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In literature, previous studies have focused on analyzing rienforced concrete (RC) columns with idealized end conditions when subjected to fire. In nature, full fixity or free rotation at column ends is not attained. Such ends may be considered partially restrained in rotation. This paper aims to shed a new light on the effect of different degrees of rotational restraint on the lateral deformation behavior of slender heated RC columns subjected to non-linear strain distributions produced by a time-dependent temperature history.

To find the strain distribution on the cross section, an iterative technique is adopted using Newton–Raphson method. By introducing a reliable calculation procedure, the lateral deformational behavior is expressed using numerical and searching techniques. A methodology is presented to calculate the effective length factor for RC columns at elevated temperature.

The results of the proposed model showed good agreement with available experimental test results. It was also found that the variation of rotational end restraint level has a considerable effect on the lateral deformation behavior of heated slender RC columns. In addition, the effectiveness and the validity of an analytical model should be verified by simultaneously validating the axial and lateral deformations. Moreover, the effective length factor for heated column is higher than that for the corresponding column at ambient temperature.

This paper shows the impact of different boundary conditions on the behavior of heated slender RC columns. It suggests powerful techniques to determine the lateral deflection and the effective length factor at high temperatures.

The purpose of this paper is to explore the potential challenges in developing numerical methodologies for inverse problems and optimizations.

Summarizing previous research results mainly contributed by two research groups of Zhejiang University and Hong Kong Polytechnic University.

Computational intelligence plays an essential role in studying inverse problems and optimizations.

An up-to-date review on the current status of numerical methodologies, especially computational intelligences, for inverse problems and optimizations contributed by Chinese researchers.

The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the existing control system, the double aligner mark searching time is decreased to reduce the working time of the integrated system.

The improved pattern matching method of genetic algorithm was adopted, including setting for template image selecting, encoding, calculating fitness function, pattern matching, template generating and genetic algorithm steps. The predetermined pixels were selected from the target template based on the minimum difference to the block image to be tested by utilizing the genetic algorithm, and the other pixels which have not been selected were neglected.

The selected pixels were encoded for recording by sequence mode, and then the target template and the image to be tested were compared based on the calculated fitness function. This method has the advantages of using the fitness function to reduce the searching time, with the help of genetic algorithm to find the optimal target template, and saving memory space by recording target template based on the sequence mode.

The genetic algorithm used in this study is a kind of optimal tool free from gradient data. As long as the fitness function and after continuous iteration are determined, the optimal solution can be found out, and then the optimal target template can be generated.

This system uses fitness function to reduce the pattern matching time. Plural pixels are preset inside the target template, and its fitness function value is calculated. When the target template is compared with the image to be tested, only the fitness function value (also the difference of the plural pixels) is calculated and compared.

The remaining pixels are neglected, so that the searching time can be reduced greatly. The sequence mode is used to save the required memory space for recording target template. Since sequence mode is adopted to record the information of selected pixels, lots of required memory space for recording target template information will be saved.

Luxury consumption in China is featured by clear conspicuous purposes. The purpose of this paper is to investigate this phenomenon from the indigenous perspective of face consciousness.

Drawing on Ho’s (1976) framework of gaining vs losing face process, the authors decomposed the construct of face consciousness into two dimensions, namely, desire to gain face and fear of losing face, and developed a multi-dimensional scale for face consciousness. Then, a survey that consisted of 338 participants was conducted to test the relationship between face consciousness and luxury consumption.

The face consciousness scale was shown to be reliable and valid. Furthermore, the authors found both desire to gain face and fear of losing face had a unique contribution in explaining why Chinese consumers purchase luxury products.

This paper fills the gap in the extant literature by developing a multi-dimensional face consciousness scale, providing convenience for empirical research in future. Moreover, this research shows that Chinese consumers’ luxury consumption behavior contains both promotion and prevention motivation.

The purpose of this paper is to develop a preventive maintenance (PM) model that encounters the problems of traditional methods of conducting PM within high component/machine variety environments.

A new platform to conduct planning of the PM actions by using clustering based on the Group Technology concept to create PM virtual cells of equipment/machines is introduced. A real case study at Arab Potash Company was used to illustrate the model. The component/machine variety that requires PM at the considered company is in thousands of items.

PM for high component/machine environments are not enough addressed in the literature. The concept of clustering and similarity coefficient was used and found very useful to model this situation.

The proposed procedure will assist maintenance managers/engineers in too many ways. It will help to optimize the inventory of the spare parts, and to create standard process plan for executing the preventive maintenance operation.

This paper presents a new procedure to implement preventive maintenance in high component/machine environments using clustering technique concept. Models that address this concept are rare and very limited in the literature.

The purpose of this paper is to investigate the impact on the cost of materials used to conduct preventive maintenance (PM). The main motivation for this work is to demonstrate how the group technology concept can be used to improve PM operations. In assessing improvement, the impact on the cost of materials used to conduct PM is investigated.

Based on the similarities between machines required maintenance and failure types, machines are grouped together into virtual cells using similarity coefficients. These cells, then, are used to come up with more efficient planning and scheduling procedures to conduct PM operations including inventory of parts and the execution of maintenance operations.

The results demonstrated that the proposed PM approach could provide a significant cost savings over a traditional PM program, especially in industries for which there is considerable material cost for the performance of PM.

The results presented in this paper are reliable, objective, and may be expanded by using the same concept of developing virtual cells to group other types manufacturing operations.

The purpose of this paper is to apply an on‐line automatic inspection and measurement of surface defect of thin‐film transistor liquid‐crystal display (TFT‐LCD) panels in the polyimide coating process with a modified template matching method and back propagation neural network classification method.

By using the technique of searching, analyzing, and recognizing image processing methods, the target pattern image of TFT‐LCD cell defects can be obtained.

With template match and neural network classification in the database of the system, the program judges the kinds of the target defects characteristics, finds out the central position of cell defect, and analyzes cell defects.

The recognition speed becomes faster and the system becomes more flexible in comparison to the previous system. The proposed method and strategy, using unsophisticated and economical equipment, is also verified. The proposed method provides highly accurate results with a low‐error rate.

In terms of sample training, the principles of artificial neural network were used to train the sample detection rate. In sample analysis, character weight was implemented to filter the noise so as to enhance discrimination and reduce detection.

The paper describes how pre‐inspection image processing was utilized in collaboration with the system to excel the inspection efficiency of present machines as well as for reducing system misjudgment. In addition, the measure for improving cell defect inspection can be applied to production line with multi‐defects to inspect and improve six defects simultaneously, which improves the system stability greatly.

The purpose of this paper was to investigate the influences of calendar year, year level, gender and language background other than English (LBOTE) on student achievement in literacy and numeracy relative to class size.

Data for this study were collected over five years (2008-2012) as test results from the Australian National Assessment Plan in Literacy and Numeracy (NAPLAN) in Years 3 and 5 from over 100 Sydney primary schools.

It was found that the most important factors influencing academic performance in literacy and numeracy were, in descending order: gender, LBOTE, the calendar year in which the test was conducted, followed by class size. All variables were significantly associated with NAPLAN performance, but effect size estimates for class size were close to zero.

The results of this study support other studies suggesting that factors other than class size are more important in influencing academic performance.

This paper aims to propose and test a modified technology acceptance model for the social media networks (SMNs) in the luxury hotel context, integrating satisfaction and continued usage intention, using a mixed-method approach. SMNs have revolutionized the way people communicate, search for information and share experiences. The technology acceptance model is the predominant theory for researching technology acceptance; however, there is a gap in identifying and testing context-specific constructs.

This paper uses a mixed-method approach. The researchers conducted 16 interviews and 258 questionnaires with luxury hotel guests. Following the collection of data, interviews and questionnaires were analyzed using thematic and partial least square analysis.

Findings show that accessibility, trust, social influence and perceived benefits influence perceived ease of use and perceived usefulness, which affect attitude and satisfaction and ultimately continued usage intentions. Findings also reveal that enjoyment, although qualitatively proposed, does not influence luxury hotel guests’ SMNs continued usage intention.

This study suggests that hotel managers have to concentrate their marketing efforts in enhancing SMN’s interaction and increasing the number of positive reviews to retain current customers and acquire new ones. Hotels should also develop effective mobile strategies by adopting mobile social network webs and applications, as accessibility becomes more important in today’s marketplace.

Former scholars adopted the approach of proposing external dimensions based on previous research and, thus, did not integrate up-to-date and context-specific variables. Therefore, the present paper uses a new approach by exploring SMN-specific dimensions and testing them in the luxury hotel context.

The purpose of this paper is to propose an automatic optical inspection system for measuring the surface profile of a microlens array.

The system set‐up was constructed according to the principle of the Fizeau interferometer. After capturing the ring interference fringe images of the microlens with a camera, the diameter, profile information and optical properties were analyzed through a microlens surface profile algorithm using innovative image pre‐processing with a precision of less than 0.09 micron.

By integrating with the genetic algorithm, the XY‐Table shortest moving path of the system is calculated to achieve the purpose of high‐speed inspection and automatic microlens array surface profile measurement.

The measurement results of this system were also compared with other systems, including the atomic force microscope and stylus profiler, to verify the measurement precision and accuracy of this system.