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Automation of detecting cracked surfaces on buildings or in any industrially manufactured products is emerging nowadays. Detection of the cracked surface is a challenging task for inspectors. Image-based automatic inspection of cracks can be very effective when compared to human eye inspection. With the advancement in deep learning techniques, by utilizing these methods the authors can create automation of work in a particular sector of various industries.

In this study, an upgraded convolutional neural network-based crack detection method has been proposed. The dataset consists of 3,886 images which include cracked and non-cracked images. Further, these data have been split into training and validation data. To inspect the cracks more accurately, data augmentation was performed on the dataset, and regularization techniques have been utilized to reduce the overfitting problems. In this work, VGG19, Xception and Inception V3, along with Resnet50 V2 CNN architectures to train the data.

A comparison between the trained models has been performed and from the obtained results, Xception performs better than other algorithms with 99.54% test accuracy. The results show detecting cracked regions and firm non-cracked regions is very efficient by the Xception algorithm.

The proposed method can be way better back to an automatic inspection of cracks in buildings with different design patterns such as decorated historical monuments.

This paper presents the phenomenographic analysis of students' approaches to learning in the first year architectural design coursework; thereby correlating contextualization in the architectural curriculum.

This paper reviews phenomenographic data of first year architecture students' learning experience through a comparative analysis of first- and fourth-year students' approaches to learning in the design studio; further co-relating this analysis to the final classification involving all five years of students' learning approaches in the architecture program.

Five meta-categories of the comparative analysis and nineteen meta-categories of the final classification are evaluated using first-year students' learning approaches – to understand the importance of contextualization in curriculums of architecture.

This phenomenographic analysis of first-year students' learning experience represents the onward journey from surface-to-deep approaches to learning that is encountered in their learning approaches, pertaining to the design process in the design coursework during five years of architectural education.

This paper systematically extends the discussion of first year architecture students' engagement in the design process that leads to deep learning; further delving into the static dimension of knowledge and its extension to the dynamic dimension of knowing architecture.

The purpose of this study was conducted at an enterprise that produces fasteners and is one of the leading companies in the sector in terms of market share. Possible defects in the coating of bolts and nuts either lead to products being scrapped or all of the coating process being repeated from beginning to end. In both cases, the enterprise faces a waste of time and excessive costs. Through this project, the six sigma theory and its means were effectively used to improve the efficiency and quality management of the company. The selection of the six sigma project has also contributed to the creation of various documents to be used for project screening and evaluation of financial results.

Six sigma is an optimization strategy that is used to improve the profitability of businesses, avoid waste, scrap and losses, reduce costs and improve the effectiveness of all activities to meet or exceed customers’ needs and expectations. Six sigma’s process improvement model, known as Definition-Measurement-Analysis-Improvement-Control, contributes to the economic and technical achievements of businesses. The normal distribution of a process should be within ±3 sigma of the mean. This represents a scale of 99.7% certainty. However, improving the process through the utilization of the six sigma rule, which accepts normal variabilities of processes twice as strict, will result in an error rate of 3.4 per million instead of 2,700 per million for each product or service.

Using six sigma practices to reduce the costs associated with low quality and to increase economic added value became a cultural practice. With this, the continuation of six sigma practices throughout the Company was intended. The annual cost reduction achieved with the utilization of six sigma practices can be up to $21,780. When time savings are also considered, a loss reduction of about $30,000 each year can be achieved. The coating thickness efficiency increased from 85% to 95% after the improvements made through the six sigma project. There is a significant increase in the efficiency of coating thickness. In addition, the coating thickness efficiency is also close to the target value of 95%–97%.

The results of the study were optimized with the help of deep learning. The performance of the model created in deep learning was quite close to the actual performance. This result implicates the validity of the improvement work. The results may act as a guide for the use of deep learning in new projects.

Challenges of conducting site visit activities, a vital component of architecture learning during the recent pandemic have proved our unreadiness in facing the digital future. The lack of understanding of learning technology has affected the education experience. Thus, there is a need to investigate immersive learning technology such as immersive virtual reality (IVR) to replace students’ concrete experience in the current learning setting. This study aims to answer: (1) What is the influence of IVR in experiential learning (EL) in enhancing the personal spatial experience? (2) Does IVR in EL influence students' approach to learning during the architecture design process?

The research was conducted as an action research design approach. Action research was employed in the first-year architecture design studio by the lecturer as a practitioner-researcher. The personal spatial experience survey was performed in the earlier phase to identify the students’ prior spatial experience. Architectural Spatial Experience Simulation (ASES) a learning tool was implemented and assessed with Architecture Design Learning Assessment (ADLA) rubric, which was developed to evaluate EL and student’s approach to learning during the architecture design learning process.

The outcomes revealed that ASES as a learning tool in EL could improve the participants’ spatial experience, particularly those with minimal prior personal spatial experience. ASES was recognized to enhance the participants’ EL experience and encourage changes in student’s approach to learning from surface to deep learning.

This research benefits the architecture design learning process by offering a learning tool and a framework to resolve challenges in performing site visit activities and digital learning. It also contributes by expanding the EL theory and students’ approach to learning knowledge in the architecture education field.

The role of entrepreneurship education in promoting entrepreneurial actions remains unclear. The purpose of this paper is to investigate the logic of different types of entrepreneurship education and the effect of learning characteristics in promoting entrepreneurial actions among student entrepreneurs in the higher education setting.

The study employs a quantitative approach involving the use of survey data collected via an Internet tool. The constructs of variables are measured using previously tested scales. The data were analysed using partial least squares modelling because it can handle formative and reflective constructs in the same model and is capable of testing for moderation.

The findings illustrate that voluntary entrepreneurship education generates learning outcomes in terms of students' entrepreneurial actions, which is important because without action, a venture will never be launched. This is especially so if students show a deep learning orientation, while mastery motivation showed a significant and negative moderating effect. This is not the case for compulsory entrepreneurship education.

Embedded in construal level theory, this paper offers knowledge that can help to advance entrepreneurship education research (1) by uncovering the role of different types of entrepreneurship education interventions, (2) by considering students' entrepreneurial actions as the dependent variable and (3) by unravelling the role of students' learning characteristics in the efficacy of entrepreneurship education interventions. By doing this, the study addresses recent repeated calls for more fine-grained research focused on how university students learn in entrepreneurship in higher education and its effects.

Many master’s students enrol in coursework-based programmes to improve their professional knowledge and skills for the job market. Most studies of employability in higher education focus on undergraduates rather than master’s students, although the number of master’s students worldwide has increased significantly in recent years. This study explores the factors involved in the perceived employability (PE) of master’s students in Hong Kong.

The authors first proposed a conceptual model of PE based on the social cognitive career theory. Using survey data from 786 master’s students in Hong Kong, the authors applied descriptive statistics and an ordinary least squares (OLS) regression to address the following research questions: How do master’s students gauge their PE? How do person, learning and environment variables influence the PE of master’s students?

The authors found that PE is influenced by students' approaches to learning and their institutional career support.

Few studies examined whether students' learning experiences during the master’s programmes influence their employability. This study highlights the importance of learning experiences and career support in coursework-based master’s programmes for enhancing graduate employability.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

The positive impact of training can be enhanced if learners set appropriate goals at the outset. By opting to pursue a mastery goal, learners are likely to engage more with the deep learning strategies that are associated with a broader range of desirable outcomes for both learners and their organization.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The asymmetry of the velocity profile caused by geometric deformation, complex turbulent motion and other factors must be considered to effectively use the flowmeter on any section. This study aims to better capture the flow field information and establish a model to predict the profile velocity, we take the classical double elbow as the research object and propose to divide the flow field into three categories with certain common characteristics.

The deep learning method is used to establish the model of multipath linear velocity fitting profile average velocity. A total of 480 groups of data are taken for training and validation, with ten integer velocity flow fields from 1 m/s to 10 m/s. Finally, accuracy research with relative error as standard is carried out.

The numerical experiment yielded the following promising results: the maximum relative error is approximately 1%, and in the majority of cases, the relative error is significantly lower than 1%. These results demonstrate that it surpasses the classical optimization algorithm Equal Tab (5%) and the traditional artificial neural network (3%) in the same scenario. In contrast with the previous research on a fixed profile, we focus on all the velocity profiles of a certain length for the first time, which can expand the application scope of a multipath ultrasonic flowmeter and promote the research on flow measurement in any section.

This work proposes to divide the flow field of double elbow into three categories with certain common characteristics to better capture the flow field information and establish a model to predict the profile velocity.

This research aimed to define the factors that may impact the effectiveness of online architectural education during COVID-19 and to examine the degree of students' and instructors' satisfaction with these factors among Jordanian governmental universities. Further, the research examines the relationships/interrelationships between the degree of their satisfaction with these factors and the students' and instructors' age, gender, education level, home size, and family size.

Different research methods were used to achieve the research purposes, including semi-structured interviews, online questionnaires and reviewing recent literature. This research used descriptive statistics and Pearson product-moment correlation coefficient (Pearson r) to analyze the data.

This research found that online architectural education during COVID-19 was stressful. It was ineffective in teaching practical architectural courses like design and negatively affected the architectural learning process and outcomes. In contrast, the online teaching of architectural theoretical courses was reliable and convenient if the students and instructors had intentional, sufficient technological and appropriate resources. Online architectural education negatively affected the students' design ability and skills, peer review, intended learning outcomes (ILOs) achievements, the quality of feedback, workload, interaction mode, participation, collaboration, productivity and increased cheating on online exams. The home environment was unsuitable for online architectural education. Family interventions, privacy, home size and family size significantly influence online architectural education's effectiveness.

Students' and instructors' satisfaction determines the continuity of using online teaching mode, which depends on information quality, system quality, service quality, perceived ease of use, perceived usefulness, achieved intended learning outcomes, cognitive absorption, skills, motivation, engagement, implementing resources and strategies and positive emotions as hope and enjoyment. Students' and instructors' satisfaction reflects how they view their learning experience, which is crucial in assessing the effectiveness of online education quality that focuses on the context, input, process and product, which is still not clearly understood, particularly for developing countries.

Online, distance, and eLearning (ODeL) continue to gain recognition as a mandatory component of delivery of education in institutions of higher learning (IHL) around the world following the outbreak of coronavirus disease (COVID-19). This paradigm shift is informed by the need to ensure uninterrupted, valuable, and safe learning experiences for learners during the pandemic. However, governments ordered the closure of schools and colleges following the declaration of COVID-19 as a world pandemic by the World Health Organization (WHO). A report by United Nations Educational, Scientific and Cultural Organization revealed that there was a significant loss of schooling time following the closure of educational facilities which affected over 1.5 billion learners in 194 nations globally. This study explored the use of online approaches to intensify online learning efficacy in IHL. Data collection was conducted using qualitative methods and data analysis done using themes and sub-themes. Findings from this study indicate that students’ engagements on discussion forums are consistent with collaborative learning. Results further support the view that regular, prompt, and meaningful feedback is critical in promoting constructive learning and reflection among students. Based on the findings of this study, practical implications are discussed for stakeholders interested in establishing and strengthening effective delivery of online learning content to enhance students’ learning experiences.