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Article
Publication date: 18 February 2019

Chen Tao, Yafeng Duan and Xinghua Hong

The purpose of this paper is to advance a digital technology that is intended to bring about innovations on the existing textile patterns.

313

Abstract

Purpose

The purpose of this paper is to advance a digital technology that is intended to bring about innovations on the existing textile patterns.

Design/methodology/approach

The pattern is deemed as a relation function between colors and positions which can be learnt by the artificial neural network (ANN). The outputs of the ANN are used for the reconstruction of the pattern and the innovation is performed by interceptors in the input/output layer. The ANN is carried out with one input layer, one output layer and several hidden layers, and the capacity of the architecture is adjusted by the scale of hidden layers to accommodate different function relations of the patterns. The training is conducted repeatedly on a sample set extracted from the pixels of the pattern image to minimize the error, and the chromatic outputs of the architecture are replaced to their origins so as to rebuild the pattern. Then, the interceptors are installed into the input and output layers to modulate the positions and the colors, and consequently the innovations are achieved on the geometric formation and color distribution of the pattern.

Findings

It has turned out that the precision of reconstruction is concerned with network scale, training epochs and color mode of the sample set. Four primary innovative effects including stripes, twisters, sandification and overprints have been qualified in terms of interceptors.

Originality/value

This study introduces ANN into textile pattern generation and provides a novel way to perform digital innovation of textile patterns.

Details

International Journal of Clothing Science and Technology, vol. 31 no. 1
Type: Research Article
ISSN: 0955-6222

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Article
Publication date: 5 December 2024

Baoku Li, Ruoxi Yao and Yafeng Nan

Benefiting from the development and innovation of artificial intelligence and affective computing technology, social chatbots that integrate cognitive analysis and affective…

188

Abstract

Purpose

Benefiting from the development and innovation of artificial intelligence and affective computing technology, social chatbots that integrate cognitive analysis and affective social services have flooded into the consumer market. For cognition and emotion-oriented tasks, social chatbots do not always receive positive consumer responses. In addition, consumers have a contradictory attitude toward the anthropomorphism of chatbots. Therefore, from the perspective of mind perception and the two dimensions of social judgment, this research explores the mechanism of consumer responses to anthropomorphic interaction styles when social chatbots complete different service tasks.

Design/methodology/approach

This paper utilizes three behavior experimental designs and survey methods to collect data and the ANOVA, t-test and bootstrap analysis methods to verify the assumed hypotheses.

Findings

The results indicate that when the service task type of a social chatbot is cognition-oriented, compared to a warm anthropomorphic interaction style, a competent anthropomorphic interaction style can improve consumer responses more effectively. During this process, agent-mind perception plays a mediating role. When the service task type of a social chatbot is emotion-oriented, compared with a competent anthropomorphic conversation style, a warm anthropomorphic conversation style can improve consumer responses. Experience-mind perception mediates this influencing relationship.

Originality/value

The research results theoretically enrich the relevant research on the anthropomorphism of social chatbots and expand the application of the theory of mind perception in the fields of artificial intelligence and interactive marketing. Our findings provide theoretical guidance for the anthropomorphic development and design of social chatbots and the practical management of service task scenarios.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

Keywords

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Article
Publication date: 6 July 2015

Xinlong Wang and Shuai Song

– The purpose of this paper is to improve the tracking performance of the tracking loops under high dynamic and severe jamming conditions.

266

Abstract

Purpose

The purpose of this paper is to improve the tracking performance of the tracking loops under high dynamic and severe jamming conditions.

Design/methodology/approach

First, as the two dominant measurement error sources of the tracking loops, the thermal noise jitter and the dynamic stress error are thoroughly analyzed. Second, a scheme of adaptive tracking loops, which could adaptively adjust the order and the bandwidth of tracking loops, is proposed. Third, real-time detections of the vehicle dynamics and the carrier-to-noise density ratio, and the adaptive bandwidth of the carrier loop are presented, respectively. Finally, simulations are operated to validate the excellent tracking performance of the adaptive tracking loops.

Findings

Based on the principle of minimizing the measurement errors, the loop order and bandwidth are adaptively adjusted in the proposed scheme. Thus, the anti-jamming capability and dynamic tracking performance of the tracking loops could be effectively enhanced.

Practical implications

This paper provides further study on the method of improving the tracking capability under complexly applied conditions of high dynamics and severe jamming.

Originality/value

The detections of carrier-to-noise density ratio and vehicle dynamics are used to adaptively adjusting the loop order and bandwidth, which could not only improve the measurement accuracy but also ensure the stable operation of tracking loops.

Details

Aircraft Engineering and Aerospace Technology: An International Journal, vol. 87 no. 4
Type: Research Article
ISSN: 0002-2667

Keywords

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