Relevant bibliographies by topics / The principle of dissimilarity

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'The principle of dissimilarity'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "The principle of dissimilarity"

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Sisodia, Dilip Singh, Shrish Verma, and Om Prakash Vyas. "Augmented intuitive dissimilarity metric for clustering of Web user sessions." Journal of Information Science 43, no. 4 (2016): 480–91. http://dx.doi.org/10.1177/0165551516648259.

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Clustering is a very useful technique to categorise Web users with common browsing activities, access patterns and navigational behaviour. Web user clustering is used to build Web visitor profiles that make the core of a personalised information recommender system. These systems are used to comprehend Web users surfing activities by offering tailored content to Web users with similar interests. The principle objective of Web user sessions clustering is to maximise the intra-group while minimising the inter-group similarity. Efficient clustering of Web users’ sessions not only depend on the clu
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Eom, Taemin. "Judging the Similarity or Dissimilarity of Marks, and Principle of Considering ‘Sound’ Foremost: With focus on Supreme Court ruling 2020Hu10957(ruled on Dec. 30, 2020)." LAW RESEARCH INSTITUTE CHUNGBUK NATIONAL UNIVERSITY 14, no. 2 (2023): 105–41. http://dx.doi.org/10.34267/cbstl.2023.14.2.105.

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This article intends to contribute to the examination of recent controversial ruling (2020Hu10957, ruled on Dec. 30, 2020) by the Supreme Court on judging the similarity or dissimilarity of Word Marks (“ ” vs. “ ”). Specifically, concerning the presented question whether the filed mark “ ” is confusingly similar to the registered mark “ ”, the Supreme Court held that there is no likelihood of confusion, mistake among the consumers because the two marks are sufficiently dissimilar in their appearance while acknowledging the auditory similarity of the two marks. The article proposes that the pri
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Polpoke, Siti Maharani, Asri Subkhan Mahulette, and Marthini Kristina Lesilolo. "Morphological Characterization of Local Jinten Cloves (Syzygium aromaticum (L.) Merr. & L. M. Perry) in Wakasihu Village, West Leihitu District, Central Maluku Regency." Jurnal Agrohut 15, no. 1 (2024): 38–46. http://dx.doi.org/10.51135/agh.v15i1.310.

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Clove jinten are one of the local cloves cultivated in Wakasihu Village, West Leihitu District, Central Maluku Regency. Until now, there has not been much information about various studies related to the morphology of cloves Jinten. The research aims to analyze the morphological characters of local cloves jinten and identify the plant's descriptor characters. The research was carried out in Wakasihu Village, West Leihitu District, Central Maluku Regency, Maluku Province in January - May 2024. The research results based on Hierarchical Cluster Analysis (HCA) showed two large groups with a dissi
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Raghavendra, Pujari, and M. R. Sajjanashetti* Dr. "A RANDOMISED CLINICAL STUDY TO EVALUATE DRAVYA SAMANYA SIDDHANT W.S.R AJAMAMSA WEIGHT GAIN." World Journal of Pharmaceutical Science and Research 3, no. 3 (2024): 171–75. https://doi.org/10.5281/zenodo.12630634.

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Ayurveda is holistic science that works for healthy, wealthy and happy life. The wisdom of Ayurveda based on various theories and principles. The concept of “Samanya Vishesh Siddhanta” is one such basic principle of Ayurveda which helps to treat diseases. Samanya means similarity and Vishesh means dissimilarity, using this concept of similarity and dissimilarity many diseases can be cured effectively. Disease mainly arises due to the disturbance in equilibrium of Dosha, Dhatu, Mala and Agni, etc. The balance of these biological entities can be established using Dravyas possessing s
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Nija Chacko. "A comprehensive view on the applicability of Samanya - Vishesha Siddhanta." Journal of Ayurveda and Integrated Medical Sciences 9, no. 12 (2025): 193–98. https://doi.org/10.21760/jaims.9.12.24.

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Ayurveda is the science of life that focusses on both prevention and cure of diseases. Its wisdom is rooted in various theories and principles, among which Samanya-Vishesha Siddhanta is fundamental. Samanya refers to similarity, while Vishesha denotes dissimilarity; by applying this principle, Ayurveda effectively cures many ailments through the balance of similar and opposing qualities. Some factors deficient in body corrected by substituting with substances similar in character (Samanya). Some factors excess in body, reduced by supplying dissimilar substance [Vishesha]. Thus, specific Dravya
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Namakule, Mirda Yanti, Asri Subkhan Mahulette, and Avia Jolanda Matatula. "Keragaman Morfologi Cengkih Tuni (Syzygium Aromaticum L.) Di Kecamatan Tehoru, Kabupaten Maluku Tengah, Provinsi Maluku." Agro Wiralodra 7, no. 1 (2024): 1–7. http://dx.doi.org/10.31943/agrowiralodra.v7i1.103.

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Clove Tuni is a superior local clove variety from Maluku, widely cultivated in Tehoru District, Central Maluku Regency. Until now, information on morphological diversity in Tuni clove populations in the region is still limited. This study aimed to inform the morphological diversity of Tuni cloves and their morphological characteristics. The research was conducted in three villages in Tehoru District, Central Maluku Regency: Haya, Tehoru, and Yaputih Villages. The clove plants characterized were >20 years old, where ten plant samples were taken from each village, so there were 30 plants. Hie
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Al-Jubouri, Hanan, and Hongbo Du. "A Content-Based Image Retrieval Method By Exploiting Cluster Shapes." Iraqi Journal for Electrical and Electronic Engineering 14, no. 2 (2018): 90–102. http://dx.doi.org/10.37917/ijeee.14.2.1.

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Content-Based Image Retrieval (CBIR) is an automatic process of retrieving images that are the most similar to a query image based on their visual content such as colour and texture features. However, CBIR faces the technical challenge known as the semantic gap between high level conceptual meaning and the low-level image based features. This paper presents a new method that addresses the semantic gap issue by exploiting cluster shapes. The method first extracts local colours and textures using Discrete Cosine Transform (DCT) coefficients. The Expectation-Maximization Gaussian Mixture Model (E
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S. Dande, Bhavana, and Shwetambari Sunil Bidgar. "CONCEPTOF SAMANYA-VISHESHA SIDDHANT & ITS ROLE IN DIFFERENT FIELD OF AYURVEDIC CHIKISTA." International Journal of Advanced Research 12, no. 09 (2024): 449–52. http://dx.doi.org/10.21474/ijar01/19474.

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Ayurveda, a holistic system of medicine originating in India, emphasizes the equilibrium of tridoshas, saptdhatus, and other essential entities for holistic health. The Samanya -Vishesha Siddhanta, a fundamental principle, provide insights into the alteration of qualities and quantities of Bhavpadarth, contributing to diagnosis and treatment. The term Samanya means similarity or oneness or uniformity or the one which causes increase in substance. While theterm Vishesha means dissimilarity or separateness or non-uniformity or the one which causes decrease in substance.
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Tanioka, Kensuke, and Hiroshi Yadohisa. "Unfolding Models for Asymmetric Dissimilarity Data With External Information Based on Path Structures." International Journal of Software Innovation 6, no. 3 (2018): 53–66. http://dx.doi.org/10.4018/ijsi.2018070104.

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This article contains asymmetric dissimilarity data which is observed in various situations. In asymmetric dissimilarity data, dissimilarity from subject i to j and from subject j to i are not the same necessarily. Asymmetric multidimensional scaling (AMDS) is a visualization method for describing the asymmetric relations between subjects, given asymmetric dissimilarity data for subjects. It is sure that AMDS is a useful tool for interpreting the asymmetric relation, however, existing AMDS cannot be considered for the external information, even if the external information of the same subjects
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Harris, Richard, and Dewi Owen. "Implementing a Multilevel Index of Dissimilarity in R with a case study of the changing scales of residential ethnic segregation in England and Wales." Environment and Planning B: Urban Analytics and City Science 45, no. 6 (2017): 1003–21. http://dx.doi.org/10.1177/2399808317748328.

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This paper introduces the Multilevel Index of Dissimilarity package, which provides tools and functions to fit a Multilevel Index of Dissimilarity in the open source software, R. It extends the conventional Index of Dissimilarity to measure both the amount and geographic scale of segregation, thereby capturing the two principal dimensions of segregation, unevenness and clustering. The statistical basis for the multilevel approach is discussed, making connections to other work in the field and looking especially at the relationships between the Index of Dissimilarity, variance as a measure of s
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Dissertations / Theses on the topic "The principle of dissimilarity"

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Ben, Henia Ouissem. "Suivi des mouvements de la main et reproduction de gestes à partir de séquences vidéo monoculaires." Thesis, Lyon 1, 2012. http://www.theses.fr/2012LYO10046.

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Les gestes de la main représentent un moyen naturel et intuitif de communication chez l'homme lui permettant d'interagir avec son environnement dans la vie de tous les jours. Ils permettent notamment de ponctuer et de renforcer l'expression orale d'un dialogue entre personnes. Outre la communication entre individus, les gestes de la main permettent de manipuler des objets ou encore d'interagir avec des machines. Avec le développement de la vision par ordinateur, on assiste à un véritable engouement pour de nouveaux types d'interactions qui exploitent le mouvement de la main et qui passent par
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Zhu, Xibin [Verfasser]. "Adaptive prototype-based dissimilarity learning / Xibin Zhu." Bielefeld : Universitätsbibliothek Bielefeld, 2015. http://d-nb.info/1072224704/34.

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Ortiz-Reynoso, Alejandra. "Perceiving similarity and dissimilarity in diverse teams." Thesis, University of Sheffield, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.422641.

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Xu, Weiping. "Non-Euclidean dissimilarity data in pattern recognition." Thesis, University of York, 2012. http://etheses.whiterose.ac.uk/3848/.

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This thesis addresses problems in dissimilarity (proximity) learning, particularly focusing on identifying the sources and rectifying the non-Euclidean dissimilarity in pattern recog- nition. We aim to develop a framework for analyzing the non-Euclidean dissimilarity by combining the methods from differential geometry and manifold learning theory. The algorithms are applied to objects represented by the dissimilarity measures. In Chapter 3 we describe how to reveal the origins of the non-Euclidean behaviors of the dissimilarity matrix for the purpose of rectifying the dissimilarities. We com-
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Cejnog, Luciano Walenty Xavier. "Rigid registration based on local geometric dissimilarity." Universidade Federal de Juiz de Fora (UFJF), 2015. https://repositorio.ufjf.br/jspui/handle/ufjf/4882.

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Deneuve, Emeline. "Three essays on key audit matters dissimilarity." Electronic Thesis or Diss., Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales, 2023. http://www.theses.fr/2023ESEC0002.

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Ma thèse se compose de trois essais rapportés dans trois chapitres différents, chacun lié à une question de recherche différente sur la section des Key Audit Matters (KAMs, en français, points clés d’audit) dans les rapports d’audit. Les KAMs ont été mis en oeuvre afin d’accroître la valeur communicative des rapports d’audit et la confiance de ses utilisateurs dans le processus d’audit et les états financiers des sociétés (EY Reporting, 2015). Les KAMs reflètent les plus grands risques d’anomalies significatives rencontrés au cours du processus d’audit, sur la base du jugement professionnel de
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Mokbel, Bassam [Verfasser]. "Dissimilarity-based learning for complex data / Bassam Mokbel." Bielefeld : Universitätsbibliothek Bielefeld, 2016. http://d-nb.info/1082033952/34.

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Gisbrecht, Andrej [Verfasser]. "Advances in dissimilarity-based data visualisation / Andrej Gisbrecht." Bielefeld : Universitätsbibliothek Bielefeld, 2015. http://d-nb.info/1068621729/34.

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Hasenfuß, Alexander [Verfasser]. "Topographic mapping of dissimilarity datasets / vorgelegt von Alexander Hasenfuß." [Clausthal-Zellerfeld] : [Univ.-Bibliothek], 2009. http://d-nb.info/997448334/34.

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Chan, Yat-ling, and 陳逸靈. "An optimization algorithm for clustering using weighted dissimilarity measures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B26667009.

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Books on the topic "The principle of dissimilarity"

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Van Cutsem, Bernard, ed. Classification and Dissimilarity Analysis. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2686-4.

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1932-, Cutsem Bernard van, ed. Classification and dissimilarity analysis. Springer-Verlag, 1994.

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Shklovskiǐ, Viktor Borisovich. Bowstring: On the dissimilarity of the similar. Dalkey Archive Press, 2011.

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Günes, M., D. G. Reina, J. M. Garcia Campos, and S. L. Toral. Mobile Ad Hoc Network Protocols Based on Dissimilarity Metrics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62740-3.

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W, Duin Robert P., ed. The dissimilarity representation for pattern recognition: Foundations and applications. World Scientific, 2005.

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Padmore, Joanne. An information based measure of dissimilarity for hierarchical cluster analysis. Sheffield University Management School, 1993.

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McGavin, John J. Chaucer and dissimilarity: Literary comparisons in Chaucer and other late-medieval writing. Fairleigh Dickinson University Presses, 2000.

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Scotus, John Duns. First principle. Revelation-Insight Pub. Co., 2008.

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Lang, Gerald. Strokes of Luck. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198868507.001.0001.

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Strokes of Luck offers a large-scale treatment of the role of luck in our judgements about blameworthiness and responsibility, in moral philosophy, and in principles of distributive justice, in political philosophy. It takes an ‘anti-anti-luckist’ stance on these matters, and is opposed to the influential ‘anti-luckist’ views which hold that judgements of blameworthiness, or distributive relations, should be adjusted to annul or neutralize differential luck. It provides a new reading of Bernard Williams’s famous essay ‘Moral Luck’ which emphasizes the dissimilarity of Williams’s aims from the
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Silber, Jacques. Inequality, Dissimilarity and Independence. Cambridge University Press, 2005.

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Book chapters on the topic "The principle of dissimilarity"

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Critchley, Frank, and Bernard Fichet. "The partial order by inclusion of the principal classes of dissimilarity on a finite set, and some of their basic properties." In Classification and Dissimilarity Analysis. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2686-4_2.

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Sato-Ilic, Mika. "Dissimilarity Based Principal Component Analysis Using Fuzzy Clustering." In Advances in Intelligent and Soft Computing. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11960-6_42.

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Grosser, David, Jean Diatta, and Noël Conruyt. "Improving Dissimilarity Functions with Domain Knowledge, applications with IKBS system." In Principles of Data Mining and Knowledge Discovery. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45372-5_44.

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Meghanathan, Natarajan. "Principal Components-Based Node Dissimilarity Index for Complex Network Analysis." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54813-0_35.

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Güneş, M., D. G. Reina, J. M. Garcia Campos, and S. L. Toral. "Dissimilarity Metrics." In SpringerBriefs in Electrical and Computer Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-62740-3_4.

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Pawlak, Zdzisław. "Dissimilarity Analysis." In Rough Sets. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3534-4_10.

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Fernande, Kenrick, Pedram Gharani, and Vineet Raghu. "TRAJEDI: Trajectory Dissimilarity." In Studies in Systems, Decision and Control. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98923-5_8.

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Rubner, Yossi, and Carlo Tomasi. "Comparing Dissimilarity Measures." In Perceptual Metrics for Image Database Navigation. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3343-3_5.

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Esposito, F., D. Malerba, V. Tamma, and H. H. Bock. "Similarity and Dissimilarity." In Analysis of Symbolic Data. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57155-8_8.

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Rubner, Yossi, and Carlo Tomasi. "Distribution-Based Dissimilarity Measures." In Perceptual Metrics for Image Database Navigation. Springer US, 2001. http://dx.doi.org/10.1007/978-1-4757-3343-3_1.

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Conference papers on the topic "The principle of dissimilarity"

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Costanzi, Gabriel Henrique, Lucas O. Teixeira, Gustavo Z. Felipe, George D. C. Cavalcanti, and Yandre M. G. Costa. "Music Genre Classification Using Contrastive Dissimilarity." In 2024 31st International Conference on Systems, Signals and Image Processing (IWSSIP). IEEE, 2024. http://dx.doi.org/10.1109/iwssip62407.2024.10634017.

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Shen, Xinyue, Yuchen Jiao, and Yuantao Gu. "SUBSPACE DATA VISUALIZATION WITH DISSIMILARITY BASED ON PRINCIPAL ANGLE." In 2018 IEEE Data Science Workshop (DSW). IEEE, 2018. http://dx.doi.org/10.1109/dsw.2018.8439916.

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Hijikata-Okunomiya, A., S. Okamoto, R. Kikumoto, and Y. Tamao. "STEREOGEOMETRY OP THE ACTIVE SITES OF SERINE ENZYMES GATHERED FROM SYNTHETIC THROMBIN-INHIBITORS." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1644606.

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MD-805 is a potent thrombin-inhibitor having the structure of tri-pods; Arg skeletone, N-terminal side and C-terminal side. MD-805 showed weaker inhibitory activity to other enzymes than thrombin. In this report, to gather more detailed informations about the structural features of serine enzymes concerning the specificity, we experimentally examined the structure-activity relationship (SAR) of a number of arginine derivatives including MD-805 and theoretically generated a MD-805-trypsin complex model using the results of X-ray crystallography of MD-805 and BPTI-trypsin complex by calculation
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Yavari, Vahid, Farshad Daneshvar, Mohammad-Hassan Kadivar, and Iraj Rajabi. "Design Parameters Effect on Load Distribution Around the Hole in Mechanically Fastened Pinned Connections." In ASME 2008 Pressure Vessels and Piping Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/pvp2008-61021.

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The pinned connection is a principal joining element in many structures. In this article, we present two-dimensional stress analyses for isotropic plate with a pinned circular hole. A study of the pin and the plate material dissimilarity was done by Iyer [6] but still different aspects of the problem are remained to be mentioned. In this work different issues of mechanical engineering interests such as stress distribution in contact area and the magnitude and location of maximum contact pressure and tangential stress are computed with the aid of commercial software ABAQUS 6.6-1 finite element
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Aryal, Sunil, Kai Ming Ting, Gholamreza Haffari, and Takashi Washio. "Mp-Dissimilarity: A Data Dependent Dissimilarity Measure." In 2014 IEEE International Conference on Data Mining (ICDM). IEEE, 2014. http://dx.doi.org/10.1109/icdm.2014.33.

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Chitturi, Bhadrachalam, and K. S. Krishnaveni. "Expected genomic dissimilarity." In 2019 8th International Conference on Modeling Simulation and Applied Optimization (ICMSAO). IEEE, 2019. http://dx.doi.org/10.1109/icmsao.2019.8880405.

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Xu, Xiao, Qing Zhao, and Ananthram Swami. "Learning from Dissimilarity." In 2018 52nd Asilomar Conference on Signals, Systems, and Computers. IEEE, 2018. http://dx.doi.org/10.1109/acssc.2018.8645546.

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Bicego, Manuele. "Dissimilarity Random Forest Clustering." In 2020 IEEE International Conference on Data Mining (ICDM). IEEE, 2020. http://dx.doi.org/10.1109/icdm50108.2020.00105.

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Cooper, J., S. Venkatesh, and L. Kitchen. "The dissimilarity corner detector." In Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments. IEEE, 1991. http://dx.doi.org/10.1109/icar.1991.240450.

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Zhang, Weifeng, and Zengchang Qin. "Dissimilarity measure of logical expressions." In 2010 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2010. http://dx.doi.org/10.1109/icmlc.2010.5581066.

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Reports on the topic "The principle of dissimilarity"

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Bubacz, Jacob A., Hana T. Chmielewski, Alexander E. Pape, et al. Phase Space Dissimilarity Measures for Structural Health Monitoring. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1029952.

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Tsyvinski, Aleh, and Nicolas Werquin. Generalized Compensation Principle. National Bureau of Economic Research, 2017. http://dx.doi.org/10.3386/w23509.

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Schulz, Karl, Aleh Tsyvinski, and Nicolas Werquin. Generalized Compensation Principle. Federal Reserve Bank of Chicago, 2022. http://dx.doi.org/10.21033/wp-2022-18.

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Sternlieb, Abraham. A New Principle in Physiscs: the Principle "Finiteness", and Some Consequences. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/984346.

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Chaigneau, Pierre, Alex Edmans, and Daniel Gottlieb. The Generalized Informativeness Principle. National Bureau of Economic Research, 2014. http://dx.doi.org/10.3386/w20729.

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Davig, Troy, and Eric Leeper. Generalizing the Taylor Principle. National Bureau of Economic Research, 2005. http://dx.doi.org/10.3386/w11874.

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Benson, Alan, Danielle Li, and Kelly Shue. Promotions and the Peter Principle. National Bureau of Economic Research, 2018. http://dx.doi.org/10.3386/w24343.

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Overfelt, Michael L. Logistics: A Principle of War. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada293268.

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Kulifay, Bernard E. The Missing Principle of War. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada381622.

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Angeletos, George-Marios, and Chen Lian. Determinacy without the Taylor Principle. National Bureau of Economic Research, 2021. http://dx.doi.org/10.3386/w28881.

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