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1 – 10 of over 4000
Article
Publication date: 25 June 2024

Ranran Yang, Zhaojun Liu, Jingjing Li and Jianling Jiao

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect…

Abstract

Purpose

Waste classification plays an important role in reducing pollution, promoting waste recycling and resource utilization. This paper aims to explore the multiple reasons that affect the performance of waste classification governance.

Design/methodology/approach

Content analysis of the existing waste classification policies is conducted using the Latent Dirichlet Allocation (LDA) model. Based on this analysis, influencing factors are identified through the technology-organization-environment (TOE) research framework. The condition configurations and action paths that cause differences in governance performance are derived using the fuzzy-set qualitative comparative analysis method (fsQCA).

Findings

The results show that there are spatial and temporal disparities in waste classification policies among different provinces/cities. In most situations, the implementation effect of policy combinations is better than that of a single type of policy, with mandatory policies playing a key role. Additionally, a single influencing factor cannot constitute the bottleneck of high governance performance. Policy topics coordinate with environmental and technical factors to influence governance performance. Finally, in light of China's actual governance situation, several targeted implications are proposed for the practical optimization of local government waste classification governance.

Originality/value

This paper presents a novel approach by integrating multiple heterogeneous data sources from both online and offline channels, adopting a public-government perspective and applying the fsQCA method to investigate the combined effects of technical, organizational and environmental factors on waste classification governance performance across 31 provinces and cities in China.

Details

Management of Environmental Quality: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1477-7835

Keywords

Article
Publication date: 29 December 2023

Thanh-Nghi Do and Minh-Thu Tran-Nguyen

This study aims to propose novel edge device-tailored federated learning algorithms of local classifiers (stochastic gradient descent, support vector machines), namely, FL-lSGD…

Abstract

Purpose

This study aims to propose novel edge device-tailored federated learning algorithms of local classifiers (stochastic gradient descent, support vector machines), namely, FL-lSGD and FL-lSVM. These algorithms are designed to address the challenge of large-scale ImageNet classification.

Design/methodology/approach

The authors’ FL-lSGD and FL-lSVM trains in a parallel and incremental manner to build an ensemble local classifier on Raspberry Pis without requiring data exchange. The algorithms load small data blocks of the local training subset stored on the Raspberry Pi sequentially to train the local classifiers. The data block is split into k partitions using the k-means algorithm, and models are trained in parallel on each data partition to enable local data classification.

Findings

Empirical test results on the ImageNet data set show that the authors’ FL-lSGD and FL-lSVM algorithms with 4 Raspberry Pis (Quad core Cortex-A72, ARM v8, 64-bit SoC @ 1.5GHz, 4GB RAM) are faster than the state-of-the-art LIBLINEAR algorithm run on a PC (Intel(R) Core i7-4790 CPU, 3.6 GHz, 4 cores, 32GB RAM).

Originality/value

Efficiently addressing the challenge of large-scale ImageNet classification, the authors’ novel federated learning algorithms of local classifiers have been tailored to work on the Raspberry Pi. These algorithms can handle 1,281,167 images and 1,000 classes effectively.

Details

International Journal of Web Information Systems, vol. 20 no. 1
Type: Research Article
ISSN: 1744-0084

Keywords

Open Access
Article
Publication date: 4 July 2023

Joacim Hansson

In this article, the author discusses works from the French Documentation Movement in the 1940s and 1950s with regard to how it formulates bibliographic classification systems as…

Abstract

Purpose

In this article, the author discusses works from the French Documentation Movement in the 1940s and 1950s with regard to how it formulates bibliographic classification systems as documents. Significant writings by Suzanne Briet, Éric de Grolier and Robert Pagès are analyzed in the light of current document-theoretical concepts and discussions.

Design/methodology/approach

Conceptual analysis.

Findings

The French Documentation Movement provided a rich intellectual environment in the late 1940s and early 1950s, resulting in original works on documents and the ways these may be represented bibliographically. These works display a variety of approaches from object-oriented description to notational concept-synthesis, and definitions of classification systems as isomorph documents at the center of politically informed critique of modern society.

Originality/value

The article brings together historical and conceptual elements in the analysis which have not previously been combined in Library and Information Science literature. In the analysis, the article discusses significant contributions to classification and document theory that hitherto have eluded attention from the wider international Library and Information Science research community. Through this, the article contributes to the currently ongoing conceptual discussion on documents and documentality.

Details

Journal of Documentation, vol. 80 no. 3
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 29 August 2024

Yizhuo Zhang, Yunfei Zhang, Huiling Yu and Shen Shi

The anomaly detection task for oil and gas pipelines based on acoustic signals faces issues such as background noise coverage, lack of effective features, and small sample sizes…

Abstract

Purpose

The anomaly detection task for oil and gas pipelines based on acoustic signals faces issues such as background noise coverage, lack of effective features, and small sample sizes, resulting in low fault identification accuracy and slow efficiency. The purpose of this paper is to study an accurate and efficient method of pipeline anomaly detection.

Design/methodology/approach

First, to address the impact of background noise on the accuracy of anomaly signals, the adaptive multi-threshold center frequency variational mode decomposition method(AMTCF-VMD) method is used to eliminate strong noise in pipeline signals. Secondly, to address the strong data dependency and loss of local features in the Swin Transformer network, a Hybrid Pyramid ConvNet network with an Agent Attention mechanism is proposed. This compensates for the limitations of CNN’s receptive field and enhances the Swin Transformer’s global contextual feature representation capabilities. Thirdly, to address the sparsity and imbalance of anomaly samples, the SpecAugment and Scaper methods are integrated to enhance the model’s generalization ability.

Findings

In the pipeline anomaly audio and environmental datasets such as ESC-50, the AMTCF-VMD method shows more significant denoising effects compared to wavelet packet decomposition and EMD methods. Additionally, the model achieved 98.7% accuracy on the preprocessed anomaly audio dataset and 99.0% on the ESC-50 dataset.

Originality/value

This paper innovatively proposes and combines the AMTCF-VMD preprocessing method with the Agent-SwinPyramidNet model, addressing noise interference and low accuracy issues in pipeline anomaly detection, and providing strong support for oil and gas pipeline anomaly recognition tasks in high-noise environments.

Details

International Journal of Intelligent Computing and Cybernetics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-378X

Keywords

Expert briefing
Publication date: 14 August 2024

Although an easing of strict data export rules has provided temporary relief for foreign entities, classification standards and local pilot projects indicate which “important…

Article
Publication date: 30 April 2024

Shiqing Wu, Jiahai Wang, Haibin Jiang and Weiye Xue

The purpose of this study is to explore a new assembly process planning and execution mode to realize rapid response, reduce the labor intensity of assembly workers and improve…

Abstract

Purpose

The purpose of this study is to explore a new assembly process planning and execution mode to realize rapid response, reduce the labor intensity of assembly workers and improve the assembly efficiency and quality.

Design/methodology/approach

Based on the related concepts of digital twin, this paper studies the product assembly planning in digital space, the process execution in physical space and the interaction between digital space and physical space. The assembly process planning is simulated and verified in the digital space to generate three-dimensional visual assembly process specification documents, the implementation of the assembly process specification documents in the physical space is monitored and feed back to revise the assembly process and improve the assembly quality.

Findings

Digital twin technology enhances the quality and efficiency of assembly process planning and execution system.

Originality/value

It provides a new perspective for assembly process planning and execution, the architecture, connections and data acquisition approaches of the digital twin-driven framework are proposed in this paper, which is of important theoretical values. What is more, a smart assembly workbench is developed, the specific image classification algorithms are presented in detail too, which is of some industrial application values.

Details

Robotic Intelligence and Automation, vol. 44 no. 3
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 30 May 2024

Riyan Benny Sukmara, Ariyaningsih   and Rizqi Bachtiar

Understanding the stakeholders' role and interest are critical for implementing climate change policy. The dichotomy between adaptation and mitigation, which arguably creates…

Abstract

Purpose

Understanding the stakeholders' role and interest are critical for implementing climate change policy. The dichotomy between adaptation and mitigation, which arguably creates uncertainty at the implementation level, for example, is shaped by the role of the actors involved. In this regard, this study aims to investigate the interests and role of stakeholders in climate change adaptation at the national and regional levels in Indonesia. The country, Indonesia, is selected because it produces the largest amount of greenhouse gas emissions, and the people are at the highest risk of the impacts of climate change in the world. Furthermore, this study discusses the challenges in climate change adaptation in Indonesia.

Design/methodology/approach

This research uses a literature review and interviews with potential stakeholders. Purposive sampling methods were applied to select stakeholders for interviews. Interviews with key stakeholders were conducted through email and Zoom. Questions were developed based on the roles and interests of stakeholders.

Findings

According to the stakeholders, there is a need to establish links between climate change adaptation and local policy at the national and regional levels. The results reveal no integration strategy or approach to support climate change adaptation. Although there has been some climate change adaptation, few people are widely regarded as authorities on climate change policy. This study also discusses some challenges and opportunities to engage key stakeholders in Indonesia.

Originality/value

The study offers an understanding of stakeholders based on key stakeholders' interests and role in climate change adaptation in Indonesia. The research findings in this study generate prospects for the government or decision-makers or other stakeholders to deliberately aspire for policy planning. In addition, to prepare climate change adaptation policies relating to the role of stakeholders or community-based approaches to climate change adaptation, stakeholders can conduct more detailed studies to achieve community resilience in term of climate change adaptation.

Details

International Journal of Disaster Resilience in the Built Environment, vol. 15 no. 4
Type: Research Article
ISSN: 1759-5908

Keywords

Article
Publication date: 22 August 2024

Reinier Stribos, Roel Bouman, Lisandro Jimenez, Maaike Slot and Marielle Stoelinga

Powder bed additive manufacturing has recently seen substantial growth, yet consistently producing high-quality parts remains challenging. Recoating streaking is a common anomaly…

Abstract

Purpose

Powder bed additive manufacturing has recently seen substantial growth, yet consistently producing high-quality parts remains challenging. Recoating streaking is a common anomaly that impairs print quality. Several data-driven models for automatically detecting this anomaly have been proposed, each with varying effectiveness. However, comprehensive comparisons among them are lacking. Additionally, these models are often tailored to specific data sets. This research addresses this gap by implementing and comparing these anomaly detection models for recoating streaking in a reproducible way. This study aims to offer a clearer, more objective evaluation of their performance, strengths and weaknesses. Furthermore, this study proposes an improvement to the Line Profiles detection model to broaden its applicability, and a novel preprocessing step was introduced to enhance the models’ performances.

Design/methodology/approach

All found anomaly detection models have been implemented along with several preprocessing steps. Additionally, a new universal benchmarking data set has been constructed. Finally, all implemented models have been evaluated on this benchmarking data set and the effect of the different preprocessing steps was studied.

Findings

This comparison shows that the improved Line Profiles model established it as the most efficient detection approach in this study’s benchmark data set. Furthermore, while most state-of-the-art neural networks perform very well off the shelf, this comparison shows that specialised detection models outperform all others with the correct preprocessing.

Originality/value

This comparison gives new insights into different recoater streaking (RCS) detection models, showcasing each one with its strengths and weaknesses. Furthermore, the improved Line Profiles model delivers compelling performance in detecting RCS.

Details

Rapid Prototyping Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 20 March 2024

Floriberta Binarti, Pranowo Pranowo, Chandra Aditya and Andreas Matzarakis

This study aims to compare the local climate characteristics of Angkor Wat, Borobudur and Prambanan parks and determine effective strategies for mitigating thermal conditions that…

Abstract

Purpose

This study aims to compare the local climate characteristics of Angkor Wat, Borobudur and Prambanan parks and determine effective strategies for mitigating thermal conditions that could suit Borobudur and Angkor Wat.

Design/methodology/approach

The study employed local climate zone (LCZ) indicators and ten-year historical climate data to identify similarities and differences in local climate characteristics. Satellite imagery processing was used to create maps of LCZ indicators. Meanwhile, microclimate models were used to analyze sky view factors and wind permeability.

Findings

The study found that the three tropical large-scale archaeological parks have low albedo, a medium vegetation index and high impervious surface index. However, various morphological characteristics, aerodynamic properties and differences in temple stone area and altitude enlarge the air temperature range.

Practical implications

Based on the similarities and differences in local climate, the study formulated mitigation strategies to preserve the sustainability of ancient temples and reduce visitors' heat stress.

Originality/value

The local climate characterization of tropical archaeological parks adds to the number of LCZs. Knowledge of the local climate characteristics of tropical archaeological parks can be the basis for improving thermal conditions.

Details

Journal of Cultural Heritage Management and Sustainable Development, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-1266

Keywords

Open Access
Article
Publication date: 17 January 2024

Anastasia Krupskaya

The purpose of this paper is to identify and describe the influence of the knowledge base (KB) of the company on driving forces of innovation processes in knowledge-intensive…

Abstract

Purpose

The purpose of this paper is to identify and describe the influence of the knowledge base (KB) of the company on driving forces of innovation processes in knowledge-intensive services (KIS) and to compare the level of innovativeness of the final services.

Design/methodology/approach

The paper investigates through qualitative research 11 KIS organisations with different KB.

Findings

The research results identified and described the influence of the KB on driving forces of innovations processes and its results in companies with four newly identified KBs (analytical, synthetic, symbolic and compliance).

Research limitations/implications

Further research, based on a larger number of companies, is needed to confirm the results of this research and to complement the effect of the KB on driving forces of innovation.

Practical implications

This research can help organisations understand how to develop strategic plans and new ideas for innovative services depending on the KB of the organisation.

Social implications

The description of successful innovation processes and results in several leading companies presented in the study may help other companies in identifying knowledge-integration practices to improve performance and innovation processes that support multiplicity, productivity and creativity.

Originality/value

The study systemised the sources of new ideas for innovation in companies with different KB, several driving forces of innovation were identified and how these forces are affected by each KB; lastly, innovation results were compared in companies with different KB.

Details

foresight, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-6689

Keywords

1 – 10 of over 4000