Rule acquisition in formal decision contexts based on formal, object-oriented and property-oriented concept lattices.
Ontology highlight
ABSTRACT:
SUBMITTER: Ren Y
PROVIDER: S-EPMC4137553 | biostudies-other | 2014
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Three-way concept analysis (3WCA) is extended research of formal concept analysis (FCA) by combining three-way decision. The three-way object oriented concept lattice (OEOL) is one of the important data structures which integrates rough set, concept lattice and three-way decision in 3WCA. In the paper, we investigate the characteristics of formal context based on the isomorphic relationship among the kinds of concept lattices with OEOL. Firstly, II-dual intersectable attributes and II-dual intersectable context are proposed and the relationship between the type I-dual intersectable context(dual intersectable context) and the type II-dual intersectable context are studied. In addition, the relationship among the kinds of concept lattices with OEOL are studied when the formal context is both I-dual intersectable context and II-dual intersectable context. Finally, the inverse problems of the above conclusions are discussed and the following two conclusions are obtained: (1) the formal context is the type II-dual intersectable context, when the object oriented concept lattice and OEOL are isomorphic. (2) In addition, the formal context is the type I-dual intersectable context, when the concept lattice and OEOL are anti-isomorphic.
| S-EPMC8625367 | biostudies-literature
Project description:Persistent homology provides a new approach for the topological simplification of big data via measuring the life time of intrinsic topological features in a filtration process and has found its success in scientific and engineering applications. However, such a success is essentially limited to qualitative data classification and analysis. Indeed, persistent homology has rarely been employed for quantitative modeling and prediction. Additionally, the present persistent homology is a passive tool, rather than a proactive technique, for classification and analysis. In this work, we outline a general protocol to construct object-oriented persistent homology methods. By means of differential geometry theory of surfaces, we construct an objective functional, namely, a surface free energy defined on the data of interest. The minimization of the objective functional leads to a Laplace-Beltrami operator which generates a multiscale representation of the initial data and offers an objective oriented filtration process. The resulting differential geometry based object-oriented persistent homology is able to preserve desirable geometric features in the evolutionary filtration and enhances the corresponding topological persistence. The cubical complex based homology algorithm is employed in the present work to be compatible with the Cartesian representation of the Laplace-Beltrami flow. The proposed Laplace-Beltrami flow based persistent homology method is extensively validated. The consistence between Laplace-Beltrami flow based filtration and Euclidean distance based filtration is confirmed on the Vietoris-Rips complex for a large amount of numerical tests. The convergence and reliability of the present Laplace-Beltrami flow based cubical complex filtration approach are analyzed over various spatial and temporal mesh sizes. The Laplace-Beltrami flow based persistent homology approach is utilized to study the intrinsic topology of proteins and fullerene molecules. Based on a quantitative model which correlates the topological persistence of fullerene central cavity with the total curvature energy of the fullerene structure, the proposed method is used for the prediction of fullerene isomer stability. The efficiency and robustness of the present method are verified by more than 500 fullerene molecules. It is shown that the proposed persistent homology based quantitative model offers good predictions of total curvature energies for ten types of fullerene isomers. The present work offers the first example to design object-oriented persistent homology to enhance or preserve desirable features in the original data during the filtration process and then automatically detect or extract the corresponding topological traits from the data.
| S-EPMC4685963 | biostudies-literature
Project description:PurposeAll methods presented to date to map both conductivity and permittivity rely on multiple acquisitions to compute quantitatively the magnitude of radiofrequency transmit fields, B1+. In this work, we propose a method to compute both conductivity and permittivity based solely on relative receive coil sensitivities ( B1-) that can be obtained in one single measurement without the need to neither explicitly perform transmit/receive phase separation nor make assumptions regarding those phases.Theory and methodsTo demonstrate the validity and the noise sensitivity of our method we used electromagnetic finite differences simulations of a 16-channel transceiver array. To experimentally validate our methodology at 7 Tesla, multi compartment phantom data was acquired using a standard 32-channel receive coil system and two-dimensional (2D) and 3D gradient echo acquisition. The reconstructed electric properties were correlated to those measured using dielectric probes.ResultsThe method was demonstrated both in simulations and in phantom data with correlations to both the modeled and bench measurements being close to identity. The noise properties were modeled and understood.ConclusionThe proposed methodology allows to quantitatively determine the electrical properties of a sample using any MR contrast, with the only constraint being the need to have 4 or more receive coils and high SNR. Magn Reson Med 74:185-195, 2015. © 2014 Wiley Periodicals, Inc.
| S-EPMC4458244 | biostudies-literature
Project description:Three-way concept analysis is a newly proposed area of formal concept analysis from which one can obtain both the inclusion decision and the exclusion decision. In general, given a context, some attributes may not be essential in three-way concept analysis, such as forming three-way concept lattice. So in this paper, we study the attribute reductions of three-way concept lattices in order to make the data easily be understood. Firstly, based on different criteria generated from object-induced three-way concept (OE-concept), four kinds of attribute reductions are proposed. The four reductions together embody different characteristics of a formal context and can be used in different occasions. Secondly, we discuss their relationships, including their advantages and disadvantages and the relationships among consistent sets and among the cores. Thirdly, based on attribute-induced three-way concept (AE-concept), we also give four attribute-induced three-way attribute reductions and discuss their relationships. Finally, the approaches to computing these attribute reductions are presented and the obtained results are demonstrated and verified by an empirical case. In this paper, we systematically investigate the attribute reductions of three-way concept lattices which enriches the study of formal concept analysis.
| S-EPMC7126604 | biostudies-literature
Project description:Pangenome analysis is fundamental to explore molecular evolution occurring in bacterial populations. Here, we introduce Pagoo, an R framework that enables straightforward handling of pangenome data. The encapsulated nature of Pagoo allows the storage of complex molecular and phenotypic information using an object-oriented approach. This facilitates to go back and forward to the data using a single programming environment and saving any stage of analysis (including the raw data) in a single file, making it sharable and reproducible. Pagoo provides tools to query, subset, compare, visualize, and perform statistical analyses, in concert with other microbial genomics packages available in the R ecosystem. As working examples, we used 1,000 Escherichia coli genomes to show that Pagoo is scalable, and a global dataset of Campylobacter fetus genomes to identify evolutionary patterns and genomic markers of host-adaptation in this pathogen.
| S-EPMC9017228 | biostudies-literature
Project description:The coupling of membrane-bound receptors to transcriptional regulators and other effector functions is mediated by multi-domain proteins that form complex assemblies. The modularity of protein interactions lends itself to a rule-based description, in which species and reactions are generated by rules that encode the necessary context for an interaction to occur, but also can produce a combinatorial explosion in the number of chemical species that make up the signalling network. The authors have shown previously that exact network reduction can be achieved using hierarchical control relationships between sites/domains on proteins to dissect multi-domain proteins into sets of non-interacting sites, allowing the replacement of each 'full' (progenitor) protein with a set of derived auxiliary (offspring) proteins. The description of a network in terms of auxiliary proteins that have fewer sites than progenitor proteins often greatly reduces network size. The authors describe here a method for automating domain-oriented model reduction and its implementation as a module in the BioNetGen modelling package. It takes as input a standard BioNetGen model and automatically performs the following steps: 1) detecting the hierarchical control relationships between sites; 2) building up the auxiliary proteins; 3) generating a raw reduced model and 4) cleaning up the raw model to provide the correct mass balance for each chemical species in the reduced network. The authors tested the performance of this module on models representing portions of growth factor receptor and immunoreceptor-mediated signalling networks and confirmed its ability to reduce the model size and simulation cost by at least one or two orders of magnitude. Limitations of the current algorithm include the inability to reduce models based on implicit site dependencies or heterodimerisation and loss of accuracy when dynamics are computed stochastically.
| S-EPMC2628550 | biostudies-literature
Project description:Transmission electron microscopy and associated methods, such as single particle analysis, two-dimensional crystallography, helical reconstruction, and tomography, are highly data-intensive experimental sciences, which also have substantial variability in experimental technique. Object-oriented databases present an attractive alternative to traditional relational databases for situations where the experiments themselves are continually evolving. We present EMEN2, an easy to use object-oriented database with a highly flexible infrastructure originally targeted for transmission electron microscopy and tomography, which has been extended to be adaptable for use in virtually any experimental science. It is a pure object-oriented database designed for easy adoption in diverse laboratory environments and does not require professional database administration. It includes a full featured, dynamic web interface in addition to APIs for programmatic access. EMEN2 installations currently support roughly 800 scientists worldwide with over 1/2 million experimental records and over 20 TB of experimental data. The software is freely available with complete source.
| S-EPMC3907281 | biostudies-literature
Project description:To make the human-robot collaboration effective, it may be necessary to provide robots with "senses" like vision and hearing. Task-oriented man-machine speech communication often relies on the use of abstract terms to describe objects. Therefore it is necessary to correctly map those terms into images of proper objects in a camera's field of view. This paper presents the results of our research in this field. A novel method for contour identification, based on flexible editable contour templates (FECT), has been developed. We demonstrate that existing methods are not appropriate for this purpose because it is difficult to formulate general rules that humans employ to rank shapes into proper classes. Therefore, the rules for shape classification should be individually formulated by the users for each application. Our aim was to create appropriate tool facilitating formulation of those rules as it could potentially be a very labor-intensive task. The core of our solution is FCD (flexible contour description) format for description of flexible templates. Users will be able to create and edit flexible contour templates, and thus, adjust image recognition systems to their needs, in order to provide task-oriented communication between humans and robots.
| S-EPMC7147712 | biostudies-literature
Project description:Additively manufactured lattices are emerging as promising candidates for structural, thermal, chemical, and biological applications. However, achieving a satisfactory prototype or final part with this level of complexity requires synthesis of disparate knowledge from the distinctly digital and physical processing stages. This work proposes an integrated framework for processing self-supporting, open lattice structures that do not require supports and facilitate material removal in post-processing steps. We describe a minimal yet comprehensive design strategy for generating uniform lattice structures with conformal open lattice skins for an arbitrary unit cell configuration. Using continuous liquid interface production (CLIP™) on a Carbon M1, printability is evaluated for five unique bending-dominated lattice structures at unit cell length scales from 0.5 - 3.5 mm and strut diameters ranging from 0.11 - 1.05 mm. Using a cubic lattice as a basis, we further examine dimensional fidelity with respect to 2D lattice void dimensions and part position, finding differences between length scales and within parts, due to physical processing artifacts. Finally, we demonstrate a functional grading strategy based on process control methods to compensate for dimensional deviations. Using an iterative approach based on a naïve process model, deviation of the planar strut radius in a cubic lattice was decreased by approximately 85% after two iterations. These insights and strategies can be readily applied to other structures, characterization techniques, and additive manufacturing processes, thereby improving the exchange of information between digital and physical processing and lowering the energy barriers to producing high-quality lattice parts.
| S-EPMC8570538 | biostudies-literature
Project description:Hamilton’s rule [W. D. Hamilton, Am. Nat. 97, 354–356 (1963); W. D. Hamilton, J. Theor. Biol. 7, 17–52 (1964)] quantifies the central evolutionary ideas of inclusive fitness and kin selection into a simple algebraic relationship. Evidence consistent with Hamilton’s rule is found in many animal species. A drawback of investigating Hamilton’s rule in these species is that one can estimate whether a given behavior is consistent with the rule, but a direct examination of the exact cutoff for altruistic behavior predicted by Hamilton is almost impossible. However, to the degree that economic resources confer survival benefits in modern society, Hamilton’s rule may be applicable to economic decision-making, in which case techniques from experimental economics offer a way to determine this cutoff. We employ these techniques to examine whether Hamilton’s rule holds in human decision-making, by measuring the dependence between an experimental subject’s maximal willingness to pay for a gift of $50 to be given to someone else and the genetic relatedness of the subject to the gift’s recipient. We find good agreement with the predictions of Hamilton’s rule. Moreover, regression analysis of the willingness to pay versus genetic relatedness, the number of years living in the same residence, age, and sex shows that almost all the variation is explained by genetic relatedness. Similar but weaker results are obtained from hypothetical questions regarding the maximal risk to her own life that the subject is willing to take in order to save the recipient’s life.
| S-EPMC9169854 | biostudies-literature