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Article
Publication date: 1 August 2000

Jiangping Wang and Venkat Allada

The ability to economically and effectively service products provides an avenue for extending the product’s useful life. Quantifying approaches are needed to assist in the…

Abstract

The ability to economically and effectively service products provides an avenue for extending the product’s useful life. Quantifying approaches are needed to assist in the serviceability evaluation. In this study, the serviceability characteristics of a product are categorized into three groups: disassembly, reassembly, and handling. Often, many of the serviceability characteristics of a product cannot be defined completely or properly using crisp design data. Moreover, the serviceability analysis is an imprecise science characterized by ill‐structured and subjective evaluation criteria. A formal methodology for representing and processing the design information of an artifact using a hierarchical fuzzy neural network (FNN) model is presented. First, three FNNs are used to compute the disassembly, reassembly, and handling indices. Second, the output of the three FNNs is fed into a separate FNN to compute the serviceability index. The designer can use the proposed model to rank alternate designs by computing the serviceability indices of each candidate design. The working of the proposed model is demonstrated by using two designs for a steam iron.

Details

International Journal of Agile Management Systems, vol. 2 no. 2
Type: Research Article
ISSN: 1465-4652

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Article
Publication date: 5 May 2021

James Faulkner, Liuxing Lu and Jiangping Chen

Archivists are charged with the preservation of their collections by reducing deterioration because of temperature, relative humidity, atmospheric pollutants and other…

Abstract

Purpose

Archivists are charged with the preservation of their collections by reducing deterioration because of temperature, relative humidity, atmospheric pollutants and other factors. The methods archivists use to preserve their collections may have a negative impact on the environment. This paper aims to identify factors for building environmentally sustainable archives to help guide archival environmental sustainability practices.

Design/methodology/approach

This paper identifies factors through a literature review, and conducts a content analysis of the websites of seven national/state archives. The analysis focuses on the policy statements of these archives.

Findings

The authors found that the literature lists 31 factors under 7 categories: electricity, facilities, water, exhibitions, pollution, collection practices and education and outreach. The content analysis of the policy documents or statements demonstrated that archives applied and addressed mostly “resource-related” efforts to protect the environment, such as factors related to electricity, facilities, water and pollution. However, factors related to “work-related” efforts, such as exhibitions, collection practices and education and outreach, were ignored.

Practical implications

This study can provide insights to archivists on current implementation and help to guide their further environmental sustainability practices.

Originality/value

Little is known regarding archivists’ implementation of environmentally sustainable practices. This study focuses on identifying factors for environmental sustainability of archives addressed by literature and existing archives, trying to find the gap between literature and practice.

Details

The Electronic Library , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0264-0473

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Article
Publication date: 27 November 2020

Mingwei Tang, Jiangping Chen, Haihua Chen, Zhenyuan Xu, Yueyao Wang, Mengting Xie and Jiangwei Lin

The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a…

Abstract

Purpose

The purpose of this paper is to provide an integrated semantic information retrieval (IR) solution based on an ontology-improved vector space model for situations where a digital collection is established or curated. It aims to create a retrieval approach which could return the results by meanings rather than by keywords.

Design/methodology/approach

In this paper, the authors propose a semantic term frequency algorithm to create a semantic vector space model (SeVSM) based on ontology. To support the calculation, a multi-branches tree model is created to represent the ontology and a set of algorithms is developed to operate it. Then, a semantic ontology-based IR system based on the SeVSM model is designed and developed to verify the effectiveness of the proposed model.

Findings

The experimental study using 30 queries from 15 different domains confirms the effectiveness of the SeVSM and the usability of the proposed system. The results demonstrate that the proposed model and system can be a significant exploration to enhance IR in specific domains, such as a digital library and e-commerce.

Originality/value

This research not only creates a semantic retrieval model, but also provides the application approach via designing and developing a semantic retrieval system based on the model. Comparing with most of the current related research, the proposed research studies the whole process of realizing a semantic retrieval.

Details

The Electronic Library , vol. 38 no. 5/6
Type: Research Article
ISSN: 0264-0473

Keywords

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Article
Publication date: 14 October 2020

Haihua Chen, Yunhan Yang, Wei Lu and Jiangping Chen

Citation contexts have been found useful in many scenarios. However, existing context-based recommendations ignored the importance of diversity in reducing the redundant…

Abstract

Purpose

Citation contexts have been found useful in many scenarios. However, existing context-based recommendations ignored the importance of diversity in reducing the redundant issues and thus cannot cover the broad range of user interests. To address this gap, the paper aims to propose a novelty task that can recommend a set of diverse citation contexts extracted from a list of citing articles. This will assist users in understanding how other scholars have cited an article and deciding which articles they should cite in their own writing.

Design/methodology/approach

This research combines three semantic distance algorithms and three diversification re-ranking algorithms for the diversifying recommendation based on the CiteSeerX data set and then evaluates the generated citation context lists by applying a user case study on 30 articles.

Findings

Results show that a diversification strategy that combined “word2vec” and “Integer Linear Programming” leads to better reading experience for participants than other diversification strategies, such as CiteSeerX using a list sorted by citation counts.

Practical implications

This diversifying recommendation task is valuable for developing better systems in information retrieval, automatic academic recommendations and summarization.

Originality/value

The originality of the research lies in the proposal of a novelty task that can recommend a diversification context list describing how other scholars cited an article, thereby making citing decisions easier. A novel mixed approach is explored to generate the most efficient diversifying strategy. Besides, rather than traditional information retrieval evaluation, a user evaluation framework is introduced to reflect user information needs more objectively.

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Article
Publication date: 12 March 2019

Jingye Qu and Jiangping Chen

This paper aims to introduce the construction methods, image organization, collection use and access of benchmark image collections to the digital library (DL) community…

Abstract

Purpose

This paper aims to introduce the construction methods, image organization, collection use and access of benchmark image collections to the digital library (DL) community. It aims to connect two distinct communities: the DL community and image processing researchers so that future image collections could be better constructed, organized and managed for both human and computer use.

Design/methodology/approach

Image collections are first identified through an extensive literature review of published journal articles and a web search. Then, a coding scheme focusing on image collections’ creation, organization, access and use is developed. Next, three major benchmark image collections are analysed based on the proposed coding scheme. Finally, the characteristics of benchmark image collections are summarized and compared to DLs.

Findings

Although most of the image collections in DLs are carefully curated and organized using various metadata schema based on an image’s external features to facilitate human use, the benchmark image collections created for promoting image processing algorithms are annotated on an image’s content to the pixel level, which makes each image collection a more fine-grained, organized database appropriate for developing automatic techniques on classification summarization, visualization and content-based retrieval.

Research limitations/implications

This paper overviews image collections by their application fields. The three most representative natural image collections in general areas are analysed in detail based on a homemade coding scheme, which could be further extended. Also, domain-specific image collections, such as medical image collections or collections for scientific purposes, are not covered.

Practical implications

This paper helps DLs with image collections to understand how benchmark image collections used by current image processing research are created, organized and managed. It informs multiple parties pertinent to image collections to collaborate on building, sustaining, enriching and providing access to image collections.

Originality/value

This paper is the first attempt to review and summarize benchmark image collections for DL managers and developers. The collection creation process and image organization used in these benchmark image collections open a new perspective to digital librarians for their future DL collection development.

Details

The Electronic Library , vol. 37 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

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Article
Publication date: 12 March 2018

Jiangping Yuan, Ming Zhu, Baohui Xu and Guangxue Chen

The purpose of this paper is provide a broad view for the standardization efforts of color quality evaluation of color 3D printing techniques. Further, this review paper…

Abstract

Purpose

The purpose of this paper is provide a broad view for the standardization efforts of color quality evaluation of color 3D printing techniques. Further, this review paper demonstrates the processes and color properties of most color 3D printing techniques with specific devices and applications to extend the range of possible memberships of standardization group.

Design/methodology/approach

Six color 3D printing techniques including plastic-based, paper-based, powder-based, organism-based, food-based and metal-based color 3D printing have been introduced and illustrated with colorization principles and forming features in detail. Moreover, for printed 3D color objects, literature about color measurement, color specification and color reproduction are described and analyzed, respectively.

Findings

Four color 3D printing techniques including plastic-based, paper-based, powder-based and food-based color 3D printing show great affinity toward standardization of color quality evaluation, while their colorization principles indicate that it is difficult with a single standard frame. It is possible to develop a completed color quality evaluation standard for color 3D printing based on approaches in color 2D printing when color measurement method and devices are standardized together.

Originality/value

The paper provides an important guide focusing on the efforts to standardize the colorization processes and color quality evaluation of the color 3D printing techniques.

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Article
Publication date: 1 April 2019

Chunxiu Qin, Yaxi Liu, Jian Mou and Jiangping Chen

Online knowledge communities make great contributions to global knowledge sharing and innovation. Resource tagging approaches have been widely adopted in such communities…

Abstract

Purpose

Online knowledge communities make great contributions to global knowledge sharing and innovation. Resource tagging approaches have been widely adopted in such communities to describe, annotate and organize knowledge resources mainly through users’ participation. However, it is unclear what causes the adoption of a particular resource tagging approach. The purpose of this paper is to identify factors that drive users to use a hybrid social tagging approach.

Design/methodology/approach

Technology acceptance model and social cognitive theory are adopted to support an integrated model proposed in this paper. Zhihu, one of the most popular online knowledge communities in China, is taken as the survey context. A survey was conducted with a questionnaire and collected data were analyzed through structural equation model.

Findings

A new hybrid social resource tagging approach was refined and described. The empirical results revealed that self-efficacy, perceived usefulness (PU) and perceived ease of use exert positive effect on users’ attitude. Moreover, social influence, PU and attitude impact significantly on users’ intention to use a hybrid social resource tagging approach.

Originality/value

Theoretically, this study enriches the type of resource tagging approaches and recognizes factors influencing user adoption to use it. Regarding the practical parts, the results provide online information system providers and designers with referential strategies to improve the performance of the current tagging approaches and promote them.

Details

Aslib Journal of Information Management, vol. 71 no. 2
Type: Research Article
ISSN: 2050-3806

Keywords

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Article
Publication date: 25 March 2019

Ji Cheng, Ping Jiang, Qi Zhou, Jiexiang Hu, Tao Yu, Leshi Shu and Xinyu Shao

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational…

Abstract

Purpose

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the adaptive metamodel-based design optimization (AMBDO) approaches have been widely used. This paper aims to develop an AMBDO approach, a lower confidence bounding approach based on the coefficient of variation (CV-LCB) approach, to balance the exploration and exploitation objectively for obtaining a global optimum under limited computational budget.

Design/methodology/approach

In the proposed CV-LCB approach, the coefficient of variation (CV) of predicted values is introduced to indicate the degree of dispersion of objective function values, while the CV of predicting errors is introduced to represent the accuracy of the established metamodel. Then, a weighted formula, which takes the degree of dispersion and the prediction accuracy into consideration, is defined based on the already-acquired CV information to adaptively update the metamodel during the optimization process.

Findings

Ten numerical examples with different degrees of complexity and an AIAA aerodynamic design optimization problem are used to demonstrate the effectiveness of the proposed CV-LCB approach. The comparisons between the proposed approach and four existing approaches regarding the computational efficiency and robustness are made. Results illustrate the merits of the proposed CV-LCB approach in computational efficiency and robustness.

Practical implications

The proposed approach exhibits high efficiency and robustness in engineering design optimization involving computational simulations.

Originality/value

CV-LCB approach can balance the exploration and exploitation objectively.

Details

Engineering Computations, vol. 36 no. 3
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 16 April 2018

Qi Zhou, Xinyu Shao, Ping Jiang, Tingli Xie, Jiexiang Hu, Leshi Shu, Longchao Cao and Zhongmei Gao

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might…

Abstract

Purpose

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.

Design/methodology/approach

In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.

Findings

Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.

Practical implications

The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.

Originality/value

A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.

Details

Engineering Computations, vol. 35 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 18 April 2017

Qi Zhou, Ping Jiang, Xinyu Shao, Hui Zhou and Jiexiang Hu

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under…

Abstract

Purpose

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under interval uncertainty can become computationally intractable because the inner level must perform robust evaluation for each design alternative delivered from the outer level. This paper aims to propose an on-line Kriging metamodel-assisted variable adjustment robust optimization (OLK-VARO) to ease the computational burden of previous VARO approach.

Design/methodology/approach

In OLK-VARO, Kriging metamodels are constructed for replacing robust evaluations of the design alternative delivered from the outer level, reducing the nested optimization structure of previous VARO approach into a single loop optimization structure. An on-line updating mechanism is introduced in OLK-VARO to exploit the obtained data from previous iterations.

Findings

One nonlinear numerical example and two engineering cases have been used to demonstrate the applicability and efficiency of the proposed OLK-VARO approach. Results illustrate that OLK-VARO is able to obtain comparable robust optimums as to that obtained by previous VARO, while at the same time significantly reducing computational cost.

Practical implications

The proposed approach exhibits great capability for practical engineering design optimization problems under interval uncertainty.

Originality/value

The main contribution of this paper lies in the following: an OLK-VARO approach under interval uncertainty is proposed, which can significantly ease the computational burden of previous VARO approach.

Details

Engineering Computations, vol. 34 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

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