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This paper is to develop a quality measure to evaluate the quality level of child care service in the regional level. By utilizing the biannual intensive child care statistical reports, ten variables are integrated and summarized as a quality measure for child care service in regional level by employing Principal Component Analysis (PCA). Conclusively, it is possible to get a comprehensive measure and the measure obtained from data between 2003 and 2008 illustrates the difference in child care service quality among regions over years. With the measure developed by this research, each region can also get very good insight into what kinds of factors of child care service should be paid more attention to in order to improve the quality of its child care service. Moreover, the measure obtained in this paper is proven reliable and robust in that it reflects the quality of child care service in each region and gives us statistically uniform quality scores with a different data set.

The purpose of this paper is to identify the most important characteristics of functional foods and the motives behind its consumption.

The data were collected in the direct interview. The sample (n=200) consisted of 137 women and 63 men at the age of 18-60 years. The research tool was a questionnaire divided into four sections. The first one included quality attributes. The second one included healthful properties, functional components and carriers. The third one concerned the motives for purchasing functional food and included the consequences and values. In the fourth section the participants were asked about gender, age and education.

Among the quality attributes the research reveals six principal components package of information on healthful properties and nutritional value of the product, attributes of taste, health and safety, practical packaging, freshness, purity and naturalness. In terms of health benefits, two components were distinguished prevention of health problems, strengthening of the body and improvement of its functions. Among functional components, the following were distinguished vitamins and minerals, dietary fibre and Omega-3 fatty acids. As the best carriers the following were recognized: cereal products, dairy products, meat products; mixtures of fruits and vegetables. As the most important consequences motivating people to consume functional food the following were recognized: the health effects of proper nutrition resulting from consciousness raising actions promoting health; and the joy of eating and improvement of the appearance. When it comes to the most important motivating factors, good health, long harmonious life and self-esteem were included. The means to achieve these goals are to be responsible for health.

The key factors determining the functional product and motivating for consumption of functional food may establish a basis for actions related to development and consumption of the food. The understanding of the factors that consumers take into account when choosing functional food will help in shaping the optimal strategies for product development. Learning about the basic motivating factors in consumption may be helpful in the development of healthy nutrition education and promotion programmes. The research may provide valuable support for actions related to food products promotion and marketing.

Participants in Internet net news bulletin board discussions can argue with others whom they do not know. The nature of each message in a discussion can be characterized by the frequency with which keywords appear in the message. This incidence or frequency can be summarized as a principal component score. By deriving two characteristic indexes – auto‐correlation coefficients and power spectra – from the principal component scores, we have come up with a novel method. Applying this method to analyze three large net news threads, the index plots revealed two‐generation cyclic fluctuations. Comparing these plots with actual points of conflict obtained by reading the message contents, a fairly good correlation was obtained between the two and it was found that most of the conflicts were among participants with different cultural backgrounds.

This chapter measures financial integration in 10 industries over 4 different periods. We use two robust measures of integration: (i) the Pukthuanthong and Roll (2009)’s multi-factor R-square and (ii) the Volosovych (2011)’s integration index. Both measures, based on PCA, indicate that the difference between the level of integration over the period 2009–2012 (“Post-Lehman” era) and the level of integration over the period 1994–1998 (“Post-Liberalizations” era) is relatively high. In addition, the level of financial integration across international equity markets decreased during the late 1990s. This suggests that de jure integration does not necessarily improve de facto integration. Overall, our findings give rise to a “diversification benefits-insurance benefits trade-off.”

The purpose of this paper is to present an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

Unlike the convention of developing a set of kinematic equations and then solving them, an alternative numerical algorithm is proposed in which the principal components of link lengths are used as a bridge to analyze the forward kinematics of a Stewart platform. The values of link lengths are firstly transformed to the values of principal components through principal component analysis. Then, the computation of the values of positional variables is transformed to a two‐dimensional nonlinear minimization problem by using the relationships between principal components and positional variables. A hybrid Nelder Mead‐particle swarm optimizer (NM‐PSO) algorithm and a modified NM algorithm are used to solve the two‐dimensional nonlinear minimization problem.

Simulation experiments have been conducted to validate the numerical algorithm and experimental results show that the numerical algorithm is valid and can achieve good accuracy and high efficiency.

This paper proposes an adaptive numerical algorithm for forward kinematics analysis of general Stewart platform.

We examine the Stein-rule shrinkage estimator for possible improvements in estimation and forecasting when there are many predictors in a linear time series model. We consider the Stein-rule estimator of Hill and Judge (1987) that shrinks the unrestricted unbiased ordinary least squares (OLS) estimator toward a restricted biased principal component (PC) estimator. Since the Stein-rule estimator combines the OLS and PC estimators, it is a model-averaging estimator and produces a combined forecast. The conditions under which the improvement can be achieved depend on several unknown parameters that determine the degree of the Stein-rule shrinkage. We conduct Monte Carlo simulations to examine these parameter regions. The overall picture that emerges is that the Stein-rule shrinkage estimator can dominate both OLS and principal components estimators within an intermediate range of the signal-to-noise ratio. If the signal-to-noise ratio is low, the PC estimator is superior. If the signal-to-noise ratio is high, the OLS estimator is superior. In out-of-sample forecasting with AR(1) predictors, the Stein-rule shrinkage estimator can dominate both OLS and PC estimators when the predictors exhibit low persistence.

This paper extends the authors’ previous research work investigating resilience for municipal infrastructure from an asset management perspective. Therefore, this paper aims to formulate a pavement resilience index while incorporating asset management and the associated resilience indicators from the authors’ previous research work.

This paper introduces a set of holistic-based key indicators that reflect municipal infrastructure resiliency. Thenceforth, the indicators were integrated using the weighted sum mean method to form the proposed resilience index. Resilience indicators weights were determined using principal components analysis (PCA) via IBM SPSS®. The developed framework for the PCA was built based on an optimization model output to generate the required weights for the desired resilience index. The output optimization data were adjusted using the standardization method before performing PCA.

This paper offers a mathematical approach to generating a resilience index for municipal infrastructure. The statistical tests conducted throughout the study showed a high significance level. Therefore, using PCA was proper for the resilience indicators data. The proposed framework is beneficial for asset management experts, where introducing the proposed index will provide ease of use to decision-makers regarding pavement network maintenance planning.

The resilience indicators used need to be updated beyond what is mentioned in this paper to include asset redundancy and structural asset capacity. Using clustering as a validation tool is an excellent opportunity for other researchers to examine the resilience index for each pavement corridor individually pertaining to the resulting clusters.

This paper provides a unique example of integrating resilience and asset management concepts and serves as a vital step toward a comprehensive integration approach between the two concepts. The used PCA framework offers dynamic resilience indicators weights and, therefore, a dynamic resilience index. Resiliency is a dynamic feature for infrastructure systems. It differs during their life cycle with the change in maintenance and rehabilitation plans, systems retrofit and the occurring disruptive events throughout their life cycle. Therefore, the PCA technique was the preferred method used where it is data-based oriented and eliminates the subjectivity while driving indicators weights.

A survey of the work‐related attitudes and demographic charcteristics of academic staff is reported. Nine institutions were surveyed: two universities and two colleges of advanced education in each of Western Australia and New South Wales, plus the largest university in New Zealand. The attitudinal items related to publication, research, teaching methods, relevance of local needs, the reward structure, the administrative hierarchy, administrative duties, the work environment, colleagues, mobility, geographical isolation and professional association meetings. The demographic characteristics surveyed included faculty, sex, rank, age, level of qualification, publications and place of highest qualification. Differences between the demographic characteristics of universities and colleges, and between the institutions of each group are reported. The attitudinal items used and the method of extracting meaningful attitudinal variables from these items are discussed. The attitudinal analysis permits the role differentiation between the institutions to be examined, and this discussion is the subject of a companion paper.

This paper aims to discuss the key factors affecting the quality characteristics, such as the number of solder balls, the spread distance of residual underfill and the completion time of the underfilling.

The Taguchi method is applied to configure the orthogonal table and schedule and execute the experiment. In addition, principal components analysis is used to obtain the points. Then, based on gray relational analysis and the technique for order preference by similarity to ideal solution, the closeness between each quality characteristic and the ideal solution is adopted as the basis for evaluating the quality characteristics.

The optimal parameter combination is proposed, which includes 4 dispensing (11 mg/dispensing), a “half flow” interval state, 80°C preheating module PCB board and an L-shaped dispensing path and verification testing is performed.

For vehicles and handheld electronic products, solder joints that connect electronic components to printed circuit boards may be cracked due to collision, vibration or falling. Consequently, solder balls are closely surrounded and protected by the underfill to improve joint strength and resist external force factors, such as collision and vibration. This paper addresses the defects caused during the second reflow process of a vehicle electronic communication module after the underfilling process.

This paper aims to develop a multivariate model that will be applicable to the Nigeria construction industry.

A self-administered questionnaire survey was used to source information on project scope factors and qualitative factors considered in the study. Principal component regression was used for data analysis and model development, using SPSS 16.0 for windows, while T-test was used for model testing and validation.

The study found that delay in progress payment by owner, lateness in revising and approving design document by owner, delay in delivering the site to the contractor by the owner, change order by owner during construction, complexity of project design, poor site management and supervision by contractors, and rain effect on construction activities are qualitative/non-project scope factors with good predictive abilities.

Cost, gross floor area and number of floors were the only quantitative/project scope factors considered in the study. The developed models therefore do not account for any variation in duration which may arise from other project scope factors, such as location, procurement route and type of contract.

The qualitative factors which emerged as predictors in the derived models increased the accuracy of the models. The models developed therefore serve as useful construction time prediction tools for both consultancy firms and contractor organizations in the Nigerian construction industry.