Use Of Knowledge Research Articles

Responsive Knowledge Management Framework in the Philippine House of Representatives for Policy Development

This study formulated a Knowledge Management Framework for the Philippine House of Representatives Secretariat- the organizational arm of the House of Representatives (HRep) to improve the technical and administrative support services to the House Members. The researcher interviewed employees from the Committee Affairs Department to describe their required features of a technology-based system, practices, and initiatives for the implementation of a framework as a basis for the development of a KM system. The developed KM framework integrated the models of Alshamsi and Othman, 2021 and the Input-Process-Output (IPO) model Galais et. al (2021), illustrated the cyclical nature of knowledge creation, sharing, and utilization within the organization, and the researcher included an outcome as the framework should reflect the long term development goals of the HRep. The framework will be the basis of the HRep in assessing the current systems in the HRep, evaluating the proposed systems, and developing indicators for monitoring and evaluation in case a certain system is already implemented.

Perspectives of Young People with Neuromuscular Diseases Regarding Their Choice of Educational Programs and Possibilities to Complete Program Requirements

Young people with impaired functioning and/or disability do not receive as much education or as high an education as fully functioning young people, thus limiting their job opportunities. Therefore, the aim of this study was to investigate perspectives of young people with neuromuscular diseases regarding their choice of educational programs and possibilities to complete program requirements to gain knowledge for use in future counselling and the development of a national questionnaire survey. The design for this study was qualitative using the interpretive description methodology and Anthony Giddens’ theory on modernity and self-identity. Data were generated through two focus group interviews with seven people between 18 and 30 years of age. Beginning and completing an education was influenced by the creation of identity: the importance of experiencing demands and expectations, the meaning of social relations when learning, and the consequences of accessibility for educational opportunities. The participants’ sense of self-identity was built by testing boundaries and developing images through social relations with peers, parents, and teachers. How they acted and behaved in the social arena of school and education influenced their choices and chances of completing educational programs.

The Impact of Gamification on the Utilization of Knowledge: The Mediating Role of Perceived Function

The Impact of Gamification on the Utilization of Knowledge: The Mediating Role of Perceived Function

Product innovation design approach driven by implicit relationship completion via patent knowledge graph

Product innovation design process involves a great deal of discrete engineering knowledge, limiting the ability of designers to quickly utilize this knowledge to support design innovation. Nowadays, innovation design based on knowledge graphs has enhanced the ability to explore design knowledge, improving the efficiency of knowledge retrieval. Previous studies have focused on mining more design knowledge to enrich the knowledge graph overlooks the implicit relationships with potential value among design knowledge, wasting design resources. To address these issues, an approach for product innovation design based on implicit knowledge relationship completion in the patent knowledge graph is proposed, which explores the implicit relationships between design knowledge to provide new knowledge satisfying design preferences and enhance the innovativeness of solutions. First, a requirements-function-structure-benefit (RFSB) knowledge ontology is constructed and extracted from the benefit knowledge of patents to build the knowledge graph. Second, an implicit relationship completion model based on the similarity of function or benefit entities explores the implicit relationships, replacing structure entities directly connected to similar function or benefit entities to generate new relationships and outputs novel ideas. Third, a scheme improvement process based on the co-occurrence frequency of requirement and structure knowledge supplements neglected design preferences. Final, a pipeline inspection robot case study is further employed to verify the proposed approach, and a patent knowledge graph assisted design solution prototype system is developed to assist in the utilization of innovative design knowledge. Evaluation results show the significant design potential of the proposed approach in inspiring innovative thinking and knowledge reuse.

Will ChatGPT be Useful for Korean Neurologists in Clinical Practice?

Background: Since the emergence of artificial intelligence (AI), such as ChatGPT, there has been extensive research on its utility in the medical field. This study evaluates the potential of utilizing the ChatGPT AI platform to provide specialized advice to Korean neurologists.Methods: Through a multifaceted approach, it assesses both the knowledge and practical clinical utility using neurology training evaluation questions and clinical case reports.Results: The accuracy of ChatGPT in answering medical exam questions (45.1%) is comparable to or slightly lower than previous studies. The study also examines performance of ChatGPT in providing advice based on clinical case reports, finding that while it can offer suitable diagnostic suggestions and propose relevant tests in some cases (8/12), its overall diagnostic accuracy is limited (2/12). Limitations include the platform’s text-based nature, which hinders the interpretation of image-based questions, and the uneven distribution of case reports across subfields.Conclusions: Despite these limitations, ongoing advancements in AI technology offer prospects for improved performance and expanded applications in the medical field, warranting continued research and monitoring of AI’s role in medicine.

Semantic-enhanced graph neural network for named entity recognition in ancient Chinese books

Named entity recognition (NER) plays a crucial role in the extraction and utilization of knowledge of ancient Chinese books. However, the challenges of ancient Chinese NER not only originate from linguistic features such as the use of single characters and short sentences but are also exacerbated by the scarcity of training data. These factors together limit the capability of deep learning models, like BERT-CRF, in capturing the semantic representation of ancient Chinese characters. In this paper, we explore the semantic enhancement of NER in ancient Chinese books through the utilization of external knowledge. We propose a novel model based on Graph Neural Networks that integrates two different forms of external knowledge: dictionary-level and chapter-level information. Through the Graph Attention Mechanism (GAT), these external knowledge are effectively incorporated into the model’s input context. Our model is evaluated on the C_CLUE dataset, showing an improvement of 3.82% over the baseline BAC-CRF model. It also achieves the best score compared to several state-of-the-art dictionary-augmented models.

Envisioning futures through decolonised tacit knowledge: The In, Out and On method

This paper presents a method for future-building based on the journey we undertook as Design and Arts researchers in POR EL Páramo project (2021–2022) in our aim to bring closer the different actors involved in the Paramos (high Andean moorlands in Boyacá region, Colombia). We did this by understanding their everyday life better, and co-designing potential pathways towards holistic sustainable futures that serve the various communities’ needs. Through a series of social innovation workshops, we applied transdisciplinary approaches aimed at decolonising the methodologies used and its facilitation dynamics. The outcomes include our contribution to design and arts-based methodologies that aids continuity to the process of reflection: In(ward), Out(ward) and On(ward). In deploying this decolonisation-based methodology, a more powerful underlying principle came to light too: the use of arts mobilises forms of knowledge that are rather unconscious, but also extremely efficacious in generating proactive mindsets and generating bottom-up ideas. In this paper we build on and argue further, from an empirical perspective, for the utilisation of the tacit knowledge that can be transmitted through non-verbal means in social research dealing with contexts of conflict, reconciliation, and future building.

Ambidextrous Innovation in Project Management: A Systematic Literature Review

Projects work under constant pressure of resource and time constraints. In order to perform effectively and efficiently, innovation seems to be a significant factor. However, due to the different nature of projects as compared to the organization, projects have been finding it difficult to undertake such innovation. However, ambidextrous innovation, which seeks to balance exploratory and exploitative innovation, offers a possible solution. However, research on the relationship between ambidextrous innovation and project management is at an early stage. The purpose of the present research is to undertake a systematic review of the literature to build and synthesize the understanding of innovation ambidexterity at the project level. Following the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) guidelines, our research collected data from the Web of Science and SCOPUS databases. By adhering to the PRISMA approach, we ensured a rigorous and transparent approach to the systematic review study, allowing for comprehensive data collection and analysis. The results of the present review study suggest that interest is building rapidly to incorporate ambidextrous innovation into project management. Ambidextrous innovation seemed to positively impact both the performance and capability of projects to undertake the innovation. Further, important drivers such as organizational culture, knowledge management, innovation activities, and agility play key roles in undertaking ambidextrous innovation at the project level. Further, elements of the team such as team integration, alignment, and knowledge utilization also play key roles. Finally, the avenue of future research has also been highlighted.

How to strengthen societal impact of research and innovation? Lessons learned from an explanatory research-on-research study on participatory knowledge infrastructures funded by the Netherlands Organization for Health Research and Development

BackgroundScientific research and innovation can generate societal impact via different pathways. Productive interactions, such as collaboration between researchers and relevant stakeholders, play an important role and have increasingly gained interest of health funders around the globe. What works, how and why in research partnerships to generate societal impact in terms of knowledge utilisation is still not well-known. To explore these issues, the Netherlands Organization for Health Research and Development (ZonMw) initiated an exploratory research-on-research study with a focus on participatory knowledge infrastructures (PKIs) that they fund in the field of public health and healthcare. PKIs are sustainable infrastructures in which knowledge production, dissemination and utilisation takes place via committed collaboration between researchers and stakeholders from policy, practice and/or education. Examples are learning networks, academic collaborative centres, care networks and living labs. The aim of the study was twofold: to gain insights in what constitutes effective collaboration in PKIs; and to learn and improve the research governance, particularly of ZonMw as part of their dissemination and implementation activities.MethodsDuring 2020–2022, we conducted a literature review on long-term research partnerships, analysed available documentation of twenty ZonMw-funded PKIs, surveyed participants of the 2021 European Implementation Event, interviewed steering committee members, organized a Group Decision Room with lecturers, and validated the findings with key experts.ResultsWe identified eight mechanisms (‘how and why’) that are conditional for effective collaboration in PKIs: transdisciplinary collaboration; defining a shared ambition; doing justice to everyone’s interests; investing in personal relationships; a professional organisation or structure; a meaningful collaborative process; mutual trust, sufficient time for and continuity of collaboration. Several factors (‘what’) may hinder (e.g., lack of ownership or structural funding) or facilitate (e.g., stakeholder commitment, embeddedness in an organisation or policy) effective collaboration in research partnerships.ConclusionTo use the study results in policy, practice, education, and/or (further) research, cultural and behavioural change of all stakeholders is needed. To facilitate this, we provide recommendations for funding organisations, particularly ZonMw and its partners within the relevant knowledge ecosystem. It is meant as a roadmap towards the realisation and demonstration of societal impact of (health) research and innovation in the upcoming years.

Assessing the value and knowledge gains from an online tick identification and tick-borne disease management course for the Southeastern United States

BackgroundTick-borne diseases are a growing public health threat in the United States. Despite the prevalence and rising burden of tick-borne diseases, there are major gaps in baseline knowledge and surveillance efforts for tick vectors, even among vector control districts and public health agencies. To address this issue, an online tick training course (OTTC) was developed through the Southeastern Center of Excellence in Vector-Borne Diseases (SECOEVBD) to provide a comprehensive knowledge base on ticks, tick-borne diseases, and their management.MethodsThe OTTC consisted of training modules covering topics including tick biology, tick identification, tick-borne diseases, and public health, personal tick safety, and tick surveillance. The course was largely promoted to vector control specialists and public health employees throughout the Southeastern US. We collected assessment and survey data on participants to gauge learning outcomes, perceptions of the utility of knowledge gained, and barriers and facilitators to applying the knowledge in the field.ResultsThe OTTC was successful in increasing participants’ baseline knowledge across all course subject areas, with the average score on assessment increasing from 62.6% (pre-course) to 86.7% (post-course). More than half of participants (63.6%) indicated that they would definitely use information from the course in their work. Barriers to using information identified in the delayed assessment included lack of opportunities to apply skills (18.5%) and the need for additional specialized training beyond what the OTTC currently offers (18.5%), while the main facilitator (70.4%) for applying knowledge was having opportunities at work, such as an existing tick surveillance program.ConclusionsOverall, this OTTC demonstrated capacity to improve knowledge in a necessary and underserved public health field, and more than half of participants use or plan to use the information in their work. The geographic reach of this online resource was much larger than simply for the Southeastern region for which it was designed, suggesting a much broader need for this resource. Understanding the utility and penetrance of training programs such as these is important for refining materials and assessing optimal targets for training.

A knowledge graph-aided decision guidance method for product conceptual design

In the fast-paced world of product design, businesses seek a competitive edge by swiftly addressing user requirements and developing precise solutions. Depending on diverse knowledge, conceptual design makes enterprises invest significantly in knowledge management. Following the philosophy of decision-based design, a knowledge graph-aided decision guidance method is proposed to streamline and enhance knowledge utilisation in product conceptual design. Firstly, the decision-making process in product conceptual design is modelled using the Concept-Decision-Knowledge (CDK) model, yielding the meta-model of CDK (mCDK). A data-augmented BERT-BiLSTM-CRF model is adopted to extract information from diverse data sources, forming a CDK knowledge graph (CDK-KG). A decision case for employing problem-solving knowledge configuration is generated to resolve specific design decision problems when new requirements arise. Validation of the method is demonstrated through a case study on the launch vehicle conceptual design of the first and second-stage separation system. The results indicate that the proposed method can automatically extract information from data resources to construct a knowledge graph. Furthermore, it can provide decision cases for design requirements through knowledge configuration, supporting decision-making.

Factors influencing nurses' compliance related to the use of personal protective equipment during the COVID-19 pandemic: A descriptive cross-sectional study.

To determine how nurses' experiences with the coronavirus disease (COVID-19) pandemic affected their knowledge, awareness, and compliance related to the use of personal protective equipment (PPE) during the COVID-19 pandemic in South Korea. A descriptive cross-sectional study. A total of 247 nurses in South Korea participated in this study between May 10 and 19, 2023. An online self-report questionnaire was used to collect data on demographic and occupational characteristics, COVID-19 experience, knowledge, awareness, and compliance related to the use of PPE. Factors affecting compliance were analysed using hierarchical multiple linear regression. Mean age of the nurses was 31.92, and 94.3% were women. Most had a bachelor's degree or higher and the mean clinical experience as a nurse was 6.45 years. Knowledge of the use of PPE was 8.45 out of 10, awareness was 3.52 out of 5, and compliance was 4.28 out of 5. Knowledge and awareness were correlated with compliance related to PPE use. Awareness (β = 0.234, p < 0.001), knowledge (β = 0.218, p < 0.001), experience caring for COVID-19 patients (β = 0.234, p = 0.004), optional fourth dose vaccine (β = 0.150, p = 0.017), clinical experience (β = 0.140, p = 0.022), and COVID-19 infection control education (β = 0.115, p = 0.037) were found to have a significant impact on compliance. During the COVID-19 pandemic, nurses' knowledge and awareness of PPE use was a crucial factor in compliance. factors such as clinical experience, experience in caring for COVID-19 patients, optional vaccination, and completion of COVID-19 education also influenced compliance. We hope that these factors can provide a basis for developing training programs for nurses to respond to future emerging infectious diseases.

Physically-informed change-point kernels for variable levels of physical knowledge inclusion in Gaussian processes

The relative balance between physics and data within any physics-informed machine learner is an important modelling consideration to ensure that the benefits of both physics and data-based approaches are maximised. An over reliance on physical knowledge can be detrimental, particularly when the physics-based component of a model may not accurately represent the true modelled system. An under utilisation of physical knowledge potentially wastes a valuable resource, along with benefits in model interpretability and reduced demand for expensive data collection. Although adjusting the relative levels of physics and data reliance within a model is possible through the adaptation of the model structure, in practice, this can be challenging, with the relative balance produced by new model structures not always clear before they are implemented. This paper presents a means of being able to tune the balance of physics and data reliance within a model through the development of physically-informed change-point kernels for Gaussian processes. These combine more structured physical kernels, capable of enforcing physically derived behaviours, with flexible, general purpose kernels, and provide means to dynamically change the relative levels of reliance on physics and data within a model.

Integration of knowledge management processes into a dynamic organizational environment

The article is devoted to the study of the impact of intellectual resources in the form of knowledge bases on the sustainable development of organizations. In today's world, where Knowledge is a key resource for success, the integration of Knowledge Management becomes an important component to ensure organizational competitiveness. The study emphasizes that successful implementation of artificial intelligence and knowledge bases requires not only technological solutions but also cultural changes within organizations, particularly in the areas of learning culture and collaboration. The authors of the article investigate the processes of acquisition, combination, and protection of Knowledge as key components of organizational sustainable development. They point out that the ability to acquire and combine Knowledge allows organizations to realize their potential in value creation. Knowledge Management is presented as a strategic component aimed at increasing productivity and competitiveness. The article discusses higher-order capabilities, such as adaptability, absorptive capacity, and innovation capacity, which affect the ability of organizations to respond to changes in the external environment. The algorithm for Knowledge utilization in organizations describes a comprehensive intellectual platform for managing and optimizing processes in the dynamic organizational environment. The Knowledge Management system includes managed and managing components, where the managed system reflects current parameters and information, while the managing system provides data storage, learning, and ontological knowledge base. The ontological knowledge base includes a set of concepts, semantic relationships, interpretation function, and axioms. Knowledge base updates occur depending on changes in time and the addition of new concepts, relationships, and axioms. Generalized ER-diagrams illustrate the structure and interaction of the learning module with the results used to update the Knowledge base. The algorithm allows you to analyze the state of the system and make optimal decisions based on the accumulated Knowledge.

Diversity, Indigenous Uses and Conservation Status of Plants Used in Socio-Cultural Traditions by Kinnaura Tribes of Himachal Pradesh, India

Himachal Pradesh, one of India's Western Himalayan states, is well-known for its distinct culture, traditions and vegetation. Kinnaura is a major tribal community of Himachal Pradesh and for ages, these people are highly dependent on locally available plant resources for fulfilling daily livelihood needs including socio-cultural traditions. Therefore, an effort has been made to; (i) assess the diversity and utilization pattern of plant resources in socio-cultural traditions; (ii) identify endemism and nativity and the threat status of these species; and (iii) suggest management options for conservation. A total of 105 species belonging to 79 genera and 39 families representing trees (14 species), shrubs (17 species), herbs (73 species) and one climber were recorded. Among these, fifty-two species were native to the Himalayan region and fifteen species were near-endemic. Flowers of plants are used in the majority. Among these, eighteen species are in the various threat categories of threatened species. Due to increasing demand, habitat destruction and overexploitation, the population of the preferred species are depleting rapidly. Therefore, assessment of natural populations, demand and supply studies, harvesting trends, developments of propagation methods, afforestation of highly preferred species and community awareness for sustainable utilization and conservation of traditional knowledge have been suggested.

Towards multi-objective high-dimensional feature selection via evolutionary multitasking

Feature selection (FS) plays a crucial role in high-dimensional classification problems by identifying relevant features that contribute to model performance. Evolutionary multitasking (EMT) has recently shown success in FS problems. However, existing EMT-based FS methods have limitations in terms of diversity in task construction, evolutionary search, and knowledge transfer, leading to inadequate acquisition, exploration, and utilization of knowledge. To this end, this paper develops a novel EMT framework for multi-objective high-dimensional FS problems, namely MO-FSEMT. In particular, multiple auxiliary tasks are constructed by distinct formulation methods to provide diverse search spaces and information representations and then simultaneously addressed with the original task by leveraging multiple evolutionary solvers with different biases and search preferences. A task-specific-based knowledge transfer mechanism is designed to leverage the advantageous information from each task, facilitating the discovery and effective transmission of high-quality solutions during the search process. Comprehensive experimental results on 27 real high-dimensional datasets demonstrate the superiority of MO-FSEMT over state-of-the-art FS methods in terms of effectiveness and efficiency. Ablation studies further confirm the contributions of key components of the proposed MO-FSEMT.

Location-enhanced syntactic knowledge for biomedical relation extraction

Biomedical relation extraction has long been considered a challenging task due to the specialization and complexity of biomedical texts. Syntactic knowledge has been widely employed in existing research to enhance relation extraction, providing guidance for the semantic understanding and text representation of models. However, the utilization of syntactic knowledge in most studies is not exhaustive, and there is often a lack of fine-grained noise reduction, leading to confusion in relation classification. In this paper, we propose an attention generator that comprehensively considers both syntactic dependency type information and syntactic position information to distinguish the importance of different dependency connections. Additionally, we integrate positional information, dependency type information, and word representations together to introduce location-enhanced syntactic knowledge for guiding our biomedical relation extraction. Experimental results on three widely used English benchmark datasets in the biomedical domain consistently outperform a range of baseline models, demonstrating that our approach not only makes full use of syntactic knowledge but also effectively reduces the impact of noisy words.

Integrating effective journal club activities into knowledge management processes to enhance evidence-based practice, service quality, research skills, and innovation among nurses: A literature review

In a rapidly emerging world, knowledge management capabilities, including knowledge creation, acquisition, sharing, and utilization, become more critical for organizational change, growth, and competitiveness. Therefore, this article argues that organizations should consider implementing effective journal club meetings as an opportunity to acquire external knowledge, evaluate and integrate new knowledge into previous existing knowledge, and disseminate and utilize new knowledge to enhance product or service quality, innovation, and the performance of an organization. The article reviews relevant literature, proposes a framework for conducting effective journal club meetings, and aligns those activities with the knowledge management processes. The article proposes a framework for conducting effective journal club meetings and a process that integrates both journal club activities and the knowledge management process. By adopting this framework, journal club activities would be more effective in developing new knowledge management capabilities among individual members and enhancing organizational performance, i.e., implementing evidence-based practices (EBP), improving service quality, and producing research.

Enhancing the Business Sustainability of Women-Owned Tourism SMEs in Indonesia: Investigating the Effects of Product Innovation, Digital Platform Adoption, Entrepreneurial Spirit, Knowledge Utilization, and Government Support

Enhancing the Business Sustainability of Women-Owned Tourism SMEs in Indonesia: Investigating the Effects of Product Innovation, Digital Platform Adoption, Entrepreneurial Spirit, Knowledge Utilization, and Government Support

Nilai Dan Kegunaan Ilmu Bagi Manusia

The value of knowledge is very important in the scientific journey, because it can give birth to the utilization of knowledge. This study wants to discuss more deeply the value and usefulness of science for humans in living life in this world. The method used in this study is a qualitative method using library research, namely by examining reading sources that have to do with the studies discussed, as well as by using document studies of previous research results related to the philosophy of science. Data collection is done by tracing reading books, scientific journals, digital libraries, and libraries. It was found that the value of science includes a deep understanding of the universe, humans, and the relationship between the two. The uses of science are that humans can change the face of the world to be more advanced, help humans solve problems more effectively, develop technology so that humans can change the way of working, the way of thinking, change the barriers of space and time, increase career opportunities and open doors for various professions.