Knowledge Modeling - Science topic

Reinforcement learning (RL) agents naturally struggle with long-sequence sparse-reward tasks due to the lack of reward feedback during exploration and the problem of identifying the necessary action sequences required to reach the goal. Previous works have used abstract symbolic task knowledge models to speed up RL agents in these tasks by either s...

The debugging process scheme is pivotal in ensuring that electronic products meet the expected quality and performance standards prior to market launch. Its design process involves the meticulous management of diverse resources and process information. Traditional approaches typically rely on the manual extraction of design knowledge from large vol...

This article serves several purposes. First, it aims to consolidate the view that knowledge models make effective diagnostic tools that terminologists can use in their attempt to find answers to research questions about communication in professional fields. Secondly, the article serves to demonstrate the results of preliminary research into profess...

The rapid expansion of civil infrastructure in China underscores the critical need for advanced solutions to ensure the structural health of aging bridges. This study introduces a novel data and knowledge-driven digital twin modeling (DK-DTM) framework designed to enhance the safe and efficient operation and maintenance (O&M) of bridges. Such a sys...

This article describes the systematic development of a resiliency intervention for Black boys that focused on Black history and racial socialization. PERSIST, which stands for Promoting Emotional Resiliency Skills In Small Teams, is based on the Black history knowledge model of coping and mental health and the phenomenological variant of ecological...

Since the 1970s, governments around the world have developed environmental regulations and environmental management system (EMSs). Public and private enterprises are obligated to comply with EMSs to prevent environmental pollution. After the International Organization of Standardization (ISO) published the ISO 14001 EMS in September 1996, environme...

This paper discusses the concept of teachers’ community of practice (CoP) based on personal knowledge management (PKM) in order to facilitate knowledge sharing among them. There are some knowledge are scatted and not well manage around the school teachers. This is lead toward waste of time, cost, and difficulties to find and applying the knowledge...

Protégé is a tool developed by the Biomedical Informatics Research Center at Stanford University and is multiplatform open source and can be installed on Windows, MacOSX and GNU\Linux to build the ontology. Protégé 5.6.4 was released on April 18, 2024 with the latest version of the ontology editor being its Web Ontology Language (OWL) representatio...

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This article is devoted to the analysis of the situation that has arisen in the practice of using artificial intelligence methods for software development. Nowadays there are many disparate approaches, models, and practices based on the use of narrow intelligence for decision-making at different stages of the life cycle of software products, and an...

-Such types of data drift in ML models as actual positive and negative drifts, as well as varieties of fragmentary drifts in different directions, are considered. An overview of the current state of the problem is given, which highlights the methods of sliding window, trigger ensemble of models, covariant shift, personalization drift correction, se...

Introducción: El cambio climático acecha al equilibrio de la humanidad. Es preciso tomar parte en el siguiente dilema: continuar con las dinámicas productivas y consumistas que arriesgan el bienestar planetario, o desacelerar estas dinámicas proporcionando nuevos modelos productivos sostenibles que requieren de un cambio conceptual global que se nu...

Facility maintenance requires thorough inspections throughout a facility’s lifecycle to ensure structural integrity and longevity. A significant challenge lies in managing the semantic relationships between various inspection data across different lifecycle phases and effectively representing inspection results. While numerous studies have focused...

This paper proposes a novel approach to semantic ontology alignment using contextual descriptors. A formalization was developed that enables the integration of essential and contextual descriptors to create a comprehensive knowledge model. The hierarchical structure of the semantic approach and the mathematical apparatus for analyzing potential con...

Large language models (LLMs) are often criticized for lacking true “understanding” and the ability to “reason” with their knowledge, being seen merely as autocomplete engines. I suggest that this assessment might be missing a nuanced insight. LLMs do develop a kind of empirical “understanding” that is “geometry”‐like, which is adequate for many app...

AI conversational agents are increasingly prevalent in marketing practices. A recent effort to make AI conversational agents humanlike is the use of conversational fillers, such as uh, um, and hmm. While computer science research has shown that conversational fillers used by AI agents generally improve users’ interactional experiences, their effect...

With the rapid development of mobile learning technologies, mobile learning environments have become an integral part of modern education, offering students flexible learning methods and a wealth of educational resources. In this context, project-based learning (PBL), a student-centered instructional model, has garnered significant attention due to...

Big data is not only a technological innovation but also provides a new value and methodology, which provides new ideas and methods to enhance and improve the effect of education and makes the realization of personalization of ideological and political education possible. In this paper, based on the disciplinary knowledge model, we draw a knowledge...

This article explores the shift in AI from traditional model-driven approaches to knowledge-based systems. It argues that while conventional AI models excel in task-specific predictions, they lack deep contextual understanding and adaptability. The future of AI lies in “knowledge models” that combine data, reasoning, and real-world context, making...

Due to the characteristics of multi-source heterogeneity of party history information resources, the organisation and storage of party history information resources remain in the digital stage at this stage. In order to achieve the transformation of important party history information resources in the new democratic period from digitalisation to in...

The demographic change calls for the creation of age-friendly environments that result from the collaboration between several fields. Previous initiatives fostering age-friendly environments often had less-than-desired impact or reach due to financial and bureaucratic constraints. Additionally, territory-specific standards and needs hinder the repl...

The CSViewer for Analysts app is designated to provide a myriad of graphical user interfaces and analytical tools for researchers to study the valuable datasets collated from the Cayo Santiago Rhesus macaque colony, which has been raised on the "monkey island" off Puerto Rico since 1938. It is a part of the effort to integrate decades of accumulate...

This research endeavors to analyze the effect of latest HR practices on the effectiveness of current HR Managers’ performance in the software industry of Pakistan. The latest quality HR practices (i.e. Technical recruitment & selection, HR Technology, HR Marketing, Dynamic Workforce & Performance Mgmt., Psychology & Stress Mgmt., Green HRM and Work...

This paper introduces a novel approach to enhancing closed-domain Question Answering (QA) systems, focusing on the specific needs of the Lawrence Berkeley National Laboratory (LBL) Science Information Technology (ScienceIT) domain. Utilizing a rich dataset derived from the ScienceIT documentation, our study embarks on a detailed comparison of two f...

The goal of our research was to formulate an original set of Artificial Intelligence tools to extract knowledge from sources not intended for this purpose. The sources of knowledge in our analysis were records of production meetings, focused on production disturbance (PD) management. We used NLP tools and a procedure for transforming speeches into...

The non-serialized nature of the construction industry, the dynamic environment of construction sites, and the high turnover of workers are conditions that hinder the application of knowledge management (KM) in the sector. Given this, several studies highlight the use of BIM as a platform capable of optimizing KM. The main objective of this study w...

In this article we share the story of a proposal for permanent training for mathematics teachers who are in charge of the training of students between 12 and 18 years old. We present a task and the fundamentals that lead us to develop it in this training scenario, for the collective construction of specialized knowledge of those who teach topics re...

In this Chapter we will discuss modelling and reductionism in science and engineering, and how this relates to the new idea of digital twins. In particular, we focus on the historical context of modelling and reductionism for dynamics and control of engineering systems. Both active and passive control methods will be discussed, including the novel...

Influencer marketing significantly impacts consumer behavior and decision-making. However, identifying the drivers of influencer marketing effectiveness and conditions that enhance their impact remains challenging. This meta-analysis, which synthesizes 1,531 effect sizes from 251 papers, assesses influencer marketing effectiveness by examining its...

Graph-based anomaly detection is pivotal in diverse security applications, such as fraud detection in transaction networks and intrusion detection for network traffic. Standard approaches, including Graph Neural Networks (GNNs), often struggle to generalize across shifting data distributions. Meanwhile, real-world domain knowledge is more stable an...

As a contribution to the discussion of how to improve the initial teacher training in mathematics of elementary teachers, this work presents a descriptive and comparative study of the courses devoted to mathematics and mathematics education in the education degrees of Greek, Romanian, and Spanish universities. Considering the constrains of each nat...

Market demands for diversified and personalized customer needs drive the need for continuous high-speed iteration of products. Among them, product conceptual design is the core process for meeting consumer needs and expectations. However, in the product conceptual design stage, data is scattered across three-dimensional models, natural language tex...

In this paper we consider how ontological knowledge graphs (KGs) can be used to move towards a reasoning functionality for digital twins of structural dynamic systems. The KG is used to integrate geometric and material properties, that determine the dynamic behaviours of the structure. A three-storey, small-scale building is used as a use case to c...

Nowadays online learning is growing strongly, with many diverse options. Learners can utilize electronic devices and internet platforms for studying, searching for materials, and looking up knowledge. In this study, a method for design a knowledge chatbot system in education is proposed. This method includes a knowledge base, which is a knowledge m...

This paper proposes a novel approach to enhancing multi-target tracking of vehicles in videos with frequent camera occlusions. Our method integrates prior knowledge about vehicle behavior into a Gaussian Mixture Probability Hypothesis Density (GMPHD) filter framework. This knowledge, extracted as a knowledge graph from historical vehicle trajectori...

Introduction: The climate crisis and social justice are at the focus of UNESCO's 2030 Agenda, which presents 17 SDGs (Sustainable Development Goals) as a roadmap for the preservation of the planet. From the educational field, its achievement can be promoted through the design of educational projects that promote sustainable meaningful learning (SML...

In industrial vision, the lack of defect samples is one of the key constraints of depth vision quality inspection. This paper mainly studies defect detection under a small training set, trying to reduce the dependence of the model on defect samples by using normal samples. Therefore, we propose a Knowledge-Embedding Relational Network. We propose a...

Ontologies have played a crucial role in addressing challenges related to knowledge modeling, artificial intelligence, clustering, and classification. Within the realm of web services, ontologies primarily serve to describe web service interfaces, facilitating the automation of functional processes, particularly to guide the registers in discoverin...

Smart city/IoT frameworks are becoming more complex for the needs regarding multi-tenancy, data streams, real-time event-driven processing, data, and visual analytics. The infrastructures also need to support multiple organizations and optimizations in terms of data, processes/services, and tools cross-exploited by multiple applications and develop...

Introduction: The climate crisis and social justice are at the focus of UNESCO's 2030 Agenda, which presents 17 SDGs (Sustainable Development Goals) as a roadmap for the preservation of the planet. From the educational field, its achievement can be promoted through the design of educational projects that promote sustainable meaningful learning (SML...

We present the Process Engineering Operations Assistant (PEOA), an AI-driven framework designed to solve complex problems in the chemical and process industries. The framework employs a modular architecture orchestrated by a meta-agent, which serves as the central coordinator, managing an action generator and instruction-tuned small-scale language...

The “RNA world” represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient’s biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public reposito...

We present MambaCSR, a simple but effective framework based on Mamba for the challenging compressed image super-resolution (CSR) task. Particularly, the scanning strategies of Mamba are crucial for effective contextual knowledge modeling in the restoration process despite it relying on selective state space modeling for all tokens. In this work, we...

Model editing aims to correct outdated or erroneous knowledge in large models without costly retraining. Recent research discovered that the mid-layer representation of the subject's final token in a prompt has a strong influence on factual predictions, and developed Large Language Model (LLM) editing techniques based on this observation. However,...

Large language models (LLMs) have transformed open-domain abstractive summarization, delivering coherent and precise summaries. However, their adaptability to user knowledge levels is largely unexplored. This study investigates LLMs’ efficacy in tailoring summaries to user familiarity. We assess various LLM architectures across different familiarit...

Este artigo explora a semântica dos tempos históricos usando Processamento de Linguagem Natural (PLN). Desenvolvemos a família de modelos Woke (Word Embedding and Knowledge Model), utilizando algoritmos de vetorização de palavras como o Word2Vec, treinados em um corpus de teses e dissertações da Universidade Federal de Santa Catarina (2003-2024). O...

Knowledge acquisition has been a bottleneck in the design for efficient User Interfaces for Disabled Community. The best suited interfaces have been oriented towards adaptability that is the User Interface needs to adapt and configure itself according to the needs and likes of the user. Such user interfaces can arouse interest in the mind of the di...

It has been reliably shown that the similarity of word embeddings obtained from popular neural models such as BERT approximates effectively a form of semantic similarity of the meaning of those words. It is therefore natural to wonder if those embeddings contain enough information to be able to connect those meanings through ontological relationshi...

For the development, training, and validation of machine learning (ML) and deep learning (DL) based methods, such as, e.g., image analysis, prediction of critical events, extraction or reconstruction of information from disrupted data streams, searching similarities in data collections, or planning of procedures, a lot of data is needed. Additional...

For students to become scientifically literate, both national (GDSU, 2013; KMK, 2005a, b, c) and international (elementary) science education standards (NGSS, 2013) and reform documents highlight the incorporation of authentic and meaningful scientific practices into science classrooms—already at the elementary level. One such scientific practice i...

Knowledge models are fundamental to dialogue systems for enabling conversational interactions, which require handling domain-specific knowledge. Ensuring effective communication in information-providing conversations entails aligning user understanding with the knowledge available to the system. However, dialogue systems often face challenges arisi...

The algebra of hierarchical numbers, operations and relations of the algebraic system are considered. A graphical representation of hierarchical numbers and operations with them is provided, and the remarkable properties of the operations are shown. Methods for normalizing hierarchical numbers for their subsequent use in processing natural language...

This article explores the convergence of connectionist and symbolic artificial intelligence (AI), from historical debates to contemporary advancements. Traditionally considered distinct paradigms, connectionist AI focuses on neural networks, while symbolic AI emphasizes symbolic representation and logic. Recent advancements in large language models...

В работе описывается веб-ориентированная программная система – Knowledge Modeling System (KMS), обеспечивающая возможность визуального моделирования знаний в форме деревьев событий и диаграмм переходов состояний, а также генерации на их основе кодов баз знаний. Полученные таким способом базы знаний могут быть использованы в качестве прототипов. При...

-Such types of data drift in ML models as actual positive and negative drifts, as well as varieties of fragmentary drifts in different directions, are considered. An overview of the current state of the problem is given, which highlights the methods of sliding window, trigger ensemble of models, covariant shift, personalization drift correction, se...

Background There is a dire need to ensure higher education institutions employ effective pedagogy in their educational programs. Hybrid teaching has received increased attention in recent decades due to its effectiveness in improving learning outcomes. There is a lack of studies exploring students’ views on hybrid teaching in acupuncture programs i...

Objective: This study aimed to carry out an investigative review, under the State of Knowledge model, which addresses the curriculum in continuing education in order to look for evidence that continuing education improves/reframes/refutes the conception of curriculum. Theoretical Framework: The incessant search for quality education seems to be the...

Ensuring compliance with complex industry standards and regulations during the design and implementation phases of construction projects is a significant challenge in the building information modeling (BIM) domain. Traditional manual compliance checking methods are inefficient and error-prone, failing to meet modern engineering demands. Natural lan...

analyzing academic data, particularly lesson records, to extract information about educational concepts. The ultimate goal is to construct a comprehensive profile that reflects the user’s accumulated knowledge throughout their learning journey. Two distinct methods are introduced for concept extraction: a gazetteer-based Named Entity Recognition ap...

This paper studies the knowledge developed by a group of sixty-two pre-service primary teachers during a training session on the definition of a polygon and the mathematical practice of defining. We explore the knowledge developed by pre-service teachers when they carry out a series of training tasks oriented around the practice of defining with pr...

Der Fragebogen wurde entwickelt, damit Lehrkräften ihr professionelles Wissen über schulische Medienkompetenzen unter dem Einsatz digitaler Medien und assisstiven Technologien in inklusiven Lerngruppen selbst einschätzen können. Die Zielgruppe des Fragebogens sind Lehramtsstudierende, Lehramtsanwärter:innen, Referendar:innen und Lehrkräfte im Berei...

The production requirements of multi-variety and high-quality products pose significant challenges for implementing intelligent production lines that integrate process sensing, adaptive processing, and precise decision-making. Digital twin is the key enabling technology for intelligent production lines, but it lacks the perception of multidimension...

Background Non-steroidal anti-inflammatory drugs (NSAIDs) have well-known adverse effects, and numerous studies have shown inappropriate behaviors regarding their use. The primary aim of this study was to analyze the knowledge, attitudes, and behaviors regarding the use of NSAIDs simultaneously in one of the largest and most populated areas of Ital...

Curriculum integration is an important aspect in developing education that is holistic and relevant to the needs of the times. This study investigates the application of the Technology Content Pedagogical Knowledge Model (TPACK) in Arabic language learning which includes four skills: listening, speaking, reading, and writing. This research uses a q...

The article aimed to investigate the perspectives of e-tutors regarding the importance of Technological Pedagogical Knowledge in an Open Distance e-Learning Institution. The article employs a quantitative survey method to allow students to articulate their impressions of how e-tutors leverage their topic expertise to impart knowledge. The study inc...

Large Language Models (LLMs) are often criticized for lacking true "understanding" and an ability to "reason" with their knowledge, being seen merely as advanced autocomplete systems. We believe that this perspective might be missing an important insight. We suggest that LLMs do develop a kind of empirical "understanding" that is "geometry"-like, w...

Keeping track of data semantics and data changes in the databases is essential to support retrospective studies and the reproducibility of longitudinal clinical analysis by preventing false conclusions from being drawn from outdated data. A knowledge model combined with a temporal model plays an essential role in organizing the data and improving q...

We present a novel annotated dataset of legal cases pertaining to Article 6 – the right to a fair trial – of the European Convention on Human Rights (ECHR). This dataset will serve as a useful resource to the research community, to assist in the training and evaluation of AI systems designed to embody the legal reasoning involved in determining the...

The startling success of ChatGPT and other large language models (LLMs) using transformer-based generative neural network architecture in applications such as natural language processing and image synthesis has many researchers excited about potential opportunities in process systems engineering (PSE). The almost human-like performance of LLMs in t...