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Power‐net is an extensible fabric and has a net structure. The biaxial extension property of this fabric is analysed and compared with experimental results obtained by a biaxial tensile tester.

In order to establish an objective method of evaluating ladies’ garment fabrics by connecting the mechanical properties of ladies’ garment fabrics to subjective evaluation, subjective assessments were examined by judges who work at textile mills or in the textile trade. We examined a method of deriving objective equations, a total hand value (THV) equation and a total appearance value (TAV) equation. The THV equation was derived directly from the mechanical properties of the fabrics and the TAV equation was derived from three mechanical parameters which are related to the beauty of garment appearance. In the case of the THV objective equation, the accuracy of regression was high within the same groups of judges; however, in the case of the TAV objective equation, accuracy was slightly low. Because there were few subjects and that caused deviation, the accuracy of prediction was slightly low; however, the objective evaluation was adequate.

Citizen participation has attracted attention in the context of decentralization. In a disaster reconstruction process, a business plan for reconstruction can be modified in line with diversified situations of disaster-affected areas by citizen participation. In Japan, the central government makes a decision about the authority in charge of an overall disaster reconstruction and the budget planning, whereas local governments are in charge of creating and implementing a business plan for reconstruction of each local municipality. Therefore, local governments play an important role in organizing citizen participation to realize the reconstruction that fits reality. It has yet to be shown as decentralization reform and citizen participation system in Japan produce the socio-spatial inequality after the Great East Japan Earthquake. However, it remains to be elucidated how local government and community have to operate the institution about citizen participation during the disaster reconstruction process. I have been doing fieldwork on three tsunami-affected sites in Miyagi Prefecture over past 4 years: Onagawa Town, Higashimatsushima City, and Natori City. I have investigated the social processes of making and implementing a reconstruction plan, and citizen participation. The findings from my fieldwork are as follows: First, citizen participation is based on organizing residents at the community level. Second, traditional community organization (such as neighborhood organization abd industrial associations) contribute to organize residents especially in the emergency phase. Third, as the disaster phase moves, local government and community organization need to change the previous participation frame to ensure residents representation and policy legitimacy.

Intensive methods of farming and food processing are particularly likely to result in food inadequate in n‐3 polyunsaturated fatty acids, and also in folic acid. These fatty acids are required for numerous metabolic functions including protection against heart attacks. Folic acid is essential for a baby′s developing nervous system.

The purpose of this paper is to explore the environment around the rail track at different sites in Nile Delta region, Egypt, through the measurements of the air pollutants and corrosive ionic species present in surface soil and also to investigate the impact of the existing contaminants on the composition of iron rust formed on the rail head surface at these sites and then the durability of rail itself.

The soil characterization was studied by means of sieve shakers, pH meter, conductivity meter and ion chromatography instrument. Scanning electron microscopy, energy dispersive spectrometry, Fourier transform infrared spectroscopy and X-ray diffraction were used to characterize the rust layer formed on the rail head surface.

The results showed the relation between the contaminants and the composition of the rust layer. Magnetite and goethite were the major phases identified in the rust layers. Akaganeite was detected in the marine atmosphere. Iron sulfide and iron oxide nitrate hydroxide were detected in environments rich in H₂S and NO₂ gases, respectively. The appearance of phases like FeCl₂ and FeOCl only at marine atmospheres reflects that the corrosive species in suspended particulate matter like chloride ion have a higher effect on the rust composition of the rail head surface than that in surface soil layer.

This paper revealed the impact of air and soil contaminants on the composition of rust layer on the rail head surface and may provide guidance for the durability of rails and the necessity for their preservation.

The aim of this research is to combine the Taguchi method and hybrid methods of artificial intelligence, to use them as the optimal tool in wire bond designing parameters for an ultra‐thin chip scale package (CSP) package, and then construct a set of the optimal parameter analysis flow and steps.

The hybrid methodology of artificial Intelligence was used in order to identify the optimum parameters design for a wire bonding of ultra‐thin CSP package. This paper employed desirability function to integrate two quality characteristics (loop height and wire pull strength) into a single quality indicator to construct a well‐trained neural network prediction system with hybrid genetic algorithm.

The processes parameters of low‐loop of micro HDD driver IC were optimized with GA, thereby achieving the objective of improving process yield and robustness design of micro HDD driver IC.

The engineers could quickly obtain the optimal production process parameter with the demand of multi‐quality characteristics, and enhance the assembly quality and yield of driver IC of micro HDD.

This paper applies the design of experiments approach to a lower wire loop processes parameters design, and improves the process yield and robustness design of micro HDD driver IC.

This paper aims to solve the problems of big data analytics for prediction including volume, veracity and velocity by improving the prediction result to an acceptable level and in the shortest possible time.

This paper is divided into two parts. The first one is to improve the result of the prediction. In this part, two ideas are proposed: the double pruning enhanced random forest algorithm and extracting a shared learning base from the stratified random sampling method to obtain a representative learning base of all original data. The second part proposes to design a distributed architecture supported by new technologies solutions, which in turn works in a coherent and efficient way with the sampling strategy under the supervision of the Map-Reduce algorithm.

The representative learning base obtained by the integration of two learning bases, the partial base and the shared base, presents an excellent representation of the original data set and gives very good results of the Big Data predictive analytics. Furthermore, these results were supported by the improved random forests supervised learning method, which played a key role in this context.

All companies are concerned, especially those with large amounts of information and want to screen them to improve their knowledge for the customer and optimize their campaigns.

Ventricular surface activation time maps are estimated from simulated and measured body surface potential (BSP) maps and extra‐corporal magnetic field maps. In a first step the transfer matrix, relating the primary cardiac sources to the measured potential and/or magnetic field data, is calculated applying the boundary element method. Activation times are determined by minimizing a cost function which is based on this transfer matrix. This optimization method is solved by a quasi Newton method. The critical point theorem is used in order to estimate the starting column matrix.

In the context of social media (SM) use, self-disclosure (SD) behaviour meets users' social and emotional needs, but it is also accompanied by risks that can harm users. This paper aims to identify the factors that influence users' SD behaviour on SM in Indonesia, using a comparative analysis based on age groups.

A survey was conducted on 2,210 respondents who were active SM users in Indonesia. Data were processed and analysed using covariance-based structural equation modelling with AMOS 24.0 software.

Results indicate that, in the overall age group data, factors such as use of information (UI), trust, privacy control (PC), interactivity, perceived benefits (PB) and perceived risks (PR) influence users' SD behaviour. This research also found differences in the characteristics of SD behaviour between age groups.

Findings from this study can help SM service providers to evaluate the credibility and reliability of their platforms to encourage user retention.