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Article
Publication date: 14 December 2023

Huaxiang Song, Chai Wei and Zhou Yong

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of…

Abstract

Purpose

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

Design/methodology/approach

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

Findings

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

Originality/value

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

Details

International Journal of Web Information Systems, vol. 20 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 1 April 2024

Zeyang Zhou and Jun Huang

This study aims to learn the dynamic radar cross-section (RCS) of a deflection air brake.

Abstract

Purpose

This study aims to learn the dynamic radar cross-section (RCS) of a deflection air brake.

Design/methodology/approach

The aircraft model with delta wing, V-shaped tail and blended wing body is designed, and high-precision unstructured grid technology is used to deal with the surface of air brake and fuselage. The calculation method based on multiple tracking and dynamic scattering is presented to calculate RCS.

Findings

The fuselage has a low scattering level, and the opening air brake will bring obvious dynamic RCS effects to itself and the whole machine. The average indicator of air brake RCS can be lower than –0.6 dBm2 under the tail azimuth, while that of forward and lateral direction is lower. The mean RCS of fuselage is obviously higher than that of air brake, while the deflected air brake and its cabin can still provide strong scattering sources at some azimuths. When the air brake is opening, the change amplitude of the aircraft forward RCS can exceed 19.81 dBm2.

Practical implications

This research has practical significance for the dynamic electromagnetic scattering analysis and stealth design of the air brake.

Originality/value

The calculation method for aircraft RCS considering air brake dynamic deflection has been established.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 26 March 2024

Keyu Chen, Beiyu You, Yanbo Zhang and Zhengyi Chen

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction…

Abstract

Purpose

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Design/methodology/approach

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

Findings

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

Originality/value

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 8 March 2024

Sarah Jerasa and Sarah K. Burriss

Artificial intelligence (AI) has become increasingly important and influential in reading and writing. The influx of social media digital spaces, like TikTok, has also shifted the…

Abstract

Purpose

Artificial intelligence (AI) has become increasingly important and influential in reading and writing. The influx of social media digital spaces, like TikTok, has also shifted the ways multimodal composition takes place alongside AI. This study aims to argue that within spaces like TikTok, human composers must attend to the ways they write for, with and against the AI-powered algorithm.

Design/methodology/approach

Data collection was drawn from a larger study on #BookTok (the TikTok subcommunity for readers) that included semi-structured interviews including watching and reflecting on a TikTok they created. The authors grounded this study in critical posthumanist literacies to analyze and open code five #BookTok content creators’ interview transcripts. Using axial coding, authors collaboratively determined three overarching and entangled themes: writing for, with and against.

Findings

Findings highlight the nuanced ways #BookTokers consider the AI algorithm in their compositional choices, namely, in the ways how they want to disseminate their videos to a larger audience or more niche-focused community. Throughout the interviews, participants revealed how the AI algorithm was situated differently as both audience member, co-author and censor.

Originality/value

This study is grounded in critical posthumanist literacies and explores composition as a joint accomplishment between humans and machines. The authors argued that it is necessary to expand our human-centered notions of what it means to write for an audience, to co-author and to resist censorship or gatekeeping.

Details

English Teaching: Practice & Critique, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1175-8708

Keywords

Open Access
Article
Publication date: 23 January 2024

Luís Jacques de Sousa, João Poças Martins, Luís Sanhudo and João Santos Baptista

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase…

Abstract

Purpose

This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.

Design/methodology/approach

This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.

Findings

This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.

Originality/value

Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.

Details

Construction Innovation , vol. 24 no. 7
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 29 February 2024

Atefeh Hemmati, Mani Zarei and Amir Masoud Rahmani

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of…

Abstract

Purpose

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

Design/methodology/approach

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

Findings

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

Research limitations/implications

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

Originality/value

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.

Details

International Journal of Pervasive Computing and Communications, vol. 20 no. 2
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 19 December 2023

Susan Gardner Archambault

Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught…

Abstract

Purpose

Research shows that postsecondary students are largely unaware of the impact of algorithms on their everyday lives. Also, most noncomputer science students are not being taught about algorithms as part of the regular curriculum. This exploratory, qualitative study aims to explore subject-matter experts’ insights and perceptions of the knowledge components, coping behaviors and pedagogical considerations to aid faculty in teaching algorithmic literacy to postsecondary students.

Design/methodology/approach

Eleven semistructured interviews and one focus group were conducted with scholars and teachers of critical algorithm studies and related fields. A content analysis was manually performed on the transcripts using a mixture of deductive and inductive coding. Data analysis was aided by the coding software program Dedoose (2021) to determine frequency totals for occurrences of a code across all participants along with how many times specific participants mentioned a code. Then, findings were organized around the three themes of knowledge components, coping behaviors and pedagogy.

Findings

The findings suggested a set of 10 knowledge components that would contribute to students’ algorithmic literacy along with seven behaviors that students could use to help them better cope with algorithmic systems. A set of five teaching strategies also surfaced to help improve students’ algorithmic literacy.

Originality/value

This study contributes to improved pedagogy surrounding algorithmic literacy and validates existing multi-faceted conceptualizations and measurements of algorithmic literacy.

Details

Information and Learning Sciences, vol. 125 no. 1/2
Type: Research Article
ISSN: 2398-5348

Keywords

Article
Publication date: 22 November 2023

Kalpana Pitchaimani, Tarik Zouadi, K.S. Lokesh and V. Raja Sreedharan

As the world is becoming more volatile and uncertain, organizations face much complexity in their daily operations. Further, there is a much ambiguity in business operations to…

Abstract

Purpose

As the world is becoming more volatile and uncertain, organizations face much complexity in their daily operations. Further, there is a much ambiguity in business operations to achieve the effective utilization of resources. The work optimizes a novel constraint programming model approach of the utilization of shuttle services vehicle while considering cost savings, employee wellbeing and other real an Information Technology enabled service (ITES) industry constraints.

Design/methodology/approach

The present work considers a novel extension of the vehicle routing problem related to the shuttle service operation in an ITES industry in VUCA context. Additionally, the model considers the women safety aspects, which engages the company to provide a security guard for women employees in the night shift.

Findings

Numerical experiments were conducted on real instances data of ITES industrial partner. The results show that the vehicle utilization increased from 75% up to 96% while ensuring in parallel the wellbeing of employees and women safety during the night shift. Finally, the proposed model is converted to a decision support application allowing ITES partner to plan employees shuttle service operations efficiently.

Originality/value

Study has evaluated the shuttle services optimization for ITES industry using data from industrial which makes it a unique contribution to literature in shuttle operations. Further, the study used constraint programming to evaluate the vehicle utilization and security allocation, thereby introducing new parameter on security allocation in open VRP problem.

Details

International Journal of Quality & Reliability Management, vol. 41 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Open Access
Article
Publication date: 21 December 2023

Rafael Pereira Ferreira, Louriel Oliveira Vilarinho and Americo Scotti

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards…

Abstract

Purpose

This study aims to propose and evaluate the progress in the basic-pixel (a strategy to generate continuous trajectories that fill out the entire surface) algorithm towards performance gain. The objective is also to investigate the operational efficiency and effectiveness of an enhanced version compared with conventional strategies.

Design/methodology/approach

For the first objective, the proposed methodology is to apply the improvements proposed in the basic-pixel strategy, test it on three demonstrative parts and statistically evaluate the performance using the distance trajectory criterion. For the second objective, the enhanced-pixel strategy is compared with conventional strategies in terms of trajectory distance, build time and the number of arcs starts and stops (operational efficiency) and targeting the nominal geometry of a part (operational effectiveness).

Findings

The results showed that the improvements proposed to the basic-pixel strategy could generate continuous trajectories with shorter distances and comparable building times (operational efficiency). Regarding operational effectiveness, the parts built by the enhanced-pixel strategy presented lower dimensional deviation than the other strategies studied. Therefore, the enhanced-pixel strategy appears to be a good candidate for building more complex printable parts and delivering operational efficiency and effectiveness.

Originality/value

This paper presents an evolution of the basic-pixel strategy (a space-filling strategy) with the introduction of new elements in the algorithm and proves the improvement of the strategy’s performance with this. An interesting comparison is also presented in terms of operational efficiency and effectiveness between the enhanced-pixel strategy and conventional strategies.

Details

Rapid Prototyping Journal, vol. 30 no. 11
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 28 February 2023

Angeliki Nikolinakou and Joe Phua

Social media has the potential to enable exchange of diverse opinions, foster dialogue on important social issues and exert positive influence on stakeholders and society…

Abstract

Purpose

Social media has the potential to enable exchange of diverse opinions, foster dialogue on important social issues and exert positive influence on stakeholders and society. However, evidence is contradictory as to whether this is the case; it is possible that millennials' behaviors on social media are mainly driven by conservation (conformity and safety) or self-enhancement (power and achievement). In this research, the authors examine the extent to which different human values (self-transcendence, conservation, self-enhancement and openness to change) influence millennials' activities and behaviors on social media.

Design/methodology/approach

The authors conduct three separate surveys on Facebook, Twitter and Instagram with 491 millennials (18–34 years of age) in the USA, examining the influence of four higher-order values of the Schwartz human values model (open self-transcendence, conservation, self-enhancement and openness to change) on specific social media activities (consumption, self-focused and sharing nonpersonal content activities).

Findings

First, the authors find that for millennial users, human values significantly influence social media activities. Second, conservation values, followed by self-enhancement values, overshadow the expression of open self-transcendence values on social media. Thus, social media platforms may function more as agents of conservation and self-enhancement than agents of personal growth.

Originality/value

This is among the first studies to examine the influence of human values on social media and to find that human values such as conservation and self-enhancement have a strong influence on users' social media activities, while open self-transcendence values, which lead to expansion and growth, do not find genuine expression on social media.

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