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The calculation of electromagnetic fields can involve many degrees of freedom (DOFs) to achieve accurate results. The DOFs are directly related to the computational effort of the simulation. The effort is decreased by using the proper generalized decomposition (PGD) and proper orthogonalized decomposition (POD). The purpose of this study is to combine the advantages of both methods. Therefore, a hybrid enrichment strategy is proposed and applied to different electromagnetic formulations.

The POD is an a-priori method, which exploits the solution space by decomposing reference solutions of the field problem. The disadvantage of this method is given by the unknown number of solutions necessary to reconstruct an accurate field representation. The PGD is an a-priori approach, which does not rely on reference solutions, but require much more computational effort than the POD. A hybrid enrichment strategy is proposed, based on building a small POD model and using it as a starting point of the PGD enrichment process.

The hybrid enrichment process is able to accurately approximate the reference system with a smaller computational effort compared to POD and PGD models. The hybrid enrichment process can be combined with the magneto-dynamic T-Ω formulation and the magnetic vector potential formulation to solve eddy current or non-linear problems.

The PGD enrichment process is improved by exploiting a POD. A linear eddy current problem and a non-linear electrical machine simulation are analyzed in terms of accuracy and computational effort. Further the PGD-AV formulation is derived and compared to the PGD-T-Ω reduced order model.

The purpose of this study is to look at the factors that drive people to participate in the sharing economy (SE). Based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), the study proposes a mathematical model. The study’s ultimate objective is to help businesses attract more involved customers and promote collaborative consumption as a sustainable alternative to typical consumption patterns. The study offers a conceptual framework established via a thorough literature review to examine Indian customers’ use behavior toward SE platforms. A one-sample two-tailed t-test is used to assess the framework’s efficacy. The research fills gap in the literature on the SE by investigating the factors that determine subjective norms (SN), attitudes (A), and perceived behavioral control (PBC). A framework is provided that takes behavioral intention (BI) contemplated as a mediating variable. The research improves TAM and TPB by including new factors such as technical characteristics. This research adds to the body of knowledge on the digital SE by underlining the relevance of usage behavior in comprehending Indian customers, where A, SN, and PBC are important aspects. The research presents a paradigm for better understanding customers’ attitudes and behaviors toward various SE platforms, which might help academics, practitioners, and policy makers situate their initiatives within the larger field of sharing. The study’s categorizations of Indian consumers’ A, SN, PBC, and BI toward the SE might potentially advise on future research and government policies.

The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts from unstructured text corpus. In the human disease domain, ontologies are found to be extremely useful for managing the diversity of technical expressions in favour of information retrieval objectives. The boundaries of these domains are expanding so fast that it is essential to continuously develop new ontologies or upgrade available ones.

This paper proposes a semi-automated approach that extracts entities/relations via text mining of scientific publications. Text mining-based ontology (TmbOnt)-named code is generated to assist a user in capturing, processing and establishing ontology elements. This code takes a pile of unstructured text files as input and projects them into high-valued entities or relations as output. As a semi-automated approach, a user supervises the process, filters meaningful predecessor/successor phrases and finalizes the demanded ontology-taxonomy. To verify the practical capabilities of the scheme, a case study was performed to drive glaucoma ontology-taxonomy. For this purpose, text files containing 10,000 records were collected from PubMed.

The proposed approach processed over 3.8 million tokenized terms of those records and yielded the resultant glaucoma ontology-taxonomy. Compared with two famous disease ontologies, TmbOnt-driven taxonomy demonstrated a 60%–100% coverage ratio against famous medical thesauruses and ontology taxonomies, such as Human Disease Ontology, Medical Subject Headings and National Cancer Institute Thesaurus, with an average of 70% additional terms recommended for ontology development.

According to the literature, the proposed scheme demonstrated novel capability in expanding the ontology-taxonomy structure with a semi-automated text mining approach, aiming for future fully-automated approaches.

The purpose of this paper is to explore the reintegration process of Wounded, Injured or Sick Employees (WISE) of the Dutch Military Armed Forces.

The research method is an exploratory, qualitative case study. A purposive sampling was drawn, including 10 WISE, and 6 reintegration stakeholders. A total of 16 interviews were conducted to explore the individual, organisational and socio-environmental factors that influence reintegration of WISE.

Findings show the importance of involvement and participation of members of the social environment in the reintegration process. Findings show that the complexity of the plethora of WISEs' injuries and disabilities requires a more person-centric reintegration approach with personalized-customized provisions, rather than a policy-driven approach to the reintegration, in order to enhance the reintegration experience and to arrive at beneficial individual and organisational reintegration outcomes.

This cross-sectional study on a limited sample of WISE and reintegration stakeholders does not allow for making inferences about the long-term effects of the reintegration process on reintegration outcomes of the wider population of WISE. Future longitudinal research, encompassing a larger sample, could examine the long-term career, organisational and societal implications of reintegration of WISE within and outside the Military Armed Forces.

This paper presents a “Wounded Warrior Workplace Reintegration Program”, aimed at deriving beneficial outcomes for all stakeholders involved in the reintegration trajectory.

This paper contributes to the literature by presenting a Model of Occupational Reintegration of WISE that considers the factors at an individual, social-environmental, and institutional level as determinants of successful reintegration.

This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video surveillance in public spaces.

This study examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Based on the requirements, this study proposes a CFL framework to gradually adapt AI models’ knowledge while reducing personal data transmission and retention. The framework uses three different federated learning strategies to rapidly learn from different new data sources while minimizing personal data transmission and retention to a central machine.

The findings confirm that the proposed CFL framework can help minimize the use of personal data without compromising the AI model's performance. The gradual learning strategies help develop AI-enabled video surveillance that continuously adapts for long-term deployment in public spaces.

This study makes two specific contributions to advance the development of AI-enabled video surveillance in public spaces. First, it examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Second, it proposes a CFL framework to minimize data transmission and retention for AI-enabled video surveillance. The study provides comprehensive experimental results to evaluate the effectiveness of the proposed framework in the context of facial expression recognition (FER) which involves large-scale datasets.

The purpose of this paper is to explore and analyze the context and concept of higher education for sustainable development (HESD) in Nepalese higher educational institutions (HEIs).

The research gathers facts and information both from primary and secondary sources. Five open-ended questions were developed to interview university high-ranking officials, such as VCs, registrars, deans and the chief of the planning division.

The inclusion of 17 sustainable development goals in the country’s Fifteenth Plan, national policy documents, and the University Grants Commission-led higher education reform programme provides sufficient context for HESD. In the absence of HESD literacy and a persuasive strategy, university leadership is less active in lobbying for SDG 4.7 with the government and funding agencies, university faculties and trade unions. In fact, both insights and initiatives to conceptualize HESD are lacking.

This study’s setting is distinct and the interpretation of the HESD concept is based on a small sample size. Thus, the generalization of its findings is intrinsically limited in the context of a country in the geographic region. However, the findings of this research provide practical insights to implement HESD in Nepalese HEIs.

This study is intended to inform and prepare the Nepalese academic community, urging HEIs to implement HESD with a well-defined plan of action. It contributes to the literature by considering how the current context and concept of HESD suites to promote sustainability in Nepalese HEIs, transforming the traditional academic structure and making academic leaders aware that HESD is only a means to an end.

This research is Nepal’s first study of its type with a broad understanding of the context and concept of HESD. It also provides information for HEI leaders on how to initiate the HESD acceleration process.