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This study aims to predict popular contributors through text representations of user-generated content in open crowds.

Three text representation approaches – count vector, Tf-Idf vector, word embedding and supervised machine learning techniques – are used to generate popular contributor predictions.

The results of the experiments demonstrate that popular contributor predictions are considered successful. The F1 scores are all higher than the baseline model. Popular contributors in open crowds can be predicted through user-generated content.

This research presents brand new empirical evidence drawn from text representations of user-generated content that reveals why some contributors' ideas are more viral than others in open crowds.

This research suggests that companies can learn from popular contributors in ways that help them improve customer agility and better satisfy customers' needs. In addition to boosting customer engagement and triggering discussion, popular contributors' ideas provide insights into the latest trends and customer preferences. The results of this study will benefit marketing strategy, new product development, customer agility and management of information systems.

The paper provides new empirical evidence for popular contributor prediction in an innovation crowd through text representation approaches.

This paper aims to propose an innovative parametric design for artificial neural network (ANN) modeling for the multi-quality function problem to determine the optimal process scenarios.

The innovative hybrid algorithm gray relational analysis (GRA)-ANN and the GRA-Entropy are proposed to effectively solve the multi-response optimization problem.

Both the GRA-ANN and the GRA-Entropy analytical approaches find that the optimal process scenario is a stencil aperture of 57 per cent and immediate processing of the printed circuit board after exposure to a room environment.

A six-week confirmation test indicates that the optimal process has improved quad flat non-lead assembly yield from 99.12 to 99.78 per cent.

The purpose of this study is to use the Taguchi Method for parametric design in the early stages of product development. electromagnetic compatibility (EMC) issues can be considered in the early stages of product design to reduce counter-measure components, product cost and labor consumption increases due to a number of design changes in the R&D cycle and to accelerate the R&D process.

The three EMC characteristics, including radiated emission, conducted emission and fast transient impulse immunity of power, are considered response values; control factors are determined with respect to the relevant parameters for printed circuit board and mechanical design of the product and peripheral devices used in conjunction with the product are considered as noise factors. The optimal parameter set is determined by using the principal component gray relational analysis in conjunction with both response surface methodology and artificial neural network.

Market specifications and cost of components are considered to propose an optimal parameter design set with the number of grounded screw holes being 14, the size of the shell heat dissipation holes being 3 mm and the arrangement angle of shell heat dissipation holes being 45 degrees, to dispose of 390 O filters on the noise source.

The optimal parameter set can improve EMC effectively to accommodate the design specifications required by customers and pass test regulations.

Differing from previous studies trying to solve the electromagnetic compatibility (EMC) issue by addressing single factor, this study aims to combine measures of shielding, filtering and grounding to design parameters with the Taguchi method at the beginning of product design to come up with the optimal parameter combination.

EMC-related performance such as radiated emission, conduction interference and electrical fast transient/burst immunity (EFT) are response variables, whereas the printed circuit board and mechanic design-relevant parameters are considered as control factors. The noise factors are peripherals used together with the tablet.

The optimal design parameter matrix based on results from the application and integration of multivariate analysis method of principal component grey relation and technique for order preference by similarity to ideal solution suggests 14 grounding screw holes, cooling aperture of casing at diameter of 3 mm and staggered layout and 300O filter located at source of noise. Validation of this matrix shows around 10, 1 and 8 per cent improvement in radiation, conduction interference and EFT immunity.

The multivariate quality parameters’ design method proposed by this study improves EMC characteristics of products and meets the design specification required by customer, accelerating electronic product research and development process and complying with electromagnetic interference test regulations set forth by individual country.

This paper aims to consider the practical production environment of electronics manufacturing industry firms, and the large quantities of information collected on machine processes, testing data and production reports, while simultaneously taking into account the properties of the processing environment, in conducting analysis to obtain valuable information.

This research constructs a prediction model of the circuit board assembly process yield. A decision tree is used to extract the key attributes. The authors also integrate association rules to determine the relevance of key attributes of undesirable phenomena.

The results assure the successful application of the methodology by reconfirming the rules for solder skip and short circuit occurrence and their causes.

Measures for improvement are recommended, production parameters determined and debugging suggestions made to improve the process yield when the new process is implemented.