Knowledge Rules Research Articles

Semantic Enrichment for Building Information Modeling: Procedure for Compiling Inference Rules and Operators for Complex Geometry

Semantic enrichment of building models adds meaningful domain-specific or application-specific information to a digital building model. It is applicable to solving interoperability problems and to compilation of models from point cloud data. The SeeBIM (Semantic Enrichment Engine for BIM) prototype software encapsulates domain expert knowledge in computer readable rules for inference of object types, identity and aggregation of systems. However, it is limited to axis-aligned bounding box geometry and the adequacy of its rule-sets cannot be guaranteed. This paper solves these drawbacks by (1) devising a new procedure for compiling inference rule sets that are known a priori to be adequate for complete and thorough classification of model objects, and (2) enhancing the operators to compute complex geometry and enable precise topological rule processing. The procedure for compiling adequate rule sets is illustrated using a synthetic concrete highway bridge model. A real-world highway bridge model, with 333 components of 13 different types and compiled from a laser scanned point cloud, is used to validate the approach and test the enhanced SeeBIM system. All of the elements are classified correctly, demonstrating the efficacy of the approach to semantic enrichment.

Enhancing semantic consistency in anti-fraud rule-based expert systems

In this study, an ontology-driven approach is proposed for semantic conflict detection and classification in rule-based expert systems. It focuses on the critical case of anti-fraud rule repositories for the inspection of Card Not Present (CNP) transactions in e-commerce environments. The main motivation is to examine and curate anti-fraud rule datasets to avoid semantic conflicts that could lead the underpinning expert system to incorrectly perform, e. g., by accepting fraudulent transactions and/or by discarding harmless ones. The proposed approach is based on Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) technologies to develop an anti-fraud rule ontology and reasoning tasks, respectively. The three main contributions of this work are: first, the creation of a conceptual knowledge model for describing anti-fraud rules and their relationships; second, the development of semantic rules as conflict-resolution methods for anti-fraud expert systems; third, experimental facts are gathered to evaluate and validate the proposed model. A real-world use case in the e-commerce (e-Tourism) industry is used to explain the ontological knowledge design and its use. The experiments show that ontological approaches can effectively discover and classify conflicts in rule-based expert systems in the field of anti-fraud applications. The proposal is also applicable to other domains where knowledge rule bases are involved.

Multi-model-based interactive authoring environment for creating shareable medical knowledge

ObjectiveTechnologically integrated healthcare environments can be realized if physicians are encouraged to use smart systems for the creation and sharing of knowledge used in clinical decision support systems (CDSS). While CDSSs are heading toward smart environments, they lack support for abstraction of technology-oriented knowledge from physicians. Therefore, abstraction in the form of a user-friendly and flexible authoring environment is required in order for physicians to create shareable and interoperable knowledge for CDSS workflows. Our proposed system provides a user-friendly authoring environment to create Arden Syntax MLM (Medical Logic Module) as shareable knowledge rules for intelligent decision-making by CDSS. Methods and materialsExisting systems are not physician friendly and lack interoperability and shareability of knowledge. In this paper, we proposed Intelligent-Knowledge Authoring Tool (I-KAT), a knowledge authoring environment that overcomes the above mentioned limitations. Shareability is achieved by creating a knowledge base from MLMs using Arden Syntax. Interoperability is enhanced using standard data models and terminologies. However, creation of shareable and interoperable knowledge using Arden Syntax without abstraction increases complexity, which ultimately makes it difficult for physicians to use the authoring environment. Therefore, physician friendliness is provided by abstraction at the application layer to reduce complexity. This abstraction is regulated by mappings created between legacy system concepts, which are modeled as domain clinical model (DCM) and decision support standards such as virtual medical record (vMR) and Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT). We represent these mappings with a semantic reconciliation model (SRM). ResultsThe objective of the study is the creation of shareable and interoperable knowledge using a user-friendly and flexible I-KAT. Therefore we evaluated our system using completeness and user satisfaction criteria, which we assessed through the system- and user-centric evaluation processes. For system-centric evaluation, we compared the implementation of clinical information modelling system requirements in our proposed system and in existing systems. The results suggested that 82.05% of the requirements were fully supported, 7.69% were partially supported, and 10.25% were not supported by our system. In the existing systems, 35.89% of requirements were fully supported, 28.20% were partially supported, and 35.89% were not supported. For user-centric evaluation, the assessment criterion was ‘ease of use’. Our proposed system showed 15 times better results with respect to MLM creation time than the existing systems. Moreover, on average, the participants made only one error in MLM creation using our proposed system, but 13 errors per MLM using the existing systems. ConclusionWe provide a user-friendly authoring environment for creation of shareable and interoperable knowledge for CDSS to overcome knowledge acquisition complexity. The authoring environment uses state-of-the-art decision support-related clinical standards with increased ease of use.

Knowledge-guided consistent correlation analysis of multimode landslide monitoring data

ABSTRACTA novel method called knowledge-guided spatio-temporal consistent correlation analysis (KSTCCA) was developed to discover reliable deformation features induced by multiple factors based on multimode landslide monitoring data. Compared to conventional approaches, KSTCCA integrates both temporal and spatial correlation analysis to improve the consistency of deformation patterns and capture the spatio-temporal heterogeneities in multimode monitoring data. KSTCCA considers both the landslide deformation mechanisms and the relationships between different influential factors as knowledge. Moreover, the method extracts the morphological structures of monitoring curves based on a seven-point approach and identifies knowledge rules using the k-means clustering method. Under the guidance of prior knowledge, a spatial correlation analysis is conducted based on support vector regression, and a temporal correlation analysis of the time lag is carried out based on the morphological structure features. Finally, three kinds of typical monitoring data, including deformation, rainfall, and reservoir water level data collected in the Baishuihe landslide area, China, are used for experimental analysis to verify the validity of the proposed method.

Domain-specific languages in Prolog for declarative expert knowledge in rules and ontologies

Declarative if–then rules have proven very useful in many applications of expert systems. They can be managed in deductive databases and evaluated using the well-known forward-chaining approach. For domain-experts, however, the syntax of rules becomes complicated quickly, and already many different knowledge representation formalisms exist. Expert knowledge is often acquired in story form using interviews. In this paper, we discuss its representation by defining domain-specific languages (Dsls) for declarative expert rules. They can be embedded in Prolog systems in internal Dsls using term expansion and as external Dsls using definite clause grammars and quasi-quotations – for more sophisticated syntaxes.Based on the declarative rules and the integration with the Prolog-based deductive database system DDbase, multiple rules acquired in practical case studies can be combined, compared, graphically analysed by domain-experts, and evaluated, resulting in an extensible system for expert knowledge. As a result, the actual modeling Dsl becomes executable; the declarative forward-chaining evaluation of deductive databases can be understood by the domain experts. Our Dsl for rules can be further improved by integrating ontologies and rule annotations.

Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

This article presents a method of object-based image analysis (OBIA) for landslide delineation and landslide-related change detection from multi-temporal satellite images. It uses both spatial and spectral information on landslides, through spectral analysis, shape analysis, textural measurements using a gray-level co-occurrence matrix (GLCM), and fuzzy logic membership functionality. Following an initial segmentation step, particular combinations of various information layers were investigated to generate objects. This was achieved by applying multi-resolution segmentation to IRS-1D, SPOT-5, and ALOS satellite imagery in sequential steps of feature selection and object classification, and using slope and flow direction derivatives from a digital elevation model together with topographically-oriented gray level co-occurrence matrices. Fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data. Six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared. A Fuzzy Synthetic Evaluation (FSE) approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database. The FSE approach revealed that the AND operator performed best with an accuracy of 93.87% for 2005 and 94.74% for 2011, closely followed by the MEAN Arithmetic operator, while the OR and AND (*) operators yielded relatively low accuracies. An object-based change detection was then applied to monitor landslide-related changes that occurred in northern Iran between 2005 and 2011. Knowledge rules to detect possible landslide-related changes were developed by evaluating all possible landslide-related objects for both time steps.

SPORT EDUCATION IN A HIGHER EDUCATION PHYSICAL ACTIVITY COURSE

The present research had the purpose to analyze how students perceived a physical activity (PA) course in higher education that used the Sport Education (SE) model. The study addressed: i) Students overall enjoyment; ii) Students’ skill acquisition self-perception; iii) Students’ game rules knowledge self-perception; iv) Students’ instructional preference. Twenty-six students from an American university located in the Southern region attended this course. The Futsal (indoor-soccer) course offered two 75 minutes class per week. Two forms of data collection were used: a five-point Likert-type scale survey and a post-course interview. Students reported to have a very high enjoyment in all six major features of the SE model. In addition, statistical significance was reached when students reported their perceived skill acquisition and game rules knowledge acquisition. Students also reported to prefer SE when comparing to other physical activity courses that used a traditional pedagogy. Article visualizations:

SPORT EDUCATION IN A HIGHER EDUCATION PHYSICAL ACTIVITY COURSE

The present research had the purpose to analyze how students perceived a physical activity (PA) course in higher education that used the Sport Education (SE) model. The study addressed: i) Students overall enjoyment; ii) Students’ skill acquisition self-perception; iii) Students’ game rules knowledge self-perception; iv) Students’ instructional preference. Twenty-six students from an American university located in the Southern region attended this course. The Futsal (indoor-soccer) course offered two 75 minutes class per week. Two forms of data collection were used: a five-point Likert-type scale survey and a post-course interview. Students reported to have a very high enjoyment in all six major features of the SE model. In addition, statistical significance was reached when students reported their perceived skill acquisition and game rules knowledge acquisition. Students also reported to prefer SE when comparing to other physical activity courses that used a traditional pedagogy. Article visualizations:

Consolidation process boundaries of the degradation of mechanical properties in compression moulding of natural-fibre bio-polymer composites

In spite of the volume of literature on natural fibres, bio-matrix materials and their composites, the choices of optimum process parameters such as moulding temperature, pressure and compression time are still largely based on experience, rules of thumb and general knowledge of the chemical and physical processes occurring in the melt during consolidation. The moulding process itself is a complex balance between processes that must occur for the composite to successfully consolidate and the onset of thermal degradation of the natural fibre and/or matrix materials. This paper brings together models of thermal penetration, melt infusion, thermal degradation and chemical degradation of natural polymers to construct an ideal processing window for a bio-composite. All processes are mapped in terms of normalized consolidation progress parameters making it easier to identify critical processes and process boundaries. Validation of the concept is achieved by measuring changes in the mechanical properties of a flax/PLA bio-composite formed over a range of processing conditions within and outside of the optimized window.

Knowledge rules dimensionality reduction method for multi-reservoir joint operation optimization

In general, reservoirs were used for many purposes, such as power generation, flood control, navigation, zoology and so on. During the process of modelling, we should consider the interest demand of relevant departments represented by water resources, electric power sector and environmental protection administration. Thus, there are numerous complex constraints with different forms in the operation model of multi-reservoir system. These constraints have such comprehensive effects as delivery, intertexture and coupling, which narrows the feasible region characterized by the complex spatiotemporal features and makes it hard for optimization method to enhance the quality of solution. Hence, based on the set operation theory, we proposed the knowledge rules dimensionality reduction method that combines multiple different operation constraints of multi-reservoir system. According to actual problems, the proposed method first identify the feasible region of single reservoir at one stage, two stages and multiple stages. Then, the feasible search space for multi-reservoir system can be identified by the dynamic coordination of various reservoirs. In this way, the infeasible state and decision variables can be removed during the calculation process of the optimization method. The results demonstrate that the proposed method can reduce the difficulty of the system modeling and calculation, and ensure the feasibility and availability of the scheduling process.

Criticism and Blame in Action and Assertion

In this paper, we develop a general normative framework for criticisability, blamelessness and blameworthiness in action. We then turn to the debate on norms of assertion. We show that an application of this framework enables champions of the so-called knowledge rule of assertion to offer a theoretically motivated response to a number of putative counterexamples in terms of blamelessness. Finally, we argue that, on closer inspection, the putative counterexamples serve to confirm the knowledge rule and disconfirm rival views.

Encoded physics knowledge in checking codes for nuclear cross section libraries at Los Alamos

Checking procedures for processed nuclear data at Los Alamos are described. Both continuous energy and multi-group nuclear data are verified by locally developed checking codes which use basic physics knowledge and common-sense rules. A list of nuclear data problems which have been identified with help of these checking codes is also given.

The formalization of the rules of knowledge base information system of classification and analytical evaluation of professional

Considered topical issue of formalizing rules knowledge base information system of classification andanalytical evaluation of professional models and theoretical bases of formalization which wereexamined by the author in earlier studies

Expansive Legal Research

AbstractThis article will introduce an approach to teaching legal research called Expansive Legal Research. The Expansive Legal Research perspective is based upon dissertation research on legal information behavior at a law school legal aid clinic. This approach is inspired by an educational perspective called Expansive Learning, which in turn has roots in the psychological theory called Activity Theory. The Expansive Legal Research perspective includes elements inspired by Expansive Learning and Activity Theory such as a focus on an activity-centered context of both the individual and social aspects of human behavior; the design-oriented nature of human problem-solving; the role of tacit knowledge and unwritten rules in daily activity and practice; and a cultural historical approach to learning and development, where both the user and their tools are undergoing a constant process of growth and change and transformation. An Expansive Legal Research approach, and the theory it is based upon, may provide new insights into legal research instruction, and may be a useful tool for legal research instructors.

The Prediction of Problem-Solving Assessed Via Microworlds

Abstract. In this study, we explored the network of relations between fluid reasoning, working memory, and the two dimensions of complex problem solving, rule knowledge and rule application. In doing so, we replicated the recent study by Bühner, Kröner, and Ziegler (2008) and the structural relations investigated therein [ Bühner, Kröner, & Ziegler, (2008) . Working memory, visual-spatial intelligence and their relationship to problem-solving. Intelligence, 36, 672–680]. However, in the present study, we used different assessment instruments by employing assessments of figural, numerical, and verbal fluid reasoning, an assessment of numerical working memory, and a complex problem solving assessment using the MicroDYN approach. In a sample of N = 2,029 Finnish sixth-grade students of which 328 students took the numerical working memory assessment, the findings diverged substantially from the results reported by Bühner et al. Importantly, in the present study, fluid reasoning was the main source of variation for rule knowledge and rule application, and working memory contributed only a little added value. Albeit generally in line with previously conducted research on the relation between complex problem solving and other cognitive abilities, these findings directly contrast the results of Bühner et al. (2008) who reported that only working memory was a source of variation in complex problem solving, whereas fluid reasoning was not. Explanations for the different patterns of results are sought, and implications for the use of assessment instruments and for research on interindividual differences in complex problem solving are discussed.

Reading the Rules of Knowledge in the Story of the Fall: Calvin and Reformed Epistemology on the Noetic Effects of Original Sin

ABSTRACT Reformed epistemology has reclaimed for contemporary apologetics not only Calvin's notion of sensus divinitatis, but also its negative counterpart—the idea of the corruption of human intellectual capacities through original sin. But while Alvin Plantinga's retrieval of the concept finds some support in Calvin's Institutes, it does not do full justice to the exegetically determined historical dynamism of Calvin's anthropology. I will support my argument with a close reading of Calvin's exegesis of the Fall, which highlights the Christological mediation of true knowledge, and Calvin's identification of disordered imagination as the primary noetic accompaniment of sin. These features deserve the attention of any contemporary retrieval of the noetic effects of original sin, while Calvin's exegesis continues to be of theological interest in itself.

Reading the Rules of Knowledge in the Story of the Fall: Calvin and Reformed Epistemology on the Noetic Effects of Original Sin

ABSTRACT Reformed epistemology has reclaimed for contemporary apologetics not only Calvin's notion of sensus divinitatis, but also its negative counterpart—the idea of the corruption of human intellectual capacities through original sin. But while Alvin Plantinga's retrieval of the concept finds some support in Calvin's Institutes, it does not do full justice to the exegetically determined historical dynamism of Calvin's anthropology. I will support my argument with a close reading of Calvin's exegesis of the Fall, which highlights the Christological mediation of true knowledge, and Calvin's identification of disordered imagination as the primary noetic accompaniment of sin. These features deserve the attention of any contemporary retrieval of the noetic effects of original sin, while Calvin's exegesis continues to be of theological interest in itself.

Social reasoning abilities in preterm and full-term children aged 5–7 years

BackgroundLiterature has evidenced behavioral and socio-emotional problems in preterm children, as well as long-term difficulties to establish and maintain social relationships in preterm population. Several studies have shown relations between behavior and social reasoning abilities in typically developing children and adults. AimThe present study aimed to investigate the social understanding and social reasoning abilities in preterm children aged between 5 and 7years in comparison to their full-term peers. Study designA social resolution task (SRT) was used to assess abilities to judge, identify and reason about others' behavior in relation to conventional and moral rules knowledge. Subjects102 preterm children and 88 full-term children were included in the study. ResultsCompared with their full-term peers, preterm children exhibited difficulties to understand and reason about inappropriate social behavior, particularly for situations related to the transgression of conventional rules. They used more irrelevant information and exhibited less social awareness when reasoning about the transgression of social rules.The only significant predictor for global SRT and social reasoning scores was the mental processing composite of the K-ABC, but the part of the variance of the SRT that could be explained by the general cognitive abilities was relatively small. ConclusionPreterm children demonstrated poorer social knowledge and social reasoning abilities compared with full-term children at early school age. Improving such abilities may reduce behavioral difficulties and peer relationship problems often described in the preterm population. These findings emphasize the need to early identify children at risk for impaired social development.

The making of uniform costing in a war economy: The case of the Uniconti Commission in Fascist Italy

This article analyses the experience of the Uniconti Commission in setting rules of uniform costing in Italy during World War II (WWII). This initiative was promoted by the Italian Fascist government and the Confederazione dell’Industria (Industry Confederation) in 1941. The purpose of the study is to investigate the process of setting the uniform costing rules and “why” and “how” they were designed. This is done according to a Foucauldian perspective that allows the problematization of accounting as a complex phenomenon, the emergence and functioning of which is linked to context and dependent on the interplay of different influences. Starting from the aims inspired by the totalitarian ideology of the government that promoted the Commission, the analysis is grounded on archival primary sources and provides perspectives on the making of new accounting rules by examining the interplay among participants in the process. The article provides evidence of the complex interplay between knowledge, techniques, institutions and ideology in setting accounting rules in a totalitarian context, marked by a prevailing role of ideology and state in the regulation of the economy.

Just the other side of the coin? From error to insight analysis

To shed more light on data explorers dealing with complex information visualizations in real-world scenarios, new methodologies and models are needed which overcome existing explanatory gaps. Therefore, a novel model to analyze users’ errors and insights is outlined that is derived from Rasmussen’s model on different levels of cognitive processing, and integrates explorers’ skills, schemes, and knowledge (skill–rule–knowledge model). After locating this model in the landscape of theories for visual analytics, the main building blocks of the model, where three cognitive processing levels are interlinked, are described in detail. A case study illustrates how the cognitive processing efforts can be identified from triangulated eye-tracking and think-aloud data. Finally, the model’s applicability, challenges in measurement, and future research options are discussed.