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The purpose of this research is to develop an automatic optical inspection system for thin film transistor (TFT) liquid crystal display (LCD).

A new algorithm that accounts for the closing, opening, etching, dilating, and genetic method is used. It helps to calculate the location and rotation angle for transistor patterns precisely and quickly. The system can adjust inspection platform parameters according to viewed performance. The parameter adaptation occurs in parallel with running the genetic algorithm and imaging processing methods. The proposed method is compared with the algorithms that use artificial parameter sets.

This system ensures high quality in an LCD production line. This multipurpose image‐based measurement method uses unsophisticated and economical equipment, and it also detects defects in the micro‐fabrication process.

The experiment's results show that the proposed method offers advantages over other competing methods.

The purpose of this paper is to explain how individuals form microblogging habits and why they continue to use microblogs from the perspective of direction social networks.

Drawing on the social network theory and the social presence theory, the authors develop a theoretical framework to explain how individuals form microblogging habits and why they continue to use microblogs. To test the proposed model and examine its external validity, the authors collected data from two microblogs: Twitter and Sina Weibo.

Satisfaction and habit have a significant influence on microblogging continuance intention. Whereas, users’ microblogging habits are developed by two key factors – satisfaction and frequency of past behavior – that are further determined by social presence and social network centrality.

Larger sample size with diverse populations is highly recommended for future studies. In addition, exploring the distinct technical functionalities of microblogs when conceptualizing habit formation would be of benefit in future studies.

In this study, it was found that social presence increases both the satisfaction of users and the frequency of past use behavior. Hence, microblog designers should provide users with greater freedom to modify the form and content of their interface, and enable these modifications to be visible in real time to increase the interactivity of microblogs.

In contrast to past studies that have largely neglected the impacts of the directed social network structure, this study aims to focus on microblogging continuance intention from the directed social network perspective. The results from two independent data sets converge on the conclusion that users’ continuance intention to use is affected by both their conscious evaluations (i.e. satisfaction) and unconscious reactions (i.e. habit).

An enterprise social network (ESN) is part of the landscape of information reform by enterprises, using Web 2.0. In terms of the marketing targets of typical Web 2.0 techniques, enterprise knowledge sharing in Web 2.0 can be classified into different types (individual interaction type, group interaction type, social interaction type, real‐time interaction type and delay interaction type). The purpose of this paper is to summarize the features and modes of different enterprises' knowledge sharing and study enterprise knowledge sharing quantitatively from an ESN perspective by selecting real‐time interaction type as the case.

Because of the area of research, the authors supplemented social network analysis (SNA) with a mathematical modeling method and additional in‐depth interviews.

The Web 2.0 era provides the opportunity to quantify knowledge sharing. Also, SNA can quantitatively and visually diagnose the knowledge sharing status of the enterprise and guide the enterprise's knowledge‐sharing process.

Only a case study regarding real‐time interaction type is presented; other types of interaction are not studied empirically.

SNA, combined with a mathematical modeling method and additional in‐depth interviews with team leaders or key managers in organizations, can diagnose quantitatively, visually and comprehensively the knowledge‐sharing status of the enterprise.

This paper systematically summarizes the features and modes of Web 2.0 enterprise knowledge sharing, and the multiple‐method research design represents a sound approach to targeting enterprise knowledge sharing.

The purpose of this paper is to address two major challenges faced by robotic fish when operating in underwater environments: insufficient path planning capabilities and difficulties in avoiding dynamic obstacles. To achieve this, a method is proposed that combines the Improved Rapid Randomized Tree Star (IRRT*) with the dynamic window approach (DWA).

The RRT-connect algorithm is used to determine an initial feasible path quickly. The quality of sampling points is then improved by dividing the regions and selecting each region’s probability based on its fitness value. The fitness function and roulette wheel method are introduced for region selection. Subtarget points of the DWA algorithm are extracted from the IRRT* algorithm to achieve real-time dynamic path planning.

In various maps, the iteration count for the IRRT* algorithm decreased by 61%, 35% and 51% respectively, compared to the RRT* algorithm, whereas the iteration time was reduced by 75%, 34% and 57%, respectively. In addition, the IRRT*-DWA algorithm can successfully navigate through multiple dynamic obstacles, and the average time, path length, etc. do not change much when parameters change, and the stability is high.

A novel IRRT*-DWA algorithm is proposed, which, by refining the sampling strategy and updating sub-target points in real time, not only addresses the limitations of existing algorithms in terms of path planning efficiency in complex environments but also enhances their capability to avoid dynamic obstacles. Ultimately, experimental results indicate a high level of similarity between the actual and ideal paths.