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Aiming to resolve cross-cultural paradoxes in combining artificial intelligence (AI) with human intelligence (HI) for international humanitarian logistics, this paper aims to adopt an unorthodox Yin–Yang dialectic approach to address how AI–HI interactions can be interpreted as a sophisticated cross-cultural knowledge creation (KC) system that enables more effective decision-making for providing humanitarian relief across borders.

This paper is conceptual and pragmatic in nature, whereas its structure design follows the requirements of a real impact study.

Based on experimental information and logical reasoning, the authors first identify three critical cross-cultural challenges in AI–HI collaboration: paradoxes of building a cross-cultural KC system, paradoxes of integrative AI and HI in moral judgement and paradoxes of processing moral-related information with emotions in AI–HI collaboration. Then applying the Yin–Yang dialectic to interpret Klir’s epistemological frame (1993), the authors propose an unconventional stratified system of cross-cultural KC for understanding integrative AI–HI decision-making for humanitarian logistics across cultures.

This paper aids not only in deeply understanding complex issues stemming from human emotions and cultural cognitions in the context of cross-border humanitarian logistics, but also equips culturally-diverse stakeholders to effectively navigate these challenges and their potential ramifications. It enhances the decision-making process and optimizes the synergy between AI and HI for cross-cultural humanitarian logistics.

The originality lies in the use of a cognitive methodology of the Yin–Yang dialectic to metaphorize the dynamic genesis of integrative AI-HI KC for international humanitarian logistics. Based on system science and knowledge management, this paper applies game theory, multi-objective optimization and Markov decision process to operationalize the conceptual framework in the context of cross-cultural humanitarian logistics.

The study aims to assess the effectiveness of engaging tutors in designing and using ICT integrated lesson activities in strengthening their pedagogical use of ICT competences.

Survey data from an intervention group of 70 tutors from two teachers colleges (TCs) were used to compare their level of ICT competences and domains of professional practice before and after the intervention. Document analysis, lesson observations and feedback from the learning management system (LMS) were used to describe tutors’ experiences from the intervention.

There was a statistically significant increase in tutors’ level of pedagogical use of ICT competences and domains of professional practice associated with hands-on practice in designing and implementing the intervention.

The intervention focus on hands-on practice, actual teaching and learning needs, and the use of active learning strategies like flipped classroom and the LMS, were useful means for tutors to make sense of pedagogical use of ICT competences.

The results offer useful insights to teacher education institutions and policymakers on how to prepare professional learning and supportive policies to enhance teaching and learning with ICT for addressing the learning needs of the subject matter.

Creating 16 ICT integrated lesson activities helped tutors to learn pedagogical use of ICT competences by doing. Use of such intervention could be a useful strategy in teacher education institutions to reposition ICT competence development from reproducing technological competences toward developing knowledge creators who could innovate their pedagogical practice with support from mentors, digital learning resources and networks.

Megaprojects are financially large and complex in scope, which require engagement of stakeholders from various institution and communities. With increased concerns from stakeholders on sustainability related issues, from environmental to socio-economic perspective, managing megaprojects has become quite challenging. Hence, there should be proactive approaches in active engagement of stakeholders from the start of the projects to overcome such issues. Currently, there is a knowledge gap on stakeholder management strategies specific to megaprojects on managing sustainability issues.

This research has adopted review of secondary data from case studies to identify stakeholder management challenges and strategies in megaprojects around Sydney area. The documents related to three different projects were reviewed and data were collected through qualitative content analysis and coding with use of NVivo software for within case analysis and was followed by thematic approach for cross case analysis.

Every case study project's sustainability-related stakeholder issues are more similar than different to others. Differences are mostly in terms of intensity of impact of any issue in a particular project, and/or intensity of impact at certain phase of any project. Moreover, significant sectors and strategies have been identified for key focus to manage environment and socioeconomic issues. Whatever be the strategies, in case of megaprojects, they need to be mostly proactive.

This research has extended the knowledge on stakeholder management, in relation to managing sustainability-related issues of megaprojects during their design, construction and operation phases. This research offers useful strategies for project teams of megaprojects to develop a proactive stakeholder management plan, addressing unavoidable sustainability challenges.

The purpose of this study is to examine tacit knowledge sharing within information systems development (ISD) projects by exploring the combination of social interdependence theory and regulatory focus theory (RFT).

A survey was conducted on 198 ISD professionals to investigate the effect of social interdependence on tacit knowledge sharing. The survey data were analyzed using partial least squares structural equation modeling (PLS-SEM), and the results were discussed.

This study reveals that team members tend to share tacit knowledge in a way characterized by cooperative interdependence, and different patterns of social interdependence have an impact on tacit knowledge sharing. The RFT explains the disparities in attitude toward tacit knowledge sharing. Specifically, individuals with a prevention-focused orientation positively moderate the impact of competitive interdependence on tacit knowledge sharing, while those with a promotion-focused orientation have a negative moderating effect on the effect of competitive interdependence on tacit knowledge sharing. Moreover, promotion-focused individuals negatively moderate the effect of cooperative interdependence on tacit knowledge sharing.

The study identifies important aspects of social interdependence in ISD projects that affect the management of tacit knowledge. Furthermore, the study shows that the influence of cooperative and competitive interdependence on tacit knowledge sharing is moderated by the regulatory focus of an individual, providing new insights into ISD knowledge management.

The application of good buildability practices is vital for improving the performance of projects and businesses in the construction sector. Despite the plethora of research into buildability in construction in the previous years, there is little information concerning how buildability practice can be successfully implemented. This paper aims to develop a conceptual framework that explains how buildability practice can be implemented successfully in the construction industry.

The paper uses an integrative literature review method to synthesise literature from different domains to describe various themes by which buildability assessment can be successfully implemented in the construction industry.

The findings of the review of literature conceptualised a buildability implementation framework at four principal themes: buildability attributes for improving the practice of construction management, factors supporting the implementation of buildability assessment, measures for improving the buildability of building designs and factors impeding the implementation of buildability assessment.

The outcome of this study contributes to knowledge in three different ways. First, the framework emerging from this study provides guidance to stakeholders on strategies for the successful implementation of buildability. Second, the information gathered in this study is useful for the development of buildability assessment tool. Finally, the framework has a potential of improving the practice of embedding buildability into designs. The detailed descriptions of the relevant variables at each principal theme advance the understanding of buildability in the construction industry and are fundamental to developing buildability assessment tools for the industry.

The purpose of the study is to identify how knowledge management processes impact innovation performance in the Jordanian medical sector (private hospitals) as well as identify how big data analytics moderates this performance.

Two hundred ninety-one questionnaires were analyzed for the purpose of this study. A structural equation model (SEM) was used to test convergence validity, discriminant validity and reliability. In order to analyze the data, bootstrapping was used.

The empirical results showed that all knowledge management processes are statistically significant in influencing innovation performance. Furthermore, big data analytics moderates the relationship between knowledge management processes and innovation performance.

The results of this cross-sectional study are limited to one country and one industry due to methodological limitations, and the results represent a snapshot at a particular point in time.

Jordan's medical leaders will benefit from this study, since it emphasizes the importance of knowledge management processes to enhance innovation performance, especially given the importance of big data analytics in the field, increasing innovation capabilities in the medical field, thereby increasing innovation levels.

The present work involves analytical and experimental investigation of sloshing in a two-dimensional rectangular tank including the effect of porous baffles to control and/or reduce the wave motion in the sloshing tank. The purpose of this study is to assess the analytical solutions of the drag coefficient effect on porous baffles performance to track free surface motion variation in the sloshing tank by comparison with experimental shake table tests under a range of sway excitation.

The linear second-order ordinary differential equations for liquid sloshing in the rectangular tank were solved using Newmark’s beta method and obtained the analytical solutions for liquid sloshing with dual vertical porous baffles of full submergence depths in a sway-oscillated rectangular tank following the methodology similar to Warnitchai and Pinkaew (1998) and Tait (2008).

The porous baffles significantly reduce wave elevation in the varying filled levels of the tank compared to the baffle-free tank under the range of excitation frequencies. It is observed that the Reynolds number-dependent drag coefficient for porous baffles in the tank can significantly reduce the sloshing elevations and is found to be effective to achieve higher damping compared to the porosity-dependent drag coefficient for porous baffles in the sloshing tank. The analytical model’s response to free surface elevation variations in the sloshing tank was compared with the experiment’s test results. The analytical results matched with shake table test results with a quantitative difference near the first resonant frequency.

The scope of the study is limited to porous baffles performance under range sway motion and three different filling levels in the tank. The porous baffle performance includes Reynolds number dependent drag coefficient to explore the damping effect in the sloshing tank.

The porous baffles with low-level porosities in the sloshing tank have many engineering applications where the first resonant mode of sloshing in the tank is more important. The porous baffle drag coefficient is an important parameter to study the baffle’s damping effect in sloshing tanks. Hence, obtained analytical solution for liquid sloshing in the rectangular tank with Reynolds number as well as porosity-dependent drag coefficient (model 1) and porosity-dependent drag coefficient porous baffles (model 2) performance is discussed. The model’s test results were validated using a series of shake table sloshing experiments for three fill levels in the tank with sway motion at various excitation frequencies covering the first four sloshing resonant modes.

In recent years, augmented reality (AR) has shown its potential to assist various construction activities. Its use commonly requires additional refinement to be integrated into the building information modeling (BIM) process. Nevertheless, few studies have investigated AR implementation in BIM-enabled projects because of numerous challenges related to its implementation. This study aims to investigate the implementation of AR in construction and identify the critical mechanisms for implementing BIM-AR successfully.

A mixed methodology was adopted for this study. First, this work presents a bibliometric analysis covering articles obtained from Scopus database published between 2000 and 2022. A sample size of 65 research papers pertinent to AR in construction was analyzed using VOSviewer software. Second, a participatory case study was conducted for a BIM-enabled project in China to gain insight into how BIM-AR implementation in construction is achieved.

The findings from the bibliometric analysis show an increasing interest in AR research within construction. The results indicate that AR research focuses on four clusters: real-time communication, project management, construction activities and education. Findings from the case study provide an empirical experience of AR application scenarios in a BIM-enabled project. Concomitantly, 15 critical success factors that influence BIM-AR implementation were finally identified and demonstrated.

This study provides a rich insight into the understanding and awareness of implementing AR. First, the findings are beneficial to construction practitioners and researchers because they provide a concentrated perspective of AR for emerging activities in the construction industry. Second, the results obtained from the case study could provide a useful guide for effectively implementing AR in a BIM-enabled construction project. Overall, this study may stimulate further research on AR-related studies in construction, such as BIM integration, factor analysis and construction education.

Records are current documents containing crucial personal, legal, financial and medical information, while archives house non-current documents with the same details. This study specifically aims to measure existing research in records and archives management with various scientific indicators.

Data extraction was conducted using the Web of Science, resulting in a data set of 2003 records for further analysis. Biblioshiny and VOSviewer have been used for mapping and visualization of the extracted data.

Managing and organizing this essential information is equally vital to maintaining records and archives. The findings encompass various aspects such as publications and citations, influential authors, source impact factors, relevant articles, affiliations, co-authorship trends across the top 10 countries and regions, references, publication year spectroscopy, keyword co-occurrence and historiography. The study concludes that medical records management prominently dominates the selected research area.

The study reflects the advancements in management systems and continues to emerge as research on the management of records and archives has gained significance.

Automatic DNA-binding protein (DNA-BP) classification is now an essential proteomic technology. Unfortunately, many systems reported in the literature are tested on only one or two datasets/tasks. The purpose of this study is to create the most optimal and universal system for DNA-BP classification, one that performs competitively across several DNA-BP classification tasks.

Efficient DNA-BP classifier systems require the discovery of powerful protein representations and feature extraction methods. Experiments were performed that combined and compared descriptors extracted from state-of-the-art matrix/image protein representations. These descriptors were trained on separate support vector machines (SVMs) and evaluated. Convolutional neural networks with different parameter settings were fine-tuned on two matrix representations of proteins. Decisions were fused with the SVMs using the weighted sum rule and evaluated to experimentally derive the most powerful general-purpose DNA-BP classifier system.

The best ensemble proposed here produced comparable, if not superior, classification results on a broad and fair comparison with the literature across four different datasets representing a variety of DNA-BP classification tasks, thereby demonstrating both the power and generalizability of the proposed system.

Most DNA-BP methods proposed in the literature are only validated on one (rarely two) datasets/tasks. In this work, the authors report the performance of our general-purpose DNA-BP system on four datasets representing different DNA-BP classification tasks. The excellent results of the proposed best classifier system demonstrate the power of the proposed approach. These results can now be used for baseline comparisons by other researchers in the field.