relationship between P-O fit and job stress, the purpose of this paper is to test a moderated mediation model.

Data were collected from 225 employees in 12 catering service organizations in Beijing. An integrated mediation and moderation model was evaluated.

The study illustrates both some new mechanisms and the boundary conditions between P-O fit and job satisfaction. Job stress mediates the relationships between P-O fit and job satisfaction; supervisor support moderates the linkage of P-O fit, job stress, and job satisfaction. The corresponding moderated mediation model was supported.

The question of causality cannot be determined because of the cross-sectional research design; self-report is a necessary strategy for the assessment of subjects’ appraisals. However, it requires some caution in interpreting the results.

The findings offer a better understanding of the way P-O fit is able to affect job satisfaction. Actions designed to promote P-O fit may be useful in reducing employees’ stress and result in higher job satisfaction. To enhance the relationships between P-O fit and employees’ job satisfaction through supervisor support, supervisors should develop a positive form of reciprocation by helping employees to solve the real problem they are facing.

No previous studies have investigated influencing factors of employees’ satisfaction from the perspective of individual and organizational interfaces.