Search results

Dimensional stability is one of the main quality problems of men’s sock manufacturing. Major shrinkage can be found after washing, undermining socks’ usability. Today, greater demand for quality is required as customers become more aware of shrinkage from laundering. In order to investigate the effect of pressing and repeated launderings on dimensional stability of men’s socks, three commonly produced socks were subject to pressing at different temperatures and for different lengths of duration by an industrial sock pressing machine. The study demonstrates that pressing causes major shrinkage in the body and sole zones. The shrinkage is inversely proportional to temperature and duration of the pressing process. After the first laundering, major shrinkage was found. The second laundering had no significant effect on dimensional variations since the sock had already taken up its fully relaxed dimensions. The results can help knitters predict sock dimensions after thermal and humid treatments.

The purpose of this paper is to analyze the wind energy technologies using the social network analysis based on patent information. Analysis of patent documents with social network analysis is used to identify the most influential and connected technologies in the field of wind energy.

In the literature, patent data are often used to evaluate technologies. Patents related to wind energy technologies are obtained from the United States Patent and Trademark Office database and the relationships among sub-technologies based on Corporate Patent Classification (CPC) codes are analyzed in this study. The results of two-phase algorithm for mining high average-utility itemsets algorithm, which is one of the utility mining algorithm in data mining, is used to find associations among wind energy technologies for social network analysis.

The results of this study show that it is very important to focus on wind motors and technologies related to energy conversion or management systems reducing greenhouse gas emissions. The results of this study imply that Y02E, F03D and F05B CPC codes are the most influential CPC codes based on social network analysis.

Analysis of patent documents with social network analysis for technology evaluation is extremely limited in the literature. There is no research related to the analysis of patent documents with social network analysis, in particular CPC codes, for wind energy technology. This paper fills this gap in the literature. This study explores technologies related to wind energy technologies and identifies the most influential wind energy technologies in practice. This study also extracts useful information and knowledge to identify core corporate patent class (es) in the field of wind energy technology.