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This paper aims to develop an optimization model to enhance pipeline assembly performance. It focuses on predicting the pipeline’s assembly pose while ensuring compliance with clamp constraints.

The assembly pose of the pipeline is quantitatively assessed by a proposed indicator based on joint defects. The assembly interference between the pipeline and assembly boundary is characterized quantitatively. Subsequently, an analytical mapping relationship is established between the assembly pose and assembly interference. A digital fitting model, along with a novel indicator, is established to discern the fit between the pipeline and clamp. Using the proposed indicators as the optimization objective and penalty term, an optimization model is established to predict the assembly pose based on the reinforced particle swarm optimization, incorporating a proposed adaptive inertia weight.

The optimization model demonstrates robust search capability and rapid convergence, effectively minimizing joint defects while adhering to clamp constraints. This leads to enhanced pipeline assembly efficiency and the achievement of a one-time assembly process.

The offset of the assembly boundary and imperfections in pipeline manufacturing may lead to joint defects during pipeline assembly, as well as failure in the fit between the pipeline and clamp. The assembly pose predicted by the proposed optimization model can effectively reduce the joint defects and satisfy clamp constraints. The efficiency of pipeline modification and assembly has been significantly enhanced.

Over the past few decades, BRICS nations have implemented several environmental legislations to combat environmental issues, along with the development of the financial sector. However, they still face the dual challenge of balancing financial development (FD) and reducing carbon emissions to achieve sustainable development. Hence, this study aims to explore how environmental policy stringency (EPS) influences FD in BRICS nations from 1993 to 2020.

The authors performed a panel data analysis to examine the effect of the EPS on FD. Firstly, they conducted a panel unit root test using the Levin–Lin–Chu and the Im–Pesaran–Shin unit root tests to check the stationarity of the data. Then, they used the fixed effect model for analysis. A feasible generalised least squares test is used to ensure the robustness of the results.

The EPS positively affects FD through financial markets and intuitions in BRICS nations, indicating that more stringent environmental policies of BRICS countries promote FD in these nations.

This study suggests that policymakers in BRICS nations should consider strengthening EPS, implying the dual benefit of aligning environmental sustainability goals with economic growth.

This study provides a deeper understanding by disassembling FD into financial markets and institutions, thereby establishing a nuanced relationship with EPS, which is highly relevant for addressing the distinctive financial systems and environmental challenges of BRICS nations. Therefore, this study fills this gap and offers new insights into the relationship between EPS and FD in these nations.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

Agriculture is an activity that plays an important role in human life. Similarly, the agricultural sector plays an important role in the national economy. One of the biggest problems of the agricultural sector is the carbon gas it produces during production. Fertilizing activities and tools used in plowing the fields cause this gas to be produced. The release of the said gas into nature causes serious damage to the environment. Therefore, carbon emissions in the agricultural sector are of vital importance. In line with this purpose, it is aimed to determine the most appropriate strategy for carbon emission in this study. As a result of the DEMATEL analysis, it was seen that the most appropriate strategy was effective regulations and auditing.

Drawing on signaling and social identity theories, the main objective of this paper is to suggest and validate a research framework to investigate the association of corporate social responsibility (CSR) perceptions with organizational attractiveness by uncovering the underlying mechanism of organizational trust.

By conducting regression analysis, the study hypotheses were tested with the data collected from a snowball convenient sample of 318 potential job seekers.

The study results revealed that prospective applicants' perceptions about a company's CSR undertakings are significantly associated with their trust in and attraction to the company. Noticeably, organizational trust partially mediated the direct relationship between CSR perceptions and organizational attractiveness.

Based on the study results, some specific theoretical advancements and helpful insights have been highlighted for human resources (HR) practitioners in today's competing organizations. The paper ends by outlining key research drawbacks and directions for possible work in the future.

Despite the plausible underlying role of organizational trust in the link between CSR and organizational attraction, empirical studies of this theoretical phenomenon are still lacking in the context of pre-hire recruitment literature. This may be the first study that identifies organizational trust as a salient psychological factor through which job seekers' CSR perceptions become more instrumental in influencing their attraction to a firm.

The attraction of online shopping has raised the demand for customized image searches, mainly in the fashion industry. Daily updates in this industry increase the size of the clothing database at a rapid rate. Hence, it is crucial to design an efficient and fast image retrieval system owing to the short-listing of images depending upon various parameters such as color, pattern, material used, style, etc.

This manuscript introduces an improved algorithm for the retrieval of images. The inherited quality of images is first enhanced through intensity modification and morphological operations achieved with the help of a light adjustment algorithm, followed by the speeded up robust feature (SURF) extraction and convolutional neural networks (CNN).

The results are validated under three performance parameters (precision, recall and accuracy) on a DeepFashion dataset. The proposed approach helps to extract the most relevant images from a larger dataset based on scores conferred by multiple cloth features to meet the demands of real-world applications. The efficiency of the proposed work is deduced from its effectiveness in comparison to existing works, as measured by performance parameters including precision, recall and F1 score. Further, it is also evaluated against other recent techniques on the basis of performance metrics.

The presented work is particularly advantageous in the fashion industry for creating precise categorization and retrieving visually appealing photographs from a diverse library based on different designs, patterns and fashion trends. The proposed approach is quite better than the other existing ML/DL-based approaches for image retrieval and classification. This further reflects a significant improvement in customized image retrieval in the field of the fashion industry.

The purpose of this study is to investigate and analyse the potential of existing buildings in the UK to contribute to the net-zero emissions target. Specifically, it aims to address the significant emissions from building fabrics which pose a threat to achieving these targets if not properly addressed.

The study, based on a literature review and ten (10) case studies, explored five investigative approaches for evaluating building fabric: thermal imaging, in situ U-value testing, airtightness testing, energy assessment and condensation risk analysis. Cross-case analysis was used to evaluate both case studies using each approach. These methodologies were pivotal in assessing buildings’ existing condition and energy consumption and contributing to the UK’s net-zero ambitions.

Findings reveal that incorporating the earlier approaches into the building fabric showed great benefits. Significant temperature regulation issues were identified, energy consumption decreased by 15% after improvements, poor insulation and artistry quality affected the U-values of buildings. Implementing retrofits such as solar panels, air vents, insulation, heat recovery and air-sourced heat pumps significantly improved thermal performance while reducing energy consumption. Pulse technology proved effective in measuring airtightness, even in extremely airtight houses, and high airflow and moisture management were essential in preserving historic building fabric.

The research stresses the need to understand investigative approaches’ strengths, limitations and synergies for cost-effective energy performance strategies. It emphasizes the urgency of eliminating carbon dioxide (CO₂) and greenhouse gas emissions to combat global warming and meet the 1.5° C threshold.

Supply chain management (SCM) has evolved to fulfill the demands of the dynamic global business environment. The development of the Internet of Things (IoT), which offers unmatched connectivity and real-time data insights, has further transformed SCM. This chapter provides an overview of SCM development and its integration with IoTs. This integration led to improved inventory control, supply chain optimization (SCO), and visibility which further enhances the conventional SCM and provides benefits, such as more accurate real-time tracking and monitoring, improved data analytics, more efficient logistics and transportation management, and reduced costs and wastages. However, despite these benefits, there are various associated challenges and concerns, like privacy and data security, compatibility and interoperability, implementation costs, returns on investment, trained workforce, and training requirements, which are required to be addressed. Additionally, the outcomes of this study and managerial implications are provided along with the future research scope. Overall, this chapter provides valuable insight into the transformative potential of IoT in SCM and practical suggestions on how managers can successfully navigate difficulties and get benefits from the IoT-SCM integration. Organizations can enhance their supply chain operations, efficiency, and innovation by actively confronting challenges and taking advantage of the opportunities provided by IoT technologies. This will ultimately result in the delivery of greater value to both stakeholders and customers.

This study intended to bridge this gap by investigating the perspectives of international students regarding Taiwan’s bilingual education policy and its impact on their willingness to enroll in graduate programs in Taiwan. Additionally, the comparisons among international students from diverse backgrounds were examined.

Employing a qualitative research design, the study included nine participants from three countries, with each country contributing three students. Three sessions of semi-structured interviews were conducted, supplemented by the analysis of 15 documents from 8 organizations and universities.

Results indicated predominantly negative views toward Taiwan’s bilingual education policy, with little impact reported by two participants and none by others. Furthermore, themes derived from document analysis deviated from participants' viewpoints.

A focus on students from southern Asia, which was the major source of international students in Taiwan, becomes critical. In the same vein, little literature has been found concerning graduate students' perceptions toward bilingual education policy, which should be thoroughly explored as well.

How does business model design play a role in enabling manufacturing firms’ services? This study aims to investigate the impact of two distinct types of business model design, namely, efficiency-centered business model design (EBMD) and novelty-centered business model design (NBMD), and their effects in balanced and imbalanced configurations, on two types of services: product- and customer-oriented services.

Using matched survey data of 390 top managers and objective performance data of 195 Chinese manufacturing firms, this study uses hierarchical regression, polynomial regression and response surface analysis to test the hypotheses.

The results show that while EBMD positively affects product-oriented services, NBMD positively affects customer-oriented services. Both types of services exert a significant influence on firm performance. Furthermore, the degree of product- and customer-oriented services increases with an increasing effort level with a balance between EBMD and NBMD. Asymmetrical, imbalanced configuration effects reveal that the degree of product-oriented services is higher when the EBMD effort exceeds the NBMD effort, and the degree of customer-oriented services is higher when the NBMD effort exceeds the EBMD effort.

This study enriches the understanding of designing business models to facilitate service growth in manufacturing firms, ultimately benefiting firm performance. In addition, exploring balanced and imbalanced configurations of EBMD and NBMD offers new insights into business model dual design research.