Journal articles: 'Multidimensional knowledge'

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Chow, Paul K. O., and Daniel S. Yeung. "A multidimensional knowledge structure." Expert Systems with Applications 9, no. 2 (January 1995): 177–87. http://dx.doi.org/10.1016/0957-4174(94)00060-9.

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Zenkert, Johannes, André Klahold, and Madjid Fathi. "Knowledge discovery in multidimensional knowledge representation framework." Iran Journal of Computer Science 1, no. 4 (April 4, 2018): 199–216. http://dx.doi.org/10.1007/s42044-018-0019-0.

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Shukla, Raj Kamal, and Rahul Patel. "Indigenous knowledge system: A multidimensional science." Asian Man (The) - An International Journal 12, no. 1 (2018): 129. http://dx.doi.org/10.5958/0975-6884.2018.00021.x.

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Zheng, Ya Lin. "Similarity Knowledge Mass and Multiple Multidimensional Approximate Reasoning." Applied Mechanics and Materials 333-335 (July 2013): 1392–96. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.1392.

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Designing the approximate reasoning matching schemes and the corresponding algorithms with similarity relation Q instead of equivalence relation R can reflect the nature of approximate reasoning and meet more application expectations. In this paper, we introduce the type V matching scheme and the corresponding type V Q-algorithm of multiple multidimensional approximate reasoning with given multidimensional input and multidimensional knowledge bases on strong Q-logic CQ.

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McCarthy, Kathryn S., and Danielle S. McNamara. "The Multidimensional Knowledge in Text Comprehension framework." Educational Psychologist 56, no. 3 (February 5, 2021): 196–214. http://dx.doi.org/10.1080/00461520.2021.1872379.

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Schuyler, Adam D., Mark W. Maciejewski, Haribabu Arthanari, and Jeffrey C. Hoch. "Knowledge-based nonuniform sampling in multidimensional NMR." Journal of Biomolecular NMR 50, no. 3 (May 29, 2011): 247–62. http://dx.doi.org/10.1007/s10858-011-9512-6.

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Purnomo, Muhammad Ridwan Andi, Chairul Saleh, Reny Lituhayu Lagaida, and Azmi Hassan. "Knowledge-Based Genetic Algorithm for Multidimensional Data Clustering." Applied Mechanics and Materials 606 (August 2014): 277–80. http://dx.doi.org/10.4028/www.scientific.net/amm.606.277.

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In this paper, a new approach of genetic algorithm called knowledge-based Genetic Algorithm (KBGA-Clustering) is proposed for multidimensional data clustering . Basically, this method adopts knowledge of what called as appropriate cluster centre for a fixed number of k-cluster. The chromosome which has inappropriate genes will be penalised with maximum value to prohibit it in the next generation. The experimental result is also provided for KBGA-Clustering and Genetic Algorithm-Clustering (GA-Clustering) to present the performance. Based on the observation, KBGA-Clustering presents better performance and more optimum solution compared to conventional GA-Clustering.

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Ouali, Sonya, Mohamed Mhiri, and Lotfi Bouzguenda. "A Multidimensional Knowledge Model for Business Process Modeling." Procedia Computer Science 96 (2016): 654–63. http://dx.doi.org/10.1016/j.procs.2016.08.247.

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López-Huertas, María. "Reflexions on Multidimensional Knowledge: Its Influence on the Foundation of Knowledge Organization." KNOWLEDGE ORGANIZATION 40, no. 6 (2013): 400–407. http://dx.doi.org/10.5771/0943-7444-2013-6-400.

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Bleiler, Sarah K., and Denisse R. Thompson. "Multidimensional Assessment of CCSSM." Teaching Children Mathematics 19, no. 5 (December 2012): 292–300. http://dx.doi.org/10.5951/teacchilmath.19.5.0292.

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Yuan, Xiu Li. "Knowledge Pushing Technology Based on the Knowledge Context Node Similarity." Applied Mechanics and Materials 687-691 (November 2014): 2660–63. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.2660.

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In order to meet the users'demand of knowledge and use knowledge efficiently,this paper adopts modeling methods of multilayer and multidimensional context tree to complete the establishment of the knowledge context tree, build the algorithm of the context entity similarity and realize the knowledge push, improve the similarity of the user with the necessary knowledge, so that a kind of very valuable method for pushing knowledge has also been put forward.

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Yuan, Xiu Li. "The Study of Knowledge Pushing Technology Based on the Knowledge Context." Applied Mechanics and Materials 644-650 (September 2014): 2350–54. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2350.

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In order to meet the users’ demand of knowledge and use knowledge efficiently in the process of knowledge management,this paper adopts modeling methods of multilayer and multidimensional context tree to complete the establishment of the knowledge context tree, build the algorithm of the context entity similarity and realize the knowledge push, so that a kind of very valuable method for pushing knowledge has also been put forward.

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Marvi, Mohammad Hossein, Morteza Maleki Minbashrazgah, Azim Zarei, and Golnar Shojaei Baghini. "Knowledge foundation in green purchase behaviour: Multidimensional scaling method." Cogent Business & Management 7, no. 1 (January 1, 2020): 1773676. http://dx.doi.org/10.1080/23311975.2020.1773676.

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Nook, Erik C., Stephanie F. Sasse, Hilary K. Lambert, Katie A. McLaughlin, and Leah H. Somerville. "Increasing verbal knowledge mediates development of multidimensional emotion representations." Nature Human Behaviour 1, no. 12 (November 27, 2017): 881–89. http://dx.doi.org/10.1038/s41562-017-0238-7.

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Stahl, Gerry, Ulrike Cress, Nancy Law, and Sten Ludvigsen. "Analyzing the multidimensional construction of knowledge in diverse contexts." International Journal of Computer-Supported Collaborative Learning 9, no. 1 (January 22, 2014): 1–6. http://dx.doi.org/10.1007/s11412-014-9189-4.

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Spraggon, Martin, and Virginia Bodolica. "A multidimensional taxonomy of intra-firm knowledge transfer processes." Journal of Business Research 65, no. 9 (September 2012): 1273–82. http://dx.doi.org/10.1016/j.jbusres.2011.10.043.

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Shi, Xiaolin, Xitian Tian, Jianguo Gu, Fan Yang, Liping Ma, Yun Chen, and Tianyi Su. "Knowledge Graph-Based Assembly Resource Knowledge Reuse towards Complex Product Assembly Process." Sustainability 14, no. 23 (November 22, 2022): 15541. http://dx.doi.org/10.3390/su142315541.

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Assembly process designers typically confront the challenge of seeking information out of large volumes of non-structured files with a view to supporting the decision-making to be made. It is a leading concern that embedding data in text documents can hardly be retrieved semantically in order to facilitate decision-making with timely support. For tackling this gap, we propose in this paper a knowledge graph-based approach used to merge and retrieve information decided to be relevant within an engineering context. The proposed approach is to establish a multidimensional integrated assembly resource knowledge graph (ARKG) based on the structure of function-structure-assembly procedure-assembly resource, and this multidimensional integrated structure can well accomplish the retrieval of related knowledge. The upper semantic framework of ARKG is established by the assembly resource ontology model, which is a semantic-type framework involving multiple domains of knowledge to create instantiated data reflecting the full profile of the assembly resource for obtaining structured data of ARKG while avoiding the data redundancy problem. The ARKG method is validated through assembly scenario of the aircraft, and the results show the effectiveness and accuracy of the ARKG used by the assembly process designer in the assembly process design phase for retrieving the target knowledge of the assembly resources.

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Vukić, Đurđica, Sanda Martinčić-Ipšić, and Ana Meštrović. "Structural Analysis of Factual, Conceptual, Procedural, and Metacognitive Knowledge in a Multidimensional Knowledge Network." Complexity 2020 (March 9, 2020): 1–17. http://dx.doi.org/10.1155/2020/9407162.

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Discovering the most suitable network structure of the learning domain represents one of the main challenges of knowledge delivery and acquisition. We propose a multidimensional knowledge network (MKN) consisting of three components: multilayer network and its two projections. Each network layer constitutes factual, conceptual, procedural, or metacognitive knowledge within the domain of databases as a standard course of computer science study. In the MKN layer, nodes are concepts or knowledge units and the edges are weighted with regard to Bloom's cognitive learning level. The projected network layers are contrasted with a monolayer network by comparing characterizations of the centrality measures: degree centrality, closeness centrality, betweenness centrality, and eccentricity. The study revealed indications of how concepts, supported with the higher number of previously introduced concepts, have a dominant role in knowledge acquisition, from a view of knowledge structure and content. The analysis of communities, assortativity coefficient, and overlap between MKN layers contributes to better structuring of knowledge. MKN enables systematic insights into the efficiency of knowledge integration across metacognitive layers, as well as the detection of crucial cognitive concepts that reduce/increase the cognitive load during learning.

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Martín-Martín, Jaime, Mónica López-García, María Dolores Medina-Abellán, Cristina María Beltrán-Aroca, Stella Martín-de-las-Heras, Leticia Rubio, and María Dolores Pérez-Cárceles. "Physicians’ and Nurses’ Knowledge in Palliative Care: Multidimensional Regression Models." International Journal of Environmental Research and Public Health 18, no. 9 (May 10, 2021): 5031. http://dx.doi.org/10.3390/ijerph18095031.

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The increase in life expectancy has led to a growth in the number of people in need of palliative care. Health professionals must possess appropriate knowledge and skills. This study aimed to assess knowledge in palliative care through the Palliative Care Knowledge Test Spanish Version (PCKT-SV)®. A cross-sectional analytical study was conducted in 40 primary care health services. A total of 600 PCKT-SV questionnaires were distributed among health professionals; 561 of them (226 nurses and 335 physicians) were properly filled up. Sociodemographic information, education, and work experience were also recorded. A total of 34.41% of the nurses and 67.40% of the physicians showed good or excellent knowledge of palliative care. Physicians’ scores for pain, dyspnea, and psychiatric disorders were higher than those of the nurses. Nurses scored significantly better in philosophy. Professionals with continuous training in palliative care showed a higher level of knowledge. Age and work experience of physicians and undergraduate training in nurses had significant weight in knowledge. Developing continuous training and enhancing undergraduate training in palliative care will lead to improved patient care at the end of life.

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Ayanwale, Musa Adekunle, and Funmilayo Rebecca Abayomi. "MULTIDIMENSIONAL INSTRUMENT OF EXAMINERS’ ATTITUDE TOWARDS KNOWLEDGE OF MALPRACTICE INDICATORS." Journal of Applied Structural Equation Modeling 4, no. 1 (January 5, 2020): 17–25. http://dx.doi.org/10.47263/jasem.4(1)02.

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In this study, the authors constructed and validated instrument to measure examiners’ disposition towards knowledge of examination malpractice indicators of West African Examinations Council (WAEC). Consequently, scale development research type of single-subject design was employed. The sample for the two phases consisted of nine hundred and sixty (960) WAEC mathematics examiners from 9 marking centres, which were drawn randomly from Osun, Ogun and Ondo State, Nigeria. The instrument used for data collection was Examiners’ Attitude Towards Knowledge of Malpractice Indicators Scale (EAKMIS). Data were analyzed using Principal Component Analysis (PCA), Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA) and Ordinal Alpha. The results showed that the scale was reduced from twenty (20) to eleven (11) items across three (3) dimensions. Final compliance indices were: χ2 = 457.54, p = 0.01, RMSEA= 0.03, GFI = 0.96, AGFI = 0.96, TLI = 0.94, NFI = 0.90, SRMR= 0.01, CFI= 0.91 and IFI= 0.91. The ordinal alpha reliability index for the three (3) factors of EAKMIS was 0.79, while the reliability index for each of the subscale of the EAKMIS ranged from 0.85 to 0.93. It was recommended that there should be intensive training and re-training for all the examiners by the examining body where issues related to the detection of examination malpractice cases while marking would be discussed.

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Curtis, Mary B., and Ralph E. Viator. "An Investigation of Multidimensional Knowledge Structure and Computer Auditor Performance." AUDITING: A Journal of Practice & Theory 19, no. 2 (September 1, 2000): 83–103. http://dx.doi.org/10.2308/aud.2000.19.2.83.

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This study assesses the internal control knowledge structure dimensions and antecedents, as well as the relationship between structure and performance, for a set of computer auditors. The study extends prior research in two ways. First, in an effort to investigate the impact of multiple knowledge structures on auditor performance, a multidimensional model is employed through the use of multidimensional scaling (MDS). An added benefit of this methodology is that it facilitates the evaluation of the extent of auditor knowledge structure. Second, a more complete understanding of the influence of experience and education on auditor performance is gained through investigating the role of knowledge structure as a mediator. Results suggest that computer auditors employ both control objective and transaction flow structural dimensions simultaneously, as well as a third dimension not previously identified, which represents the degree of computerization of a particular procedure. Transaction flow was identified as the dominant structural dimension for most computer auditors. Computer auditor knowledge structures were found to be associated with college education and prior computer information systems (CIS) work experience. The extent (weight) of auditors' control objective and transaction flow dimensions was related to their performance on an internal control review task. However, no significant interactions were found.

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Zhong, Dong, Yi-An Zhu, Lanqing Wang, Junhua Duan, and Jiaxuan He. "A Cognition Knowledge Representation Model Based on Multidimensional Heterogeneous Data." Complexity 2020 (December 28, 2020): 1–17. http://dx.doi.org/10.1155/2020/8812459.

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The information in the working environment of industrial Internet is characterized by diversity, semantics, hierarchy, and relevance. However, the existing representation methods of environmental information mostly emphasize the concepts and relationships in the environment and have an insufficient understanding of the items and relationships at the instance level. There are also some problems such as low visualization of knowledge representation, poor human-machine interaction ability, insufficient knowledge reasoning ability, and slow knowledge search speed, which cannot meet the needs of intelligent and personalized service. Based on this, this paper designs a cognitive information representation model based on a knowledge graph, which combines the perceptual information of industrial robot ontology with semantic description information such as functional attributes obtained from the Internet to form a structured and logically reasoned cognitive knowledge graph including perception layer and cognition layer. Aiming at the problem that the data sources of the knowledge base for constructing the cognitive knowledge graph are wide and heterogeneous, and there are entity semantic differences and knowledge system differences among different data sources, a multimodal entity semantic fusion model based on vector features and a system fusion framework based on HowNet are designed, and the environment description information such as object semantics, attributes, relations, spatial location, and context acquired by industrial robots and their own state information are unified and standardized. The automatic representation of robot perceived information is realized, and the universality, systematicness, and intuition of robot cognitive information representation are enhanced, so that the cognition reasoning ability and knowledge retrieval efficiency of robots in the industrial Internet environment can be effectively improved.

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Scott, G., and Chi-Ren Shyu. "Knowledge-Driven Multidimensional Indexing Structure for Biomedical Media Database Retrieval." IEEE Transactions on Information Technology in Biomedicine 11, no. 3 (May 2007): 320–31. http://dx.doi.org/10.1109/titb.2006.880551.

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Swart, Juani, and Nicholas Kinnie. "Managing multidimensional knowledge assets: HR configurations in professional service firms." Human Resource Management Journal 23, no. 2 (July 8, 2012): 160–79. http://dx.doi.org/10.1111/j.1748-8583.2012.00197.x.

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Vie, Jill-Jenn, and Hisashi Kashima. "Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 750–57. http://dx.doi.org/10.1609/aaai.v33i01.3301750.

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Knowledge tracing is a sequence prediction problem where the goal is to predict the outcomes of students over questions as they are interacting with a learning platform. By tracking the evolution of the knowledge of some student, one can optimize instruction. Existing methods are either based on temporal latent variable models, or factor analysis with temporal features. We here show that factorization machines (FMs), a model for regression or classification, encompasses several existing models in the educational literature as special cases, notably additive factor model, performance factor model, and multidimensional item response theory. We show, using several real datasets of tens of thousands of users and items, that FMs can estimate student knowledge accurately and fast even when student data is sparsely observed, and handle side information such as multiple knowledge components and number of attempts at item or skill level. Our approach allows to fit student models of higher dimension than existing models, and provides a testbed to try new combinations of features in order to improve existing models.

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Hoseini, Mohamad, Fatemeh Saghafi, and Emad Aghayi. "A multidimensional model of knowledge sharing behavior in mobile social networks." Kybernetes 48, no. 5 (May 7, 2019): 906–29. http://dx.doi.org/10.1108/k-07-2017-0249.

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Purpose A great number of people use mobile social networks (MSNs) to communicate, entertain, learn, search and get advice. Growth and survival of any community depends on the activities of its members in sharing information and knowledge. The purpose of this study is to assess the influential factors on knowledge sharing behavior in MSNs in different perspectives in a comprehensive manner. Design/methodology/approach A model of factors affecting knowledge sharing behavior in MSNs is proposed by applying the structural equation modeling and path analysis to data collected from a sample of users of a well-known MSN through a questionnaire. Findings This study supports the contributive aspects of trust and enjoying participation in sharing knowledge, while there is no significant correlation between perceived ease of use and knowledge sharing behavior in MSNs. Furthermore, intention to share knowledge can lead to actual behavior in MSNs environments. Practical implications The results obtained here provide a grasp of factors that influence knowledge sharing in mobile communities which would promote enhanced contribution towards their online communities by MSNs administrators. Originality/value A four-dimensional comprehensive model consisting of social, psychological, cultural and technological perspectives in one package is proposed here for knowledge sharing behavior in MSNs. Such a comprehensive perspective is overlooked in the existing literature.

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Déguernel, Ken, Emmanuel Vincent, and Gérard Assayag. "Probabilistic Factor Oracles for Multidimensional Machine Improvisation." Computer Music Journal 42, no. 2 (June 2018): 52–66. http://dx.doi.org/10.1162/comj_a_00460.

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This article presents two methods to generate automatic improvisation using training over multidimensional sequences. We consider musical features such as melody, harmony, timbre, etc., as dimensions. We first present a system combining interpolated probabilistic models with a factor oracle. The probabilistic models are trained on a corpus of musical work to learn the correlation between dimensions, and they are used to guide the navigation in the factor oracle to ensure a logical improvisation. Improvisations are therefore created in a way in which the intuition of a context is enriched with multidimensional knowledge. We then introduce a system creating multidimensional improvisations based on communication between dimensions via probabilistic message passing. The communication infers some anticipatory behavior on each dimension influenced by the others, creating a consistent multidimensional improvisation. Both systems were evaluated by professional improvisers during listening sessions. Overall, the systems received good feedback and showed encouraging results—first, on how multidimensional knowledge can improve navigation in the factor oracle and, second, on how communication through message passing can emulate the interactivity between dimensions or musicians.

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Pancholi, Surabhi, Tan Yigitcanlar, and Mirko Guaralda. "Governance that matters." Journal of Place Management and Development 10, no. 1 (March 6, 2017): 73–87. http://dx.doi.org/10.1108/jpmd-08-2016-0053.

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Purpose This study aims to scrutinise the prominence of place making as a strategy in the development of knowledge and innovation spaces with a specific focus on distinguishing the role of governance. Design/methodology/approach The study adopts a multidimensional conceptual framework of place making to investigate a knowledge and innovation space case through a qualitative analysis approach involving a range of key stakeholders. Findings The study finds that governance is critical in facilitating place making in knowledge and innovation spaces, and place-making practices in these locations benefit from adopting a multidimensional approach. Originality/value The study expands our knowledge on the role of governance in place making that helps achieve desired knowledge and innovation space outcomes.

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Bazylev, V. N., I. A. Kuperman, E. V. Chmykhova, and M. L. Aranovich. "Consolidated Knowledge Corpus: Design Technique." Alma mater. Vestnik Vysshey Shkoly, no. 12 (December 2021): 69–76. http://dx.doi.org/10.20339/am.12-21.069.

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The article presents the results of a pilot study for the structural transformation of 18 Bachelor’s Degree Programs for e-learning using Consolidated Knowledge Corpus. Consolidated Knowledge Corpus is a multidimensional object-oriented structure of educational content objects and their connections. All academic topics from 224 disciplines were combined into a Consolidated Knowledge Corpus to unify similarities and eliminate duplication. A unified matrix of educational content for the first year of study for 18 bachelor’s programs was compiled and an optimized modular structure of the curriculum was built. As a result, the necessary production volume of digital educational products and subsequently the necessary volume of investments were reduced by 55 percent.

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Bilò, Vittorio, Michele Flammini, Vasco Gallotti, and Cosimo Vinci. "On Multidimensional Congestion Games." Algorithms 13, no. 10 (October 15, 2020): 261. http://dx.doi.org/10.3390/a13100261.

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We introduce multidimensional congestion games, that is, congestion games whose set of players is partitioned into d+1 clusters C0,C1,…,Cd. Players in C0 have full information about all the other participants in the game, while players in Ci, for any 1≤i≤d, have full information only about the members of C0∪Ci and are unaware of all the others. This model has at least two interesting applications: (i) it is a special case of graphical congestion games induced by an undirected social knowledge graph with independence number equal to d, and (ii) it represents scenarios in which players have a type and the level of competition they experience on a resource depends on their type and on the types of the other players using it. We focus on the case in which the cost function associated with each resource is affine and bound the price of anarchy and stability as a function of d with respect to two meaningful social cost functions and for both weighted and unweighted players. We also provide refined bounds for the special case of d=2 in presence of unweighted players.

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Bocharnikov, V. N. "MULTIDIMENSIONAL METAPHOR OF GEOGRAPHICAL KNOWLEDGE IN THE STRUCTURAL TRANSMISSION OF PHILOSOPHY." Астраханский вестник экологического образования 19, no. 2 (2020): 25–35. http://dx.doi.org/10.36698/2304-5957-2020-19-2-25-35.

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Martins, Cátia, Tiago Brandão, Adelaide Almeida, and Sílvia M. Rocha. "Enlarging Knowledge on Lager Beer Volatile Metabolites Using Multidimensional Gas Chromatography." Foods 9, no. 9 (September 11, 2020): 1276. http://dx.doi.org/10.3390/foods9091276.

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Foodomics, emergent field of metabolomics, has been applied to study food system processes, and it may be useful to understand sensorial food properties, among others, through foods metabolites profiling. Thus, as beer volatile components represent the major contributors for beer overall and peculiar aroma properties, this work intends to perform an in-depth profiling of lager beer volatile metabolites and to generate new data that may contribute for molecules’ identification, by using multidimensional gas chromatography. A set of lager beers were used as case-study, and 329 volatile metabolites were determined, distributed over 8 chemical families: acids, alcohols, esters, monoterpenic compounds, norisoprenoids, sesquiterpenic compounds, sulfur compounds, and volatile phenols. From these, 96 compounds are reported for the first time in the lager beer volatile composition. Around half of them were common to all beers under study. Clustering analysis allowed a beer typing according to production system: macro- and microbrewer beers. Monoterpenic and sesquiterpenic compounds were the chemical families that showed wide range of chemical structures, which may contribute for the samples’ peculiar aroma characteristics. In summary, as far as we know, this study presents the most in-depth lager beer volatile composition, which may be further used in several approaches, namely, in beer quality control, monitoring brewing steps, raw materials composition, among others.

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Yenidogan, Tugba Gurcaylilar. "A multidimensional typology of automaker-supplier relationships: the knowledge sharing dilemma." International Journal of Automotive Technology and Management 14, no. 1 (2014): 1. http://dx.doi.org/10.1504/ijatm.2014.058363.

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Hwang, Yujong. "A study on the multidimensional information management capability of knowledge workers." Aslib Journal of Information Management 68, no. 2 (March 21, 2016): 138–54. http://dx.doi.org/10.1108/ajim-06-2015-0093.

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Purpose – Drawing upon the extant literature from information systems (IS), information science, psychology, marketing, management, and IT training, the purpose of this paper is to propose information management capability (IMC) construct and its sub-dimensions. Design/methodology/approach – New instruments were developed and validated to measure the proposed IMC constructs. The proposed model was empirically tested using the data collected from 120 knowledge workers using SPSS and partial least square. Findings – This research proposes and confirms that IMC has formative sub-dimensions such as sensing, collecting, organizing, processing, and maintaining. Originality/value – The study findings provide important insights on enhancing knowledge workers’ information management practices and subsequent knowledge management practices. The new instruments can be used as diagnostic tools for knowledge workers’ recruiting, ongoing assessment, and training.

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Wolff, K. E., G. K. Hartmann, A. Nölle, and M. L. Richards. "Conceptual knowledge processing and graphical representation of multidimensional atmospheric ozone data." Physics and Chemistry of the Earth, Part A: Solid Earth and Geodesy 25, no. 8 (January 2000): 619–24. http://dx.doi.org/10.1016/s1464-1895(00)00094-6.

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Eckardt, Franziska. "The multidimensional role of science parks in attracting international knowledge migrants." Regional Studies, Regional Science 4, no. 1 (January 2017): 218–26. http://dx.doi.org/10.1080/21681376.2017.1383181.

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Usman, Muhammad, Russel Pears, and A. C. M. Fong. "A data mining approach to knowledge discovery from multidimensional cube structures." Knowledge-Based Systems 40 (March 2013): 36–49. http://dx.doi.org/10.1016/j.knosys.2012.11.008.

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Engberg, Jan. "Comparative Law for Legal Translation: Through Multiple Perspectives to Multidimensional Knowledge." International Journal for the Semiotics of Law - Revue internationale de Sémiotique juridique 33, no. 2 (May 8, 2020): 263–82. http://dx.doi.org/10.1007/s11196-020-09706-9.

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Caverni, Jean Paul, and Jean Luc Péris. "Cognitive reality of multidimensional information processing in knowledge assessment by experts." European Journal of Psychology of Education 7, no. 2 (June 1992): 109–22. http://dx.doi.org/10.1007/bf03172888.

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Chen, Chiu-Ching, Po-Wen Chiu, and Ching-Yuan Chang. "Analysis of Personal Assumptions about Knowledge and Knowing by Multidimensional Visualization." International Journal of Learning: Annual Review 17, no. 3 (2010): 241–54. http://dx.doi.org/10.18848/1447-9494/cgp/v17i03/46914.

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Aboslaiman,, Lucrecia. "A proposal against the current context: multidimensional law." Perspectivas 11, no. 1 (December 30, 2020): 121–32. http://dx.doi.org/10.19137/perspectivas-2021-v11n1a07.

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To consider the main questions that changes produced in contemporary societies make to law is a debate that implies assuming what happens with knowledge in general and in the legal realm in particular. The present paper addresses the problem of a complex, postmodern and globalized socio-cultural reality, and presents the need for its approach from a right considered not only in its normative face, but also anthropological, social, cultural and ethical-legal. We propose a set of ideas and some hypotheses, keys and orientations, based on a globalized society, with the insertion of the claim of human rights protected by a universal ethics connected and related to law. We seek to build a multidimensional legal world in a free, fair and democratic society, within a context of postmodern and globalized society, with technological advances that grow in a dizzying manner and impact on man, society and law in different ways, depending on the place and the time in which they occur.

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Sue, Derald Wing. "Multidimensional Facets of Cultural Competence." Counseling Psychologist 29, no. 6 (November 2001): 790–821. http://dx.doi.org/10.1177/0011000001296002.

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Calls for incorporating cultural competence in psychology have been hindered for a number of reasons: belief in the universality of psychological laws and theories, the invisibility of monocultural policies and practices, differences over defining cultural competence, and the lack of a conceptual framework for organizing its multifaceted dimensions. A proposed multidimensional model of cultural competence (MDCC) incorporates three primary dimensions: (a) racial and culture-specific attributes of competence, (b) components of cultural competence, and (c) foci of cultural competence. Based on a 3 (Awareness, Knowledge, and Skills) × 4 (Individual, Professional, Organizational, and Societal) × 5 (African American, Asian American, Latino/Hispanic American, Native American, and European American) factorial combination, the MDCC allows for the systematic identification of cultural competence in a number of different areas. Its uses in education and training, practice, and research are discussed.

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Nan, Chunping. "Multidimensional Psychological Model Construction of Public English Teaching Based on Deep Learning from Multimodal Perspective." Mobile Information Systems 2022 (August 4, 2022): 1–11. http://dx.doi.org/10.1155/2022/1653452.

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Public English instruction focuses on language skill development while also enhancing students’ business professional knowledge and all-around ability under the direction of public English teaching objectives. From a knowledge standpoint, public English instruction contains a lot of tacit knowledge, making it appropriate for case teaching. This paper analyses the knowledge-locking factors in traditional case teaching based on deep learning from the multimodality perspective and builds a mental model to compensate for the shortcomings of the traditional case teaching. In this paper, a multidimensional psychological model is built that overcomes the limitations of conventional approaches. It is based on the multimodal feature extraction and modal selection algorithm of deep learning and multidimensional psychology in public English teaching. The method suggested in this paper outperforms the benchmark model created for the three evaluation indices and also demonstrates the benefits of multimodality. Create a fully integrated multidimensional mental model of the teaching and activity situations so that students can learn with a passion, become more engaged in practising their English, and ultimately develop the language skills required for employment.

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Morrow-Howell, Nancy. "Multidimensional Assessment of the Elderly Client." Families in Society: The Journal of Contemporary Social Services 73, no. 7 (September 1992): 395–407. http://dx.doi.org/10.1177/104438949207300702.

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Practitioners encounter more elderly clients and their families as the service demands of our aging society continue to grow. This article seeks to increase gerontological knowledge among students and practitioners by providing an outline for the multidimensional assessment of the elderly client. Seven domains of assessment are reviewed: physical health, mental health, social support, physical environments, functioning, coping styles, and formal service usage. Discussion includes topics to be covered in each dimension, helpful assessment instruments, particularly relevant interviewing skills, and use of allied professionals.

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Pedroso, Elsa, and Carlos F. Gomes. "The effectiveness of management accounting systems in SMEs: a multidimensional measurement approach." Journal of Applied Accounting Research 21, no. 3 (June 6, 2020): 497–515. http://dx.doi.org/10.1108/jaar-05-2018-0059.

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PurposeThe purpose of this paper is to present and validate a multidimensional approach to measure the effectiveness of management accounting systems.Design/methodology/approachBased on an extensive literature review, the most appropriate information dimensions were identified. To validate the multidimensional tool, survey data were obtained from 284 chief financial officers of Portuguese small- and medium-sized enterprises (SMEs). A structural equation model, evaluating the influence on the managerial performance, was used to verify the nomological validity of this new construct.FindingsThe results of this study suggest that the effectiveness of management accounting systems can be measured using a second-order construct. This construct includes 14 items, covering four dimensions of the management information characteristics.Research limitations/implicationsAlthough contributing to the advancement of knowledge, it is, however, limited to the Portuguese organizational environment and culture. Therefore, further studies should be carried out in other organizational contexts and cultures, to test and validate this multidimensional tool.Practical implicationsThe multidimensional tool presented and validated in this study can be used by executives of SMEs for assessing the effectiveness of their management accounting systems, which can help to improve SMEs' performance measurement and benchmarking processes.Originality/valueOn the best of our knowledge, this is the first study wherein the management accounting system is modeled as a second-order construct from the perspective of multidimensional information characteristics. This second-order approach recognizes the contribution and retains the distinctive nature of each first-order construct, representing the management accounting system. This multidimensional construct could be very important for future research by allowing to capture synergies resulting from the balanced development of its four information dimensions, and consequently, offer new contributions to management accounting knowledge.

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Kulbok, Pamela A., Kimberly F. Carter, Joan H. Baldwin, Mattia J. Gilmartin, and Bessie Kirkwood. "The Multidimensional Health Behavior Inventory." Journal of Nursing Measurement 7, no. 2 (January 1999): 177–95. http://dx.doi.org/10.1891/1061-3749.7.2.177.

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Gaps in knowledge about what constitutes healthy and risky behaviors for young people hinder successful health promotion intervention strategies. With the development of appropriate instruments, behaviors can be measured and interventions can be implemented to improve health outcomes. The structure of a new health behavior instrument, the Multidimensional Health Behavior Inventory (MHBI), was explored with data from 1,077 college students, ages 18 to 24 years. Factor analysis of 116 health behavior questions yielded 7 factor-based scales with 57 items: diet (13 items), substance use (10 items), safety (9 items), checkup (9 items), social (6 items), stress (6 items), and exercise (4 items). Evaluation of the 7 behavior scales of the MHBI using subgroups defined by age, gender, and race will contribute to an understanding of health behaviors of older adolescents and young adults and will provide directions for research and clinical interventions.

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Melnikas, Borisas. "THE GLOBAL CHANGES: CREATING KNOWLEDGE-BASED SOCIETY AND KNOWLEDGE ECONOMY." Ekonomika 90, no. 3 (January 1, 2011): 7–25. http://dx.doi.org/10.15388/ekon.2011.0.938.

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The processes of creating knowledge-based society and knowledge economy in the context of global changes are described. A variety of global changes and the main processes of creating knowledge-based society and knowledge economy in the context of globalization are identified. The processes of creating knowledge-based society and knowledge economy are defined as the processes belonging to the category of global transformation processes; it means that the complex interaction between the general processes of global transformations and the processes of creating knowledge-based society and knowledge economy are a very important factor of positive changes in social life in the context of globalization. A complex analysis and the multidimensional evaluation of the processes of global transformations and of creating knowledge-based society and knowledge economy as a promising theoretical approach in research of social changes in the context of globalization is carried out. The main ideas of the complex analysis and of the evaluation of the factors of interaction between the general processes of global transformations and the processes of creating knowledge-based society and knowledge economy are analyzed.

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Albers, Michael J. "Multidimensional Audience Analysis for Dynamic Information." Journal of Technical Writing and Communication 33, no. 3 (July 2003): 263–79. http://dx.doi.org/10.2190/6kjn-95qv-jmd3-e5ee.

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As technical communication gains the technology to deliver dynamic custom documents, the importance of audience analysis increases. As a major factor in supporting dynamic adjustment of document content, the audience analysis must clearly capture the range of user goals and information needs in a flexible manner. Replacing a linear audience analysis model with a multidimensional model provides one method of achieving that flexibility. With a minimum of three separate dimensions to capture topic knowledge, detail required, and user cognitive ability, this model provides the writer a means of connecting content with information requirements and ensuring the dynamic document fits varying audience needs.

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Li, Guohua, An Liu, and Huajie Shen. "A Massive Image Recognition Algorithm Based on Attribute Modelling and Knowledge Acquisition." Advances in Mathematical Physics 2021 (November 24, 2021): 1–12. http://dx.doi.org/10.1155/2021/4632070.

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In this paper, an in-depth study and analysis of attribute modelling and knowledge acquisition of massive images are conducted using image recognition. For the complexity of association relationships between attributes of incomplete data, a single-output subnetwork modelling method for incomplete data is proposed to build a neural network model with each missing attribute as output alone and other attributes as input in turn, and the network structure can deeply portray the association relationships between each attribute and other attributes. To address the problem of incomplete model inputs due to the presence of missing values, we propose to treat and describe the missing values as system-level variables and realize the alternate update of network parameters and dynamic filling of missing values through iterative learning among subnets. The method can effectively utilize the information of all the present attribute values in incomplete data, and the obtained subnetwork population model is a fit to the attribute association relationships implied by all the present attribute values in incomplete data. The strengths and weaknesses of existing image semantic modelling algorithms are analysed. To reduce the workload of manually labelling data, this paper proposes the use of a streaming learning algorithm to automatically pass image-level semantic labels to pixel regions of an image, where the algorithm does not need to rely on external detectors and a priori knowledge of the dataset. Then, an efficient deep neural network mapping algorithm is designed and implemented for the microprocessing architecture and software programming framework of this edge processor, and a layout scheme is proposed to place the input feature maps outside the kernel DDR and the reordered convolutional kernel matrices inside the kernel storage body and to design corresponding efficient vectorization algorithms for the multidimensional matrix convolution computation, multidimensional pooling computation, local linear normalization, etc., which exist in the deep convolutional neural network model. The efficient vectorized mapping scheme is designed for the multidimensional matrix convolution computation, multidimensional pooling computation, local linear normalization, etc. in the deep convolutional neural network model so that the utilization of MAC components in the core loop can reach 100%.

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Van den Heuvel, Charles, and Richard P. Smiraglia. "Likeness and Likeliness: Exploring Multidimensional Classification for the Multiverse of Information." Advances in Classification Research Online 23, no. 1 (January 30, 2013): 35. http://dx.doi.org/10.7152/acro.v23i1.14235.

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In previous studies grouped under the common denominator “Idea Collider,” the CERN Hadron-Collider was used as a metaphor to explore the meaning of breaking down existing structured and less-structured clusters of information into the finest particles to get a better understanding of the laws and nature of the universe of knowledge (Heuvel and Smiraglia, 2010). Moreover we compared past conceptualizations and visualizations of multidimensional classifications, in particular of faceted systems, and tried to assess their potential for future information retrieval (Heuvel 2011; Heuvel and Akdag Salah, 2011). Where most classification theories focused on knowledge integration in a single universe of knowledge, we outlined the framework of an elementary theory of knowledge interaction in a multiverse of knowledge (Smiraglia, Heuvel and Dousa 2011). We believe that similar to the real universe, not only matter, but also energy and gravitational forces are of importance for understanding the multiverse of information better. For that reason we want to elaborate on the question of how one perceives and interacts with knowledge production.

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Journal articles on the topic 'Multidimensional knowledge'

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