Search results

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.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

This paper aims to shed light on how the composition of future blended learning (BL) courses can be changed to provide students with quality academic learning experiences. The model suggested in this study will guide instructors on how to design their course learning outcomes to ensure effective delivery.

The new model has been developed by combining Bloom's taxonomy and Carman's model. Later, a new framework entitled “PATHCO” based on an extensive literature review is applied to enhance the quality of all five components of Carman's model.

The PATHCO conceptual framework has been developed to ensure quality in the five main teaching and learning factors. This framework covers criteria like pedagogical, assessments, technical, health care and organizational. Further research is required to broaden the main elements of the suggested framework and to validate this research through a case study.

The COVID-19 pandemic has transformed the landscape of the education sector by encouraging an extensive acceptance of technology-enhanced learning and teaching. Blended learning (BL) has become the most appropriate medium to deliver online learning (OL). However, educators and students have reported dissatisfaction with the BL mode of delivery. To address this dissatisfaction, this study outlines, using the PATHCO model, all the essential building blocks which are required to find the right blend of both face-to-face and online components.

Crowdfunding is an increasingly popular channel for project fundraising for entrepreneurial ventures. Such efforts require fundraisers to develop and manage a crowdfunding campaign over a period of time and several stages. Thus, the authors aim to identify the stages fundraisers go through in their crowdfunding campaign process and how their engagement evolves throughout this process.

Following a multiple case study research design analysing six successful campaigns, the current study suggests a taxonomy of stages the fundraisers go through in their crowdfunding campaign management process while identifying the types of engagement displayed and their relative intensity at each of these stages.

The study proposes a five-stage process framework (pre-launch, launch, mid-campaign, conclusion and post-campaign), accompanied by a series of propositions outlining the relative intensity of different types of engagement throughout this process. The authors show that engagement levels appear with high intensity at pre-launch, and to a lesser degree also at the post-launch stage while showing low intensity at the stages in between them. More specifically, cognitive and behavioural engagement are most prominent at the pre- and post-launch stages. Emotional engagement is highest during the launch, mid-launch and conclusion stages. And social engagement maintains moderate levels of intensity throughout the process.

This study focuses on the campaign process using engagement theory, thus identifying the differing engagement patterns throughout the dynamic crowdfunding campaign management process, not just in one part.

In collaboration with their home cities, universities increasingly develop courses in which students investigate urban sustainability challenges. This paper aims to understand how far-reaching the collaboration with urban stakeholders in these courses is and what students are meant to learn from the transdisciplinary pedagogies.

This research is designed as a qualitative multiple-case study into the intentions of transdisciplinary courses in which universities collaborate with their home cities: Delft University of Technology in Delft and Amsterdam Institute for Advanced Metropolitan Solutions in Amsterdam. The study compares the written intentions of eight courses in course descriptions with the ideal intentions that teachers describe in interviews.

First, seven of the eight investigated courses were designed for urban stakeholders to participate at a distance or as a client but rarely was a course intended to lead to a collaborative partnership between the city and students. Second, the metacognitive learning objectives, such as learning to deal with biases and values of others or getting to know one’s strengths and weaknesses in collaboration, were often absent in the course descriptions. Learning objectives relating to metacognition are at the heart of transdisciplinary work, yet when they remain implicit in the learning objectives, they are difficult to teach.

This paper presents insight into the levels of participation intended in transdisciplinary courses. Furthermore, it shows the (mis)alignment between intended learning objectives in course descriptions and teachers’ ideals. Understanding both the current state of transdisciplinarity in sustainability courses and what teachers envision is vital for the next steps in the development of transdisciplinary education.

Industrialization is a major contributor to pollution and the worsening of some social problems. A change in this context would help in a new industrial model aiming at a viable and sustainable manufacturing system. This research aims to verify the state of the art of sustainability within the industrial production process through a systematic literature review, verifying the main characteristics in relation to industrial sustainability that the literature demonstrates.

The development of the research took place in three stages: a survey of articles with Journal Citation Reports (JCR), the construction of the database and descriptive analysis and text mining analyses of social networks and content. The survey took place through academically endorsed research platforms, totaling a total of 352 scientific articles, which included 18 quality management tools and worked with at least one sustainability indicator (financial, social and environmental).

Lean manufacturing, integrated management system and Six Sigma were the most cited quality tools, and articles containing the three indicators were found more frequently. It was found that most authors treated sustainability only as an environmental contribution. Knowledge of the organization's structural and management issues is essential for implementing sustainability and production process improvement.

This work is the first to develop a systematic analysis regarding the use of sustainability implementation in the industrial production process, considering a wide scope of production process tools, guiding on the characteristics of sustainability relating to the main critical success factors (CSFs), motivations, difficulties and benefits that lead industries in different parts of the world to implement sustainability.

This paper aims to shed light on the perception of the consequences of implementing home teleworking (TW) for employers and employees amid the pandemic. By doing so, the research analyzes the factors that explain employers' and employees' perceptions of home TW and the symmetry of their impact on its acceptance and rejection.

The analysis is done over the survey “Trends in the digital society during SARS-COV-2 crisis in Spain” by the Spanish “Centro de Investigaciones Sociológicas.” The explanatory variables were selected and classified using the well-known taxonomy of Baruch and Nicholson (i.e. individual factors, family/home, organizational and job-related).

The global judgment of HTW is positive, but factors such as gender, age, children in care or being an employer nuance that perception. While some factors, such as the attitude of employees toward information communication technologies (ICTs), perceived productivity or the distance from home to work, have a significant link with both positive and negative perceptions of HTW, other factors can only explain either positive or negative perceptions. Likewise, the authors observed that being female and having children on care had a detrimental influence on opinions about HTW.

A clearer regulation of TW is needed to prevent imbalances in rights and obligations between companies and employees. The authors also highlight the potentially favorable effects of telecommuting on mitigating depopulation in rural areas.

The authors have also measured not only the significance of assessed factors on the overall judgment of HTW for firms and workers but also whether these factors impact acceptance and resistance attitudes toward TW symmetrically.

According to regulations, aircraft must be in an airworthy condition before they can be operated. To ensure airworthiness, they must be maintained by an approved component maintenance organisation. This study is aimed to identify potential errors that may arise during the final inspection and certification process of aircraft components, categorise them, determine their consequences and quantify the associated risks. Any removed aircraft components must be sent to an approved aircraft component maintenance organisation for further maintenance and issuance of European Union Aviation Safety Agency (EASA) Form 1. Thereafter, a final inspection and certification process must be conducted by certifying staff to receive an EASA Form 1. This process is crucial because any errors during this stage can result in the installation of unsafe components in an aircraft.

The Systematic Human Error Reduction and Prediction Approach (SHERPA) method was used to identify potential errors. This method involved a review of the procedures of three maintenance organisations, individual interviews with ten subject matter experts and a consensus group of 14 certifying staff from different maintenance organisations to achieve the desired results.

In this study, 39 potential errors were identified during the final inspection and certification process. Furthermore, analysis revealed that 48.7% of these issues were attributed to checking errors, making it the most common type of error observed.

This study pinpoints the potential errors in the final inspection and certification of aircraft components. It offers maintenance organisations a roadmap to assess procedures, implement preventive measures and reduce the likelihood of these errors.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.