Relevant bibliographies by topics / ID. Knowledge representation

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'ID. Knowledge representation'

Author: Grafiati
Published: 10 March 2023
Last updated: 31 July 2025

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Journal articles on the topic "ID. Knowledge representation"

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Li, Jiachen, and Xiaojin Gong. "Unleashing the Potential of Pre-Trained Diffusion Models for Generalizable Person Re-Identification." Sensors 25, no. 2 (2025): 552. https://doi.org/10.3390/s25020552.

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Domain-generalizable re-identification (DG Re-ID) aims to train a model on one or more source domains and evaluate its performance on unseen target domains, a task that has attracted growing attention due to its practical relevance. While numerous methods have been proposed, most rely on discriminative or contrastive learning frameworks to learn generalizable feature representations. However, these approaches often fail to mitigate shortcut learning, leading to suboptimal performance. In this work, we propose a novel method called diffusion model-assisted representation learning with a correla
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Chen, Jiankang, Tong Zhang, Wei-Shi Zheng, and Ruixuan Wang. "TagFog: Textual Anchor Guidance and Fake Outlier Generation for Visual Out-of-Distribution Detection." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (2024): 1100–1109. http://dx.doi.org/10.1609/aaai.v38i2.27871.

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Out-of-distribution (OOD) detection is crucial in many real-world applications. However, intelligent models are often trained solely on in-distribution (ID) data, leading to overconfidence when misclassifying OOD data as ID classes. In this study, we propose a new learning framework which leverage simple Jigsaw-based fake OOD data and rich semantic embeddings (`anchors') from the ChatGPT description of ID knowledge to help guide the training of the image encoder. The learning framework can be flexibly combined with existing post-hoc approaches to OOD detection, and extensive empirical evaluati
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Anigala, Omeshamisu, Kwanghee Won, and Chulwoo Pack. "PEARL: Perceptual and Analytical Representation Learning for Video Anomaly Detection." ACM SIGAPP Applied Computing Review 25, no. 1 (2025): 5–15. https://doi.org/10.1145/3727257.3727258.

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Video anomaly detection is crucial for applications like surveillance and autonomous systems. Traditional methods often rely solely on visual cues, missing valuable contextual data. This paper presents Perceptual and Analytical Representation Learning (PEARL), a novel method that combines perceptual (raw sensory input) and analytical (higher-level context) modalities. Specifically, we integrate visual information with object tracking data, along with the tracking data-specialized normalization method, DOT-Norm , leveraging ID switching to capture high-level contexts of abnormal movements. We e
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Farooq, Ammarah, Muhammad Awais, Josef Kittler, and Syed Safwan Khalid. "AXM-Net: Implicit Cross-Modal Feature Alignment for Person Re-identification." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (2022): 4477–85. http://dx.doi.org/10.1609/aaai.v36i4.20370.

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Cross-modal person re-identification (Re-ID) is critical for modern video surveillance systems. The key challenge is to align cross-modality representations conforming to semantic information present for a person and ignore background information. This work presents a novel convolutional neural network (CNN) based architecture designed to learn semantically aligned cross-modal visual and textual representations. The underlying building block, named AXM-Block, is a unified multi-layer network that dynamically exploits the multi-scale knowledge from both modalities and re-calibrates each modalit
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Wu, Guile, and Shaogang Gong. "Generalising without Forgetting for Lifelong Person Re-Identification." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 2889–97. http://dx.doi.org/10.1609/aaai.v35i4.16395.

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Existing person re-identification (Re-ID) methods mostly prepare all training data in advance, while real-world Re-ID data are inherently captured over time or from different locations, which requires a model to be incrementally generalised from sequential learning of piecemeal new data without forgetting what is already learned. In this work, we call this lifelong person Re-ID, characterised by solving a problem of unseen class identification subject to continuous new domain generalisation and adaptation with class imbalanced learning. We formulate a new Generalising without Forgetting method
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Vlaeminck, H., J. Vennekens, M. Denecker, and M. Bruynooghe. "An approximative inference method for solving ∃∀SO satisfiability problems." Journal of Artificial Intelligence Research 45 (September 25, 2012): 79–124. http://dx.doi.org/10.1613/jair.3658.

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This paper considers the fragment ∃∀SO of second-order logic. Many interesting problems, such as conformant planning, can be naturally expressed as finite domain satisfiability problems of this logic. Such satisfiability problems are computationally hard (ΣP2) and many of these problems are often solved approximately. In this paper, we develop a general approximative method, i.e., a sound but incomplete method, for solving ∃∀SO satisfiability problems. We use a syntactic representation of a constraint propagation method for first-order logic to transform such an ∃∀SO satisfiability problem to
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Dani Manesah. "Analisis Id Ego dan Super Ego pada Iklan Televisi Gojek Mempersembahkan: Cerdikiawan." Abstrak : Jurnal Kajian Ilmu seni, Media dan Desain 1, no. 3 (2024): 44–56. http://dx.doi.org/10.62383/abstrak.v1i3.272.

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This study analyzes the representation of the Id, Ego, and Superego in Gojek's television commercial titled "Gojek Presents: Cerdikiawan" using Sigmund Freud's psychoanalytic theory. The study aims to identify how these three components of personality are depicted in the advertisement's narrative and their impact on the audience. The research employs a qualitative case study design, with data collected through observation and content analysis. The results show that the advertisement successfully portrays the conflict between the Id, Ego, and Superego through characters and scenes reflecting pr
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Bharara, Reva, Aryan Rathore, and Krishna Kumar Tiwari. "Language Agnostic Ontology Extension Framework." Asian Journal of Research in Computer Science 16, no. 4 (2023): 327–35. http://dx.doi.org/10.9734/ajrcos/2023/v16i4394.

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Ontologies are powerful structures used to define the schema and organization of knowledge. They provide a framework for precisely and explicitly organizing concepts, entities, attributes, and relationships within a domain, enabling effective data management, knowledge sharing, and intelligent decisionmaking. Knowledge graphs, on the other hand, store data in a graphical form, facilitating semantically rich and interconnected data analysis, management, and exploration. Nodes represent entities, edges depict relationships between nodes, and attributes showcase node properties. Combining the str
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Buchnat, Marzena, and Aleksandra Jasielska. "Knowledge about anger in children with a mild intellectual disability." International Journal of Special Education (IJSE) 37, no. 2 (2022): 92–105. http://dx.doi.org/10.52291/ijse.2022.37.43.

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"The knowledge of children with a mild intellectual disability (ID) is less complex and poorer than that of their peers in the intellectual norm (IN). The aim of this study was to characterize knowledge about anger in children with mild intellectual disabilities. The study used the authoring tool to measure children’s knowledge of emotions, including anger. This tool facilitated the exploration of the cognitive representation of the basic emotions available in three codes (which perform the functions of perception, expression, and understanding) and the interconnections between them. Children
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Humayun, Shamim, Shabana Sartaj, and Waqar Ali Shah. "Exploring Linguistic Representation of Women on Facebook: A Study in Pakistani Context." Advances in Language and Literary Studies 10, no. 2 (2019): 152. http://dx.doi.org/10.7575/aiac.alls.v.10n.2p.152.

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Facebook is an online platform where people form a self-presentation and construct an identity through a personal ID or profile. Use of this social website fully depicts the norms and perceptions of patriarchal society. This study aims to explore the waymen of society speaks to the women as well as the speaking of women with other women that reflects an idea of women in Pakistani society on Facebook through quantitative study. The Analysis revealed that the women, in Pakistani society in particular and elsewhere in general is linguistically expressed as a being that is not equal to men in inte
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Dissertations / Theses on the topic "ID. Knowledge representation"

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Khor, Sebastian Wankun. "A fuzzy knowledge map framework for knowledge representation." Thesis, Khor, Sebastian Wankun (2007) A fuzzy knowledge map framework for knowledge representation. PhD thesis, Murdoch University, 2007. https://researchrepository.murdoch.edu.au/id/eprint/129/.

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Cognitive Maps (CMs) have shown promise as tools for modelling and simulation of knowledge in computers as representation of real objects, concepts, perceptions or events and their relations. This thesis examines the application of fuzzy theory to the expression of these relations, and investigates the development of a framework to better manage the operations of these relations. The Fuzzy Cognitive Map (FCM) was introduced in 1986 but little progress has been made since. This is because of the difficulty of modifying or extending its reasoning mechanism from causality to relations other th
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Grau, Ron. "The acquisition and representation of knowledge about complex multi-dynamic processes." Thesis, University of Sussex, 2009. http://sro.sussex.ac.uk/id/eprint/15370/.

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This thesis is concerned with the acquisition, representation, modelling and discovery of knowledge in ill-structured domains. In the context of this work, these are referred to as domains that involve "complex multi-dynamic (CMD) processes". A CMD process is an abstract concept for thinking about combinations of different processes where any specification and explanation involves large amounts of heterogeneous knowledge. Due to manifold cognitive and representational problems, this particular knowledge is currently hard to acquire from experts and difficult to integrate in process models. The
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Matikainen, Tiina Johanna. "Semantic Representation of L2 Lexicon in Japanese University Students." Diss., Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/133319.

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CITE/Language Arts<br>Ed.D.<br>In a series of studies using semantic relatedness judgment response times, Jiang (2000, 2002, 2004a) has claimed that L2 lexical entries fossilize with their equivalent L1 content or something very close to it. In another study using a more productive test of lexical knowledge (Jiang 2004b), however, the evidence for this conclusion was less clear. The present study is a partial replication of Jiang (2004b) with Japanese learners of English. The aims of the study are to investigate the influence of the first language (L1) on second language (L2) lexical knowledge
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Glinos, Demetrios. "SYNTAX-BASED CONCEPT EXTRACTION FOR QUESTION ANSWERING." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3565.

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Question answering (QA) stands squarely along the path from document retrieval to text understanding. As an area of research interest, it serves as a proving ground where strategies for document processing, knowledge representation, question analysis, and answer extraction may be evaluated in real world information extraction contexts. The task is to go beyond the representation of text documents as "bags of words" or data blobs that can be scanned for keyword combinations and word collocations in the manner of internet search engines. Instead, the goal is to recognize and extract the semantic
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Rudolph, Sebastian. "Relational Exploration: Combining Description Logics and Formal Concept Analysis for Knowledge Specification." Doctoral thesis, Technische Universität Dresden, 2006. https://tud.qucosa.de/id/qucosa%3A25002.

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Facing the growing amount of information in today's society, the task of specifying human knowledge in a way that can be unambiguously processed by computers becomes more and more important. Two acknowledged fields in this evolving scientific area of Knowledge Representation are Description Logics (DL) and Formal Concept Analysis (FCA). While DL concentrates on characterizing domains via logical statements and inferring knowledge from these characterizations, FCA builds conceptual hierarchies on the basis of present data. This work introduces Relational Exploration, a method for acquiring comp
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Turhan, Anni-Yasmin. "On the Computation of Common Subsumers in Description Logics." Doctoral thesis, Technische Universität Dresden, 2007. https://tud.qucosa.de/id/qucosa%3A23919.

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Description logics (DL) knowledge bases are often build by users with expertise in the application domain, but little expertise in logic. To support this kind of users when building their knowledge bases a number of extension methods have been proposed to provide the user with concept descriptions as a starting point for new concept definitions. The inference service central to several of these approaches is the computation of (least) common subsumers of concept descriptions. In case disjunction of concepts can be expressed in the DL under consideration, the least common subsumer (lcs) is just
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Carlan, Eliana. "Sistemas de Organização do Conhecimento: uma reflexão no contexto da Ciência da Informação." Thesis, reponame:Repositório Institucional da UnB, 2010. http://eprints.rclis.org/14519/1/Carlan-Eliana-Dissertacao.pdf.

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This research studies the knowledge organization systems (KOS) related to theories to build thesaurus, taxonomies, ontologies and classification systems in the literature field of Information Science. It uses the methodology of literature review and a research on the same field databases in order to investigate the bibliographic production about the theme, from 1998 up to July 2009. A bibliographic research about knowledge organization and representation is carried out, specifically related to the development of thesaurus, taxonomies, ontologies and classification systems. It identifies the sa
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Lima, João Alberto de Oliveira. "Modelo Genérico de Relacionamentos na Organização da Informação Legislativa e Jurídica." Thesis, reponame:Repositório Institucional da UnB, 2008. http://eprints.rclis.org/11352/1/tese_Joao_Lima_FINAL.pdf.

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In most of the time information does not work in an isolate form and it always belongs to one context, making relationships with other entities. Legislative and legal information, in a certain way, is characterized by their high degree of relationships. Laws, bills, legal cases and doctrine are connected by several forms, creating a rich network of information. Efforts done for the organization of information generate artificial models that try to represent the real world, creating systems and schemes of concepts used in the classification processes and indexing of information resources. This
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Münnich, Stefan. "Ontologien als semantische Zündstufe für die digitale Musikwissenschaft?" De Gruyter, Berlin / Boston, 2018. https://slub.qucosa.de/id/qucosa%3A36849.

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Ontologien spielen eine zentrale Rolle für die formalisierte Repräsentation von Wissen und Informationen sowie für die Infrastruktur des sogenannten semantic web. Trotz früherer Initiativen der Bibliotheken und Gedächtnisinstitutionen hat sich die deutschsprachige Musikwissenschaft insgesamt nur sehr zögerlich dem Thema genähert. Im Rahmen einer Bestandsaufnahme werden neben der Erläuterung grundlegender Konzepte, Herausforderungen und Herangehensweisen bei der Modellierung von Ontologien daher auch vielversprechende Modelle und bereits erprobte Anwendungsbeispiele für eine ‚semantische‘ digit
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Baader, Franz, and Adrian Nuradiansyah. "Mixing Description Logics in Privacy-Preserving Ontology Publishing." Springer, 2019. https://tud.qucosa.de/id/qucosa%3A75565.

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In previous work, we have investigated privacy-preserving publishing of Description Logic (DL) ontologies in a setting where the knowledge about individuals to be published is an EL instance store, and both the privacy policy and the possible background knowledge of an attacker are represented by concepts of the DL EL. We have introduced the notions of compliance of a concept with a policy and of safety of a concept for a policy, and have shown how, in the context mentioned above, optimal compliant (safe) generalizations of a given EL concept can be computed. In the present paper, we consider
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Book chapters on the topic "ID. Knowledge representation"

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da Silva Klahr Patrícia, Corrêa Coronel Christian, Cabral Robinson Caroline, Fonseca João Marcelo, Dias Flores Cecília, and Della Méa Plentz Rodrigo. "Influence Diagram As a Support Tool for Clinical Decisions In Cardiopulmonary And Metabolic Rehabilitation." In Studies in Health Technology and Informatics. IOS Press, 2015. https://doi.org/10.3233/978-1-61499-564-7-290.

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An influence diagram (ID) is a method of graphical representation of uncertain knowledge, which can be employed to support decisions in health care using probabilistic reasoning. We aimed to describe the development of an ID to support the decision-making process in phase II at Cardiopulmonary and Metabolic Rehabilitation Program (CPMR). The development of the ID was carried out through the identification of relevant variables and their possible values, as well as the identification of details of each variable, in order to find a network structure that appropriately connects the nodes that rep
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Bogaerts Bart, Vennekens Joost, Denecker Marc, and Van den Bussche Jan. "Inference in the FO(C) Modelling Language." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2014. https://doi.org/10.3233/978-1-61499-419-0-111.

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Recently, FO(C), the integration of C-LOG with classical logic, was introduced as a knowledge representation language. Up to this point, no systems exist that perform inference on FO(C), and very little is known about properties of inference in FO(C). In this paper, we study both of the above problems. We define normal forms for FO(C), one of which corresponds to FO(ID). We define transformations between these normal forms, and show that, using these transformations, several inference tasks for FO(C) can be reduced to inference tasks for FO(ID), for which solvers exist. We implemented this tra
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Nodenot, Thierry, Pierre Laforcade, and Xavier Le Pallec. "Visual Design of coherent Technology-Enhanced Learning Systems." In Handbook of Visual Languages for Instructional Design. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-729-4.ch013.

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Visual instructional design languages currently provide notations for representing the intermediate and final results of a knowledge engineering process. As some languages particularly focus on the formal representation of a learning design that can be transformed into machine interpretable code (i.e., IML-LD players), others have been developed to support the creativity of designers while exploring their problem-spaces and solutions. This chapter introduces CPM (Computer Problem-based Metamodel), a visual language for the instructional design of Problem-Based Learning (PBL) situations. On the
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Vinayakumar, R., K. P. Soman, and Prabaharan Poornachandran. "Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch018.

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This article describes how sequential data modeling is a relevant task in Cybersecurity. Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent neural networks (RNNs) are a subset of artificial neural networks (ANNs) which have appeared as a powerful, principle approach to learn dynamic temporal behaviors in an arbitrary length of large-scale sequence data. Furthermore, stacked recurrent neural networks (S-RNNs) have the potential to learn complex temporal behaviors quickly, including sparse representations. To leverage this, the authors model network traf
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Conference papers on the topic "ID. Knowledge representation"

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Balhorn, Lukas Schulze, Niels Seijsener, Kevin Dao, et al. "Rule-Based Autocorrection of Piping and Instrumentation Diagrams (P&IDs) on Graphs." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.150968.

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A piping and instrumentation diagram (P&amp;ID) is a central reference document in chemical process engineering. Currently, chemical engineers manually review P&amp;IDs through visual inspection to find and rectify errors. However, engineering projects can involve hundreds to thousands of P&amp;ID pages, creating a significant revision workload. This study proposes a rule-based method to support engineers with error detection and correction in P&amp;IDs. The method is based on a graph representation of P&amp;IDs, enabling automated error detection and correction, i.e., autocorrection, through
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Alimin, Achmad Anggawirya, Dominik P. Goldstein, Lukas Schulze Balhorn, and Artur M. Schweidtmann. "Talking like Piping and Instrumentation Diagrams (P&IDs)." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.159477.

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We propose a methodology that allows communication with Piping and Instrumentation Diagrams (P&amp;IDs) using natural language. In particular, we represent P&amp;IDs through the DEXPI data model as labeled property graphs and integrate them with Large Language Models (LLMs). The approach consists of three main parts: 1) P&amp;IDs are cast into a graph representation from the DEXPI format using our pyDEXPI Python package. 2) A tool for generating P&amp;ID knowledge graphs from pyDEXPI. 3) Integration of the P&amp;ID knowledge graph to LLMs using graph-based retrieval augmented generation (graph
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Southward, Steve C. "Real-Time Parameter ID Using Polynomial Chaos Expansions." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-43745.

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A novel real-time parameter identification algorithm has been developed that exploits polynomial chaos expansion (PCE) representations of uncertain parameters. Dynamic system models inevitably contain parameters whose values are rarely known with absolute certainty. In many cases, such parameters are either not measurable, or they are slowly time varying. In some cases, the dynamic system model is inadequate and parameter values are simply chosen to provide a “best fit” representation. For the method proposed here, we assume apriori knowledge of the probability distributions associated with th
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Perfetto-Demarchi, Ana Paula, Cleuza Fornasier, Bernabé Hernandis Ortuño, and Elingth Simoné Rosales Marquina. "O uso do dispositivo ID-Think no compartilhamento de conhecimento." In Systems & Design: Beyond Processes and Thinking. Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/ifdp.2016.2400.

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Considering that the great advantage of an organization today is the knowledge it has, and how it manages this knowledge, this article reports the application of the IDThink device in a fashion organization's manufacturing sector for its validation. This device applies knowledge management through the skills and attitudes of the design thinker. The device shown here is to assist the process of innovation in organizations by using some design thinkers skills in the knowledge explicitation and externalization. To Brown (2009) design thinking begins with the skills that designers have learned ove
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Xu, Xingcheng, Zihao Pan, Haipeng Zhang, and Yanqing Yang. "It Ain’t That Bad: Understanding the Mysterious Performance Drop in OOD Generalization for Generative Transformer Models." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/727.

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Large language models (LLMs) have achieved remarkable proficiency on solving diverse problems. However, their generalization ability is not always satisfying and the generalization problem is common for generative transformer models in general. Researchers take basic mathematical tasks like n-digit addition or multiplication as important perspectives for investigating their generalization behaviors. It is observed that when training models on n-digit operations (e.g., additions) in which both input operands are n-digit in length, models generalize successfully on unseen n-digit inputs (in-dist
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