WorldWideScience

Sample records for production rule based

  1. A new pattern associative memory model for image recognition based on Hebb rules and dot product

    Science.gov (United States)

    Gao, Mingyue; Deng, Limiao; Wang, Yanjiang

    2018-04-01

    A great number of associative memory models have been proposed to realize information storage and retrieval inspired by human brain in the last few years. However, there is still much room for improvement for those models. In this paper, we extend a binary pattern associative memory model to accomplish real-world image recognition. The learning process is based on the fundamental Hebb rules and the retrieval is implemented by a normalized dot product operation. Our proposed model can not only fulfill rapid memory storage and retrieval for visual information but also have the ability on incremental learning without destroying the previous learned information. Experimental results demonstrate that our model outperforms the existing Self-Organizing Incremental Neural Network (SOINN) and Back Propagation Neuron Network (BPNN) on recognition accuracy and time efficiency.

  2. Drivers of Changes in Product Development Rules

    DEFF Research Database (Denmark)

    Christiansen, John K.; Varnes, Claus J.

    2015-01-01

    regimes. However, the analysis here indicates that there are different drivers, both internal and external, that cause companies to adopt new rules or modify their existing ones, such as changes in organizational structures, organizational conflicts, and changes in ownership or strategy. In addition......Purpose: - The purpose of this research is to investigate the drivers that induce companies to change their rules for managing product development. Most companies use a form of rule-based management approach, but surprisingly little is known about what makes companies change these rules...... 10 years based on three rounds of interviews with 40 managers. Findings: - Previous research has assumed that the dynamics of product development rules are based on internal learning processes, and that increasingly competent management will stimulate the implementation of newer and more complex rule...

  3. The Product and Quotient Rules Revisited

    Science.gov (United States)

    Eggleton, Roger; Kustov, Vladimir

    2011-01-01

    Mathematical elegance is illustrated by strikingly parallel versions of the product and quotient rules of basic calculus, with some applications. Corresponding rules for second derivatives are given: the product rule is familiar, but the quotient rule is less so.

  4. Considerations Regarding the Expert Systems in the Economy and the Use Method of the Production Systems Based on Rules

    Directory of Open Access Journals (Sweden)

    Eugenia IANCU

    2010-01-01

    Full Text Available As it is known, the expert systems- particularlyreferring to the ones in the economical area, represent a currentissue of our days, them being approached by all the economicalbranches. Starting from these aspects, we wish to present somenecessary principles and considerations regarding the expertsystems, representation of the facts, systems based onproduction rules. The objective of this paper is aimed toidentifying the exigencies of the production system based onrules.

  5. Proof of Kochen–Specker Theorem: Conversion of Product Rule to Sum Rule

    International Nuclear Information System (INIS)

    Toh, S.P.; Zainuddin, Hishamuddin

    2009-01-01

    Valuation functions of observables in quantum mechanics are often expected to obey two constraints called the sum rule and product rule. However, the Kochen–Specker (KS) theorem shows that for a Hilbert space of quantum mechanics of dimension d ≤ 3, these constraints contradict individually with the assumption of value definiteness. The two rules are not irrelated and Peres [Found. Phys. 26 (1996) 807] has conceived a method of converting the product rule into a sum rule for the case of two qubits. Here we apply this method to a proof provided by Mermin based on the product rule for a three-qubit system involving nine operators. We provide the conversion of this proof to one based on sum rule involving ten operators. (general)

  6. Product and Quotient Rules from Logarithmic Differentiation

    Science.gov (United States)

    Chen, Zhibo

    2012-01-01

    A new application of logarithmic differentiation is presented, which provides an alternative elegant proof of two basic rules of differentiation: the product rule and the quotient rule. The proof can intrigue students, help promote their critical thinking and rigorous reasoning and deepen their understanding of previously encountered concepts. The…

  7. When do ruling elites support productive sectors?

    DEFF Research Database (Denmark)

    Kjær, Anne Mette

    that the ruling elite initially supported the fishing industry because of industry pressure. They have failed to enforce fisheries management because there are big political costs associated with such enforcement. The dairy sector in the southwestern milk region was initially supported because the ruling elite......This paper explains the differences in ruling elite support for the fisheries and dairy sectors in Uganda. Although production in Uganda has not generally been promoted in any sustained way, ruling elites have to varying degrees supported the dairy and fisheries sectors. The paper shows...... wanted to build a coalition of support in this region. Coming from the region himself, the president had a keen interest in dairy cattle. The sector was subsequently regulated because the biggest processor put pressure on the ruling elite to do so. Even when the ruling coalition is fragmented, promoting...

  8. Rule-Based Event Processing and Reaction Rules

    Science.gov (United States)

    Paschke, Adrian; Kozlenkov, Alexander

    Reaction rules and event processing technologies play a key role in making business and IT / Internet infrastructures more agile and active. While event processing is concerned with detecting events from large event clouds or streams in almost real-time, reaction rules are concerned with the invocation of actions in response to events and actionable situations. They state the conditions under which actions must be taken. In the last decades various reaction rule and event processing approaches have been developed, which for the most part have been advanced separately. In this paper we survey reaction rule approaches and rule-based event processing systems and languages.

  9. Influence of dispatching rules on average production lead time for multi-stage production systems.

    Science.gov (United States)

    Hübl, Alexander; Jodlbauer, Herbert; Altendorfer, Klaus

    2013-08-01

    In this paper the influence of different dispatching rules on the average production lead time is investigated. Two theorems based on covariance between processing time and production lead time are formulated and proved theoretically. Theorem 1 links the average production lead time to the "processing time weighted production lead time" for the multi-stage production systems analytically. The influence of different dispatching rules on average lead time, which is well known from simulation and empirical studies, can be proved theoretically in Theorem 2 for a single stage production system. A simulation study is conducted to gain more insight into the influence of dispatching rules on average production lead time in a multi-stage production system. We find that the "processing time weighted average production lead time" for a multi-stage production system is not invariant of the applied dispatching rule and can be used as a dispatching rule independent indicator for single-stage production systems.

  10. Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

    KAUST Repository

    Barton, Michael

    2016-03-14

    We introduce optimal quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. Using the homotopy continuation concept (Bartoň and Calo, 2016) that transforms optimal quadrature rules from source spaces to target spaces, we derive optimal rules for splines defined on finite domains. Starting with the classical Gaussian quadrature for polynomials, which is an optimal rule for a discontinuous odd-degree space, we derive rules for target spaces of higher continuity. We further show how the homotopy methodology handles cases where the source and target rules require different numbers of optimal quadrature points. We demonstrate it by deriving optimal rules for various odd-degree spline spaces, particularly with non-uniform knot sequences and non-uniform multiplicities. We also discuss convergence of our rules to their asymptotic counterparts, that is, the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains. For spaces of low continuities, we numerically show that the derived rules quickly converge to their asymptotic counterparts as the weights and nodes of a few boundary elements differ from the asymptotic values.

  11. Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

    KAUST Repository

    Barton, Michael; Calo, Victor M.

    2016-01-01

    We introduce optimal quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. Using the homotopy continuation concept (Bartoň and Calo, 2016) that transforms optimal quadrature rules from source spaces to target spaces, we derive optimal rules for splines defined on finite domains. Starting with the classical Gaussian quadrature for polynomials, which is an optimal rule for a discontinuous odd-degree space, we derive rules for target spaces of higher continuity. We further show how the homotopy methodology handles cases where the source and target rules require different numbers of optimal quadrature points. We demonstrate it by deriving optimal rules for various odd-degree spline spaces, particularly with non-uniform knot sequences and non-uniform multiplicities. We also discuss convergence of our rules to their asymptotic counterparts, that is, the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains. For spaces of low continuities, we numerically show that the derived rules quickly converge to their asymptotic counterparts as the weights and nodes of a few boundary elements differ from the asymptotic values.

  12. Methodological approaches based on business rules

    Directory of Open Access Journals (Sweden)

    Anca Ioana ANDREESCU

    2008-01-01

    Full Text Available Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize the rules and move them outside the application. This paper analyzes and evaluates three well-known business rules approaches. It also outlines some critical factors that have to be taken into account in the decision to introduce business rules facilities in a software system. Based on the concept of explicit manipulation of business rules in a software system, the need for a general approach based on business rules is discussed.

  13. A Constructivist Approach to Rule Bases

    NARCIS (Netherlands)

    Sileno, G.; Boer, A.; van Engers, T.; Loiseau, S.; Filipe, J.; Duval, B.; van den Herik, J.

    2015-01-01

    The paper presents a set of algorithms for the conversion of rule bases between priority-based and constraint-based representations. Inspired by research in precedential reasoning in law, such algorithms can be used for the analysis of a rule base, and for the study of the impact of the introduction

  14. Natural representation of the deduction; applying to the temporal reasoning for expert systems based on production rules

    International Nuclear Information System (INIS)

    Baudin, Patrick

    1990-01-01

    The expert systems development within a real time context, requires both to master the necessary reasoning about the time as well as to master the necessary response time for reasoning. Although rigorous temporal logic formalisms exist, strategies for temporal reasoning are either incomplete or else imply unacceptable response times. The first part presents the logic formalism upon which is based the production system. This formalism contains a three-valued logic system with truth-valued matrix, and a deductive system with a formal system. It does a rigorous work for this no standard logic, where the notions of consistency and completeness can be studied. Its development supports itself on the will to formalise the reasoning used at the elaboration time of the strategies to make them more explicit as the natural deduction method. The second part proposes an extension for the source logic formalism to take explicitly the time into account. The approach proposed through 'TANIS', the prototype of such an expert system shell, using a natural reasoning application is proposed. It allows, at the generation time, the implementation within the expert system, of an adapted deduction strategy to the symbolic temporal reasoning which is complete and ease the determination of the response time. (author) [fr

  15. Evidence Based Cataloguing: Moving Beyond the Rules

    Directory of Open Access Journals (Sweden)

    Kathy Carter

    2010-12-01

    Full Text Available Cataloguing is sometimes regarded as a rule-bound, production-based activity that offers little scope for professional judgement and decision-making. In reality, cataloguing involves challenging decisions that can have significant service and financial impacts. The current environment for cataloguing is a maelstrom of changing demands and competing visions for the future. With information-seekers turning en masse to Google and their behaviour receiving greater attention, library vendors are offering “discovery layer” products to replace traditional OPACs, and cataloguers are examining and debating a transformed version of their descriptive cataloguing rules (Resource Description and Access or RDA. In his “Perceptions of the future of cataloging: Is the sky really falling?” (2009, Ivey provides a good summary of this environment. At the same time, myriad new metadata formats and schema are being developed and applied for digital collections in libraries and other institutions. In today’s libraries, cataloguing is no longer limited to management of traditional AACR and MARC-based metadata for traditional library collections. And like their parent institutions, libraries cannot ignore growing pressures to demonstrate accountability and tangible value provided by their services. More than ever, research and an evidence based approach can help guide cataloguing decision-making.

  16. Incremental Learning of Context Free Grammars by Parsing-Based Rule Generation and Rule Set Search

    Science.gov (United States)

    Nakamura, Katsuhiko; Hoshina, Akemi

    This paper discusses recent improvements and extensions in Synapse system for inductive inference of context free grammars (CFGs) from sample strings. Synapse uses incremental learning, rule generation based on bottom-up parsing, and the search for rule sets. The form of production rules in the previous system is extended from Revised Chomsky Normal Form A→βγ to Extended Chomsky Normal Form, which also includes A→B, where each of β and γ is either a terminal or nonterminal symbol. From the result of bottom-up parsing, a rule generation mechanism synthesizes minimum production rules required for parsing positive samples. Instead of inductive CYK algorithm in the previous version of Synapse, the improved version uses a novel rule generation method, called ``bridging,'' which bridges the lacked part of the derivation tree for the positive string. The improved version also employs a novel search strategy, called serial search in addition to minimum rule set search. The synthesis of grammars by the serial search is faster than the minimum set search in most cases. On the other hand, the size of the generated CFGs is generally larger than that by the minimum set search, and the system can find no appropriate grammar for some CFL by the serial search. The paper shows experimental results of incremental learning of several fundamental CFGs and compares the methods of rule generation and search strategies.

  17. Rule-based Information Integration

    NARCIS (Netherlands)

    de Keijzer, Ander; van Keulen, Maurice

    2005-01-01

    In this report, we show the process of information integration. We specifically discuss the language used for integration. We show that integration consists of two phases, the schema mapping phase and the data integration phase. We formally define transformation rules, conversion, evolution and

  18. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha

    2013-11-25

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  19. Classifiers based on optimal decision rules

    KAUST Repository

    Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

    2013-01-01

    Based on dynamic programming approach we design algorithms for sequential optimization of exact and approximate decision rules relative to the length and coverage [3, 4]. In this paper, we use optimal rules to construct classifiers, and study two questions: (i) which rules are better from the point of view of classification-exact or approximate; and (ii) which order of optimization gives better results of classifier work: length, length+coverage, coverage, or coverage+length. Experimental results show that, on average, classifiers based on exact rules are better than classifiers based on approximate rules, and sequential optimization (length+coverage or coverage+length) is better than the ordinary optimization (length or coverage).

  20. Exploration of SWRL Rule Bases through Visualization, Paraphrasing, and Categorization of Rules

    Science.gov (United States)

    Hassanpour, Saeed; O'Connor, Martin J.; Das, Amar K.

    Rule bases are increasingly being used as repositories of knowledge content on the Semantic Web. As the size and complexity of these rule bases increases, developers and end users need methods of rule abstraction to facilitate rule management. In this paper, we describe a rule abstraction method for Semantic Web Rule Language (SWRL) rules that is based on lexical analysis and a set of heuristics. Our method results in a tree data structure that we exploit in creating techniques to visualize, paraphrase, and categorize SWRL rules. We evaluate our approach by applying it to several biomedical ontologies that contain SWRL rules, and show how the results reveal rule patterns within the rule base. We have implemented our method as a plug-in tool for Protégé-OWL, the most widely used ontology modeling software for the Semantic Web. Our tool can allow users to rapidly explore content and patterns in SWRL rule bases, enabling their acquisition and management.

  1. Integrated Case Based and Rule Based Reasoning for Decision Support

    OpenAIRE

    Eshete, Azeb Bekele

    2009-01-01

    This project is a continuation of my specialization project which was focused on studying theoretical concepts related to case based reasoning method, rule based reasoning method and integration of them. The integration of rule-based and case-based reasoning methods has shown a substantial improvement with regards to performance over the individual methods. Verdande Technology As wants to try integrating the rule based reasoning method with an existing case based system. This project focu...

  2. Rule-based decision making model

    International Nuclear Information System (INIS)

    Sirola, Miki

    1998-01-01

    A rule-based decision making model is designed in G2 environment. A theoretical and methodological frame for the model is composed and motivated. The rule-based decision making model is based on object-oriented modelling, knowledge engineering and decision theory. The idea of safety objective tree is utilized. Advanced rule-based methodologies are applied. A general decision making model 'decision element' is constructed. The strategy planning of the decision element is based on e.g. value theory and utility theory. A hypothetical process model is built to give input data for the decision element. The basic principle of the object model in decision making is division in tasks. Probability models are used in characterizing component availabilities. Bayes' theorem is used to recalculate the probability figures when new information is got. The model includes simple learning features to save the solution path. A decision analytic interpretation is given to the decision making process. (author)

  3. Rules of origin and development of regional production network in ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    Simpler Rules of Origin (RoO) with product specific rules can act as a catalyst in trade even if tariff rates are not low. Sector specific restrictiveness across trade agreements are assessed, in view of potential growth of International production networks (IPN). RoO is shown to play a significant role in promoting IPN.

  4. Knowledge base rule partitioning design for CLIPS

    Science.gov (United States)

    Mainardi, Joseph D.; Szatkowski, G. P.

    1990-01-01

    This describes a knowledge base (KB) partitioning approach to solve the problem of real-time performance using the CLIPS AI shell when containing large numbers of rules and facts. This work is funded under the joint USAF/NASA Advanced Launch System (ALS) Program as applied research in expert systems to perform vehicle checkout for real-time controller and diagnostic monitoring tasks. The Expert System advanced development project (ADP-2302) main objective is to provide robust systems responding to new data frames of 0.1 to 1.0 second intervals. The intelligent system control must be performed within the specified real-time window, in order to meet the demands of the given application. Partitioning the KB reduces the complexity of the inferencing Rete net at any given time. This reduced complexity improves performance but without undo impacts during load and unload cycles. The second objective is to produce highly reliable intelligent systems. This requires simple and automated approaches to the KB verification & validation task. Partitioning the KB reduces rule interaction complexity overall. Reduced interaction simplifies the V&V testing necessary by focusing attention only on individual areas of interest. Many systems require a robustness that involves a large number of rules, most of which are mutually exclusive under different phases or conditions. The ideal solution is to control the knowledge base by loading rules that directly apply for that condition, while stripping out all rules and facts that are not used during that cycle. The practical approach is to cluster rules and facts into associated 'blocks'. A simple approach has been designed to control the addition and deletion of 'blocks' of rules and facts, while allowing real-time operations to run freely. Timing tests for real-time performance for specific machines under R/T operating systems have not been completed but are planned as part of the analysis process to validate the design.

  5. Enhancing reliable online transaction with intelligent rule-based ...

    African Journals Online (AJOL)

    Enhancing reliable online transaction with intelligent rule-based fraud detection technique. ... These are with a bid to reducing amongst other things the cost of production and also dissuade the poor handling of Nigeria currency. The CBN pronouncement has necessitated the upsurge in transactions completed with credit ...

  6. Sum rules and moments for lepton-pair production. [Cross sections, Drell--Yan formula

    Energy Technology Data Exchange (ETDEWEB)

    Hwa, R.C.

    1978-01-01

    Sum rules on lepton-pair production cross sections are derived on the bases of the Drell--Yan formula and the known sum rules in leptoproduction. Also exact relations are obtained between the average transverse momenta squared of the valence quarks and moments of the dilepton cross sections. 12 references.

  7. Verifying Architectural Design Rules of the Flight Software Product Line

    Science.gov (United States)

    Ganesan, Dharmalingam; Lindvall, Mikael; Ackermann, Chris; McComas, David; Bartholomew, Maureen

    2009-01-01

    This paper presents experiences of verifying architectural design rules of the NASA Core Flight Software (CFS) product line implementation. The goal of the verification is to check whether the implementation is consistent with the CFS architectural rules derived from the developer's guide. The results indicate that consistency checking helps a) identifying architecturally significant deviations that were eluded during code reviews, b) clarifying the design rules to the team, and c) assessing the overall implementation quality. Furthermore, it helps connecting business goals to architectural principles, and to the implementation. This paper is the first step in the definition of a method for analyzing and evaluating product line implementations from an architecture-centric perspective.

  8. Rule-of-thumb consumers, productivity and hours

    OpenAIRE

    Furlanetto, Francesco; Seneca, Martin

    2007-01-01

    In this paper we study the transmission mechanism of productivity shocks in a model with rule-of-thumb consumers. In the literature, this financial friction has been studied only with reference to fiscal shocks. We show that the presence of rule-of-thumb consumers is also very helpful in accounting for recent empirical evidence on productivity shocks. Rule-of-thumb agents, together with nominal and real rigidities, play an important role in reproducing the negative response of hours and the d...

  9. Personalization of Rule-based Web Services.

    Science.gov (United States)

    Choi, Okkyung; Han, Sang Yong

    2008-04-04

    Nowadays Web users have clearly expressed their wishes to receive personalized services directly. Personalization is the way to tailor services directly to the immediate requirements of the user. However, the current Web Services System does not provide any features supporting this such as consideration of personalization of services and intelligent matchmaking. In this research a flexible, personalized Rule-based Web Services System to address these problems and to enable efficient search, discovery and construction across general Web documents and Semantic Web documents in a Web Services System is proposed. This system utilizes matchmaking among service requesters', service providers' and users' preferences using a Rule-based Search Method, and subsequently ranks search results. A prototype of efficient Web Services search and construction for the suggested system is developed based on the current work.

  10. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    OpenAIRE

    Aminifar, Sadegh; bin Marzuki, Arjuna

    2013-01-01

    Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal...

  11. Rule based deterioration identification and management system

    International Nuclear Information System (INIS)

    Kataoka, S.; Pavinich, W.; Lapides, M.

    1993-01-01

    Under the sponsorship of IHI and EPRI, a rule-based screening system has been developed that can be used by utility engineers to determine which deterioration mechanisms are acting on specific LWR components, and to evaluate the efficacy of an age-related deterioration management program. The screening system was developed using the rule-based shell, NEXPERT, which provides traceability to the data sources used in the logic development. The system addresses all the deterioration mechanisms of specific metals encountered in either BWRs or PWRs. Deterioration mechanisms are listed with reasons why they may occur during the design life of LWRs, considering the plant environment, manufacturing process, service history, material chemical composition, etc. of components in a specific location of a LWR. To eliminate the evaluation of inactive deterioration quickly, a tier structure is applied to the rules. The reasons why deterioration will occur are extracted automatically by backward chaining. To reduce the amount of user input, plant environmental data are stored in files as default environmental data. (author)

  12. Using Rule-Based Computer Programming to Unify Communication Rules Research.

    Science.gov (United States)

    Sanford, David L.; Roach, J. W.

    This paper proposes the use of a rule-based computer programming language as a standard for the expression of rules, arguing that the adoption of a standard would enable researchers to communicate about rules in a consistent and significant way. Focusing on the formal equivalence of artificial intelligence (AI) programming to different types of…

  13. 77 FR 21065 - Certain High Production Volume Chemicals; Test Rule and Significant New Use Rule; Fourth Group of...

    Science.gov (United States)

    2012-04-09

    ... 2070-AJ66 Certain High Production Volume Chemicals; Test Rule and Significant New Use Rule; Fourth... an opportunity to comment on a proposed test rule for 23 high production volume (HPV) chemical... necessary, to prohibit or limit that activity before it occurs. The opportunity to present oral comment was...

  14. Moral empiricism and the bias for act-based rules.

    Science.gov (United States)

    Ayars, Alisabeth; Nichols, Shaun

    2017-10-01

    Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the

  15. Methodological approaches based on business rules

    OpenAIRE

    Anca Ioana ANDREESCU; Adina UTA

    2008-01-01

    Business rules and business processes are essential artifacts in defining the requirements of a software system. Business processes capture business behavior, while rules connect processes and thus control processes and business behavior. Traditionally, rules are scattered inside application code. This approach makes it very difficult to change rules and shorten the life cycle of the software system. Because rules change more quickly than the application itself, it is desirable to externalize...

  16. Performance based regulation - The maintenance rule

    Energy Technology Data Exchange (ETDEWEB)

    Correia, Richard P. [NRR/DOTS/TQMP, U.S. Nuclear Regulatory Commission, Office of Nuclear Reactor Regulation, M/S OWFN 10A19, Washington, D.C. 20555 (United States)

    1997-07-01

    The U.S. Nuclear Regulatory Commission has begun a transition from 'process-oriented' to 'results-oriented' regulations. The maintenance rule is a results-oriented rule that mandates consideration of risk and plant performance. The Maintenance Rule allows licensees to devise the most effective and efficient means of achieving the results described in the rule including the use of Probabilistic Risk (or Safety) Assessments. The NRC staff conducted a series of site visits to evaluate implementation of the Rule. Conclusions from the site visits indicated that the results-oriented Maintenance Rule can be successfully implemented and enforced. (author)

  17. Performance based regulation - The maintenance rule

    International Nuclear Information System (INIS)

    Correia, Richard P.

    1997-01-01

    The U.S. Nuclear Regulatory Commission has begun a transition from 'process-oriented' to 'results-oriented' regulations. The maintenance rule is a results-oriented rule that mandates consideration of risk and plant performance. The Maintenance Rule allows licensees to devise the most effective and efficient means of achieving the results described in the rule including the use of Probabilistic Risk (or Safety) Assessments. The NRC staff conducted a series of site visits to evaluate implementation of the Rule. Conclusions from the site visits indicated that the results-oriented Maintenance Rule can be successfully implemented and enforced. (author)

  18. Sum rule limitations of kinetic particle-production models

    International Nuclear Information System (INIS)

    Knoll, J.; CEA Centre d'Etudes Nucleaires de Grenoble, 38; Guet, C.

    1988-04-01

    Photoproduction and absorption sum rules generalized to systems at finite temperature provide a stringent check on the validity of kinetic models for the production of hard photons in intermediate energy nuclear collisions. We inspect such models for the case of nuclear matter at finite temperature employed in a kinetic regime which copes those encountered in energetic nuclear collisions, and find photon production rates which significantly exceed the limits imposed by the sum rule even under favourable concession. This suggests that coherence effects are quite important and the production of photons cannot be considered as an incoherent addition of individual NNγ production processes. The deficiencies of present kinetic models may also apply for the production of probes such as the pion which do not couple perturbatively to the nuclear currents. (orig.)

  19. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  20. Idioms-based Business Rule Extraction

    NARCIS (Netherlands)

    R Smit (Rob)

    2011-01-01

    htmlabstractThis thesis studies the extraction of embedded business rules, using the idioms of the used framework to identify them. Embedded business rules exist as source code in the software system and knowledge about them may get lost. Extraction of those business rules could make them accessible

  1. Oxytocin modulates trait-based rule following

    NARCIS (Netherlands)

    Gross, J.; de Dreu, C.K.W.

    Rules, whether in the form of norms, taboos or laws, regulate and coordinate human life. Some rules, however, are arbitrary and adhering to them can be personally costly. Rigidly sticking to such rules can be considered maladaptive. Here, we test whether, at the neurobiological level, (mal)adaptive

  2. A rule-based smart automated fertilization and irrigation systems

    Science.gov (United States)

    Yousif, Musab El-Rashid; Ghafar, Khairuddin; Zahari, Rahimi; Lim, Tiong Hoo

    2018-04-01

    Smart automation in industries has become very important as it can improve the reliability and efficiency of the systems. The use of smart technologies in agriculture have increased over the year to ensure and control the production of crop and address food security. However, it is important to use proper irrigation systems avoid water wastage and overfeeding of the plant. In this paper, a Smart Rule-based Automated Fertilization and Irrigation System is proposed and evaluated. We propose a rule based decision making algorithm to monitor and control the food supply to the plant and the soil quality. A build-in alert system is also used to update the farmer using a text message. The system is developed and evaluated using a real hardware.

  3. Online Dispatching Rules For Vehicle-Based Internal Transport Systems

    NARCIS (Netherlands)

    T. Le-Anh (Tuan); M.B.M. de Koster (René)

    2004-01-01

    textabstractOn-line vehicles dispatching rules are widely used in many facilities such as warehouses to control vehicles' movements. Single-attribute dispatching rules, which dispatch vehicles based on only one parameter, are used commonly. However, multi-attribute dispatching rules prove to be

  4. Designing Fuzzy Rule Based Expert System for Cyber Security

    OpenAIRE

    Goztepe, Kerim

    2016-01-01

    The state of cyber security has begun to attract more attention and interest outside the community of computer security experts. Cyber security is not a single problem, but rather a group of highly different problems involving different sets of threats. Fuzzy Rule based system for cyber security is a system consists of a rule depository and a mechanism for accessing and running the rules. The depository is usually constructed with a collection of related rule sets. The aim of this study is to...

  5. Analysis of Rules for Islamic Inheritance Law in Indonesia Using Hybrid Rule Based Learning

    Science.gov (United States)

    Khosyi'ah, S.; Irfan, M.; Maylawati, D. S.; Mukhlas, O. S.

    2018-01-01

    Along with the development of human civilization in Indonesia, the changes and reform of Islamic inheritance law so as to conform to the conditions and culture cannot be denied. The distribution of inheritance in Indonesia can be done automatically by storing the rule of Islamic inheritance law in the expert system. In this study, we analyze the knowledge of experts in Islamic inheritance in Indonesia and represent it in the form of rules using rule-based Forward Chaining (FC) and Davis-Putman-Logemann-Loveland (DPLL) algorithms. By hybridizing FC and DPLL algorithms, the rules of Islamic inheritance law in Indonesia are clearly defined and measured. The rules were conceptually validated by some experts in Islamic laws and informatics. The results revealed that generally all rules were ready for use in an expert system.

  6. A rule-based software test data generator

    Science.gov (United States)

    Deason, William H.; Brown, David B.; Chang, Kai-Hsiung; Cross, James H., II

    1991-01-01

    Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.

  7. A C++ Class for Rule-Base Objects

    Directory of Open Access Journals (Sweden)

    William J. Grenney

    1992-01-01

    Full Text Available A C++ class, called Tripod, was created as a tool to assist with the development of rule-base decision support systems. The Tripod class contains data structures for the rule-base and member functions for operating on the data. The rule-base is defined by three ASCII files. These files are translated by a preprocessor into a single file that is located when a rule-base object is instantiated. The Tripod class was tested as part of a proto-type decision support system (DSS for winter highway maintenance in the Intermountain West. The DSS is composed of two principal modules: the main program, called the wrapper, and a Tripod rule-base object. The wrapper is a procedural module that interfaces with remote sensors and an external meterological database. The rule-base contains the logic for advising an inexperienced user and for assisting with the decision making process.

  8. The solubility of solid fission products in carbides and nitrides of uranium and plutonium: Pt.2. Solubility rules based on lattice parameter differences

    International Nuclear Information System (INIS)

    Benedict, U.

    1977-01-01

    The Relative Lattice Parameter Difference (RLPD) is defined for a solute element with respect to cubic carbides and nitrides of uranium and plutonium as solvents. Rules are given for the relationship between the solubility and the RLPD. NaCl type monocarbides with RLPD's from -10.2% to +7.8% are completely miscible with UC and PuC. NaCl type mononitrides with RLPD's from -7.5% to +8.5% are completely miscible with UN and PuN. The solubility in the sesquicarbides increases with decreasing RPLD and becomes complete in Pu 2 C 3 at RLPD = +4%, and in U 2 C 3 at RLPD approximately +1.5%. Solubilities are predicted on the basis of these rules for the cases where no experimental results are available

  9. Association-rule-based tuberculosis disease diagnosis

    Science.gov (United States)

    Asha, T.; Natarajan, S.; Murthy, K. N. B.

    2010-02-01

    Tuberculosis (TB) is a disease caused by bacteria called Mycobacterium tuberculosis. It usually spreads through the air and attacks low immune bodies such as patients with Human Immunodeficiency Virus (HIV). This work focuses on finding close association rules, a promising technique in Data Mining, within TB data. The proposed method first normalizes of raw data from medical records which includes categorical, nominal and continuous attributes and then determines Association Rules from the normalized data with different support and confidence. Association rules are applied on a real data set containing medical records of patients with TB obtained from a state hospital. The rules determined describes close association between one symptom to another; as an example, likelihood that an occurrence of sputum is closely associated with blood cough and HIV.

  10. Rule-based energy management strategies for hybrid vehicles

    NARCIS (Netherlands)

    Hofman, T.; Druten, van R.M.; Serrarens, A.F.A.; Steinbuch, M.

    2007-01-01

    Int. J. of Electric and Hybrid Vehicles (IJEHV), The highest control layer of a (hybrid) vehicular drive train is termed the Energy Management Strategy (EMS). In this paper an overview of different control methods is given and a new rule-based EMS is introduced based on the combination of Rule-Based

  11. Optical Generation of Fuzzy-Based Rules

    Science.gov (United States)

    Gur, Eran; Mendlovic, David; Zalevsky, Zeev

    2002-08-01

    In the last third of the 20th century, fuzzy logic has risen from a mathematical concept to an applicable approach in soft computing. Today, fuzzy logic is used in control systems for various applications, such as washing machines, train-brake systems, automobile automatic gear, and so forth. The approach of optical implementation of fuzzy inferencing was given by the authors in previous papers, giving an extra emphasis to applications with two dominant inputs. In this paper the authors introduce a real-time optical rule generator for the dual-input fuzzy-inference engine. The paper briefly goes over the dual-input optical implementation of fuzzy-logic inferencing. Then, the concept of constructing a set of rules from given data is discussed. Next, the authors show ways to implement this procedure optically. The discussion is accompanied by an example that illustrates the transformation from raw data into fuzzy set rules.

  12. Constructing rule-based models using the belief functions framework

    NARCIS (Netherlands)

    Almeida, R.J.; Denoeux, T.; Kaymak, U.; Greco, S.; Bouchon-Meunier, B.; Coletti, G.; Fedrizzi, M.; Matarazzo, B.; Yager, R.R.

    2012-01-01

    Abstract. We study a new approach to regression analysis. We propose a new rule-based regression model using the theoretical framework of belief functions. For this purpose we use the recently proposed Evidential c-means (ECM) to derive rule-based models solely from data. ECM allocates, for each

  13. A Fuzzy Rule-based Controller For Automotive Vehicle Guidance

    OpenAIRE

    Hessburg, Thomas; Tomizuka, Masayoshi

    1991-01-01

    A fuzzy rule-based controller is applied to lateral guidance of a vehicle for an automated highway system. The fuzzy rules, based on human drivers' experiences, are developed to track the center of a lane in the presence of external disturbances and over a range of vehicle operating conditions.

  14. Rule - based Fault Diagnosis Expert System for Wind Turbine

    Directory of Open Access Journals (Sweden)

    Deng Xiao-Wen

    2017-01-01

    Full Text Available Under the trend of increasing installed capacity of wind power, the intelligent fault diagnosis of wind turbine is of great significance to the safe and efficient operation of wind farms. Based on the knowledge of fault diagnosis of wind turbines, this paper builds expert system diagnostic knowledge base by using confidence production rules and expert system self-learning method. In Visual Studio 2013 platform, C # language is selected and ADO.NET technology is used to access the database. Development of Fault Diagnosis Expert System for Wind Turbine. The purpose of this paper is to realize on-line diagnosis of wind turbine fault through human-computer interaction, and to improve the diagnostic capability of the system through the continuous improvement of the knowledge base.

  15. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  16. Connecting clinical and actuarial prediction with rule-based methods.

    Science.gov (United States)

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

  17. Horizontal and Vertical Rule Bases Method in Fuzzy Controllers

    Directory of Open Access Journals (Sweden)

    Sadegh Aminifar

    2013-01-01

    Full Text Available Concept of horizontal and vertical rule bases is introduced. Using this method enables the designers to look for main behaviors of system and describes them with greater approximations. The rules which describe the system in first stage are called horizontal rule base. In the second stage, the designer modulates the obtained surface by describing needed changes on first surface for handling real behaviors of system. The rules used in the second stage are called vertical rule base. Horizontal and vertical rule bases method has a great roll in easing of extracting the optimum control surface by using too lesser rules than traditional fuzzy systems. This research involves with control of a system with high nonlinearity and in difficulty to model it with classical methods. As a case study for testing proposed method in real condition, the designed controller is applied to steaming room with uncertain data and variable parameters. A comparison between PID and traditional fuzzy counterpart and our proposed system shows that our proposed system outperforms PID and traditional fuzzy systems in point of view of number of valve switching and better surface following. The evaluations have done both with model simulation and DSP implementation.

  18. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment (Presentation)

    Science.gov (United States)

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  19. Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment

    Science.gov (United States)

    Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

  20. Risk-based rules for crane safety systems

    Energy Technology Data Exchange (ETDEWEB)

    Ruud, Stian [Section for Control Systems, DNV Maritime, 1322 Hovik (Norway)], E-mail: Stian.Ruud@dnv.com; Mikkelsen, Age [Section for Lifting Appliances, DNV Maritime, 1322 Hovik (Norway)], E-mail: Age.Mikkelsen@dnv.com

    2008-09-15

    The International Maritime Organisation (IMO) has recommended a method called formal safety assessment (FSA) for future development of rules and regulations. The FSA method has been applied in a pilot research project for development of risk-based rules and functional requirements for systems and components for offshore crane systems. This paper reports some developments in the project. A method for estimating target reliability for the risk-control options (safety functions) by means of the cost/benefit decision criterion has been developed in the project and is presented in this paper. Finally, a structure for risk-based rules is proposed and presented.

  1. Risk-based rules for crane safety systems

    International Nuclear Information System (INIS)

    Ruud, Stian; Mikkelsen, Age

    2008-01-01

    The International Maritime Organisation (IMO) has recommended a method called formal safety assessment (FSA) for future development of rules and regulations. The FSA method has been applied in a pilot research project for development of risk-based rules and functional requirements for systems and components for offshore crane systems. This paper reports some developments in the project. A method for estimating target reliability for the risk-control options (safety functions) by means of the cost/benefit decision criterion has been developed in the project and is presented in this paper. Finally, a structure for risk-based rules is proposed and presented

  2. Coherent lower previsions in systems modelling: products and aggregation rules

    International Nuclear Information System (INIS)

    Cooman, Gert de; Troffaes, Matthias C.M.

    2004-01-01

    We discuss why coherent lower previsions provide a good uncertainty model for solving generic uncertainty problems involving possibly conflicting expert information. We study various ways of combining expert assessments on different domains, such as natural extension, independent natural extension and the type-I product, as well as on common domains, such as conjunction and disjunction. We provide each of these with a clear interpretation, and we study how they are related. Observing that in combining expert assessments no information is available about the order in which they should be combined, we suggest that the final result should be independent of the order of combination. The rules of combination we study here satisfy this requirement

  3. Fuzzy rule-based model for hydropower reservoirs operation

    Energy Technology Data Exchange (ETDEWEB)

    Moeini, R.; Afshar, A.; Afshar, M.H. [School of Civil Engineering, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2011-02-15

    Real-time hydropower reservoir operation is a continuous decision-making process of determining the water level of a reservoir or the volume of water released from it. The hydropower operation is usually based on operating policies and rules defined and decided upon in strategic planning. This paper presents a fuzzy rule-based model for the operation of hydropower reservoirs. The proposed fuzzy rule-based model presents a set of suitable operating rules for release from the reservoir based on ideal or target storage levels. The model operates on an 'if-then' principle, in which the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. In this paper, reservoir storage, inflow, and period are used as premises and the release as the consequence. The steps involved in the development of the model include, construction of membership functions for the inflow, storage and the release, formulation of fuzzy rules, implication, aggregation and defuzzification. The required knowledge bases for the formulation of the fuzzy rules is obtained form a stochastic dynamic programming (SDP) model with a steady state policy. The proposed model is applied to the hydropower operation of ''Dez'' reservoir in Iran and the results are presented and compared with those of the SDP model. The results indicate the ability of the method to solve hydropower reservoir operation problems. (author)

  4. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  5. A Belief Rule-Based Expert System to Diagnose Influenza

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin; Akter, Shamima

    2014-01-01

    , development and application of an expert system to diagnose influenza under uncertainty. The recently developed generic belief rule-based inference methodology by using the evidential reasoning (RIMER) approach is employed to develop this expert system, termed as Belief Rule Based Expert System (BRBES......). The RIMER approach can handle different types of uncertainties, both in knowledge representation, and in inference procedures. The knowledge-base of this system was constructed by using records of the real patient data along with in consultation with the Influenza specialists of Bangladesh. Practical case...

  6. COLLABORATIVE NETWORK SECURITY MANAGEMENT SYSTEM BASED ON ASSOCIATION MINING RULE

    Directory of Open Access Journals (Sweden)

    Nisha Mariam Varughese

    2014-07-01

    Full Text Available Security is one of the major challenges in open network. There are so many types of attacks which follow fixed patterns or frequently change their patterns. It is difficult to find the malicious attack which does not have any fixed patterns. The Distributed Denial of Service (DDoS attacks like Botnets are used to slow down the system performance. To address such problems Collaborative Network Security Management System (CNSMS is proposed along with the association mining rule. CNSMS system is consists of collaborative Unified Threat Management (UTM, cloud based security centre and traffic prober. The traffic prober captures the internet traffic and given to the collaborative UTM. Traffic is analysed by the Collaborative UTM, to determine whether it contains any malicious attack or not. If any security event occurs, it will reports to the cloud based security centre. The security centre generates security rules based on association mining rule and distributes to the network. The cloud based security centre is used to store the huge amount of tragic, their logs and the security rule generated. The feedback is evaluated and the invalid rules are eliminated to improve the system efficiency.

  7. Autonomous Rule Based Robot Navigation In Orchards

    DEFF Research Database (Denmark)

    Andersen, Jens Christian; Ravn, Ole; Andersen, Nils Axel

    2010-01-01

    Orchard navigation using sensor-based localization and exible mission management facilitates successful missions independent of the Global Positioning System (GPS). This is especially important while driving between tight tree rows where the GPS coverage is poor. This paper suggests localization ...

  8. Rule-Based Storytelling Text-to-Speech (TTS Synthesis

    Directory of Open Access Journals (Sweden)

    Ramli Izzad

    2016-01-01

    Full Text Available In recent years, various real life applications such as talking books, gadgets and humanoid robots have drawn the attention to pursue research in the area of expressive speech synthesis. Speech synthesis is widely used in various applications. However, there is a growing need for an expressive speech synthesis especially for communication and robotic. In this paper, global and local rule are developed to convert neutral to storytelling style speech for the Malay language. In order to generate rules, modification of prosodic parameters such as pitch, intensity, duration, tempo and pauses are considered. Modification of prosodic parameters is examined by performing prosodic analysis on a story collected from an experienced female and male storyteller. The global and local rule is applied in sentence level and synthesized using HNM. Subjective tests are conducted to evaluate the synthesized storytelling speech quality of both rules based on naturalness, intelligibility, and similarity to the original storytelling speech. The results showed that global rule give a better result than local rule

  9. Hierarchical graphs for rule-based modeling of biochemical systems

    Directory of Open Access Journals (Sweden)

    Hu Bin

    2011-02-01

    Full Text Available Abstract Background In rule-based modeling, graphs are used to represent molecules: a colored vertex represents a component of a molecule, a vertex attribute represents the internal state of a component, and an edge represents a bond between components. Components of a molecule share the same color. Furthermore, graph-rewriting rules are used to represent molecular interactions. A rule that specifies addition (removal of an edge represents a class of association (dissociation reactions, and a rule that specifies a change of a vertex attribute represents a class of reactions that affect the internal state of a molecular component. A set of rules comprises an executable model that can be used to determine, through various means, the system-level dynamics of molecular interactions in a biochemical system. Results For purposes of model annotation, we propose the use of hierarchical graphs to represent structural relationships among components and subcomponents of molecules. We illustrate how hierarchical graphs can be used to naturally document the structural organization of the functional components and subcomponents of two proteins: the protein tyrosine kinase Lck and the T cell receptor (TCR complex. We also show that computational methods developed for regular graphs can be applied to hierarchical graphs. In particular, we describe a generalization of Nauty, a graph isomorphism and canonical labeling algorithm. The generalized version of the Nauty procedure, which we call HNauty, can be used to assign canonical labels to hierarchical graphs or more generally to graphs with multiple edge types. The difference between the Nauty and HNauty procedures is minor, but for completeness, we provide an explanation of the entire HNauty algorithm. Conclusions Hierarchical graphs provide more intuitive formal representations of proteins and other structured molecules with multiple functional components than do the regular graphs of current languages for

  10. An Embedded Rule-Based Diagnostic Expert System in Ada

    Science.gov (United States)

    Jones, Robert E.; Liberman, Eugene M.

    1992-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with it portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assumed a growing role in providing human-like reasoning capability expertise for computer systems. The integration is discussed of expert system technology with Ada programming language, especially a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell. NASA Lewis was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-based power expert system, in ART-Ada. Three components, the rule-based expert systems, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The rules were written in the ART-Ada development environment and converted to Ada source code. The graphics interface was developed with the Transportable Application Environment (TAE) Plus, which generates Ada source code to control graphics images. SMART-Ada communicates with a remote host to obtain either simulated or real data. The Ada source code generated with ART-Ada, TAE Plus, and communications code was incorporated into an Ada expert system that reads the data from a power distribution test bed, applies the rule to determine a fault, if one exists, and graphically displays it on the screen. The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  11. Evolving rule-based systems in two medical domains using genetic programming.

    Science.gov (United States)

    Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan; Axer, Hubertus; Bjerregaard, Beth; von Keyserlingk, Diedrich Graf

    2004-11-01

    To demonstrate and compare the application of different genetic programming (GP) based intelligent methodologies for the construction of rule-based systems in two medical domains: the diagnosis of aphasia's subtypes and the classification of pap-smear examinations. Past data representing (a) successful diagnosis of aphasia's subtypes from collaborating medical experts through a free interview per patient, and (b) correctly classified smears (images of cells) by cyto-technologists, previously stained using the Papanicolaou method. Initially a hybrid approach is proposed, which combines standard genetic programming and heuristic hierarchical crisp rule-base construction. Then, genetic programming for the production of crisp rule based systems is attempted. Finally, another hybrid intelligent model is composed by a grammar driven genetic programming system for the generation of fuzzy rule-based systems. Results denote the effectiveness of the proposed systems, while they are also compared for their efficiency, accuracy and comprehensibility, to those of an inductive machine learning approach as well as to those of a standard genetic programming symbolic expression approach. The proposed GP-based intelligent methodologies are able to produce accurate and comprehensible results for medical experts performing competitive to other intelligent approaches. The aim of the authors was the production of accurate but also sensible decision rules that could potentially help medical doctors to extract conclusions, even at the expense of a higher classification score achievement.

  12. GRAMMAR RULE BASED INFORMATION RETRIEVAL MODEL FOR BIG DATA

    Directory of Open Access Journals (Sweden)

    T. Nadana Ravishankar

    2015-07-01

    Full Text Available Though Information Retrieval (IR in big data has been an active field of research for past few years; the popularity of the native languages presents a unique challenge in big data information retrieval systems. There is a need to retrieve information which is present in English and display it in the native language for users. This aim of cross language information retrieval is complicated by unique features of the native languages such as: morphology, compound word formations, word spelling variations, ambiguity, word synonym, other language influence and etc. To overcome some of these issues, the native language is modeled using a grammar rule based approach in this work. The advantage of this approach is that the native language is modeled and its unique features are encoded using a set of inference rules. This rule base coupled with the customized ontological system shows considerable potential and is found to show better precision and recall.

  13. Ruled-based control of off-grid desalination powered by renewable energies

    Directory of Open Access Journals (Sweden)

    Alvaro Serna

    2015-08-01

    Full Text Available A rule-based control is presented for desalination plants operating under variable, renewable power availability. This control algorithm is based on two sets of rules: first, a list that prioritizes the reverse osmosis (RO units of the plant is created, based on the current state and the expected water demand; secondly, the available energy is then dispatched to these units following this prioritized list. The selected strategy is tested on a specific case study: a reverse osmosis plant designed for the production of desalinated water powered by wind and wave energy. Simulation results illustrate the correct performance of the plant under this control.

  14. 17 CFR 41.24 - Rule amendments to security futures products.

    Science.gov (United States)

    2010-04-01

    ... rule amendment relating to a security futures product if the registered derivatives transaction... 17 Commodity and Securities Exchanges 1 2010-04-01 2010-04-01 false Rule amendments to security futures products. 41.24 Section 41.24 Commodity and Securities Exchanges COMMODITY FUTURES TRADING...

  15. Method for automatic control rod operation using rule-based control

    International Nuclear Information System (INIS)

    Kinoshita, Mitsuo; Yamada, Naoyuki; Kiguchi, Takashi

    1988-01-01

    An automatic control rod operation method using rule-based control is proposed. Its features are as follows: (1) a production system to recognize plant events, determine control actions and realize fast inference (fast selection of a suitable production rule), (2) use of the fuzzy control technique to determine quantitative control variables. The method's performance was evaluated by simulation tests on automatic control rod operation at a BWR plant start-up. The results were as follows; (1) The performance which is related to stabilization of controlled variables and time required for reactor start-up, was superior to that of other methods such as PID control and program control methods, (2) the process time to select and interpret the suitable production rule, which was the same as required for event recognition or determination of control action, was short (below 1 s) enough for real time control. The results showed that the method is effective for automatic control rod operation. (author)

  16. A Production-Rule Analysis System for Nuclear Plant monitoring and emergency response applications

    International Nuclear Information System (INIS)

    Ragheb, M.; Tsoukalas, L.; McDonough, T.; Parker, M.

    1987-01-01

    A Production-Rule Analysis System for Nuclear Power Plant Monitoring is presented. The signals generated by the Zion-1 Plant are considered for emergency Response applications. The integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems, is monitored. Representation of the system is in the form of a goal-tree generating a Knowledge-Base searched by an Inference Engine functioning in the forward-chaining mode. The Gaol-tree is built from Fault-Trees based on plant operational information. The system is implemented on a VAX-8500 and is programmed in OPS-5

  17. Good and Bad Objects : Cardinality-Based Rules

    NARCIS (Netherlands)

    Dimitrov, D.A.; Borm, P.E.M.; Hendrickx, R.L.P.

    2003-01-01

    We consider the problem of ranking sets of objects, the members of which are mutually compatible.Assuming that each object is either good or bad, we axiomatically characterize three cardinality-based rules which arise naturally in this dichotomous setting.They are what we call the symmetric

  18. Rule-based emergency action level monitor prototype

    International Nuclear Information System (INIS)

    Touchton, R.A.; Gunter, A.D.; Cain, D.

    1985-01-01

    In late 1983, the Electric Power Research Institute (EPRI) began a program to encourage and stimulate the development of artificial intelligence (AI) applications for the nuclear industry. Development of a rule-based emergency action level classification system prototype is discussed. The paper describes both the full prototype currently under development and the completed, simplified prototype

  19. Rule-based Test Generation with Mind Maps

    Directory of Open Access Journals (Sweden)

    Dimitry Polivaev

    2012-02-01

    Full Text Available This paper introduces basic concepts of rule based test generation with mind maps, and reports experiences learned from industrial application of this technique in the domain of smart card testing by Giesecke & Devrient GmbH over the last years. It describes the formalization of test selection criteria used by our test generator, our test generation architecture and test generation framework.

  20. Optimal Sequential Rules for Computer-Based Instruction.

    Science.gov (United States)

    Vos, Hans J.

    1998-01-01

    Formulates sequential rules for adapting the appropriate amount of instruction to learning needs in the context of computer-based instruction. Topics include Bayesian decision theory, threshold and linear-utility structure, psychometric model, optimal sequential number of test questions, and an empirical example of sequential instructional…

  1. A rule-based automatic sleep staging method.

    Science.gov (United States)

    Liang, Sheng-Fu; Kuo, Chin-En; Hu, Yu-Han; Cheng, Yu-Shian

    2012-03-30

    In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Design Transformations for Rule-based Procedural Modeling

    KAUST Repository

    Lienhard, Stefan; Lau, Cheryl; Mü ller, Pascal; Wonka, Peter; Pauly, Mark

    2017-01-01

    We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

  3. Design Transformations for Rule-based Procedural Modeling

    KAUST Repository

    Lienhard, Stefan

    2017-05-24

    We introduce design transformations for rule-based procedural models, e.g., for buildings and plants. Given two or more procedural designs, each specified by a grammar, a design transformation combines elements of the existing designs to generate new designs. We introduce two technical components to enable design transformations. First, we extend the concept of discrete rule switching to rule merging, leading to a very large shape space for combining procedural models. Second, we propose an algorithm to jointly derive two or more grammars, called grammar co-derivation. We demonstrate two applications of our work: we show that our framework leads to a larger variety of models than previous work, and we show fine-grained transformation sequences between two procedural models.

  4. A Rule Based Approach to ISS Interior Volume Control and Layout

    Science.gov (United States)

    Peacock, Brian; Maida, Jim; Fitts, David; Dory, Jonathan

    2001-01-01

    Traditional human factors design involves the development of human factors requirements based on a desire to accommodate a certain percentage of the intended user population. As the product is developed human factors evaluation involves comparison between the resulting design and the specifications. Sometimes performance metrics are involved that allow leniency in the design requirements given that the human performance result is satisfactory. Clearly such approaches may work but they give rise to uncertainty and negotiation. An alternative approach is to adopt human factors design rules that articulate a range of each design continuum over which there are varying outcome expectations and interactions with other variables, including time. These rules are based on a consensus of human factors specialists, designers, managers and customers. The International Space Station faces exactly this challenge in interior volume control, which is based on anthropometric, performance and subjective preference criteria. This paper describes the traditional approach and then proposes a rule-based alternative. The proposed rules involve spatial, temporal and importance dimensions. If successful this rule-based concept could be applied to many traditional human factors design variables and could lead to a more effective and efficient contribution of human factors input to the design process.

  5. A forecast-based STDP rule suitable for neuromorphic implementation.

    Science.gov (United States)

    Davies, S; Galluppi, F; Rast, A D; Furber, S B

    2012-08-01

    Artificial neural networks increasingly involve spiking dynamics to permit greater computational efficiency. This becomes especially attractive for on-chip implementation using dedicated neuromorphic hardware. However, both spiking neural networks and neuromorphic hardware have historically found difficulties in implementing efficient, effective learning rules. The best-known spiking neural network learning paradigm is Spike Timing Dependent Plasticity (STDP) which adjusts the strength of a connection in response to the time difference between the pre- and post-synaptic spikes. Approaches that relate learning features to the membrane potential of the post-synaptic neuron have emerged as possible alternatives to the more common STDP rule, with various implementations and approximations. Here we use a new type of neuromorphic hardware, SpiNNaker, which represents the flexible "neuromimetic" architecture, to demonstrate a new approach to this problem. Based on the standard STDP algorithm with modifications and approximations, a new rule, called STDP TTS (Time-To-Spike) relates the membrane potential with the Long Term Potentiation (LTP) part of the basic STDP rule. Meanwhile, we use the standard STDP rule for the Long Term Depression (LTD) part of the algorithm. We show that on the basis of the membrane potential it is possible to make a statistical prediction of the time needed by the neuron to reach the threshold, and therefore the LTP part of the STDP algorithm can be triggered when the neuron receives a spike. In our system these approximations allow efficient memory access, reducing the overall computational time and the memory bandwidth required. The improvements here presented are significant for real-time applications such as the ones for which the SpiNNaker system has been designed. We present simulation results that show the efficacy of this algorithm using one or more input patterns repeated over the whole time of the simulation. On-chip results show that

  6. A Rules-Based Simulation of Bacterial Turbulence

    Science.gov (United States)

    Mikel-Stites, Maxwell; Staples, Anne

    2015-11-01

    In sufficiently dense bacterial populations (>40% bacteria by volume), unusual collective swimming behaviors have been consistently observed, resembling von Karman vortex streets. The source of these collective swimming behavior has yet to be fully determined, and as of yet, no research has been conducted that would define whether or not this behavior is derived predominantly from the properties of the surrounding media, or if it is an emergent behavior as a result of the ``rules'' governing the behavior of individual bacteria. The goal of this research is to ascertain whether or not it is possible to design a simulation that can replicate the qualitative behavior of the densely packed bacterial populations using only behavioral rules to govern the actions of each bacteria, with the physical properties of the media being neglected. The results of the simulation will address whether or not it is possible for the system's overall behavior to be driven exclusively by these rule-based dynamics. In order to examine this, the behavioral simulation was written in MATLAB on a fixed grid, and updated sequentially with the bacterial behavior, including randomized tumbling, gathering and perceptual sub-functions. If the simulation is successful, it will serve as confirmation that it is possible to generate these qualitatively vortex-like behaviors without specific physical media (that the phenomena arises in emergent fashion from behavioral rules), or as evidence that the observed behavior requires some specific set of physical parameters.

  7. Guidelines for visualizing and annotating rule-based models†

    Science.gov (United States)

    Chylek, Lily A.; Hu, Bin; Blinov, Michael L.; Emonet, Thierry; Faeder, James R.; Goldstein, Byron; Gutenkunst, Ryan N.; Haugh, Jason M.; Lipniacki, Tomasz; Posner, Richard G.; Yang, Jin; Hlavacek, William S.

    2011-01-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models. PMID:21647530

  8. Guidelines for visualizing and annotating rule-based models.

    Science.gov (United States)

    Chylek, Lily A; Hu, Bin; Blinov, Michael L; Emonet, Thierry; Faeder, James R; Goldstein, Byron; Gutenkunst, Ryan N; Haugh, Jason M; Lipniacki, Tomasz; Posner, Richard G; Yang, Jin; Hlavacek, William S

    2011-10-01

    Rule-based modeling provides a means to represent cell signaling systems in a way that captures site-specific details of molecular interactions. For rule-based models to be more widely understood and (re)used, conventions for model visualization and annotation are needed. We have developed the concepts of an extended contact map and a model guide for illustrating and annotating rule-based models. An extended contact map represents the scope of a model by providing an illustration of each molecule, molecular component, direct physical interaction, post-translational modification, and enzyme-substrate relationship considered in a model. A map can also illustrate allosteric effects, structural relationships among molecular components, and compartmental locations of molecules. A model guide associates elements of a contact map with annotation and elements of an underlying model, which may be fully or partially specified. A guide can also serve to document the biological knowledge upon which a model is based. We provide examples of a map and guide for a published rule-based model that characterizes early events in IgE receptor (FcεRI) signaling. We also provide examples of how to visualize a variety of processes that are common in cell signaling systems but not considered in the example model, such as ubiquitination. An extended contact map and an associated guide can document knowledge of a cell signaling system in a form that is visual as well as executable. As a tool for model annotation, a map and guide can communicate the content of a model clearly and with precision, even for large models.

  9. Test of the Okubo-Zweig-Iizuka rule in phi production

    International Nuclear Information System (INIS)

    Etkin, A.; Foley, K.J.; Goldman, J.H.; Love, W.A.; Morris, T.W.; Ozaki, S.; Platner, E.D.; Saulys, A.C.; Wheeler, C.D.; Willen, E.H.; Lindenbaum, S.J.; Kramer, M.A.; Mallik, U.

    1978-01-01

    We have measured the reaction π - p → K + K - K + K - n at 22.6 GeV/c and defect strong phi signals in the K + K - effective-mass plots. We do not observe the expected Okubo-Zweig-Iizuka--rule suppression of the phiphin final state and conclude that the rule is working poorly in the observed production processes

  10. Fuzzy Sets-based Control Rules for Terminating Algorithms

    Directory of Open Access Journals (Sweden)

    Jose L. VERDEGAY

    2002-01-01

    Full Text Available In this paper some problems arising in the interface between two different areas, Decision Support Systems and Fuzzy Sets and Systems, are considered. The Model-Base Management System of a Decision Support System which involves some fuzziness is considered, and in that context the questions on the management of the fuzziness in some optimisation models, and then of using fuzzy rules for terminating conventional algorithms are presented, discussed and analyzed. Finally, for the concrete case of the Travelling Salesman Problem, and as an illustration of determination, management and using the fuzzy rules, a new algorithm easy to implement in the Model-Base Management System of any oriented Decision Support System is shown.

  11. Rule Induction-Based Knowledge Discovery for Energy Efficiency

    OpenAIRE

    Chen, Qipeng; Fan, Zhong; Kaleshi, Dritan; Armour, Simon M D

    2015-01-01

    Rule induction is a practical approach to knowledge discovery. Provided that a problem is developed, rule induction is able to return the knowledge that addresses the goal of this problem as if-then rules. The primary goals of knowledge discovery are for prediction and description. The rule format knowledge representation is easily understandable so as to enable users to make decisions. This paper presents the potential of rule induction for energy efficiency. In particular, three rule induct...

  12. Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

    KAUST Repository

    Delimata, Paweł

    2010-01-01

    We discuss two, in a sense extreme, kinds of nondeterministic rules in decision tables. The first kind of rules, called as inhibitory rules, are blocking only one decision value (i.e., they have all but one decisions from all possible decisions on their right hand sides). Contrary to this, any rule of the second kind, called as a bounded nondeterministic rule, can have on the right hand side only a few decisions. We show that both kinds of rules can be used for improving the quality of classification. In the paper, two lazy classification algorithms of polynomial time complexity are considered. These algorithms are based on deterministic and inhibitory decision rules, but the direct generation of rules is not required. Instead of this, for any new object the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory decision rules are often better than those based on deterministic decision rules. We also present an application of bounded nondeterministic rules in construction of rule based classifiers. We include the results of experiments showing that by combining rule based classifiers based on minimal decision rules with bounded nondeterministic rules having confidence close to 1 and sufficiently large support, it is possible to improve the classification quality. © 2010 Springer-Verlag.

  13. Inclusive gluon production in the dipole approach: Abramovskii-Gribov-Kancheli (AGK) cutting rules

    International Nuclear Information System (INIS)

    Levin, Eugene; Prygarin, Alex

    2008-01-01

    We consider single gluon production in the dipole model and reproduce the result of Kovchegov and Tuchin for the adjoint (gluonic) dipole structure of the inclusive cross section. We show the validity of the adjoint dipole structure to any order of evolution by deriving and solving the nonlinear evolution for the nondiagonal cross section of a dipole scattering off the target. The form of the solution to this equation restores the dipole interpretation for nondiagonal cross sections that appear in gluon production. Using this formalism, we analyze the single inclusive production cross section in terms of the contributions of different multiplicities, and we derive the Abramovskii-Gribov-Kancheli (AGK) cutting rules for two-Pomeron exchange. The cutting rules, which were found in this formalism, fully reproduce the original AGK rules for the total cross section. However, for the case of gluon production, the AGK rules are violated already for one-gluon emission from the vertex

  14. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  15. A hierarchical fuzzy rule-based approach to aphasia diagnosis.

    Science.gov (United States)

    Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

    2007-10-01

    Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy.

  16. A high-level language for rule-based modelling.

    Science.gov (United States)

    Pedersen, Michael; Phillips, Andrew; Plotkin, Gordon D

    2015-01-01

    Rule-based languages such as Kappa excel in their support for handling the combinatorial complexities prevalent in many biological systems, including signalling pathways. But Kappa provides little structure for organising rules, and large models can therefore be hard to read and maintain. This paper introduces a high-level, modular extension of Kappa called LBS-κ. We demonstrate the constructs of the language through examples and three case studies: a chemotaxis switch ring, a MAPK cascade, and an insulin signalling pathway. We then provide a formal definition of LBS-κ through an abstract syntax and a translation to plain Kappa. The translation is implemented in a compiler tool which is available as a web application. We finally demonstrate how to increase the expressivity of LBS-κ through embedded scripts in a general-purpose programming language, a technique which we view as generally applicable to other domain specific languages.

  17. Rough set and rule-based multicriteria decision aiding

    Directory of Open Access Journals (Sweden)

    Roman Slowinski

    2012-08-01

    Full Text Available The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA. DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems.

  18. 78 FR 36693 - Rules and Regulations Under the Fur Products Labeling Act

    Science.gov (United States)

    2013-06-19

    ... marketing or sale of the products would violate the Act or Rules.\\27\\ \\27\\ NRF at 5. As discussed in the... products as private label products; unless the retailers knew or should have known that the marketing or... Skills Needed To Comply As explained earlier in this document, the proposed amendments would clarify and...

  19. A rule-based stemmer for Arabic Gulf dialect

    Directory of Open Access Journals (Sweden)

    Belal Abuata

    2015-04-01

    Full Text Available Arabic dialects arewidely used from many years ago instead of Modern Standard Arabic language in many fields. The presence of dialects in any language is a big challenge. Dialects add a new set of variational dimensions in some fields like natural language processing, information retrieval and even in Arabic chatting between different Arab nationals. Spoken dialects have no standard morphological, phonological and lexical like Modern Standard Arabic. Hence, the objective of this paper is to describe a procedure or algorithm by which a stem for the Arabian Gulf dialect can be defined. The algorithm is rule based. Special rules are created to remove the suffixes and prefixes of the dialect words. Also, the algorithm applies rules related to the word size and the relation between adjacent letters. The algorithm was tested for a number of words and given a good correct stem ratio. The algorithm is also compared with two Modern Standard Arabic algorithms. The results showed that Modern Standard Arabic stemmers performed poorly with Arabic Gulf dialect and our algorithm performed poorly when applied for Modern Standard Arabic words.

  20. Formulation of the verbal thought process based on generative rules

    Energy Technology Data Exchange (ETDEWEB)

    Suehiro, N; Fujisaki, H

    1984-01-01

    As assumption is made on the generative nature of the verbal thought process, based on an analogy between language use and verbal thought. A procedure is then presented for acquiring the set of generative rules from a given set of concept strings, leading to an efficient representation of verbal knowledge. The non-terminal symbols derived in the acquisition process are found to correspond to concepts and superordinate concepts in the human process of verbal thought. The validity of the formulation and the efficiency of knowledge representation is demonstrated by an example in which knowledge of biological properties of animals is reorganized into a set of generative rules. The process of inductive inference is then defined as a generalization of the acquired knowledge, and the principle of maximum simplicity of rules is proposed as a possible criterion for such generalization. The proposal is also tested by an example in which only a small part of a systematic body of knowledge is utilized to make interferences on the unknown parts of the system. 6 references.

  1. A rough set-based association rule approach implemented on a brand trust evaluation model

    Science.gov (United States)

    Liao, Shu-Hsien; Chen, Yin-Ju

    2017-09-01

    In commerce, businesses use branding to differentiate their product and service offerings from those of their competitors. The brand incorporates a set of product or service features that are associated with that particular brand name and identifies the product/service segmentation in the market. This study proposes a new data mining approach, a rough set-based association rule induction, implemented on a brand trust evaluation model. In addition, it presents as one way to deal with data uncertainty to analyse ratio scale data, while creating predictive if-then rules that generalise data values to the retail region. As such, this study uses the analysis of algorithms to find alcoholic beverages brand trust recall. Finally, discussions and conclusion are presented for further managerial implications.

  2. Research on Fault Diagnosis Method Based on Rule Base Neural Network

    Directory of Open Access Journals (Sweden)

    Zheng Ni

    2017-01-01

    Full Text Available The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location. And neural network is effective in dealing with nonlinear problem. In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward. At first, the structure of BP neural network is built and the learning rule is given. Then, the rule base is built by fuzzy theory. An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given. Simulation results confirm the effectiveness of this method.

  3. 77 FR 52977 - Regulatory Capital Rules: Advanced Approaches Risk-Based Capital Rule; Market Risk Capital Rule

    Science.gov (United States)

    2012-08-30

    ...-weighted assets for residential mortgages, securitization exposures, and counterparty credit risk. The.... Risk-Weighted Assets--Proposed Modifications to the Advanced Approaches Rules A. Counterparty Credit... Margin Period of Risk 3. Changes to the Internal Models Methodology (IMM) 4. Credit Valuation Adjustments...

  4. Biometric image enhancement using decision rule based image fusion techniques

    Science.gov (United States)

    Sagayee, G. Mary Amirtha; Arumugam, S.

    2010-02-01

    Introducing biometrics into information systems may result in considerable benefits. Most of the researchers confirmed that the finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. For finger prints applications, choosing proper sensor is at risk. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analyzed with its entropy levels and root mean square error.

  5. Rule-based detection of intrathoracic airway trees

    International Nuclear Information System (INIS)

    Sonka, M.; Park, W.; Hoffman, E.A.

    1996-01-01

    New sensitive and reliable methods for assessing alterations in regional lung structure and function are critically important for the investigation and treatment of pulmonary diseases. Accurate identification of the airway tree will provide an assessment of airway structure and will provide a means by which multiple volumetric images of the lung at the same lung volume over time can be used to assess regional parenchymal changes. The authors describe a novel rule-based method for the segmentation of airway trees from three-dimensional (3-D) sets of computed tomography (CT) images, and its validation. The presented method takes advantage of a priori anatomical knowledge about pulmonary airway and vascular trees and their interrelationships. The method is based on a combination of 3-D seeded region growing that is used to identify large airways, rule-based two-dimensional (2-D) segmentation of individual CT slices to identify probable locations of smaller diameter airways, and merging of airway regions across the 3-D set of slices resulting in a tree-like airway structure. The method was validated in 40 3-mm-thick CT sections from five data sets of canine lungs scanned via electron beam CT in vivo with lung volume held at a constant pressure. The method's performance was compared with that of the conventional 3-D region growing method. The method substantially outperformed an existing conventional approach to airway tree detection

  6. GraDit: graph-based data repair algorithm for multiple data edits rule violations

    Science.gov (United States)

    Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

    2018-03-01

    Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

  7. Rule-based expert system for maritime anomaly detection

    Science.gov (United States)

    Roy, Jean

    2010-04-01

    Maritime domain operators/analysts have a mandate to be aware of all that is happening within their areas of responsibility. This mandate derives from the needs to defend sovereignty, protect infrastructures, counter terrorism, detect illegal activities, etc., and it has become more challenging in the past decade, as commercial shipping turned into a potential threat. In particular, a huge portion of the data and information made available to the operators/analysts is mundane, from maritime platforms going about normal, legitimate activities, and it is very challenging for them to detect and identify the non-mundane. To achieve such anomaly detection, they must establish numerous relevant situational facts from a variety of sensor data streams. Unfortunately, many of the facts of interest just cannot be observed; the operators/analysts thus use their knowledge of the maritime domain and their reasoning faculties to infer these facts. As they are often overwhelmed by the large amount of data and information, automated reasoning tools could be used to support them by inferring the necessary facts, ultimately providing indications and warning on a small number of anomalous events worthy of their attention. Along this line of thought, this paper describes a proof-of-concept prototype of a rule-based expert system implementing automated rule-based reasoning in support of maritime anomaly detection.

  8. Uncertain rule-based fuzzy systems introduction and new directions

    CERN Document Server

    Mendel, Jerry M

    2017-01-01

    The second edition of this textbook provides a fully updated approach to fuzzy sets and systems that can model uncertainty — i.e., “type-2” fuzzy sets and systems. The author demonstrates how to overcome the limitations of classical fuzzy sets and systems, enabling a wide range of applications from time-series forecasting to knowledge mining to control. In this new edition, a bottom-up approach is presented that begins by introducing classical (type-1) fuzzy sets and systems, and then explains how they can be modified to handle uncertainty. The author covers fuzzy rule-based systems – from type-1 to interval type-2 to general type-2 – in one volume. For hands-on experience, the book provides information on accessing MatLab and Java software to complement the content. The book features a full suite of classroom material. Presents fully updated material on new breakthroughs in human-inspired rule-based techniques for handling real-world uncertainties; Allows those already familiar with type-1 fuzzy se...

  9. Gain ratio based fuzzy weighted association rule mining classifier for ...

    Indian Academy of Sciences (India)

    association rule mining algorithm for extracting both association rules and member- .... The disadvantage of this work is in considering the generalization at each ... If the new attribute is entered, the generalization process does not consider the ...

  10. WellnessRules: A Web 3.0 Case Study in RuleML-Based Prolog-N3 Profile Interoperation

    Science.gov (United States)

    Boley, Harold; Osmun, Taylor Michael; Craig, Benjamin Larry

    An interoperation study, WellnessRules, is described, where rules about wellness opportunities are created by participants in rule languages such as Prolog and N3, and translated within a wellness community using RuleML/XML. The wellness rules are centered around participants, as profiles, encoding knowledge about their activities conditional on the season, the time-of-day, the weather, etc. This distributed knowledge base extends FOAF profiles with a vocabulary and rules about wellness group networking. The communication between participants is organized through Rule Responder, permitting wellness-profile translation and distributed querying across engines. WellnessRules interoperates between rules and queries in the relational (Datalog) paradigm of the pure-Prolog subset of POSL and in the frame (F-logic) paradigm of N3. An evaluation of Rule Responder instantiated for WellnessRules revealed acceptable Web response times.

  11. Integration of object-oriented knowledge representation with the CLIPS rule based system

    Science.gov (United States)

    Logie, David S.; Kamil, Hasan

    1990-01-01

    The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

  12. SPARQL Query Re-writing Using Partonomy Based Transformation Rules

    Science.gov (United States)

    Jain, Prateek; Yeh, Peter Z.; Verma, Kunal; Henson, Cory A.; Sheth, Amit P.

    Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology's containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query constraints and knowledge base. Our experiments were performed on completely third party datasets and queries. Evaluations were performed on Geonames dataset using questions from National Geographic Bee serialized into SPARQL and British Administrative Geography Ontology using questions from a popular trivia website. These experiments demonstrate high precision in retrieval of results and ease in writing queries.

  13. Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

    Science.gov (United States)

    Hinchey, Mike; Rash, James; Erickson, John; Gracanin, Denis; Rouff, Chris

    2010-01-01

    Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

  14. Associations between rule-based parenting practices and child screen viewing: A cross-sectional study

    Directory of Open Access Journals (Sweden)

    Joanna M. Kesten

    2015-01-01

    Conclusions: Limit setting is associated with greater SV. Collaborative rule setting may be effective for managing boys' game-console use. More research is needed to understand rule-based parenting practices.

  15. Strategy-Driven Exploration for Rule-Based Models of Biochemical Systems with Porgy

    OpenAIRE

    Andrei , Oana; Fernández , Maribel; Kirchner , Hélène; Pinaud , Bruno

    2016-01-01

    This paper presents Porgy – an interactive visual environment for rule-based modelling of biochemical systems. We model molecules and molecule interactions as port graphs and port graph rewrite rules, respectively. We use rewriting strategies to control which rules to apply, and where and when to apply them. Our main contributions to rule-based modelling of biochemical systems lie in the strategy language and the associated visual and interactive features offered by Porgy. These features faci...

  16. Derivative-Based Trapezoid Rule for the Riemann-Stieltjes Integral

    Directory of Open Access Journals (Sweden)

    Weijing Zhao

    2014-01-01

    Full Text Available The derivative-based trapezoid rule for the Riemann-Stieltjes integral is presented which uses 2 derivative values at the endpoints. This kind of quadrature rule obtains an increase of two orders of precision over the trapezoid rule for the Riemann-Stieltjes integral and the error term is investigated. At last, the rationality of the generalization of derivative-based trapezoid rule for Riemann-Stieltjes integral is demonstrated.

  17. Degree product rule tempers explosive percolation in the absence of global information

    Science.gov (United States)

    Trevelyan, Alexander J.; Tsekenis, Georgios; Corwin, Eric I.

    2018-02-01

    We introduce a guided network growth model, which we call the degree product rule process, that uses solely local information when adding new edges. For small numbers of candidate edges our process gives rise to a second-order phase transition, but becomes first order in the limit of global choice. We provide the set of critical exponents required to characterize the nature of this percolation transition. Such a process permits interventions which can delay the onset of percolation while tempering the explosiveness caused by cluster product rule processes.

  18. Implementing a Rule-Based Contract Compliance Checker

    Science.gov (United States)

    Strano, Massimo; Molina-Jimenez, Carlos; Shrivastava, Santosh

    The paper describes the design and implementation of an independent, third party contract monitoring service called Contract Compliance Checker (CCC). The CCC is provided with the specification of the contract in force, and is capable of observing and logging the relevant business-to-business (B2B) interaction events, in order to determine whether the actions of the business partners are consistent with the contract. A contract specification language called EROP (for Events, Rights, Obligations and Prohibitions) for the CCC has been developed based on business rules, that provides constructs to specify what rights, obligation and prohibitions become active and inactive after the occurrence of events related to the execution of business operations. The system has been designed to work with B2B industry standards such as ebXML and RosettaNet.

  19. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Directory of Open Access Journals (Sweden)

    Yaacob Sazali

    2005-01-01

    Full Text Available We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI system. The NAVI has a single board processing system (SBPS, a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  20. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Science.gov (United States)

    Nagarajan, R.; Sainarayanan, G.; Yaacob, Sazali; Porle, Rosalyn R.

    2005-12-01

    We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  1. An XML-Based Manipulation and Query Language for Rule-Based Information

    Science.gov (United States)

    Mansour, Essam; Höpfner, Hagen

    Rules are utilized to assist in the monitoring process that is required in activities, such as disease management and customer relationship management. These rules are specified according to the application best practices. Most of research efforts emphasize on the specification and execution of these rules. Few research efforts focus on managing these rules as one object that has a management life-cycle. This paper presents our manipulation and query language that is developed to facilitate the maintenance of this object during its life-cycle and to query the information contained in this object. This language is based on an XML-based model. Furthermore, we evaluate the model and language using a prototype system applied to a clinical case study.

  2. Rule-based model of vein graft remodeling.

    Directory of Open Access Journals (Sweden)

    Minki Hwang

    Full Text Available When vein segments are implanted into the arterial system for use in arterial bypass grafting, adaptation to the higher pressure and flow of the arterial system is accomplished thorough wall thickening and expansion. These early remodeling events have been found to be closely coupled to the local hemodynamic forces, such as shear stress and wall tension, and are believed to be the foundation for later vein graft failure. To further our mechanistic understanding of the cellular and extracellular interactions that lead to global changes in tissue architecture, a rule-based modeling method is developed through the application of basic rules of behaviors for these molecular and cellular activities. In the current method, smooth muscle cell (SMC, extracellular matrix (ECM, and monocytes are selected as the three components that occupy the elements of a grid system that comprise the developing vein graft intima. The probabilities of the cellular behaviors are developed based on data extracted from in vivo experiments. At each time step, the various probabilities are computed and applied to the SMC and ECM elements to determine their next physical state and behavior. One- and two-dimensional models are developed to test and validate the computational approach. The importance of monocyte infiltration, and the associated effect in augmenting extracellular matrix deposition, was evaluated and found to be an important component in model development. Final model validation is performed using an independent set of experiments, where model predictions of intimal growth are evaluated against experimental data obtained from the complex geometry and shear stress patterns offered by a mid-graft focal stenosis, where simulation results show good agreements with the experimental data.

  3. Challenges for Rule Systems on the Web

    Science.gov (United States)

    Hu, Yuh-Jong; Yeh, Ching-Long; Laun, Wolfgang

    The RuleML Challenge started in 2007 with the objective of inspiring the issues of implementation for management, integration, interoperation and interchange of rules in an open distributed environment, such as the Web. Rules are usually classified as three types: deductive rules, normative rules, and reactive rules. The reactive rules are further classified as ECA rules and production rules. The study of combination rule and ontology is traced back to an earlier active rule system for relational and object-oriented (OO) databases. Recently, this issue has become one of the most important research problems in the Semantic Web. Once we consider a computer executable policy as a declarative set of rules and ontologies that guides the behavior of entities within a system, we have a flexible way to implement real world policies without rewriting the computer code, as we did before. Fortunately, we have de facto rule markup languages, such as RuleML or RIF to achieve the portability and interchange of rules for different rule systems. Otherwise, executing real-life rule-based applications on the Web is almost impossible. Several commercial or open source rule engines are available for the rule-based applications. However, we still need a standard rule language and benchmark for not only to compare the rule systems but also to measure the progress in the field. Finally, a number of real-life rule-based use cases will be investigated to demonstrate the applicability of current rule systems on the Web.

  4. Concession rules for hydropower production without reference to ownership

    International Nuclear Information System (INIS)

    2002-01-01

    The report deals with the socio-economic consequences of various ways of changing the regulations defined in the industrial concession law about reversion of hydroelectric power plants. Currently only public Norwegian owners may be given concession unlimited in time, which makes a sort of lock-up effect. Discontinuation of reversion will remove the lock-up effect. On certain conditions this also applies to models based on reversion for all and option for the Government to implement reversion, and time limited concessions without reversion. All the alteration models may therefore lead to easier trading of Norwegian hydropower plants. The alteration models have different consequences for the total external conditions for the power sector

  5. Rule base system in developing groundwater pollution expert system: predicting model

    International Nuclear Information System (INIS)

    Mongkon Ta-oun; Mohamed Daud; Mohd Zohadie Bardaie; Shamshuddin Jusop

    2000-01-01

    New techniques are now available for use in the protection of the environment. One of these techniques is the use of expert system for prediction groundwater pollution potential. Groundwater Pollution Expert system (GWPES) rules are a collection of principles and procedures used to know the comprehension of groundwater pollution prediction. The rules of groundwater pollution expert system in the form of questions, choice, radio-box, slide rule, button or frame are translated in to IF-THEN rule. The rules including of variables, types, domains and descriptions were used by the function of wxCLIPS (C Language Integrate Production System) expert system shell. (author)

  6. A new type of simplified fuzzy rule-based system

    Science.gov (United States)

    Angelov, Plamen; Yager, Ronald

    2012-02-01

    Over the last quarter of a century, two types of fuzzy rule-based (FRB) systems dominated, namely Mamdani and Takagi-Sugeno type. They use the same type of scalar fuzzy sets defined per input variable in their antecedent part which are aggregated at the inference stage by t-norms or co-norms representing logical AND/OR operations. In this paper, we propose a significantly simplified alternative to define the antecedent part of FRB systems by data Clouds and density distribution. This new type of FRB systems goes further in the conceptual and computational simplification while preserving the best features (flexibility, modularity, and human intelligibility) of its predecessors. The proposed concept offers alternative non-parametric form of the rules antecedents, which fully reflects the real data distribution and does not require any explicit aggregation operations and scalar membership functions to be imposed. Instead, it derives the fuzzy membership of a particular data sample to a Cloud by the data density distribution of the data associated with that Cloud. Contrast this to the clustering which is parametric data space decomposition/partitioning where the fuzzy membership to a cluster is measured by the distance to the cluster centre/prototype ignoring all the data that form that cluster or approximating their distribution. The proposed new approach takes into account fully and exactly the spatial distribution and similarity of all the real data by proposing an innovative and much simplified form of the antecedent part. In this paper, we provide several numerical examples aiming to illustrate the concept.

  7. Optimization of Simple Monetary Policy Rules on the Base of Estimated DSGE-model

    OpenAIRE

    Shulgin, A.

    2015-01-01

    Optimization of coefficients in monetary policy rules is performed on the base of the DSGE-model with two independent monetary policy instruments estimated on the Russian data. It was found that welfare maximizing policy rules lead to inadequate result and pro-cyclical monetary policy. Optimal coefficients in Taylor rule and exchange rate rule allow to decrease volatility estimated on Russian data of 2001-2012 by about 20%. The degree of exchange rate flexibility parameter was found to be low...

  8. A Novel Rules Based Approach for Estimating Software Birthmark

    Science.gov (United States)

    Binti Alias, Norma; Anwar, Sajid

    2015-01-01

    Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark. PMID:25945363

  9. Technique Based on Image Pyramid and Bayes Rule for Noise Reduction in Unsupervised Change Detection

    Institute of Scientific and Technical Information of China (English)

    LI Zhi-qiang; HUO hong; FANG Tao; ZHU Ju-lian; GE Wei-li

    2009-01-01

    In this paper, a technique based on image pyramid and Bayes rule for reducing noise effects in unsupervised change detection is proposed. By using Gaussian pyramid to process two multitemporal images respectively, two image pyramids are constructed. The difference pyramid images are obtained by point-by-point subtraction between the same level images of the two image pyramids. By resizing all difference pyramid images to the size of the original multitemporal image and then making product operator among them, a map being similar to the difference image is obtained. The difference image is generated by point-by-point subtraction between the two multitemporal images directly. At last, the Bayes rule is used to distinguish the changed pixels. Both synthetic and real data sets are used to evaluate the performance of the proposed technique. Experimental results show that the map from the proposed technique is more robust to noise than the difference image.

  10. Agent-oriented enterprise modeling based on business rules

    NARCIS (Netherlands)

    Taveter, K.; Wagner, G.R.; Kunii, H.S.; Jajodia, S.; Solvberg, A.

    2001-01-01

    Business rules are statements that express (certain parts of) a business policy, defining business terms and defining or constraining the operations of an enterprise, in a declarative manner. Since these rules define and constrain the interaction among business agents in the course of business

  11. 76 FR 68690 - Rules and Regulations Under the Textile Fiber Products Identification Act

    Science.gov (United States)

    2011-11-07

    ... Products Identification Act; add or clarify definitions of terms set forth in the Rules; and modify its..., ``Textiles--Man-made fibres--Generic Names'' in Section 303.7.\\1\\ Later in 1998, the Commission amended the... updated version of ISO 2076: 1999(E), ``Textiles--Man-made fibres--Generic Names,'' referenced in Section...

  12. 17 CFR 39.4 - Procedures for implementing derivatives clearing organization rules and clearing new products.

    Science.gov (United States)

    2010-04-01

    ... 17 Commodity and Securities Exchanges 1 2010-04-01 2010-04-01 false Procedures for implementing derivatives clearing organization rules and clearing new products. 39.4 Section 39.4 Commodity and Securities Exchanges COMMODITY FUTURES TRADING COMMISSION DERIVATIVES CLEARING ORGANIZATIONS § 39.4 Procedures for...

  13. Optimizing Environmental Flow Operation Rules based on Explicit IHA Constraints

    Science.gov (United States)

    Dongnan, L.; Wan, W.; Zhao, J.

    2017-12-01

    Multi-objective operation of reservoirs are increasingly asked to consider the environmental flow to support ecosystem health. Indicators of Hydrologic Alteration (IHA) is widely used to describe environmental flow regimes, but few studies have explicitly formulated it into optimization models and thus is difficult to direct reservoir release. In an attempt to incorporate the benefit of environmental flow into economic achievement, a two-objective reservoir optimization model is developed and all 33 hydrologic parameters of IHA are explicitly formulated into constraints. The benefit of economic is defined by Hydropower Production (HP) while the benefit of environmental flow is transformed into Eco-Index (EI) that combined 5 of the 33 IHA parameters chosen by principal component analysis method. Five scenarios (A to E) with different constraints are tested and solved by nonlinear programming. The case study of Jing Hong reservoir, located in the upstream of Mekong basin, China, shows: 1. A Pareto frontier is formed by maximizing on only HP objective in scenario A and on only EI objective in scenario B. 2. Scenario D using IHA parameters as constraints obtains the optimal benefits of both economic and ecological. 3. A sensitive weight coefficient is found in scenario E, but the trade-offs between HP and EI objectives are not within the Pareto frontier. 4. When the fraction of reservoir utilizable capacity reaches 0.8, both HP and EI capture acceptable values. At last, to make this modelmore conveniently applied to everyday practice, a simplified operation rule curve is extracted.

  14. Using fuzzy rule-based knowledge model for optimum plating conditions search

    Science.gov (United States)

    Solovjev, D. S.; Solovjeva, I. A.; Litovka, Yu V.; Arzamastsev, A. A.; Glazkov, V. P.; L’vov, A. A.

    2018-03-01

    The paper discusses existing approaches to plating process modeling in order to decrease the distribution thickness of plating surface cover. However, these approaches do not take into account the experience, knowledge, and intuition of the decision-makers when searching the optimal conditions of electroplating technological process. The original approach to optimal conditions search for applying the electroplating coatings, which uses the rule-based model of knowledge and allows one to reduce the uneven product thickness distribution, is proposed. The block diagrams of a conventional control system of a galvanic process as well as the system based on the production model of knowledge are considered. It is shown that the fuzzy production model of knowledge in the control system makes it possible to obtain galvanic coatings of a given thickness unevenness with a high degree of adequacy to the experimental data. The described experimental results confirm the theoretical conclusions.

  15. Rule-Based and Case-Based Reasoning in Housing Prices

    OpenAIRE

    Gabrielle Gayer; Itzhak Gilboa; Offer Lieberman

    2004-01-01

    People reason about real-estate prices both in terms of general rules and in terms of analogies to similar cases. We propose to empirically test which mode of reasoning fits the data better. To this end, we develop the statistical techniques required for the estimation of the case-based model. It is hypothesized that case-based reasoning will have relatively more explanatory power in databases of rental apartments, whereas rule-based reasoning will have a relative advantage in sales data. We ...

  16. Graphical matching rules for cardinality based service feature diagrams

    Directory of Open Access Journals (Sweden)

    Faiza Kanwal

    2017-03-01

    Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.

  17. Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications

    Science.gov (United States)

    Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy. PMID:24511304

  18. Classification based on pruning and double covered rule sets for the internet of things applications.

    Science.gov (United States)

    Li, Shasha; Zhou, Zhongmei; Wang, Weiping

    2014-01-01

    The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy.

  19. Decision fusion recognition based on modified evidence rule

    Institute of Scientific and Technical Information of China (English)

    黎湘; 刘永祥; 付耀文; 庄钊文

    2001-01-01

    A modified evidence combination rule with a combination parameter λ is proposed to solve some problems in D-S theory by considering the correlation and complement among the evidences as well as the size and intersection of subsets in evidence. It can get reasonable results even the evidences are conflicting. Applying this rule to the real infrared/millimetre wave fusion system, a satisfactory result has been obtained.

  20. Light-cone sum rules: A SCET-based formulation

    CERN Document Server

    De Fazio, F; Hurth, Tobias; Feldmann, Th.

    2007-01-01

    We describe the construction of light-cone sum rules (LCSRs) for exclusive $B$-meson decays into light energetic hadrons from correlation functions within soft-collinear effective theory (SCET). As an example, we consider the SCET sum rule for the $B \\to \\pi$ transition form factor at large recoil, including radiative corrections from hard-collinear loop diagrams at first order in the strong coupling constant.

  1. Transfer of Rule-Based Expertise through a Tutorial Dialogue

    Science.gov (United States)

    1979-09-01

    be causing the infection (.2) [RULE633]. {The student asks, "Does the patient have a fever ?") " FEBRILE MYCIN never needed to inquire about whether...remaining clauses, some we classified most as restrictions, and the one or two that remained constituted the key factor(s) of the rule. The " petechial ...Infection is bacterial, KEY-FACTORt 4) Petechial is one of the types of rash which the patient has, RESTRICTIONS 5) Purpuric is not one of the types

  2. Product integration rules at Clenshaw-Curtis and related points: A robust implementation

    International Nuclear Information System (INIS)

    Adam, G.; Nobile, A.

    1989-12-01

    Product integration rules generalizing the Fejer, Clenshaw-Curtis and Filippi quadrature rules respectively are derived for integrals with trigonometric and hyperbolic weight factors. The study puts in evidence the existence of well-conditioned fully analytic solutions, in terms of hypergeometric functions 0 F 1 . An a priori error estimator is discussed which is shown both to avoid wasteful invocation of the integration rule and to increase significantly the robustness of the automatic quadrature procedure. Then, specializing to extended Clenshaw-Curtis (ECC) rules, three types of a posteriori error estimates are considered and the existence of a great risk of their failure is put into evidence by large scale validation tests. An empirical error estimator, superseding them at slowly varying integrands, is found to result in a spectacular increase in the output reliability. Finally, enhancements in the control of the interval subdivision strategy aiming at increasing code robustness is discussed. Comparison with the code DQAWO of QUADPACK, extending over a statistics of about hundred thousand solved integrals, is illustrative for the increased robustness and error estimate reliability of our computer code implementation of the ECC rules. (author). 19 refs, 8 tabs

  3. A General Attribute and Rule Based Role-Based Access Control Model

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Growing numbers of users and many access control policies which involve many different resource attributes in service-oriented environments bring various problems in protecting resource. This paper analyzes the relationships of resource attributes to user attributes in all policies, and propose a general attribute and rule based role-based access control(GAR-RBAC) model to meet the security needs. The model can dynamically assign users to roles via rules to meet the need of growing numbers of users. These rules use different attribute expression and permission as a part of authorization constraints, and are defined by analyzing relations of resource attributes to user attributes in many access policies that are defined by the enterprise. The model is a general access control model, and can support many access control policies, and also can be used to wider application for service. The paper also describes how to use the GAR-RBAC model in Web service environments.

  4. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

    Science.gov (United States)

    Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

    2015-01-01

    Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

  5. Heuristic simulation of nuclear systems on a supercomputer using the HAL-1987 general-purpose production-rule analysis system

    International Nuclear Information System (INIS)

    Ragheb, M.; Gvillo, D.; Makowitz, H.

    1987-01-01

    HAL-1987 is a general-purpose tool for the construction of production-rule analysis systems. It uses the rule-based paradigm from the part of artificial intelligence concerned with knowledge engineering. It uses backward-chaining and forward-chaining in an antecedent-consequent logic, and is programmed in Portable Standard Lisp (PSL). The inference engine is flexible and accommodates general additions and modifications to the knowledge base. The system is used in coupled symbolic-procedural programming adaptive methodologies for stochastic simulations. In Monte Carlo simulations of particle transport, the system considers the pre-processing of the input data to the simulation and adaptively controls the variance reduction process as the simulation progresses. This is accomplished through the use of a knowledge base of rules which encompass the user's expertise in the variance reduction process. It is also applied to the construction of model-based systems for monitoring, fault-diagnosis and crisis-alert in engineering devices, particularly in the field of nuclear reactor safety analysis

  6. Neural underpinnings of divergent production of rules in numerical analogical reasoning.

    Science.gov (United States)

    Wu, Xiaofei; Jung, Rex E; Zhang, Hao

    2016-05-01

    Creativity plays an important role in numerical problem solving. Although the neural underpinnings of creativity have been studied over decades, very little is known about neural mechanisms of the creative process that relates to numerical problem solving. In the present study, we employed a numerical analogical reasoning task with functional Magnetic Resonance Imaging (fMRI) to investigate the neural correlates of divergent production of rules in numerical analogical reasoning. Participants performed two tasks: a multiple solution analogical reasoning task and a single solution analogical reasoning task. Results revealed that divergent production of rules involves significant activations at Brodmann area (BA) 10 in the right middle frontal cortex, BA 40 in the left inferior parietal lobule, and BA 8 in the superior frontal cortex. The results suggest that right BA 10 and left BA 40 are involved in the generation of novel rules, and BA 8 is associated with the inhibition of initial rules in numerical analogical reasoning. The findings shed light on the neural mechanisms of creativity in numerical processing. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. Functional networks inference from rule-based machine learning models.

    Science.gov (United States)

    Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

    2016-01-01

    Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The

  8. Moving from Rule-based to Principle-based in Public Sector: Preparers' Perspective

    OpenAIRE

    Roshayani Arshad; Normah Omar; Siti Fatimah Awang

    2013-01-01

    The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived signific...

  9. Design rules and reality check for carbon-based ultracapacitors

    Science.gov (United States)

    Eisenmann, Erhard T.

    1995-04-01

    Design criteria for carbon-based Ultracapacitors have been determined for specified energy and power requirements, using the geometry of the components and such material properties as density, porosity and conductivity as parameters, while also considering chemical compatibility. This analysis shows that the weights of active and inactive components of the capacitor structure must be carefully balanced for maximum energy and power density. When applied to nonaqueous electrolytes, the design rules for a 5 Wh/kg device call for porous carbon with a specific capacitance of about 30 F/cu cm. This performance is not achievable with pure, electrostatic double layer capacitance. Double layer capacitance is only 5 to 30% of that observed in aqueous electrolyte. Tests also showed that nonaqueous electrolytes have a diminished capability to access micropores in activated carbon, in one case yielding a capacitance of less than 1 F/cu cm for carbon that had 100 F/cu cm in aqueous electrolyte. With negative results on nonaqueous electrolytes dominating the present study, the obvious conclusion is to concentrate on aqueous systems. Only aqueous double layer capacitors offer adequate electrostatic charging characteristics which is the basis for high power performance. There arc many opportunities for further advancing aqueous double layer capacitors, one being the use of highly activated carbon films, as opposed to powders, fibers and foams. While the manufacture of carbon films is still costly, and while the energy and power density of the resulting devices may not meet the optimistic goals that have been proposed, this technology could produce true double layer capacitors with significantly improved performance and large commercial potential.

  10. Changing from a Rules-based to a Principles-based Accounting Logic: A Review

    Directory of Open Access Journals (Sweden)

    Marta Silva Guerreiro

    2014-06-01

    Full Text Available We explore influences on unlisted companies when Portugal moved from a code law, rules-based accounting system, to a principles-based accounting system of adapted International Financial Reporting Standards (IFRS. Institutionalisation of the new principles-based system was generally facilitated by a socio-economic and political context that increasingly supported IFRS logic. This helped central actors gain political opportunity, mobilise important allies, and accommodate major protagonists. The preparedness of unlisted companies to adopt the new IFRS-based accounting system voluntarily was explained by their desire to maintain social legitimacy. However, it was affected negatively by the embeddedness of rule-based practices in the ‘old’ prevailing institutional logic.

  11. Optimization of decision rules based on dynamic programming approach

    KAUST Repository

    Zielosko, Beata

    2014-01-14

    This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.

  12. Design of a Fuzzy Rule Base Expert System to Predict and Classify ...

    African Journals Online (AJOL)

    The main objective of design of a rule base expert system using fuzzy logic approach is to predict and forecast the risk level of cardiac patients to avoid sudden death. In this proposed system, uncertainty is captured using rule base and classification using fuzzy c-means clustering is discussed to overcome the risk level, ...

  13. Rule-based conversion of closely-related languages: a Dutch-to-Afrikaans convertor

    CSIR Research Space (South Africa)

    Van Huyssteen, GB

    2009-11-01

    Full Text Available and performance of a rule-based Dutch-to-Afrikaans converter, with the aim to transform Dutch text so that it looks more like an Afrikaans text (even though it might not even be a good Dutch translation). The rules we used is based on systematic orthographic...

  14. Rules for integrals over products of distributions from coordinate independence of path integrals

    International Nuclear Information System (INIS)

    Kleinert, H.; Chervyakov, A.

    2001-01-01

    In perturbative calculations of quantum-mechanical path integrals in curvilinear coordinates, one encounters Feynman diagrams involving multiple temporal integrals over products of distributions which are mathematically undefined. In addition, there are terms proportional to powers of Dirac δ-functions at the origin coming from the measure of path integration. We derive simple rules for dealing with such singular terms from the natural requirement of coordinate independence of the path integrals. (orig.)

  15. Opinion evolution based on cellular automata rules in small world networks

    Science.gov (United States)

    Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

    2010-03-01

    In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

  16. Association Rule-based Predictive Model for Machine Failure in Industrial Internet of Things

    Science.gov (United States)

    Kwon, Jung-Hyok; Lee, Sol-Bee; Park, Jaehoon; Kim, Eui-Jik

    2017-09-01

    This paper proposes an association rule-based predictive model for machine failure in industrial Internet of things (IIoT), which can accurately predict the machine failure in real manufacturing environment by investigating the relationship between the cause and type of machine failure. To develop the predictive model, we consider three major steps: 1) binarization, 2) rule creation, 3) visualization. The binarization step translates item values in a dataset into one or zero, then the rule creation step creates association rules as IF-THEN structures using the Lattice model and Apriori algorithm. Finally, the created rules are visualized in various ways for users’ understanding. An experimental implementation was conducted using R Studio version 3.3.2. The results show that the proposed predictive model realistically predicts machine failure based on association rules.

  17. Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks.

    Science.gov (United States)

    Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

    2016-07-07

    In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles.

  18. Scenario based product design

    NARCIS (Netherlands)

    Tideman, M.

    2008-01-01

    Creating good products is not an easy thing to do. There are usually many different people who have an interest in the product. People such as the user, of course, but also marketing managers, production engineers, maintenance workers, recycling specialists, and government representatives, just to

  19. Domain-based Teaching Strategy for Intelligent Tutoring System Based on Generic Rules

    Science.gov (United States)

    Kseibat, Dawod; Mansour, Ali; Adjei, Osei; Phillips, Paul

    In this paper we present a framework for selecting the proper instructional strategy for a given teaching material based on its attributes. The new approach is based on a flexible design by means of generic rules. The framework was adapted in an Intelligent Tutoring System to teach Modern Standard Arabic language to adult English-speaking learners with no pre-knowledge of Arabic language is required.

  20. Fuzzylot: a novel self-organising fuzzy-neural rule-based pilot system for automated vehicles.

    Science.gov (United States)

    Pasquier, M; Quek, C; Toh, M

    2001-10-01

    This paper presents part of our research work concerned with the realisation of an Intelligent Vehicle and the technologies required for its routing, navigation, and control. An automated driver prototype has been developed using a self-organising fuzzy rule-based system (POPFNN-CRI(S)) to model and subsequently emulate human driving expertise. The ability of fuzzy logic to represent vague information using linguistic variables makes it a powerful tool to develop rule-based control systems when an exact working model is not available, as is the case of any vehicle-driving task. Designing a fuzzy system, however, is a complex endeavour, due to the need to define the variables and their associated fuzzy sets, and determine a suitable rule base. Many efforts have thus been devoted to automating this process, yielding the development of learning and optimisation techniques. One of them is the family of POP-FNNs, or Pseudo-Outer Product Fuzzy Neural Networks (TVR, AARS(S), AARS(NS), CRI, Yager). These generic self-organising neural networks developed at the Intelligent Systems Laboratory (ISL/NTU) are based on formal fuzzy mathematical theory and are able to objectively extract a fuzzy rule base from training data. In this application, a driving simulator has been developed, that integrates a detailed model of the car dynamics, complete with engine characteristics and environmental parameters, and an OpenGL-based 3D-simulation interface coupled with driving wheel and accelerator/ brake pedals. The simulator has been used on various road scenarios to record from a human pilot driving data consisting of steering and speed control actions associated to road features. Specifically, the POPFNN-CRI(S) system is used to cluster the data and extract a fuzzy rule base modelling the human driving behaviour. Finally, the effectiveness of the generated rule base has been validated using the simulator in autopilot mode.

  1. An evaluation and implementation of rule-based Home Energy Management System using the Rete algorithm.

    Science.gov (United States)

    Kawakami, Tomoya; Fujita, Naotaka; Yoshihisa, Tomoki; Tsukamoto, Masahiko

    2014-01-01

    In recent years, sensors become popular and Home Energy Management System (HEMS) takes an important role in saving energy without decrease in QoL (Quality of Life). Currently, many rule-based HEMSs have been proposed and almost all of them assume "IF-THEN" rules. The Rete algorithm is a typical pattern matching algorithm for IF-THEN rules. Currently, we have proposed a rule-based Home Energy Management System (HEMS) using the Rete algorithm. In the proposed system, rules for managing energy are processed by smart taps in network, and the loads for processing rules and collecting data are distributed to smart taps. In addition, the number of processes and collecting data are reduced by processing rules based on the Rete algorithm. In this paper, we evaluated the proposed system by simulation. In the simulation environment, rules are processed by a smart tap that relates to the action part of each rule. In addition, we implemented the proposed system as HEMS using smart taps.

  2. An investigation of care-based vs. rule-based morality in frontotemporal dementia, Alzheimer's disease, and healthy controls.

    Science.gov (United States)

    Carr, Andrew R; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S; Mather, Michelle; Jimenez, Elvira E; Thompson, Paul; Mendez, Mario F

    2015-11-01

    Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer's disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. Published by Elsevier Ltd.

  3. Life cycle of medical product rules issued by the US Food and Drug Administration.

    Science.gov (United States)

    Hwang, Thomas J; Avorn, Jerry; Kesselheim, Aaron S

    2014-08-01

    The US Food and Drug Administration (FDA) uses rulemaking as one of its primary tools to protect the public health and implement laws enacted by Congress and the president. Because of the many effects that these rules have on social welfare and the economy, the FDA and other executive agencies receive input from the executive branch, the public, and in some cases, the courts, during the process of rulemaking. In this article, we examine the life cycle of FDA regulations concerning medical products and review notable features of the rulemaking process. The current system grants substantial opportunities for diverse stakeholders to participate in and influence how rules are written and implemented. However, the duration, complexity, and adversarial qualities of the rulemaking process can hinder the FDA's ability to achieve its policy and public health goals. There is considerable variation in the level of transparency at different stages in the process, ranging from freely accessible public comments to undisclosed internal agency deliberations. In addition, significant medical product rules are associated with lengthy times to finalization, in some cases for unclear reasons. We conclude by identifying potential areas for reform on the basis of transparency and efficiency. Copyright © 2014 by Duke University Press.

  4. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  5. Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

    Science.gov (United States)

    Oesterle, Jonathan; Lionel, Amodeo

    2018-06-01

    The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.

  6. Rule-based topology system for spatial databases to validate complex geographic datasets

    Science.gov (United States)

    Martinez-Llario, J.; Coll, E.; Núñez-Andrés, M.; Femenia-Ribera, C.

    2017-06-01

    A rule-based topology software system providing a highly flexible and fast procedure to enforce integrity in spatial relationships among datasets is presented. This improved topology rule system is built over the spatial extension Jaspa. Both projects are open source, freely available software developed by the corresponding author of this paper. Currently, there is no spatial DBMS that implements a rule-based topology engine (considering that the topology rules are designed and performed in the spatial backend). If the topology rules are applied in the frontend (as in many GIS desktop programs), ArcGIS is the most advanced solution. The system presented in this paper has several major advantages over the ArcGIS approach: it can be extended with new topology rules, it has a much wider set of rules, and it can mix feature attributes with topology rules as filters. In addition, the topology rule system can work with various DBMSs, including PostgreSQL, H2 or Oracle, and the logic is performed in the spatial backend. The proposed topology system allows users to check the complex spatial relationships among features (from one or several spatial layers) that require some complex cartographic datasets, such as the data specifications proposed by INSPIRE in Europe and the Land Administration Domain Model (LADM) for Cadastral data.

  7. Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

    Science.gov (United States)

    Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

    In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

  8. Flavours of XChange, a Rule-Based Reactive Language for the (Semantic) Web

    OpenAIRE

    Bailey, James; Bry, François; Eckert, Michael; Patrânjan, Paula Lavinia

    2005-01-01

    This article introduces XChange, a rule-based reactive language for the Web. Stressing application scenarios, it first argues that high-level reactive languages are needed for bothWeb and SemanticWeb applications. Then, it discusses technologies and paradigms relevant to high-level reactive languages for the (Semantic) Web. Finally, it presents the Event-Condition-Action rules of XChange.

  9. Prediction on carbon dioxide emissions based on fuzzy rules

    Science.gov (United States)

    Pauzi, Herrini; Abdullah, Lazim

    2014-06-01

    There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

  10. Concurrence of rule- and similarity-based mechanisms in artificial grammar learning.

    Science.gov (United States)

    Opitz, Bertram; Hofmann, Juliane

    2015-03-01

    A current theoretical debate regards whether rule-based or similarity-based learning prevails during artificial grammar learning (AGL). Although the majority of findings are consistent with a similarity-based account of AGL it has been argued that these results were obtained only after limited exposure to study exemplars, and performance on subsequent grammaticality judgment tests has often been barely above chance level. In three experiments the conditions were investigated under which rule- and similarity-based learning could be applied. Participants were exposed to exemplars of an artificial grammar under different (implicit and explicit) learning instructions. The analysis of receiver operating characteristics (ROC) during a final grammaticality judgment test revealed that explicit but not implicit learning led to rule knowledge. It also demonstrated that this knowledge base is built up gradually while similarity knowledge governed the initial state of learning. Together these results indicate that rule- and similarity-based mechanisms concur during AGL. Moreover, it could be speculated that two different rule processes might operate in parallel; bottom-up learning via gradual rule extraction and top-down learning via rule testing. Crucially, the latter is facilitated by performance feedback that encourages explicit hypothesis testing. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. Collaborative Working e-Learning Environments Supported by Rule-Based e-Tutor

    Directory of Open Access Journals (Sweden)

    Salaheddin Odeh

    2007-10-01

    Full Text Available Collaborative working environments for distance education sets a goal of convenience and an adaptation into our technologically advanced societies. To achieve this revolutionary new way of learning, environments must allow the different participants to communicate and coordinate with each other in a productive manner. Productivity and efficiency is obtained through synchronized communication between the different coordinating partners, which means that multiple users can execute an experiment simultaneously. Within this process, coordination can be accomplished by voice communication and chat tools. In recent times, multi-user environments have been successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat text tools, and multi-player games. Thus, understanding the ideas and the techniques behind these systems can be of great significance regarding the contribution of newer ideas to collaborative working e-learning environments. However, many problems still exist in distance learning and tele-education, such as not finding the proper assistance while performing the remote experiment. Therefore, the students become overwhelmed and the experiment will fail. In this paper, we are going to discuss a solution that enables students to obtain an automated help by either a human tutor or a rule-based e-tutor (embedded rule-based system for the purpose of student support in complex remote experimentative environments. The technical implementation of the system can be realized by using the powerful Microsoft .NET, which offers a complete integrated developmental environment (IDE with a wide collection of products and technologies. Once the system is developed, groups of students are independently able to coordinate and to execute the experiment at any time and from any place, organizing the work between them positively.

  12. A self-learning rule base for command following in dynamical systems

    Science.gov (United States)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  13. Research on key technology of the verification system of steel rule based on vision measurement

    Science.gov (United States)

    Jia, Siyuan; Wang, Zhong; Liu, Changjie; Fu, Luhua; Li, Yiming; Lu, Ruijun

    2018-01-01

    The steel rule plays an important role in quantity transmission. However, the traditional verification method of steel rule based on manual operation and reading brings about low precision and low efficiency. A machine vison based verification system of steel rule is designed referring to JJG1-1999-Verificaiton Regulation of Steel Rule [1]. What differentiates this system is that it uses a new calibration method of pixel equivalent and decontaminates the surface of steel rule. Experiments show that these two methods fully meet the requirements of the verification system. Measuring results strongly prove that these methods not only meet the precision of verification regulation, but also improve the reliability and efficiency of the verification system.

  14. Declarative Rule-based Safety for Robotic Perception Systems

    DEFF Research Database (Denmark)

    Mogensen, Johann Thor Ingibergsson; Kraft, Dirk; Schultz, Ulrik Pagh

    2017-01-01

    Mobile robots are used across many domains from personal care to agriculture. Working in dynamic open-ended environments puts high constraints on the robot perception system, which is critical for the safety of the system as a whole. To achieve the required safety levels the perception system needs...... to be certified, but no specific standards exist for computer vision systems, and the concept of safe vision systems remains largely unexplored. In this paper we present a novel domain-specific language that allows the programmer to express image quality detection rules for enforcing safety constraints...

  15. Permanent Discontinuance or Interruption in Manufacturing of Certain Drug or Biological Products. Final rule.

    Science.gov (United States)

    2015-07-08

    The Food and Drug Administration (FDA or the Agency) is amending its regulations to implement certain drug shortages provisions of the Federal Food, Drug, and Cosmetic Act (the FD&C Act), as amended by the Food and Drug Administration Safety and Innovation Act (FDASIA). The rule requires all applicants of covered approved drugs or biological products--including certain applicants of blood or blood components for transfusion and all manufacturers of covered drugs marketed without an approved application--to notify FDA electronically of a permanent discontinuance or an interruption in manufacturing of the product that is likely to lead to a meaningful disruption in supply (or a significant disruption in supply for blood or blood components) of the product in the United States.

  16. Information Based Productivity.

    Science.gov (United States)

    Bennett, Scott

    A digital project undertaken last year at Yale (Connecticut) offers an opportunity to explore productivity matters. The project aimed at improving the quality of library support and of student learning in one of the most heavily enrolled undergraduate courses at Yale, "Introduction to the History of Art, from Prehistory to the…

  17. Diversity of Rule-based Approaches: Classic Systems and Recent Applications

    Directory of Open Access Journals (Sweden)

    Grzegorz J. Nalepa

    2016-11-01

    Full Text Available Rules are a common symbolic model of knowledge. Rule-based systems share roots in cognitive science and artificial intelligence. In the former, they are mostly used in cognitive architectures; in the latter, they are developed in several domains including knowledge engineering and machine learning. This paper aims to give an overview of these issues with the focus on the current research perspective of artificial intelligence. Moreover, in this setting we discuss our results in the design of rule-based systems and their applications in context-aware and business intelligence systems.

  18. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    International Nuclear Information System (INIS)

    Wang, M; Hu, N Q; Qin, G J

    2011-01-01

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  19. Comparison of some classification algorithms based on deterministic and nondeterministic decision rules

    KAUST Repository

    Delimata, Paweł; Marszał-Paszek, Barbara; Moshkov, Mikhail; Paszek, Piotr; Skowron, Andrzej; Suraj, Zbigniew

    2010-01-01

    the considered algorithms extract from a given decision table efficiently some information about the set of rules. Next, this information is used by a decision-making procedure. The reported results of experiments show that the algorithms based on inhibitory

  20. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    Energy Technology Data Exchange (ETDEWEB)

    Wang, M; Hu, N Q; Qin, G J, E-mail: hnq@nudt.edu.cn, E-mail: wm198063@yahoo.com.cn [School of Mechatronic Engineering and Automation, National University of Defense Technology, ChangSha, Hunan, 410073 (China)

    2011-07-19

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  1. Design and performance of a rule-based controller in a naturally ventilated room

    OpenAIRE

    Marjanovic-Halburd, Ljiljana; Angelov, P.; Eftekhari, M. M.

    2003-01-01

    This paper reflects the final phase of the EPSRC project, and the PhD work of Marjanovic, on rule-based control in naturally ventilated buildings. Marjanovic is the second author. Eftekhari was her PhD supervisor.

  2. Rule-Based Analytic Asset Management for Space Exploration Systems (RAMSES), Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Payload Systems Inc. (PSI) and the Massachusetts Institute of Technology (MIT) were selected to jointly develop the Rule-based Analytic Asset Management for Space...

  3. Platform-based production development

    DEFF Research Database (Denmark)

    Bossen, Jacob; Brunoe, Thomas Ditlev; Nielsen, Kjeld

    2015-01-01

    Platforms as a means for applying modular thinking in product development is relatively well studied, but platforms in the production system has until now not been given much attention. With the emerging concept of platform-based co-development the importance of production platforms is though...

  4. Applicability of creep damage rules to a nickel-base heat-resistant alloy Hastelloy XR

    International Nuclear Information System (INIS)

    Tsuji, Hirokazu; Nakajima, Najime; Tanabe, Tatsuhiko; Nakasone, Yuji

    1992-01-01

    A series of constant load and temperature creep rupture tests and varying load and/or temperature creep rupture tests was carried out on a nickel-base heat-resistant alloy Hastelloy XR, which was developed for applications in the High-Temperature Engineering Test Reactor, at temperatures ranging from 850 to 1000deg C in order to examine the applicability of the conventional creep damage rules, i.e., the life fraction, the strain fraction and their mixed rules. The life fraction rule showed the best applicability of these three criteria. The good applicability of the rule was considered to result from the fact that the creep strength of Hastelloy XR was not strongly affected by the change of the chemical composition and/or the microstructure during exposure to the high-temperature simulated HTGR helium environment. In conclusion the life fraction rule is applicable in engineering design of high-temperature components made of Hastelloy XR. (orig.)

  5. Study of quark line selection rule (OZI rule) in the hadron processes. 3. Study of the OZI rule in production of φ and ω mesons in diffractive p N interactions at the energy of 70 GeV

    International Nuclear Information System (INIS)

    Balats, M.Ya.; Vavilov, D.V.; Viktorov, V.A.

    1996-01-01

    Ratio of cross sections for pφ- and pω-production in diffractive p N-interactions was measured with the Sphinx facility at the energy of E p = 70 GeV. Results of this work demonstrate significant OZI rule violation in proton-induced reactions. 12 refs., 8 figs

  6. A Fuzzy Rule-Based Expert System for Evaluating Intellectual Capital

    Directory of Open Access Journals (Sweden)

    Mohammad Hossein Fazel Zarandi

    2012-01-01

    Full Text Available A fuzzy rule-based expert system is developed for evaluating intellectual capital. A fuzzy linguistic approach assists managers to understand and evaluate the level of each intellectual capital item. The proposed fuzzy rule-based expert system applies fuzzy linguistic variables to express the level of qualitative evaluation and criteria of experts. Feasibility of the proposed model is demonstrated by the result of intellectual capital performance evaluation for a sample company.

  7. Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices

    OpenAIRE

    Lim, Suhwan; Bae, Jong-Ho; Eum, Jai-Ho; Lee, Sungtae; Kim, Chul-Heung; Kwon, Dongseok; Park, Byung-Gook; Lee, Jong-Ho

    2017-01-01

    In this paper, we propose a learning rule based on a back-propagation (BP) algorithm that can be applied to a hardware-based deep neural network (HW-DNN) using electronic devices that exhibit discrete and limited conductance characteristics. This adaptive learning rule, which enables forward, backward propagation, as well as weight updates in hardware, is helpful during the implementation of power-efficient and high-speed deep neural networks. In simulations using a three-layer perceptron net...

  8. Combination Rules for Morse-Based van der Waals Force Fields.

    Science.gov (United States)

    Yang, Li; Sun, Lei; Deng, Wei-Qiao

    2018-02-15

    In traditional force fields (FFs), van der Waals interactions have been usually described by the Lennard-Jones potentials. Conventional combination rules for the parameters of van der Waals (VDW) cross-termed interactions were developed for the Lennard-Jones based FFs. Here, we report that the Morse potentials were a better function to describe VDW interactions calculated by highly precise quantum mechanics methods. A new set of combination rules was developed for Morse-based FFs, in which VDW interactions were described by Morse potentials. The new set of combination rules has been verified by comparing the second virial coefficients of 11 noble gas mixtures. For all of the mixed binaries considered in this work, the combination rules work very well and are superior to all three other existing sets of combination rules reported in the literature. We further used the Morse-based FF by using the combination rules to simulate the adsorption isotherms of CH 4 at 298 K in four covalent-organic frameworks (COFs). The overall agreement is great, which supports the further applications of this new set of combination rules in more realistic simulation systems.

  9. Reservoir adaptive operating rules based on both of historical streamflow and future projections

    Science.gov (United States)

    Zhang, Wei; Liu, Pan; Wang, Hao; Chen, Jie; Lei, Xiaohui; Feng, Maoyuan

    2017-10-01

    Climate change is affecting hydrological variables and consequently is impacting water resources management. Historical strategies are no longer applicable under climate change. Therefore, adaptive management, especially adaptive operating rules for reservoirs, has been developed to mitigate the possible adverse effects of climate change. However, to date, adaptive operating rules are generally based on future projections involving uncertainties under climate change, yet ignoring historical information. To address this, we propose an approach for deriving adaptive operating rules considering both historical information and future projections, namely historical and future operating rules (HAFOR). A robustness index was developed by comparing benefits from HAFOR with benefits from conventional operating rules (COR). For both historical and future streamflow series, maximizations of both average benefits and the robustness index were employed as objectives, and four trade-offs were implemented to solve the multi-objective problem. Based on the integrated objective, the simulation-based optimization method was used to optimize the parameters of HAFOR. Using the Dongwushi Reservoir in China as a case study, HAFOR was demonstrated to be an effective and robust method for developing adaptive operating rules under the uncertain changing environment. Compared with historical or projected future operating rules (HOR or FPOR), HAFOR can reduce the uncertainty and increase the robustness for future projections, especially regarding results of reservoir releases and volumes. HAFOR, therefore, facilitates adaptive management in the context that climate change is difficult to predict accurately.

  10. Testing the performance of technical trading rules in the Chinese markets based on superior predictive test

    Science.gov (United States)

    Wang, Shan; Jiang, Zhi-Qiang; Li, Sai-Ping; Zhou, Wei-Xing

    2015-12-01

    Technical trading rules have a long history of being used by practitioners in financial markets. The profitable ability and efficiency of technical trading rules are yet controversial. In this paper, we test the performance of more than seven thousand traditional technical trading rules on the Shanghai Securities Composite Index (SSCI) from May 21, 1992 through June 30, 2013 and China Securities Index 300 (CSI 300) from April 8, 2005 through June 30, 2013 to check whether an effective trading strategy could be found by using the performance measurements based on the return and Sharpe ratio. To correct for the influence of the data-snooping effect, we adopt the Superior Predictive Ability test to evaluate if there exists a trading rule that can significantly outperform the benchmark. The result shows that for SSCI, technical trading rules offer significant profitability, while for CSI 300, this ability is lost. We further partition the SSCI into two sub-series and find that the efficiency of technical trading in sub-series, which have exactly the same spanning period as that of CSI 300, is severely weakened. By testing the trading rules on both indexes with a five-year moving window, we find that during the financial bubble from 2005 to 2007, the effectiveness of technical trading rules is greatly improved. This is consistent with the predictive ability of technical trading rules which appears when the market is less efficient.

  11. AN QUALITY BASED ENHANCEMENT OF USER DATA PROTECTION VIA FUZZY RULE BASED SYSTEMS IN CLOUD ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    R Poorva Devi

    2016-04-01

    Full Text Available So far, in cloud computing distinct customer is accessed and consumed enormous amount of services through web, offered by cloud service provider (CSP. However cloud is providing one of the services is, security-as-a-service to its clients, still people are terrified to use the service from cloud vendor. Number of solutions, security components and measurements are coming with the new scope for the cloud security issue, but 79.2% security outcome only obtained from the different scientists, researchers and other cloud based academy community. To overcome the problem of cloud security the proposed model that is, “Quality based Enhancing the user data protection via fuzzy rule based systems in cloud environment”, will helps to the cloud clients by the way of accessing the cloud resources through remote monitoring management (RMMM and what are all the services are currently requesting and consuming by the cloud users that can be well analyzed with Managed service provider (MSP rather than a traditional CSP. Normally, people are trying to secure their own private data by applying some key management and cryptographic based computations again it will direct to the security problem. In order to provide good quality of security target result by making use of fuzzy rule based systems (Constraint & Conclusion segments in cloud environment. By using this technique, users may obtain an efficient security outcome through the cloud simulation tool of Apache cloud stack simulator.

  12. Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis

    International Nuclear Information System (INIS)

    Li Qiang; Doi Kunio

    2006-01-01

    Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists detect various lesions in medical images. In CAD schemes, classifiers play a key role in achieving a high lesion detection rate and a low false-positive rate. Although many popular classifiers such as linear discriminant analysis and artificial neural networks have been employed in CAD schemes for reduction of false positives, a rule-based classifier has probably been the simplest and most frequently used one since the early days of development of various CAD schemes. However, with existing rule-based classifiers, there are major disadvantages that significantly reduce their practicality and credibility. The disadvantages include manual design, poor reproducibility, poor evaluation methods such as resubstitution, and a large overtraining effect. An automated rule-based classifier with a minimized overtraining effect can overcome or significantly reduce the extent of the above-mentioned disadvantages. In this study, we developed an 'optimal' method for the selection of cutoff thresholds and a fully automated rule-based classifier. Experimental results performed with Monte Carlo simulation and a real lung nodule CT data set demonstrated that the automated threshold selection method can completely eliminate overtraining effect in the procedure of cutoff threshold selection, and thus can minimize overall overtraining effect in the constructed rule-based classifier. We believe that this threshold selection method is very useful in the construction of automated rule-based classifiers with minimized overtraining effect

  13. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  14. Knowledge rule base for the beam optics program TRACE 3-D

    International Nuclear Information System (INIS)

    Gillespie, G.H.; Van Staagen, P.K.; Hill, B.W.

    1993-01-01

    An expert system type of knowledge rule base has been developed for the input parameters used by the particle beam transport program TRACE 3-D. The goal has been to provide the program's user with adequate on-screen information to allow him to initially set up a problem with minimal open-quotes off-lineclose quotes calculations. The focus of this work has been in developing rules for the parameters which define the beam line transport elements. Ten global parameters, the particle mass and charge, beam energy, etc., are used to provide open-quotes expertclose quotes estimates of lower and upper limits for each of the transport element parameters. For example, the limits for the field strength of the quadrupole element are based on a water-cooled, iron-core electromagnet with dimensions derived from practical engineering constraints, and the upper limit for the effective length is scaled with the particle momenta so that initially parallel trajectories do not cross the axis inside the magnet. Limits for the quadrupole doublet and triplet parameters incorporate these rules and additional rules based on stable FODO lattices and bidirectional focusing requirements. The structure of the rule base is outlined and examples for the quadrupole singlet, doublet and triplet are described. The rule base has been implemented within the Shell for Particle Accelerator Related Codes (SPARC) graphical user interface (GUI)

  15. A two-stage stochastic rule-based model to determine pre-assembly buffer content

    Science.gov (United States)

    Gunay, Elif Elcin; Kula, Ufuk

    2018-01-01

    This study considers instant decision-making needs of the automobile manufactures for resequencing vehicles before final assembly (FA). We propose a rule-based two-stage stochastic model to determine the number of spare vehicles that should be kept in the pre-assembly buffer to restore the altered sequence due to paint defects and upstream department constraints. First stage of the model decides the spare vehicle quantities, where the second stage model recovers the scrambled sequence respect to pre-defined rules. The problem is solved by sample average approximation (SAA) algorithm. We conduct a numerical study to compare the solutions of heuristic model with optimal ones and provide following insights: (i) as the mismatch between paint entrance and scheduled sequence decreases, the rule-based heuristic model recovers the scrambled sequence as good as the optimal resequencing model, (ii) the rule-based model is more sensitive to the mismatch between the paint entrance and scheduled sequences for recovering the scrambled sequence, (iii) as the defect rate increases, the difference in recovery effectiveness between rule-based heuristic and optimal solutions increases, (iv) as buffer capacity increases, the recovery effectiveness of the optimization model outperforms heuristic model, (v) as expected the rule-based model holds more inventory than the optimization model.

  16. A Web-Based Rice Plant Expert System Using Rule-Based Reasoning

    Directory of Open Access Journals (Sweden)

    Anton Setiawan Honggowibowo

    2009-12-01

    Full Text Available Rice plants can be attacked by various kinds of diseases which are possible to be determined from their symptoms. However, it is to recognize that to find out the exact type of disease, an agricultural expert’s opinion is needed, meanwhile the numbers of agricultural experts are limited and there are too many problems to be solved at the same time. This makes a system with a capability as an expert is required. This system must contain the knowledge of the diseases and symptom of rice plants as an agricultural expert has to have. This research designs a web-based expert system using rule-based reasoning. The rule are modified from the method of forward chaining inference and backward chaining in order to to help farmers in the rice plant disease diagnosis. The web-based rice plants disease diagnosis expert system has the advantages to access and use easily. With web-based features inside, it is expected that the farmer can accesse the expert system everywhere to overcome the problem to diagnose rice diseases.

  17. Hedging Rules for Water Supply Reservoir Based on the Model of Simulation and Optimization

    Directory of Open Access Journals (Sweden)

    Yi Ji

    2016-06-01

    Full Text Available This study proposes a hedging rule model which is composed of a two-period reservior operation model considering the damage depth and hedging rule parameter optimization model. The former solves hedging rules based on a given poriod’s water supply weighting factor and carryover storage target, while the latter optimization model is used to optimize the weighting factor and carryover storage target based on the hedging rules. The coupling model gives the optimal poriod’s water supply weighting factor and carryover storage target to guide release. The conclusions achieved from this study as follows: (1 the water supply weighting factor and carryover storage target have a direct impact on the three elements of the hedging rule; (2 parameters can guide reservoirs to supply water reasonably after optimization of the simulation and optimization model; and (3 in order to verify the utility of the hedging rule, the Heiquan reservoir is used as a case study and particle swarm optimization algorithm with a simulation model is adopted for optimizing the parameter. The results show that the proposed hedging rule can improve the operation performances of the water supply reservoir.

  18. Implementasi Rule Based Expert Systems untuk Realtime Monitoring Penyelesaian Perkara Pidana Menggunakan Teknologi Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mar Fuah

    2017-05-01

    Full Text Available One of the problems in the criminal case completions is that the difficulty of making decision to estimate when the settlement of the case file will be fulfilled. It is caused by the number of case files handled and detention time changing. Therefore, the fast and accurate information is needed. The research aims to develop a monitoring system tracking and tracking of scheduling rules using Rule Based Expert Systems method with 17 rules, and supported by Radio Frequency Identification technology (RFID in the form of computer applications. Based on the output of the system, an analysis is performed in the criminal case settlement process with a set of IF-THEN rules. The RFID reader read the data of case files through radio wave signals emitted by the antenna toward active-Tag attached in the criminal case file. The system is designed to monitor the tracking and tracing of RFID-based scheduling rules in realtime way that was built in the form of computer application in accordance with the system design. This study results in no failure in reading active tags by the RFID reader to detect criminal case files that had been examined. There were many case files handled in three different location, they were the constabulary, prosecutor, and judges of district court and RFID was able to identify them simultaneously. So, RFID supports the implementation of Rule Based Expert Systems very much for realtime monitoring in criminal case accomplishment.

  19. Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode.

    Science.gov (United States)

    Scheib, Jean P P; Stoll, Sarah; Thürmer, J Lukas; Randerath, Jennifer

    2018-01-01

    The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous

  20. Fusion of Thresholding Rules During Wavelet-Based Noisy Image Compression

    Directory of Open Access Journals (Sweden)

    Bekhtin Yury

    2016-01-01

    Full Text Available The new method for combining semisoft thresholding rules during wavelet-based data compression of images with multiplicative noise is suggested. The method chooses the best thresholding rule and the threshold value using the proposed criteria which provide the best nonlinear approximations and take into consideration errors of quantization. The results of computer modeling have shown that the suggested method provides relatively good image quality after restoration in the sense of some criteria such as PSNR, SSIM, etc.

  1. TRICARE revision to CHAMPUS DRG-based payment system, pricing of hospital claims. Final rule.

    Science.gov (United States)

    2014-05-21

    This Final rule changes TRICARE's current regulatory provision for inpatient hospital claims priced under the DRG-based payment system. Claims are currently priced by using the rates and weights that are in effect on a beneficiary's date of admission. This Final rule changes that provision to price such claims by using the rates and weights that are in effect on a beneficiary's date of discharge.

  2. Application of rule-based data mining techniques to real time ATLAS Grid job monitoring data

    CERN Document Server

    Ahrens, R; The ATLAS collaboration; Kalinin, S; Maettig, P; Sandhoff, M; dos Santos, T; Volkmer, F

    2012-01-01

    The Job Execution Monitor (JEM) is a job-centric grid job monitoring software developed at the University of Wuppertal and integrated into the pilot-based “PanDA” job brokerage system leveraging physics analysis and Monte Carlo event production for the ATLAS experiment on the Worldwide LHC Computing Grid (WLCG). With JEM, job progress and grid worker node health can be supervised in real time by users, site admins and shift personnel. Imminent error conditions can be detected early and countermeasures can be initiated by the Job’s owner immideatly. Grid site admins can access aggregated data of all monitored jobs to infer the site status and to detect job and Grid worker node misbehaviour. Shifters can use the same aggregated data to quickly react to site error conditions and broken production tasks. In this work, the application of novel data-centric rule based methods and data-mining techniques to the real time monitoring data is discussed. The usage of such automatic inference techniques on monitorin...

  3. Attribute Index and Uniform Design Based Multiobjective Association Rule Mining with Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    2013-01-01

    Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  4. Attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm.

    Science.gov (United States)

    Zhang, Jie; Wang, Yuping; Feng, Junhong

    2013-01-01

    In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.

  5. Using an improved association rules mining optimization algorithm in web-based mobile-learning system

    Science.gov (United States)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

    Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

  6. Evaluation of Rule-based Modularization in Model Transformation Languages illustrated with ATL

    NARCIS (Netherlands)

    Ivanov, Ivan; van den Berg, Klaas; Jouault, Frédéric

    This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are identified on the base of the relations between source and target metamodels and on the base of generic transformation

  7. A Rule-Based Model for Bankruptcy Prediction Based on an Improved Genetic Ant Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Yudong Zhang

    2013-01-01

    Full Text Available In this paper, we proposed a hybrid system to predict corporate bankruptcy. The whole procedure consists of the following four stages: first, sequential forward selection was used to extract the most important features; second, a rule-based model was chosen to fit the given dataset since it can present physical meaning; third, a genetic ant colony algorithm (GACA was introduced; the fitness scaling strategy and the chaotic operator were incorporated with GACA, forming a new algorithm—fitness-scaling chaotic GACA (FSCGACA, which was used to seek the optimal parameters of the rule-based model; and finally, the stratified K-fold cross-validation technique was used to enhance the generalization of the model. Simulation experiments of 1000 corporations’ data collected from 2006 to 2009 demonstrated that the proposed model was effective. It selected the 5 most important factors as “net income to stock broker’s equality,” “quick ratio,” “retained earnings to total assets,” “stockholders’ equity to total assets,” and “financial expenses to sales.” The total misclassification error of the proposed FSCGACA was only 7.9%, exceeding the results of genetic algorithm (GA, ant colony algorithm (ACA, and GACA. The average computation time of the model is 2.02 s.

  8. Rules-based analysis with JBoss Drools: adding intelligence to automation

    International Nuclear Information System (INIS)

    Ley, E. de; Jacobs, D.

    2012-01-01

    Rule engines are specialized software systems for applying conditional actions (if/then rules) on data. They are also known as 'production rule systems'. Rules engines are less-known as software technology than the traditional procedural, object-oriented, scripting or dynamic development languages. This is a pity, as their usage may offer an important enrichment to a development toolbox. JBoss Drools is an open-source rules engine that can easily be embedded in any Java application. Through an integration in our Passerelle process automation suite, we have been able to provide advanced solutions for intelligent process automation, complex event processing, system monitoring and alarming, automated repair etc. This platform has been proven for many years as an automated diagnosis and repair engine for Belgium's largest telecom provider, and it is being piloted at Synchrotron Soleil for device monitoring and alarming. After an introduction to rules engines in general and JBoss Drools in particular, we will present its integration in a solution platform, some important principles and a practical use case. (authors)

  9. Verification of product design using regulation knowledge base and Web services

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ik June [KAERI, Daejeon (Korea, Republic of); Lee, Jae Chul; Mun Du Hwan [Kyungpook National University, Daegu (Korea, Republic of); Kim, Byung Chul [Dong-A University, Busan (Korea, Republic of); Hwang, Jin Sang [PartDB Co., Ltd., Daejeom (Korea, Republic of); Lim, Chae Ho [Korea Institute of Industrial Technology, Incheon (Korea, Republic of)

    2015-11-15

    Since product regulations contain important rules or codes that manufacturers must follow, automatic verification of product design with the regulations related to a product is necessary. For this, this study presents a new method for the verification of product design using regulation knowledge base and Web services. Regulation knowledge base consisting of product ontology and rules was built with a hybrid technique combining ontology and programming languages. Web service for design verification was developed ensuring the flexible extension of knowledge base. By virtue of two technical features, design verification is served to various products while the change of system architecture is minimized.

  10. Verification of product design using regulation knowledge base and Web services

    International Nuclear Information System (INIS)

    Kim, Ik June; Lee, Jae Chul; Mun Du Hwan; Kim, Byung Chul; Hwang, Jin Sang; Lim, Chae Ho

    2015-01-01

    Since product regulations contain important rules or codes that manufacturers must follow, automatic verification of product design with the regulations related to a product is necessary. For this, this study presents a new method for the verification of product design using regulation knowledge base and Web services. Regulation knowledge base consisting of product ontology and rules was built with a hybrid technique combining ontology and programming languages. Web service for design verification was developed ensuring the flexible extension of knowledge base. By virtue of two technical features, design verification is served to various products while the change of system architecture is minimized.

  11. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

    Science.gov (United States)

    Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

    2013-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

  12. Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

    Science.gov (United States)

    Chylek, Lily A; Harris, Leonard A; Tung, Chang-Shung; Faeder, James R; Lopez, Carlos F; Hlavacek, William S

    2014-01-01

    Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

  13. Post-decomposition optimizations using pattern matching and rule-based clustering for multi-patterning technology

    Science.gov (United States)

    Wang, Lynn T.-N.; Madhavan, Sriram

    2018-03-01

    A pattern matching and rule-based polygon clustering methodology with DFM scoring is proposed to detect decomposition-induced manufacturability detractors and fix the layout designs prior to manufacturing. A pattern matcher scans the layout for pre-characterized patterns from a library. If a pattern were detected, rule-based clustering identifies the neighboring polygons that interact with those captured by the pattern. Then, DFM scores are computed for the possible layout fixes: the fix with the best score is applied. The proposed methodology was applied to two 20nm products with a chip area of 11 mm2 on the metal 2 layer. All the hotspots were resolved. The number of DFM spacing violations decreased by 7-15%.

  14. THE RULE OF TRANSPARENCY: as an element of democratization in the journalism production process

    Directory of Open Access Journals (Sweden)

    Marta Regina Maia

    2008-12-01

    Full Text Available This article´s purpose is to discuss the need for improving theknowledge of readers, listeners, TV spectators and people whouse the Internet, mainly of the information process, focusing onthe communication media in Brazil. Among the possibilities, itis important to understand information production behind thescenes, which is possible with a Rule of Transparency, one of theintellectual principles of the science of reporting called “Disciplineof Verification” by journalists Bill Kovach and Tom Rosenstiel. The existence of a place that officially relates the making of, through books, blogs, or other means of communication, contributes to the democratization of the access to the process used by journalists who are most of the time unable to speak out and publish their ideas because of the editorial demands or even due to the lack of time and space.

  15. The rule of transparency: as an element of democratization in the journalism production process

    Directory of Open Access Journals (Sweden)

    Marta Regina Maia

    2008-12-01

    Full Text Available This article´s purpose is to discuss the need for improving the knowledge of readers, listeners, TV spectators and people who use the Internet, mainly of the information process, focusing on the communication media in Brazil. Among the possibilities, it is important to understand information production behind the scenes, which is possible with a Rule of Transparency, one of the intellectual principles of the science of reporting called “Discipline of Verification” by journalists Bill Kovach and Tom Rosenstiel. The existence of a place that officially relates the making of, through books, blogs, or other means of communication, contributes to the democratization of the access to the process used by journalists who are most of the time unable to speak out and publish their ideas because of the editorial demands or even due to the lack of time and space.

  16. Situation-assessment and decision-aid production-rule analysis system for nuclear plant monitoring and emergency preparedness

    International Nuclear Information System (INIS)

    Gvillo, D.; Ragheb, M.; Parker, M.; Swartz, S.

    1987-01-01

    A Production-Rule Analysis System is developed for Nuclear Plant Monitoring. The signals generated by the Zion-1 Plant are considered. A Situation-Assessment and Decision-Aid capability is provided for monitoring the integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems. A total of 41 signals are currently fed as facts to an Inference Engine functioning in the backward-chaining mode and built along the same structure as the E-Mycin system. The Goal-Tree constituting the Knowledge Base was generated using a representation in the form of Fault Trees deduced from plant procedures information. The system is constructed in support of the Data Analysis and Emergency Preparedness tasks at the Illinois Radiological Emergency Assessment Center (REAC)

  17. Situation-Assessment And Decision-Aid Production-Rule Analysis System For Nuclear Plant Monitoring And Emergency Preparedness

    Science.gov (United States)

    Gvillo, D.; Ragheb, M.; Parker, M.; Swartz, S.

    1987-05-01

    A Production-Rule Analysis System is developed for Nuclear Plant Monitoring. The signals generated by the Zion-1 Plant are considered. A Situation-Assessment and Decision-Aid capability is provided for monitoring the integrity of the Plant Radiation, the Reactor Coolant, the Fuel Clad, and the Containment Systems. A total of 41 signals are currently fed as facts to an Inference Engine functioning in the backward-chaining mode and built along the same structure as the E-Mycin system. The Goal-Tree constituting the Knowledge Base was generated using a representation in the form of Fault Trees deduced from plant procedures information. The system is constructed in support of the Data Analysis and Emergency Preparedness tasks at the Illinois Radiological Emergency Assessment Center (REAC).

  18. Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization

    Science.gov (United States)

    Misirli, Goksel; Cavaliere, Matteo; Waites, William; Pocock, Matthew; Madsen, Curtis; Gilfellon, Owen; Honorato-Zimmer, Ricardo; Zuliani, Paolo; Danos, Vincent; Wipat, Anil

    2016-01-01

    Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general. Availability and implementation: The annotation ontology for rule-based models can be found at http

  19. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  20. Automated implementation of rule-based expert systems with neural networks for time-critical applications

    Science.gov (United States)

    Ramamoorthy, P. A.; Huang, Song; Govind, Girish

    1991-01-01

    In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

  1. Rule-based category learning in children: the role of age and executive functioning.

    Directory of Open Access Journals (Sweden)

    Rahel Rabi

    Full Text Available Rule-based category learning was examined in 4-11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning.

  2. Agile Service Development: A Rule-Based Method Engineering Approach

    NARCIS (Netherlands)

    dr. Martijn Zoet; Stijn Hoppenbrouwers; Inge van de Weerd; Johan Versendaal

    2011-01-01

    Agile software development has evolved into an increasingly mature software development approach and has been applied successfully in many software vendors’ development departments. In this position paper, we address the broader agile service development. Based on method engineering principles we

  3. Automatic detection of esophageal pressure events. Is there an alternative to rule-based criteria?

    DEFF Research Database (Denmark)

    Kruse-Andersen, S; Rütz, K; Kolberg, Jens Godsk

    1995-01-01

    of relevant pressure peaks at the various recording levels. Until now, this selection has been performed entirely by rule-based systems, requiring each pressure deflection to fit within predefined rigid numerical limits in order to be detected. However, due to great variations in the shapes of the pressure...... curves generated by muscular contractions, rule-based criteria do not always select the pressure events most relevant for further analysis. We have therefore been searching for a new concept for automatic event recognition. The present study describes a new system, based on the method of neurocomputing.......79-0.99 and accuracies of 0.89-0.98, depending on the recording level within the esophageal lumen. The neural networks often recognized peaks that clearly represented true contractions but that had been rejected by a rule-based system. We conclude that neural networks have potentials for automatic detections...

  4. Sensor-based activity recognition using extended belief rule-based inference methodology.

    Science.gov (United States)

    Calzada, A; Liu, J; Nugent, C D; Wang, H; Martinez, L

    2014-01-01

    The recently developed extended belief rule-based inference methodology (RIMER+) recognizes the need of modeling different types of information and uncertainty that usually coexist in real environments. A home setting with sensors located in different rooms and on different appliances can be considered as a particularly relevant example of such an environment, which brings a range of challenges for sensor-based activity recognition. Although RIMER+ has been designed as a generic decision model that could be applied in a wide range of situations, this paper discusses how this methodology can be adapted to recognize human activities using binary sensors within smart environments. The evaluation of RIMER+ against other state-of-the-art classifiers in terms of accuracy, efficiency and applicability was found to be significantly relevant, specially in situations of input data incompleteness, and it demonstrates the potential of this methodology and underpins the basis to develop further research on the topic.

  5. An Enhanced Rule-Based Web Scanner Based on Similarity Score

    Directory of Open Access Journals (Sweden)

    LEE, M.

    2016-08-01

    Full Text Available This paper proposes an enhanced rule-based web scanner in order to get better accuracy in detecting web vulnerabilities than the existing tools, which have relatively high false alarm rate when the web pages are installed in unconventional directory paths. Using the proposed matching method based on similarity score, the proposed scheme can determine whether two pages have the same vulnerabilities or not. With this method, the proposed scheme is able to figure out the target web pages are vulnerable by comparing them to the web pages that are known to have vulnerabilities. We show the proposed scanner reduces 12% false alarm rate compared to the existing well-known scanner through the performance evaluation via various experiments. The proposed scheme is especially helpful in detecting vulnerabilities of the web applications which come from well-known open-source web applications after small customization, which happens frequently in many small-sized companies.

  6. A Belief Rule-Based (BRB) Decision Support System for Assessing Clinical Asthma Suspicion

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Hossain, Emran; Khalid, Md. Saifuddin

    2014-01-01

    conditions of uncertainty. The Belief Rule-Based Inference Methodology Using the Evidential Reasoning (RIMER) approach was adopted to develop this expert system; which is named the Belief Rule-Based Expert System (BRBES). The system can handle various types of uncertainty in knowledge representation...... and inference procedures. The knowledge base of this system was constructed by using real patient data and expert opinion. Practical case studies were used to validate the system. The system-generated results are more effective and reliable in terms of accuracy than the results generated by a manual system....

  7. Rule-based modularization in model transformation languages illustrated with ATL

    NARCIS (Netherlands)

    Ivanov, Ivan; van den Berg, Klaas; Jouault, Frédéric

    2007-01-01

    This paper studies ways for modularizing transformation definitions in current rule-based model transformation languages. Two scenarios are shown in which the modular units are identified on the basis of relations between source and target metamodels and on the base of generic transformation

  8. ABOUT CLINICAL EXPERT SYSTEM BASED ON RULES USING DATA MINING TECHNOLOGY

    Directory of Open Access Journals (Sweden)

    V. P. Martsenyuk

    2015-05-01

    Full Text Available In the work the topics of software implementation of rule induction method based on sequential covering algorithm are considered. Such approach allows us to develop clinical decision support system. The project is implemented within Netbeans IDE based on Java-classes.

  9. A comparison between model and rule based control of a periodic activated sludge process

    DEFF Research Database (Denmark)

    Isaacs, Steven Howard; Thornberg, D.

    1997-01-01

    Two strategies for control of nitrogen removal in an alternating activated sludge plant are compared. One is based on simple model predictions determining the cycle length at the beginning of each cycle. The other is based on simple rules relating present ammonia and nitrate concentrations. Both ...

  10. DEVELOP-FPS: a First Person Shooter Development Tool for Rule-based Scripts

    Directory of Open Access Journals (Sweden)

    Bruno Correia

    2012-09-01

    Full Text Available We present DEVELOP-FPS, a software tool specially designed for the development of First Person Shooter (FPS players controlled by Rule Based Scripts. DEVELOP-FPS may be used by FPS developers to create, debug, maintain and compare rule base player behaviours, providing a set of useful functionalities: i for an easy preparation of the right scenarios for game debugging and testing; ii for controlling the game execution: users can stop and resume the game execution at any instant, monitoring and controlling every player in the game, monitoring the state of each player, their rule base activation, being able to issue commands to control their behaviour; and iii to automatically run a certain number of game executions and collect data in order to evaluate and compare the players performance along a sufficient number of similar experiments.

  11. Probabilistic based design rules for intersystem LOCAS in ABWR piping

    International Nuclear Information System (INIS)

    Ware, A.G.; Wesley, D.A.

    1993-01-01

    A methodology has been developed for probability-based standards for low-pressure piping systems that are attached to the reactor coolant loops of advanced light water reactors (ALWRs) which could experience reactor coolant loop temperatures and pressures because of multiple isolation valve failures. This accident condition is called an intersystem loss-of-coolant accident (ISLOCA). The methodology was applied to various sizes of carbon and stainless steel piping designed to advanced boiling water reactor (ABWR) temperatures and pressures

  12. Criterion learning in rule-based categorization: simulation of neural mechanism and new data.

    Science.gov (United States)

    Helie, Sebastien; Ell, Shawn W; Filoteo, J Vincent; Maddox, W Todd

    2015-04-01

    In perceptual categorization, rule selection consists of selecting one or several stimulus-dimensions to be used to categorize the stimuli (e.g., categorize lines according to their length). Once a rule has been selected, criterion learning consists of defining how stimuli will be grouped using the selected dimension(s) (e.g., if the selected rule is line length, define 'long' and 'short'). Very little is known about the neuroscience of criterion learning, and most existing computational models do not provide a biological mechanism for this process. In this article, we introduce a new model of rule learning called Heterosynaptic Inhibitory Criterion Learning (HICL). HICL includes a biologically-based explanation of criterion learning, and we use new category-learning data to test key aspects of the model. In HICL, rule selective cells in prefrontal cortex modulate stimulus-response associations using pre-synaptic inhibition. Criterion learning is implemented by a new type of heterosynaptic error-driven Hebbian learning at inhibitory synapses that uses feedback to drive cell activation above/below thresholds representing ionic gating mechanisms. The model is used to account for new human categorization data from two experiments showing that: (1) changing rule criterion on a given dimension is easier if irrelevant dimensions are also changing (Experiment 1), and (2) showing that changing the relevant rule dimension and learning a new criterion is more difficult, but also facilitated by a change in the irrelevant dimension (Experiment 2). We conclude with a discussion of some of HICL's implications for future research on rule learning. Copyright © 2015 Elsevier Inc. All rights reserved.

  13. Under What Conditions Do Rules-Based and Capability-Based Management Modes Dominate?

    Directory of Open Access Journals (Sweden)

    Lukas Michel

    2018-04-01

    Full Text Available Despite real changes in the work place and the negative consequences of prevailing hierarchical structures with rigid management systems, little attention has yet been paid to shifting management modes to accommodate the dynamics of the external environment, particularly when a firm’s operating environment demands a high degree of flexibility. Building on the resource-based view as a basis for competitive advantage, we posit that differences in the stability of an organization’s environment and the degree of managerial control explain variations in the management mode used in firms. Unlike other studies which mainly focus on either the dynamics of the external environment or management control, we have developed a theoretical model combining both streams of research, in a context frame to describe under what conditions firms engage in rules-based, change-based, engagement-based and capability-based management modes. To test our theoretical framework, we conducted a survey with 54 firms in various industries and nations on how their organizations cope with a dynamic environment and what management style they used in response. Our study reveals that the appropriate mode can be determined by analyzing purpose, motivation, knowledge and information, as well as the degree of complexity, volatility and uncertainty the firm is exposed to. With our framework, we attempt to advance the understanding of when organizations should adapt their management style to the changing business environment.

  14. A Belief Rule Based Expert System to Assess Mental Disorder under Uncertainty

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Afif Monrat, Ahmed; Hasan, Mamun

    2016-01-01

    to ignorance, incompleteness, and randomness. So, a belief rule-based expert system (BRBES) has been designed and developed with the capability of handling the uncertainties mentioned. Evidential reasoning works as the inference engine and the belief rule base as the knowledge representation schema......Mental disorder is a change of mental or behavioral pattern that causes sufferings and impairs the ability to function in ordinary life. In psychopathology, the assessment methods of mental disorder contain various types of uncertainties associated with signs and symptoms. This study identifies...

  15. Rule-based learning of regular past tense in children with specific language impairment.

    Science.gov (United States)

    Smith-Lock, Karen M

    2015-01-01

    The treatment of children with specific language impairment was used as a means to investigate whether a single- or dual-mechanism theory best conceptualizes the acquisition of English past tense. The dual-mechanism theory proposes that regular English past-tense forms are produced via a rule-based process whereas past-tense forms of irregular verbs are stored in the lexicon. Single-mechanism theories propose that both regular and irregular past-tense verbs are stored in the lexicon. Five 5-year-olds with specific language impairment received treatment for regular past tense. The children were tested on regular past-tense production and third-person singular "s" twice before treatment and once after treatment, at eight-week intervals. Treatment consisted of one-hour play-based sessions, once weekly, for eight weeks. Crucially, treatment focused on different lexical items from those in the test. Each child demonstrated significant improvement on the untreated past-tense test items after treatment, but no improvement on the untreated third-person singular "s". Generalization to untreated past-tense verbs could not be attributed to a frequency effect or to phonological similarity of trained and tested items. It is argued that the results are consistent with a dual-mechanism theory of past-tense inflection.

  16. Consumer-based product profiling

    DEFF Research Database (Denmark)

    Giacalone, Davide; Ribeiro, Leticia Machado; Frøst, Michael Bom

    2013-01-01

    Napping® is an inexpensive and rapid method for sensory characterization, suitable for both trained and untrained subjects. In the study presented, the method was applied on 9 specialty beers. Subjects were 17 consumers without any training as sensory panelists, of whom 8 were beer experts and 9 ...... for sensory characterization, with the advantage of providing a product characterization based on consumer descriptions, thus better reflecting consumers’ experience with the product....

  17. Development of a rule-based diagnostic platform on an object-oriented expert system shell

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming; Seong, Poong Hyun

    2016-01-01

    Highlights: • Multilevel Flow Model represents system knowledge as a domain map in expert system. • Rule-based fault diagnostic expert system can identify root cause via a causal chain. • Rule-based fault diagnostic expert system can be used for fault simulation training. - Abstract: This paper presents the development and implementation of a real-time rule-based diagnostic platform. The knowledge is acquired from domain experts and textbooks and the design of the fault diagnosis expert system was performed in the following ways: (i) establishing of corresponding classes and instances to build the domain map, (ii) creating of generic fault models based on events, and (iii) building of diagnostic reasoning based on rules. Knowledge representation is a complicated issue of expert systems. One highlight of this paper is that the Multilevel Flow Model has been used to represent the knowledge, which composes the domain map within the expert system as well as providing a concise description of the system. The developed platform is illustrated using the pressure safety system of a pressurized water reactor as an example of the simulation test bed; the platform is developed using the commercial and industrially validated software G2. The emulation test was conducted and it has been proven that the fault diagnosis expert system can identify the faults correctly and in a timely way; this system can be used as a simulation-based training tool to assist operators to make better decisions.

  18. Techniques and implementation of the embedded rule-based expert system using Ada

    Science.gov (United States)

    Liberman, Eugene M.; Jones, Robert E.

    1991-01-01

    Ada is becoming an increasingly popular programming language for large Government-funded software projects. Ada with its portability, transportability, and maintainability lends itself well to today's complex programming environment. In addition, expert systems have also assured a growing role in providing human-like reasoning capability and expertise for computer systems. The integration of expert system technology with Ada programming language, specifically a rule-based expert system using an ART-Ada (Automated Reasoning Tool for Ada) system shell is discussed. The NASA Lewis Research Center was chosen as a beta test site for ART-Ada. The test was conducted by implementing the existing Autonomous Power EXpert System (APEX), a Lisp-base power expert system, in ART-Ada. Three components, the rule-based expert system, a graphics user interface, and communications software make up SMART-Ada (Systems fault Management with ART-Ada). The main objective, to conduct a beta test on the ART-Ada rule-based expert system shell, was achieved. The system is operational. New Ada tools will assist in future successful projects. ART-Ada is one such tool and is a viable alternative to the straight Ada code when an application requires a rule-based or knowledge-based approach.

  19. Inheritance rules for Hierarchical Metadata Based on ISO 19115

    Science.gov (United States)

    Zabala, A.; Masó, J.; Pons, X.

    2012-04-01

    registry is complete for each metadata hierarchical level, but at the implementation level most of the metadata elements are not stored at both levels but only at more generic one. This communication defines a metadata system that covers 4 levels, describes which metadata has to support series-layer inheritance and in which way, and how hierarchical levels are defined and stored. Metadata elements are classified according to the type of inheritance between products, series, tiles and the datasets. It explains the metadata elements classification and exemplifies it using core metadata elements. The communication also presents a metadata viewer and edition tool that uses the described model to propagate metadata elements and to show to the user a complete set of metadata for each level in a transparent way. This tool is integrated in the MiraMon GIS software.

  20. An expert system design to diagnose cancer by using a new method reduced rule base.

    Science.gov (United States)

    Başçiftçi, Fatih; Avuçlu, Emre

    2018-04-01

    A Medical Expert System (MES) was developed which uses Reduced Rule Base to diagnose cancer risk according to the symptoms in an individual. A total of 13 symptoms were used. With the new MES, the reduced rules are controlled instead of all possibilities (2 13 = 8192 different possibilities occur). By controlling reduced rules, results are found more quickly. The method of two-level simplification of Boolean functions was used to obtain Reduced Rule Base. Thanks to the developed application with the number of dynamic inputs and outputs on different platforms, anyone can easily test their own cancer easily. More accurate results were obtained considering all the possibilities related to cancer. Thirteen different risk factors were determined to determine the type of cancer. The truth table produced in our study has 13 inputs and 4 outputs. The Boolean Function Minimization method is used to obtain less situations by simplifying logical functions. Diagnosis of cancer quickly thanks to control of the simplified 4 output functions. Diagnosis made with the 4 output values obtained using Reduced Rule Base was found to be quicker than diagnosis made by screening all 2 13 = 8192 possibilities. With the improved MES, more probabilities were added to the process and more accurate diagnostic results were obtained. As a result of the simplification process in breast and renal cancer diagnosis 100% diagnosis speed gain, in cervical cancer and lung cancer diagnosis rate gain of 99% was obtained. With Boolean function minimization, less number of rules is evaluated instead of evaluating a large number of rules. Reducing the number of rules allows the designed system to work more efficiently and to save time, and facilitates to transfer the rules to the designed Expert systems. Interfaces were developed in different software platforms to enable users to test the accuracy of the application. Any one is able to diagnose the cancer itself using determinative risk factors. Thereby

  1. Sistem Evaluasi Jamunan Mutu Menggunakan Rule Based System Untuk Monitoring Mutu Perguruan Tinggi

    Directory of Open Access Journals (Sweden)

    Sri Hartono

    2017-05-01

    Full Text Available The needs for continuous quality improvement resulting in the more complex. The research aims to develop system of quality assurance evaluation using rule based system to monitor the quality of higher education. This process of the research begins by documenting the daily activity of study program which consists of lecturer data, research data, service data, staff data, student data, and infrastructure data into a database. The data were evaluated by using rule based system  by adopting rules on quality standards of study program of National Accreditation Board for Higher Education as the knowledge base. Evaluation process was carried out by using the forward chaining methods by matching the existing data to the knowledge base to determine the quality status of each quality standard. While the reccomendation process was carried out by using the backward chaining methods by matching the results of quality status to the desired projection of quality status to determine the nearest target which can be achieved. The result of the research is system of quality assurance evaluation with rule based system that is capable of producing an output system in the form of internal evaluation report and recommendation system that can be used to monitor the quality of higher education.

  2. Spin alignment and violation of the OZI rule in exclusive ω and φ production in pp collisions

    NARCIS (Netherlands)

    Adolph, C.; Akhunzyanov, R.; Alexeev, M. G.; Alexeev, G. D.; Amoroso, A.; Andrieux, V.; Anosov, V.; Austregesilo, A.; Badełek, B.; Balestra, F.; Barth, J.; Baum, G.; Beck, R.; Bedfer, Y.; Berlin, A.; Bernhard, J.; Bicker, K.; Bieling, J.; Birsa, R.; Bisplinghoff, J.; Bodlak, M.; Boer, M.; Bordalo, P.; Bradamante, F.; Braun, C.; Bressan, A.; Büchele, M.; Burtin, E.; Capozza, L.; Chiosso, M.; Chung, S. U.; Cicuttin, A.; Crespo, M. L.; Curiel, Q.; Dalla Torre, S.; Dasgupta, S. S.; Dasgupta, S.; Denisov, O. Yu; Donskov, S. V.; Doshita, N.; Duic, V.; Dünnweber, W.; Dziewiecki, M.; Efremov, A.; Elia, C.; Eversheim, P. D.; Eyrich, W.; Faessler, M.; Ferrero, A.; Filin, A.; Finger, M.; Finger, M.; Fischer, H.; Franco, C.; du Fresne von Hohenesche, N.; Friedrich, J. M.; Frolov, V.; Gautheron, F.; Gavrichtchouk, O. P.; Gerassimov, S.; Geyer, R.; Gnesi, I.; Gobbo, B.; Goertz, S.; Gorzellik, M.; Grabmüller, S.; Grasso, A.; Grube, B.; Grussenmeyer, T.; Guskov, A.; Guthörl, T.; Haas, F.; von Harrach, D.; Hahne, D.; Hashimoto, R.; Heinsius, F. H.; Herrmann, F.; Hinterberger, F.; Höppner, Ch; Horikawa, N.; d'Hose, N.; Huber, S.; Ishimoto, S.; Ivanov, A.; Ivanshin, Yu; Iwata, T.; Jahn, R.; Jary, V.; Jasinski, P.; Joerg, P.; Joosten, R.; Kabuß, E.; Ketzer, B.; Khaustov, G. V.; Khokhlov, Yu A.; Kisselev, Yu; Klein, F.; Klimaszewski, K.; Koivuniemi, J. H.; Kolosov, V. N.; Kondo, K.; Königsmann, K.; Konorov, I.; Konstantinov, V. F.; Kotzinian, A. M.; Kouznetsov, O.; Krämer, M.; Kroumchtein, Z. V.; Kuchinski, N.; Kunne, F.; Kurek, K.; Kurjata, R. P.; Lednev, A. A.; Lehmann, A.; Levillain, M.; Levorato, S.; Lichtenstadt, J.; Maggiora, A.; Magnon, A.; Makke, N.; Mallot, G. K.; Marchand, C.; Martin, A.; Marzec, J.; Matousek, J.; Matsuda, H.; Matsuda, T.; Meshcheryakov, G.; Meyer, W.; Michigami, T.; Mikhailov, Yu V.; Miyachi, Y.; Nagaytsev, A.; Nagel, T.; Nerling, F.; Neubert, S.; Neyret, D.; Nikolaenko, V. I.; Novy, J.; Nowak, W. D.; Nunes, A. S.; Olshevsky, A. G.; Orlov, I.; Ostrick, M.; Panknin, R.; Panzieri, D.; Parsamyan, B.; Paul, S.; Platchkov, S.; Pochodzalla, J.; Polyakov, V. A.; Pretz, J.; Quaresma, M.; Quintans, C.; Ramos, S.; Regali, C.; Reicherz, G.; Rocco, E.; Rossiyskaya, N. S.; Ryabchikov, D. I.; Rychter, A.; Samoylenko, V. D.; Sandacz, A.; Sapozhnikov, M.; Sarkar, S.; Savin, I. A.; Sbrizzai, G.; Schiavon, P.; Schill, C.; Schlüter, T.; Schmidt, K.; Schmieden, H.; Schönning, K.; Schopferer, S.; Schott, M.; Shevchenko, O. Yu; Silva, L.; Sinha, L.; Sirtl, S.; Slunecka, M.; Sosio, S.; Sozzi, F.; Srnka, A.; Steiger, L.; Stolarski, M.; Sulc, M.; Sulej, R.; Suzuki, H.; Szableski, A.; Szameitat, T.; Sznajder, P.; Takekawa, S.; ter Wolbeek, J.; Tessaro, S.; Tessarotto, F.; Thibaud, F.; Uhl, S.; Uman, I.; Virius, M.; Wang, L.; Weisrock, T.; Wilfert, M.; Windmolders, R.; Wollny, H.; Zaremba, K.; Zavertyaev, M.; Zemlyanichkina, E.; Ziembicki, M.; Zink, A.

    Exclusive production of the isoscalar vector mesons ω and φ is measured with a 190GeV/c proton beam impinging on a liquid hydrogen target. Cross section ratios are determined in three intervals of the Feynman variable xF of the fast proton. A significant violation of the OZI rule is found,

  3. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  4. Generation of facial expressions from emotion using a fuzzy rule based system

    NARCIS (Netherlands)

    Bui, T.D.; Heylen, Dirk K.J.; Poel, Mannes; Nijholt, Antinus; Stumptner, Markus; Corbett, Dan; Brooks, Mike

    2001-01-01

    We propose a fuzzy rule-based system to map representations of the emotional state of an animated agent onto muscle contraction values for the appropriate facial expressions. Our implementation pays special attention to the way in which continuous changes in the intensity of emotions can be

  5. Re-Evaluation of Acid-Base Prediction Rules in Patients with Chronic Respiratory Acidosis

    Directory of Open Access Journals (Sweden)

    Tereza Martinu

    2003-01-01

    Full Text Available RATIONALE: The prediction rules for the evaluation of the acid-base status in patients with chronic respiratory acidosis, derived primarily from an experimental canine model, suggest that complete compensation should not occur. This appears to contradict frequent observations of normal or near-normal pH levels in patients with chronic hypercapnia.

  6. Evolving Rule-Based Systems in two Medical Domains using Genetic Programming

    DEFF Research Database (Denmark)

    Tsakonas, A.; Dounias, G.; Jantzen, Jan

    2004-01-01

    We demonstrate, compare and discuss the application of two genetic programming methodologies for the construction of rule-based systems in two medical domains: the diagnosis of Aphasia's subtypes and the classification of Pap-Smear Test examinations. The first approach consists of a scheme...

  7. Control of Angra 1' PZR by a fuzzy rule base build through genetic programming

    International Nuclear Information System (INIS)

    Caldas, Gustavo Henrique Flores; Schirru, Roberto

    2002-01-01

    There is an optimum pressure for the normal operation of nuclear power plant reactors and thresholds that must be respected during transients, what make the pressurizer an important control mechanism. Inside a pressurizer there are heaters and a shower. From their actuation levels, they control the vapor pressure inside the pressurizer and, consequently, inside the primary circuit. Therefore, the control of the pressurizer consists in controlling the actuation levels of the heaters and of the shower. In the present work this function is implemented through a fuzzy controller. Besides the efficient way of exerting control, this approach presents the possibility of extracting knowledge of how this control is been made. A fuzzy controller consists basically in an inference machine and a rule base, the later been constructed with specialized knowledge. In some circumstances, however, this knowledge is not accurate, and may lead to non-efficient results. With the development of artificial intelligence techniques, there wore found methods to substitute specialists, simulating its knowledge. Genetic programming is an evolutionary algorithm particularly efficient in manipulating rule base structures. In this work genetic programming was used as a substitute for the specialist. The goal is to test if an irrational object, a computer, is capable, by it self, to find out a rule base reproducing a pre-established actuation levels profile. The result is positive, with the discovery of a fuzzy rule base presenting an insignificant error. A remarkable result that proves the efficiency of the approach. (author)

  8. Rule-based emotion detection on social media : putting tweets on Plutchik's wheel

    NARCIS (Netherlands)

    Tromp, E.; Pechenizkiy, M.

    2014-01-01

    We study sentiment analysis beyond the typical granularity of polarity and instead use Plutchik's wheel of emotions model. We introduce RBEM-Emo as an extension to the Rule-Based Emission Model algorithm to deduce such emotions from human-written messages. We evaluate our approach on two different

  9. Improved Personalized Recommendation Based on Causal Association Rule and Collaborative Filtering

    Science.gov (United States)

    Lei, Wu; Qing, Fang; Zhou, Jin

    2016-01-01

    There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

  10. Rule-based versus probabilistic selection for active surveillance using three definitions of insignificant prostate cancer

    NARCIS (Netherlands)

    L.D.F. Venderbos (Lionne); M.J. Roobol-Bouts (Monique); C.H. Bangma (Chris); R.C.N. van den Bergh (Roderick); L.P. Bokhorst (Leonard); D. Nieboer (Daan); Godtman, R; J. Hugosson (Jonas); van der Kwast, T; E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractTo study whether probabilistic selection by the use of a nomogram could improve patient selection for active surveillance (AS) compared to the various sets of rule-based AS inclusion criteria currently used. We studied Dutch and Swedish patients participating in the European Randomized

  11. A rule-based backchannel prediction model using pitch and pause information

    NARCIS (Netherlands)

    Truong, Khiet Phuong; Poppe, Ronald Walter; Heylen, Dirk K.J.

    We manually designed rules for a backchannel (BC) prediction model based on pitch and pause information. In short, the model predicts a BC when there is a pause of a certain length that is preceded by a falling or rising pitch. This model was validated against the Dutch IFADV Corpus in a

  12. Attempts to Dodge Drowning in Data : Rule- and Risk-Based Anti Money Laundering Policies Compared

    NARCIS (Netherlands)

    Unger, B.; van Waarden, F.

    Both in the US and in Europe anti money laundering policy switched from a rule-to a risk-based reporting system in order to avoid over-reporting by the private sector. However, reporting increased in most countries, while the quality of information decreased. Governments drowned in data because

  13. Belief-rule-based expert systems for evaluation of e-government

    DEFF Research Database (Denmark)

    Hossain, Mohammad Shahadat; Zander, Pär-Ola Mikael; Kamal, Md Sarwar

    2015-01-01

    , known as the Belief Rule Based Expert System (BRBES) and implemented in the local e-government of Bangladesh. The results have been compared with a recently developed method of evaluating e-government, and it is demonstrated that the results of the BRBES are more accurate and reliable. The BRBES can...

  14. Capacities and overlap indexes with an application in fuzzy rule-based classification systems

    Czech Academy of Sciences Publication Activity Database

    Paternain, D.; Bustince, H.; Pagola, M.; Sussner, P.; Kolesárová, A.; Mesiar, Radko

    2016-01-01

    Roč. 305, č. 1 (2016), s. 70-94 ISSN 0165-0114 Institutional support: RVO:67985556 Keywords : Capacity * Overlap index * Overlap function * Choquet integral * Fuzzy rule-based classification systems Subject RIV: BA - General Mathematics Impact factor: 2.718, year: 2016 http://library.utia.cas.cz/separaty/2016/E/mesiar-0465739.pdf

  15. Ant-based extraction of rules in simple decision systems over ontological graphs

    Directory of Open Access Journals (Sweden)

    Pancerz Krzysztof

    2015-06-01

    Full Text Available In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA. In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems

  16. Optimizing Fuzzy Rule Base for Illumination Compensation in Face Recognition using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Bima Sena Bayu Dewantara

    2014-12-01

    Full Text Available Fuzzy rule optimization is a challenging step in the development of a fuzzy model. A simple two inputs fuzzy model may have thousands of combination of fuzzy rules when it deals with large number of input variations. Intuitively and trial‐error determination of fuzzy rule is very difficult. This paper addresses the problem of optimizing Fuzzy rule using Genetic Algorithm to compensate illumination effect in face recognition. Since uneven illumination contributes negative effects to the performance of face recognition, those effects must be compensated. We have developed a novel algorithmbased on a reflectance model to compensate the effect of illumination for human face recognition. We build a pair of model from a single image and reason those modelsusing Fuzzy.Fuzzy rule, then, is optimized using Genetic Algorithm. This approachspendsless computation cost by still keepinga high performance. Based on the experimental result, we can show that our algorithm is feasiblefor recognizing desired person under variable lighting conditions with faster computation time. Keywords: Face recognition, harsh illumination, reflectance model, fuzzy, genetic algorithm

  17. Multilevel Association Rule Mining for Bridge Resource Management Based on Immune Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Yang Ou

    2014-01-01

    Full Text Available This paper is concerned with the problem of multilevel association rule mining for bridge resource management (BRM which is announced by IMO in 2010. The goal of this paper is to mine the association rules among the items of BRM and the vessel accidents. However, due to the indirect data that can be collected, which seems useless for the analysis of the relationship between items of BIM and the accidents, the cross level association rules need to be studied, which builds the relation between the indirect data and items of BRM. In this paper, firstly, a cross level coding scheme for mining the multilevel association rules is proposed. Secondly, we execute the immune genetic algorithm with the coding scheme for analyzing BRM. Thirdly, based on the basic maritime investigation reports, some important association rules of the items of BRM are mined and studied. Finally, according to the results of the analysis, we provide the suggestions for the work of seafarer training, assessment, and management.

  18. Long-Term Homeostatic Properties Complementary to Hebbian Rules in CuPc-Based Multifunctional Memristor

    Science.gov (United States)

    Wang, Laiyuan; Wang, Zhiyong; Lin, Jinyi; Yang, Jie; Xie, Linghai; Yi, Mingdong; Li, Wen; Ling, Haifeng; Ou, Changjin; Huang, Wei

    2016-10-01

    Most simulations of neuroplasticity in memristors, which are potentially used to develop artificial synapses, are confined to the basic biological Hebbian rules. However, the simplex rules potentially can induce excessive excitation/inhibition, even collapse of neural activities, because they neglect the properties of long-term homeostasis involved in the frameworks of realistic neural networks. Here, we develop organic CuPc-based memristors of which excitatory and inhibitory conductivities can implement both Hebbian rules and homeostatic plasticity, complementary to Hebbian patterns and conductive to the long-term homeostasis. In another adaptive situation for homeostasis, in thicker samples, the overall excitement under periodic moderate stimuli tends to decrease and be recovered under intense inputs. Interestingly, the prototypes can be equipped with bio-inspired habituation and sensitization functions outperforming the conventional simplified algorithms. They mutually regulate each other to obtain the homeostasis. Therefore, we develop a novel versatile memristor with advanced synaptic homeostasis for comprehensive neural functions.

  19. Solar based hydrogen production systems

    CERN Document Server

    Dincer, Ibrahim

    2013-01-01

    This book provides a comprehensive analysis of various solar based hydrogen production systems. The book covers first-law (energy based) and second-law (exergy based) efficiencies and provides a comprehensive understanding of their implications. It will help minimize the widespread misuse of efficiencies among students and researchers in energy field by using an intuitive and unified approach for defining efficiencies. The book gives a clear understanding of the sustainability and environmental impact analysis of the above systems. The book will be particularly useful for a clear understanding

  20. A Belief Rule-Based Expert System to Assess Bronchiolitis Suspicion from Signs and Symptoms Under Uncertainty

    DEFF Research Database (Denmark)

    Karim, Rezuan; Hossain, Mohammad Shahadat; Khalid, Md. Saifuddin

    2017-01-01

    developed generic belief rule-based inference methodology by using evidential reasoning (RIMER) acts as the inference engine of this BRBES while belief rule base as the knowledge representation schema. The knowledge base of the system is constructed by using real patient data and expert opinion from...

  1. On the effects of adaptive reservoir operating rules in hydrological physically-based models

    Science.gov (United States)

    Giudici, Federico; Anghileri, Daniela; Castelletti, Andrea; Burlando, Paolo

    2017-04-01

    Recent years have seen a significant increase of the human influence on the natural systems both at the global and local scale. Accurately modeling the human component and its interaction with the natural environment is key to characterize the real system dynamics and anticipate future potential changes to the hydrological regimes. Modern distributed, physically-based hydrological models are able to describe hydrological processes with high level of detail and high spatiotemporal resolution. Yet, they lack in sophistication for the behavior component and human decisions are usually described by very simplistic rules, which might underperform in reproducing the catchment dynamics. In the case of water reservoir operators, these simplistic rules usually consist of target-level rule curves, which represent the average historical level trajectory. Whilst these rules can reasonably reproduce the average seasonal water volume shifts due to the reservoirs' operation, they cannot properly represent peculiar conditions, which influence the actual reservoirs' operation, e.g., variations in energy price or water demand, dry or wet meteorological conditions. Moreover, target-level rule curves are not suitable to explore the water system response to climate and socio economic changing contexts, because they assume a business-as-usual operation. In this work, we quantitatively assess how the inclusion of adaptive reservoirs' operating rules into physically-based hydrological models contribute to the proper representation of the hydrological regime at the catchment scale. In particular, we contrast target-level rule curves and detailed optimization-based behavioral models. We, first, perform the comparison on past observational records, showing that target-level rule curves underperform in representing the hydrological regime over multiple time scales (e.g., weekly, seasonal, inter-annual). Then, we compare how future hydrological changes are affected by the two modeling

  2. Labeling and effectiveness testing; sunscreen drug products for over-the-counter human use; delay of compliance dates. Final rule; delay of compliance dates; request for comments.

    Science.gov (United States)

    2012-05-11

    The Food and Drug Administration (FDA) is delaying the compliance dates for the final rule for over-the-counter (OTC) sunscreen drug products that published in the Federal Register of June 17, 2011 (76 FR 35620). The final rule establishes labeling and effectiveness testing for certain OTC sunscreen products containing specified active ingredients and marketed without approved applications. It also amends labeling claims that are not currently supported by data and lifts the previously-published delay of implementation of the Drug Facts labeling requirements for OTC sunscreens. The 2011 final rule's compliance dates are being delayed because information received after publication of the 2011 final rule indicates that full implementation of the 2011 final rule's requirements for all affected products will require an additional 6 months. This final rule is part of FDA's ongoing review of OTC drug products.

  3. Assessing the operation rules of a reservoir system based on a detailed modelling-chain

    Science.gov (United States)

    Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B.

    2014-09-01

    According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two muti-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking, to control floods, to produce hydropower and to reduce low-flow condition. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

  4. Assessing the operation rules of a reservoir system based on a detailed modelling chain

    Science.gov (United States)

    Bruwier, M.; Erpicum, S.; Pirotton, M.; Archambeau, P.; Dewals, B. J.

    2015-03-01

    According to available climate change scenarios for Belgium, drier summers and wetter winters are expected. In this study, we focus on two multi-purpose reservoirs located in the Vesdre catchment, which is part of the Meuse basin. The current operation rules of the reservoirs are first analysed. Next, the impacts of two climate change scenarios are assessed and enhanced operation rules are proposed to mitigate these impacts. For this purpose, an integrated model of the catchment was used. It includes a hydrological model, one-dimensional and two-dimensional hydraulic models of the river and its main tributaries, a model of the reservoir system and a flood damage model. Five performance indicators of the reservoir system have been defined, reflecting its ability to provide sufficient drinking water, to control floods, to produce hydropower and to reduce low-flow conditions. As shown by the results, enhanced operation rules may improve the drinking water potential and the low-flow augmentation while the existing operation rules are efficient for flood control and for hydropower production.

  5. A rule of seven in Watson-Crick base-pairing of mismatched sequences.

    Science.gov (United States)

    Cisse, Ibrahim I; Kim, Hajin; Ha, Taekjip

    2012-05-13

    Sequence recognition through base-pairing is essential for DNA repair and gene regulation, but the basic rules governing this process remain elusive. In particular, the kinetics of annealing between two imperfectly matched strands is not well characterized, despite its potential importance in nucleic acid-based biotechnologies and gene silencing. Here we use single-molecule fluorescence to visualize the multiple annealing and melting reactions of two untethered strands inside a porous vesicle, allowing us to precisely quantify the annealing and melting rates. The data as a function of mismatch position suggest that seven contiguous base pairs are needed for rapid annealing of DNA and RNA. This phenomenological rule of seven may underlie the requirement for seven nucleotides of complementarity to seed gene silencing by small noncoding RNA and may help guide performance improvement in DNA- and RNA-based bio- and nanotechnologies, in which off-target effects can be detrimental.

  6. Domain XML semantic integration based on extraction rules and ontology mapping

    Directory of Open Access Journals (Sweden)

    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  7. A Rule-Based Data Transfer Protocol for On-Demand Data Exchange in Vehicular Environment

    Directory of Open Access Journals (Sweden)

    Liao Hsien-Chou

    2009-01-01

    Full Text Available The purpose of Intelligent Transport System (ITS is mainly to increase the driving safety and efficiency. Data exchange is an important way to achieve the purpose. An on-demand data exchange is especially useful to assist a driver avoiding some emergent events. In order to handle the data exchange under dynamic situations, a rule-based data transfer protocol is proposed in this paper. A set of rules is designed according to the principle of request-forward-reply (RFR. That is, they are used to determine the timing of data broadcasting, forwarding, and replying automatically. Two typical situations are used to demonstrate the operation of rules. One is the front view of a driver occluded by other vehicles. The other is the traffic jam. The proposed protocol is flexible and extensible for unforeseen situations. Three simulation tools were also implemented to demonstrate the feasibility of the protocol and measure the network transmission under high density of vehicles. The simulation results show that the rule-based protocol is efficient on data exchange to increase the driving safety.

  8. SPATKIN: a simulator for rule-based modeling of biomolecular site dynamics on surfaces.

    Science.gov (United States)

    Kochanczyk, Marek; Hlavacek, William S; Lipniacki, Tomasz

    2017-11-15

    Rule-based modeling is a powerful approach for studying biomolecular site dynamics. Here, we present SPATKIN, a general-purpose simulator for rule-based modeling in two spatial dimensions. The simulation algorithm is a lattice-based method that tracks Brownian motion of individual molecules and the stochastic firing of rule-defined reaction events. Because rules are used as event generators, the algorithm is network-free, meaning that it does not require to generate the complete reaction network implied by rules prior to simulation. In a simulation, each molecule (or complex of molecules) is taken to occupy a single lattice site that cannot be shared with another molecule (or complex). SPATKIN is capable of simulating a wide array of membrane-associated processes, including adsorption, desorption and crowding. Models are specified using an extension of the BioNetGen language, which allows to account for spatial features of the simulated process. The C ++ source code for SPATKIN is distributed freely under the terms of the GNU GPLv3 license. The source code can be compiled for execution on popular platforms (Windows, Mac and Linux). An installer for 64-bit Windows and a macOS app are available. The source code and precompiled binaries are available at the SPATKIN Web site (http://pmbm.ippt.pan.pl/software/spatkin). spatkin.simulator@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  9. A rule-based computer control system for PBX-M neutral beams

    International Nuclear Information System (INIS)

    Frank, K.T.; Kozub, T.A.; Kugel, H.W.

    1987-01-01

    The Princeton Beta Experiment (PBX) neutral beams have been routinely operated under automatic computer control. A major upgrade of the computer configuration was undertaken to coincide with the PBX machine modification. The primary tasks included in the computer control system are data acquisition, waveform reduction, automatic control and data storage. The portion of the system which will remain intact is the rule-based approach to automatic control. Increased computational and storage capability will allow the expansion of the knowledge base previously used. The hardware configuration supported by the PBX Neutral Beam (XNB) software includes a dedicated Microvax with five CAMAC crates and four process controllers. The control algorithms are rule-based and goal-driven. The automatic control system raises ion source electrical parameters to selected energy goals and maintains these levels until new goals are requested or faults are detected

  10. RULE-BASE METHOD FOR ANALYSIS OF QUALITY E-LEARNING IN HIGHER EDUCATION

    Directory of Open Access Journals (Sweden)

    darsih darsih darsih

    2016-04-01

    Full Text Available ABSTRACT Assessing the quality of e-learning courses to measure the success of e-learning systems in online learning is essential. The system can be used to improve education. The study analyzes the quality of e-learning course on the web site www.kulon.undip.ac.id used a questionnaire with questions based on the variables of ISO 9126. Penilaiann Likert scale was used with a web app. Rule-base reasoning method is used to subject the quality of e-learningyang assessed. A case study conducted in four e-learning courses with 133 sample / respondents as users of the e-learning course. From the obtained results of research conducted both for the value of e-learning from each subject tested. In addition, each e-learning courses have different advantages depending on certain variables. Keywords : E-Learning, Rule-Base, Questionnaire, Likert, Measuring.

  11. Genetic Programming for the Generation of Crisp and Fuzzy Rule Bases in Classification and Diagnosis of Medical Data

    DEFF Research Database (Denmark)

    Dounias, George; Tsakonas, Athanasios; Jantzen, Jan

    2002-01-01

    This paper demonstrates two methodologies for the construction of rule-based systems in medical decision making. The first approach consists of a method combining genetic programming and heuristic hierarchical rule-base construction. The second model is composed by a strongly-typed genetic...

  12. A knowledge representation meta-model for rule-based modelling of signalling networks

    Directory of Open Access Journals (Sweden)

    Adrien Basso-Blandin

    2016-03-01

    Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

  13. Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

    Science.gov (United States)

    van Ginneken, Bram

    2017-03-01

    Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

  14. A Novel Method of Interestingness Measures for Association Rules Mining Based on Profit

    Directory of Open Access Journals (Sweden)

    Chunhua Ju

    2015-01-01

    Full Text Available Association rules mining is an important topic in the domain of data mining and knowledge discovering. Some papers have presented several interestingness measure methods; the most typical are Support, Confidence, Lift, Improve, and so forth. But their limitations are obvious, like no objective criterion, lack of statistical base, disability of defining negative relationship, and so forth. This paper proposes three new methods, Bi-lift, Bi-improve, and Bi-confidence, for Lift, Improve, and Confidence, respectively. Then, on the basis of utility function and the executing cost of rules, we propose interestingness function based on profit (IFBP considering subjective preferences and characteristics of specific application object. Finally, a novel measure framework is proposed to improve the traditional one through experimental analysis. In conclusion, the new methods and measure framework are prior to the traditional ones in the aspects of objective criterion, comprehensive definition, and practical application.

  15. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID

    Directory of Open Access Journals (Sweden)

    Ardhyanti Mita Nugraha Joanna

    2018-01-01

    Full Text Available Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP. This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

  16. Towards a framework for threaded inference in rule-based systems

    Directory of Open Access Journals (Sweden)

    Luis Casillas Santillan

    2013-11-01

    Full Text Available nformation and communication technologies have shown a significant advance and fast pace in their performance and pervasiveness. Knowledge has become a significant asset for organizations, which need to deal with large amounts of data and information to produce valuable knowledge. Dealing with knowledge is turning the axis for organizations in the new economy. One of the choices to gather the goal of knowledge managing is the use of rule-based systems. This kind of approach is the new chance for expert-systems’ technology. Modern languages and cheap computing allow the implementation of concurrent systems for dealing huge volumes of information in organizations. The present work is aimed at proposing the use of contemporary programming elements, as easy to exploit threading, when implementing rule-based treatment over huge data volumes.

  17. Rule Based System for Medicine Inventory Control Using Radio Frequency Identification (RFID)

    Science.gov (United States)

    Nugraha, Joanna Ardhyanti Mita; Suryono; Suseno, dan Jatmiko Endro

    2018-02-01

    Rule based system is very efficient to ensure stock of drug to remain available by utilizing Radio Frequency Identification (RFID) as input means automatically. This method can ensure the stock of drugs to remain available by analyzing the needs of drug users. The research data was the amount of drug usage in hospital for 1 year. The data was processed by using ABC classification to determine the drug with fast, medium and slow movement. In each classification result, rule based algorithm was given for determination of safety stock and Reorder Point (ROP). This research yielded safety stock and ROP values that vary depending on the class of each drug. Validation is done by comparing the calculation of safety stock and reorder point both manually and by system, then, it was found that the mean deviation value at safety stock was 0,03 and and ROP was 0,08.

  18. Systematic construction of qualitative physics-based rules for process diagnostics

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.

    1995-01-01

    A novel first-principles-based expert system is proposed for on-line detection and identification of faulty component candidates during incipient off-normal process operations. The system performs function-oriented diagnostics and can be reused for diagnosing single-component failures in different processes and different plants through the provision of the appropriate process schematics information. The function-oriented and process-independent diagnostic features of the proposed expert system are achieved by constructing a knowledge base containing three distinct types of information, qualitative balance equation rules, functional classification of process components, and the process piping and instrumentation diagram. The various types of qualitative balance equation rules for processes utilizing single-phase liquids are derived and their usage is illustrated through simulation results of a realistic process in a nuclear power plant

  19. Simulation of operating rules and discretional decisions using a fuzzy rule-based system integrated into a water resources management model

    Science.gov (United States)

    Macian-Sorribes, Hector; Pulido-Velazquez, Manuel

    2013-04-01

    Water resources systems are operated, mostly, using a set of pre-defined rules not regarding, usually, to an optimal allocation in terms of water use or economic benefits, but to historical and institutional reasons. These operating policies are reproduced, commonly, as hedging rules, pack rules or zone-based operations, and simulation models can be used to test their performance under a wide range of hydrological and/or socio-economic hypothesis. Despite the high degree of acceptation and testing that these models have achieved, the actual operation of water resources systems hardly follows all the time the pre-defined rules with the consequent uncertainty on the system performance. Real-world reservoir operation is very complex, affected by input uncertainty (imprecision in forecast inflow, seepage and evaporation losses, etc.), filtered by the reservoir operator's experience and natural risk-aversion, while considering the different physical and legal/institutional constraints in order to meet the different demands and system requirements. The aim of this work is to expose a fuzzy logic approach to derive and assess the historical operation of a system. This framework uses a fuzzy rule-based system to reproduce pre-defined rules and also to match as close as possible the actual decisions made by managers. After built up, the fuzzy rule-based system can be integrated in a water resources management model, making possible to assess the system performance at the basin scale. The case study of the Mijares basin (eastern Spain) is used to illustrate the method. A reservoir operating curve regulates the two main reservoir releases (operated in a conjunctive way) with the purpose of guaranteeing a high realiability of supply to the traditional irrigation districts with higher priority (more senior demands that funded the reservoir construction). A fuzzy rule-based system has been created to reproduce the operating curve's performance, defining the system state (total

  20. Fuzzy Rule-based Analysis of Promotional Efficiency in Vietnam’s Tourism Industry

    OpenAIRE

    Nguyen Quang VINH; Dam Van KHANH; Nguyen Viet ANH

    2015-01-01

    This study aims to determine an effective method of measuring the efficiency of promotional strategies for tourist destinations. Complicating factors that influence promotional efficiency (PE), such as promotional activities (PA), destination attribute (DA), and destination image (DI), make it difficult to evaluate the effectiveness of PE. This study develops a rule-based decision support mechanism using fuzzy set theory and the Analytic Hierarchy Process (AHP) to evaluate the effectiveness o...

  1. Depfix, a Tool for Automatic Rule-based Post-editing of SMT

    Directory of Open Access Journals (Sweden)

    Rudolf Rosa

    2014-09-01

    Full Text Available We present Depfix, an open-source system for automatic post-editing of phrase-based machine translation outputs. Depfix employs a range of natural language processing tools to obtain analyses of the input sentences, and uses a set of rules to correct common or serious errors in machine translation outputs. Depfix is currently implemented only for English-to-Czech translation direction, but extending it to other languages is planned.

  2. LPS: a rule-based, schema-oriented knowledge representation system

    Energy Technology Data Exchange (ETDEWEB)

    Anzai, Y; Mitsuya, Y; Nakajima, S; Ura, S

    1981-01-01

    A new knowledge representation system called LPS is presented. The global control structure of LPS is rule-based, but the local representational structure is schema-oriented. The present version of LPS was designed to increase the understandability of representation while keeping time efficiency reasonable. Pattern matching through slot-networks and meta-actions from among the implemented facilities of LPS, are especially described in detail. 7 references.

  3. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Directory of Open Access Journals (Sweden)

    Ujjwal Maulik

    Full Text Available Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution. The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post

  4. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.

    Science.gov (United States)

    Maulik, Ujjwal; Mallik, Saurav; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra

    2015-01-01

    Microarray and beadchip are two most efficient techniques for measuring gene expression and methylation data in bioinformatics. Biclustering deals with the simultaneous clustering of genes and samples. In this article, we propose a computational rule mining framework, StatBicRM (i.e., statistical biclustering-based rule mining) to identify special type of rules and potential biomarkers using integrated approaches of statistical and binary inclusion-maximal biclustering techniques from the biological datasets. At first, a novel statistical strategy has been utilized to eliminate the insignificant/low-significant/redundant genes in such way that significance level must satisfy the data distribution property (viz., either normal distribution or non-normal distribution). The data is then discretized and post-discretized, consecutively. Thereafter, the biclustering technique is applied to identify maximal frequent closed homogeneous itemsets. Corresponding special type of rules are then extracted from the selected itemsets. Our proposed rule mining method performs better than the other rule mining algorithms as it generates maximal frequent closed homogeneous itemsets instead of frequent itemsets. Thus, it saves elapsed time, and can work on big dataset. Pathway and Gene Ontology analyses are conducted on the genes of the evolved rules using David database. Frequency analysis of the genes appearing in the evolved rules is performed to determine potential biomarkers. Furthermore, we also classify the data to know how much the evolved rules are able to describe accurately the remaining test (unknown) data. Subsequently, we also compare the average classification accuracy, and other related factors with other rule-based classifiers. Statistical significance tests are also performed for verifying the statistical relevance of the comparative results. Here, each of the other rule mining methods or rule-based classifiers is also starting with the same post-discretized data

  5. Mining association rule based on the diseases population for recommendation of medicine need

    Science.gov (United States)

    Harahap, M.; Husein, A. M.; Aisyah, S.; Lubis, F. R.; Wijaya, B. A.

    2018-04-01

    Selection of medicines that is inappropriate will lead to an empty result at medicines, this has an impact on medical services and economic value in hospital. The importance of an appropriate medicine selection process requires an automated way to select need based on the development of the patient's illness. In this study, we analyzed patient prescriptions to identify the relationship between the disease and the medicine used by the physician in treating the patient's illness. The analytical framework includes: (1) patient prescription data collection, (2) applying k-means clustering to classify the top 10 diseases, (3) applying Apriori algorithm to find association rules based on support, confidence and lift value. The results of the tests of patient prescription datasets in 2015-2016, the application of the k-means algorithm for the clustering of 10 dominant diseases significantly affects the value of trust and support of all association rules on the Apriori algorithm making it more consistent with finding association rules of disease and related medicine. The value of support, confidence and the lift value of disease and related medicine can be used as recommendations for appropriate medicine selection. Based on the conditions of disease progressions of the hospital, there is so more optimal medicine procurement.

  6. Spatial Rule-Based Modeling: A Method and Its Application to the Human Mitotic Kinetochore

    Directory of Open Access Journals (Sweden)

    Jan Huwald

    2013-07-01

    Full Text Available A common problem in the analysis of biological systems is the combinatorial explosion that emerges from the complexity of multi-protein assemblies. Conventional formalisms, like differential equations, Boolean networks and Bayesian networks, are unsuitable for dealing with the combinatorial explosion, because they are designed for a restricted state space with fixed dimensionality. To overcome this problem, the rule-based modeling language, BioNetGen, and the spatial extension, SRSim, have been developed. Here, we describe how to apply rule-based modeling to integrate experimental data from different sources into a single spatial simulation model and how to analyze the output of that model. The starting point for this approach can be a combination of molecular interaction data, reaction network data, proximities, binding and diffusion kinetics and molecular geometries at different levels of detail. We describe the technique and then use it to construct a model of the human mitotic inner and outer kinetochore, including the spindle assembly checkpoint signaling pathway. This allows us to demonstrate the utility of the procedure, show how a novel perspective for understanding such complex systems becomes accessible and elaborate on challenges that arise in the formulation, simulation and analysis of spatial rule-based models.

  7. Executable specifications for hypothesis-based reasoning with Prolog and Constraint Handling Rules

    DEFF Research Database (Denmark)

    Christiansen, Henning

    2009-01-01

    Constraint Handling Rules (CHR) is an extension to Prolog which opens up a  spectrum of hypotheses-based reasoning in logic programs without additional interpretation overhead. Abduction with integrity constraints is one example of hypotheses-based reasoning which can be implemented directly...... in Prolog and CHR with a straightforward use of available and efficiently implemented facilities The present paper clarifies the semantic foundations for this way of doing abduction in CHR and Prolog as well as other examples  of hypotheses-based reasoning that is possible, including assumptive logic...

  8. Weighted Evidence Combination Rule Based on Evidence Distance and Uncertainty Measure: An Application in Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Lei Chen

    2018-01-01

    Full Text Available Conflict management in Dempster-Shafer theory (D-S theory is a hot topic in information fusion. In this paper, a novel weighted evidence combination rule based on evidence distance and uncertainty measure is proposed. The proposed approach consists of two steps. First, the weight is determined based on the evidence distance. Then, the weight value obtained in first step is modified by taking advantage of uncertainty. Our proposed method can efficiently handle high conflicting evidences with better performance of convergence. A numerical example and an application based on sensor fusion in fault diagnosis are given to demonstrate the efficiency of our proposed method.

  9. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis

    Directory of Open Access Journals (Sweden)

    Saurav Mallik

    2017-12-01

    Full Text Available For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures—weighted rank-based Jaccard and Cosine measures—and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm—RANWAR—was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  10. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.

    Science.gov (United States)

    Mallik, Saurav; Zhao, Zhongming

    2017-12-28

    For transcriptomic analysis, there are numerous microarray-based genomic data, especially those generated for cancer research. The typical analysis measures the difference between a cancer sample-group and a matched control group for each transcript or gene. Association rule mining is used to discover interesting item sets through rule-based methodology. Thus, it has advantages to find causal effect relationships between the transcripts. In this work, we introduce two new rule-based similarity measures-weighted rank-based Jaccard and Cosine measures-and then propose a novel computational framework to detect condensed gene co-expression modules ( C o n G E M s) through the association rule-based learning system and the weighted similarity scores. In practice, the list of evolved condensed markers that consists of both singular and complex markers in nature depends on the corresponding condensed gene sets in either antecedent or consequent of the rules of the resultant modules. In our evaluation, these markers could be supported by literature evidence, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and Gene Ontology annotations. Specifically, we preliminarily identified differentially expressed genes using an empirical Bayes test. A recently developed algorithm-RANWAR-was then utilized to determine the association rules from these genes. Based on that, we computed the integrated similarity scores of these rule-based similarity measures between each rule-pair, and the resultant scores were used for clustering to identify the co-expressed rule-modules. We applied our method to a gene expression dataset for lung squamous cell carcinoma and a genome methylation dataset for uterine cervical carcinogenesis. Our proposed module discovery method produced better results than the traditional gene-module discovery measures. In summary, our proposed rule-based method is useful for exploring biomarker modules from transcriptomic data.

  11. Neural Substrates of Similarity and Rule-based Strategies in Judgment

    Directory of Open Access Journals (Sweden)

    Bettina eVon Helversen

    2014-10-01

    Full Text Available Making accurate judgments is a core human competence and a prerequisite for success in many areas of life. Plenty of evidence exists that people can employ different judgment strategies to solve identical judgment problems. In categorization, it has been demonstrated that similarity-based and rule-based strategies are associated with activity in different brain regions. Building on this research, the present work tests whether solving two identical judgment problems recruits different neural substrates depending on people's judgment strategies. Combining cognitive modeling of judgment strategies at the behavioral level with functional magnetic resonance imaging (fMRI, we compare brain activity when using two archetypal judgment strategies: a similarity-based exemplar strategy and a rule-based heuristic strategy. Using an exemplar-based strategy should recruit areas involved in long-term memory processes to a larger extent than a heuristic strategy. In contrast, using a heuristic strategy should recruit areas involved in the application of rules to a larger extent than an exemplar-based strategy. Largely consistent with our hypotheses, we found that using an exemplar-based strategy led to relatively higher BOLD activity in the anterior prefrontal and inferior parietal cortex, presumably related to retrieval and selective attention processes. In contrast, using a heuristic strategy led to relatively higher activity in areas in the dorsolateral prefrontal and the temporal-parietal cortex associated with cognitive control and information integration. Thus, even when people solve identical judgment problems, different neural substrates can be recruited depending on the judgment strategy involved.

  12. A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    H. Y. Gu

    2017-09-01

    Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  13. Autonomous Rule Creation for Intrusion Detection

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Jim Alves-Foss; Milos Manic

    2011-04-01

    Many computational intelligence techniques for anomaly based network intrusion detection can be found in literature. Translating a newly discovered intrusion recognition criteria into a distributable rule can be a human intensive effort. This paper explores a multi-modal genetic algorithm solution for autonomous rule creation. This algorithm focuses on the process of creating rules once an intrusion has been identified, rather than the evolution of rules to provide a solution for intrusion detection. The algorithm was demonstrated on anomalous ICMP network packets (input) and Snort rules (output of the algorithm). Output rules were sorted according to a fitness value and any duplicates were removed. The experimental results on ten test cases demonstrated a 100 percent rule alert rate. Out of 33,804 test packets 3 produced false positives. Each test case produced a minimum of three rule variations that could be used as candidates for a production system.

  14. Orthogonal search-based rule extraction for modelling the decision to transfuse.

    Science.gov (United States)

    Etchells, T A; Harrison, M J

    2006-04-01

    Data from an audit relating to transfusion decisions during intermediate or major surgery were analysed to determine the strengths of certain factors in the decision making process. The analysis, using orthogonal search-based rule extraction (OSRE) from a trained neural network, demonstrated that the risk of tissue hypoxia (ROTH) assessed using a 100-mm visual analogue scale, the haemoglobin value (Hb) and the presence or absence of on-going haemorrhage (OGH) were able to reproduce the transfusion decisions with a joint specificity of 0.96 and sensitivity of 0.93 and a positive predictive value of 0.9. The rules indicating transfusion were: 1. ROTH > 32 mm and Hb 13 mm and Hb 38 mm, Hb < 102 g x l(-1) and OGH; 4. Hb < 78 g x l(-1).

  15. Merit-Based Incentive Payment System: Meaningful Changes in the Final Rule Brings Cautious Optimism.

    Science.gov (United States)

    Manchikanti, Laxmaiah; Helm Ii, Standiford; Calodney, Aaron K; Hirsch, Joshua A

    2017-01-01

    The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) eliminated the flawed Sustainable Growth Rate (SGR) act formula - a longstanding crucial issue of concern for health care providers and Medicare beneficiaries. MACRA also included a quality improvement program entitled, "The Merit-Based Incentive Payment System, or MIPS." The proposed rule of MIPS sought to streamline existing federal quality efforts and therefore linked 4 distinct programs into one. Three existing programs, meaningful use (MU), Physician Quality Reporting System (PQRS), value-based payment (VBP) system were merged with the addition of Clinical Improvement Activity category. The proposed rule also changed the name of MU to Advancing Care Information, or ACI. ACI contributes to 25% of composite score of the four programs, PQRS contributes 50% of the composite score, while VBP system, which deals with resource use or cost, contributes to 10% of the composite score. The newest category, Improvement Activities or IA, contributes 15% to the composite score. The proposed rule also created what it called a design incentive that drives movement to delivery system reform principles with the inclusion of Advanced Alternative Payment Models (APMs).Following the release of the proposed rule, the medical community, as well as Congress, provided substantial input to Centers for Medicare and Medicaid Services (CMS),expressing their concern. American Society of Interventional Pain Physicians (ASIPP) focused on 3 important aspects: delay the implementation, provide a 3-month performance period, and provide ability to submit meaningful quality measures in a timely and economic manner. The final rule accepted many of the comments from various organizations, including several of those specifically emphasized by ASIPP, with acceptance of 3-month reporting period, as well as the ability to submit non-MIPS measures to improve real quality and make the system meaningful. CMS also provided a mechanism for

  16. Tuning rules for robust FOPID controllers based on multi-objective optimization with FOPDT models.

    Science.gov (United States)

    Sánchez, Helem Sabina; Padula, Fabrizio; Visioli, Antonio; Vilanova, Ramon

    2017-01-01

    In this paper a set of optimally balanced tuning rules for fractional-order proportional-integral-derivative controllers is proposed. The control problem of minimizing at once the integrated absolute error for both the set-point and the load disturbance responses is addressed. The control problem is stated as a multi-objective optimization problem where a first-order-plus-dead-time process model subject to a robustness, maximum sensitivity based, constraint has been considered. A set of Pareto optimal solutions is obtained for different normalized dead times and then the optimal balance between the competing objectives is obtained by choosing the Nash solution among the Pareto-optimal ones. A curve fitting procedure has then been applied in order to generate suitable tuning rules. Several simulation results show the effectiveness of the proposed approach. Copyright © 2016. Published by Elsevier Ltd.

  17. Multi-arrhythmias detection with an XML rule-based system from 12-Lead Electrocardiogram.

    Science.gov (United States)

    Khelassi, Abdeldjalil; Yelles-Chaouche, Sarra-Nassira; Benais, Faiza

    2017-05-01

    The computer-aided detection of cardiac arrhythmias stills a crucial application in medical technologies. The rule based systems RBS ensure a high level of transparency and interpretability of the obtained results. To facilitate the diagnosis of the cardiologists and to reduce the uncertainty made in this diagnosis. In this research article, we have realized a classification and automatic recognition of cardiac arrhythmias, by using XML rules that represent the cardiologist knowledge. Thirteen experiments with different knowledge bases were realized for improving the performance of the used method in the detection of 13 cardiac arrhythmias. In the first 12 experiments, we have designed a specialized knowledge base for each cardiac arrhythmia, which contains just one arrhythmia detection rule. In the last experiment, we applied the knowledge base which contains rules of 12 arrhythmias. We used, for the experiments, an international data set with 279 features and 452 records characterizing 12 leads of ECG signal and social information of patients. The data sets were constructed and published at Bilkent University of Ankara, Turkey. In addition, the second version of the self-developed software "XMLRULE" was used; the software can infer more than one class and facilitate the interpretability of the obtained results. The 12 first experiments give 82.80% of correct detection as the mean of all experiments, the results were between 19% and 100% with a low rate in just one experiment. The last experiment in which all arrhythmias are considered, the results of correct detection was 38.33% with 90.55% of sensibility and 46.24% of specificity. It was clearly show that in these results the good choice of the classification model is very beneficial in terms of performance. The obtained results were better than the published results with other computational methods for the mono class detection, but it was less in multi-class detection. The RBS is the most transparent method for

  18. The rule of law

    Directory of Open Access Journals (Sweden)

    Besnik Murati

    2015-07-01

    Full Text Available The state as an international entity and its impact on the individual’s right has been and still continues to be a crucial factor in the relationship between private and public persons. States vary in terms of their political system, however, democratic states are based on the separation of powers and human rights within the state. Rule of law is the product of many actors in a state, including laws, individuals, society, political system, separation of powers, human rights, the establishment of civil society, the relationship between law and the individual, as well as, individual-state relations. Purpose and focus of this study is the importance of a functioning state based on law, characteristics of the rule of law, separation of powers and the basic concepts of the rule of law.

  19. An Investigation of Care-Based vs. Rule-Based Morality in Frontotemporal Dementia, Alzheimer’s Disease, and Healthy Controls

    Science.gov (United States)

    Carr, Andrew R.; Paholpak, Pongsatorn; Daianu, Madelaine; Fong, Sylvia S.; Mather, Michelle; Jimenez, Elvira E.; Thompson, Paul; Mendez, Mario F.

    2015-01-01

    Behavioral changes in dementia, especially behavioral variant frontotemporal dementia (bvFTD), may result in alterations in moral reasoning. Investigators have not clarified whether these alterations reflect differential impairment of care-based vs. rule-based moral behavior. This study investigated 18 bvFTD patients, 22 early onset Alzheimer’s disease (eAD) patients, and 20 healthy age-matched controls on care-based and rule-based items from the Moral Behavioral Inventory and the Social Norms Questionnaire, neuropsychological measures, and magnetic resonance imaging (MRI) regions of interest. There were significant group differences with the bvFTD patients rating care-based morality transgressions less severely than the eAD group and rule-based moral behavioral transgressions more severely than controls. Across groups, higher care-based morality ratings correlated with phonemic fluency on neuropsychological tests, whereas higher rule-based morality ratings correlated with increased difficulty set-shifting and learning new rules to tasks. On neuroimaging, severe care-based reasoning correlated with cortical volume in right anterior temporal lobe, and rule-based reasoning correlated with decreased cortical volume in the right orbitofrontal cortex. Together, these findings suggest that frontotemporal disease decreases care-based morality and facilitates rule-based morality possibly from disturbed contextual abstraction and set-shifting. Future research can examine whether frontal lobe disorders and bvFTD result in a shift from empathic morality to the strong adherence to conventional rules. PMID:26432341

  20. Paper Improving Rule Based Stemmers to Solve Some Special Cases of Arabic Language

    Directory of Open Access Journals (Sweden)

    Soufiane Farrah

    2017-04-01

    Full Text Available Analysis of Arabic language has become a necessity because of its big evolution; we propose in this paper a rule based extraction method of Arabic text to solve some weaknesses founded on previous research works. Our approach is divided on preprocessing phase, on which we proceed to the tokenization of the text, and formatting it by removing any punctuation, diacritics and non-letter characters. Treatment phase based on the elimination of several sets of affixes (diacritics, prefixes, and suffixes, and on the application of several patterns. A check phase that verifies if the root extracted is correct, by searching the result in root dictionaries.

  1. Optical MSD symbolic substitution system based on a higher ordered rule

    Science.gov (United States)

    Reddy, A. K.; Mallikarjun, Tatipamula; Raina, J. P.

    1992-12-01

    The advantages provided by Photonic Computing has been well documented. An Optical arithmetic processor has to take full advantage of the massive parallelism in optical signals. Such a processor, using the Modified - Signed - Digit (MSD) number . (i) representation, has been presented here based (2) on the symbolic substitution 1ogi. The higher order symbolic substitution rules are formulated for the addition operation, which is carried out in just two steps. Based on the addition operation, the other arithmetic operations - subtraction, multiplication and division - are implemented. Finally, the usefulness of this MSD system is studied.

  2. Effects of Memorization of Rule Statements on Acquisition and Retention of Rule-Governed Behavior in a Computer-Based Learning Task.

    Science.gov (United States)

    Towle, Nelson J.

    One hundred and twenty-four high school students were randomly assigned to four groups: 33 subjects memorized the rule statement before, 29 subjects memorized the rule statement during, and 30 subjects memorized the rule statement after instruction in rule application skills. Thirty-two subjects were not required to memorize rule statements.…

  3. Dandruff, seborrheic dermatitis, and psoriasis drug products containing coal tar and menthol for over-the-counter human use; amendment to the monograph. Final rule

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2006-03-15

    The Food and Drug Administration (FDA) is issuing a final rule amending the final monograph (FM) for over-the-counter (OTC) dandruff, seborrheic dermatitis, and psoriasis drug products to include the combination of 1.8 percent coal tar solution and 1.5 percent menthol in a shampoo drug product to control dandruff. FDA did not receive any comments or data in response to its previously proposed rule to include this combination. This final rule is part of FDA's ongoing review of OTC drug products.

  4. Some remarks on Feynman rules for non-commutative gauge theories based on groups G≠U(N)

    International Nuclear Information System (INIS)

    Dorn, Harald; Sieg, Christoph

    2002-01-01

    We study for subgroups G is a subset of U(N) partial summations of the θ-expanded perturbation theory. On diagrammatic level a summation procedure is established, which in the U(N) case delivers the full star-product induced rules. Thereby we uncover a cancellation mechanism between certain diagrams, which is crucial in the U(N) case, but set out of work for G is a subset of U(N). In addition, an explicit proof is given that for G is a subset of U(N), G≠U(M), M< N there is no partial summation of the θ-expanded rules resulting in new Feynman rules using the U(N) star-product vertices and besides suitable modified propagators at most a finite number of additional building blocks. Finally, we show that certain SO(N) Feynman rules conjectured in the literature cannot be derived from the enveloping algebra approach. (author)

  5. Reduction rules-based search algorithm for opportunistic replacement strategy of multiple life-limited parts

    Directory of Open Access Journals (Sweden)

    Xuyun FU

    2018-01-01

    Full Text Available The opportunistic replacement of multiple Life-Limited Parts (LLPs is a problem widely existing in industry. The replacement strategy of LLPs has a great impact on the total maintenance cost to a lot of equipment. This article focuses on finding a quick and effective algorithm for this problem. To improve the algorithm efficiency, six reduction rules are suggested from the perspectives of solution feasibility, determination of the replacement of LLPs, determination of the maintenance occasion and solution optimality. Based on these six reduction rules, a search algorithm is proposed. This search algorithm can identify one or several optimal solutions. A numerical experiment shows that these six reduction rules are effective, and the time consumed by the algorithm is less than 38 s if the total life of equipment is shorter than 55000 and the number of LLPs is less than 11. A specific case shows that the algorithm can obtain optimal solutions which are much better than the result of the traditional method in 10 s, and it can provide support for determining to-be-replaced LLPs when determining the maintenance workscope of an aircraft engine. Therefore, the algorithm is applicable to engineering applications concerning opportunistic replacement of multiple LLPs in aircraft engines.

  6. Analysis of QCD sum rule based on the maximum entropy method

    International Nuclear Information System (INIS)

    Gubler, Philipp

    2012-01-01

    QCD sum rule was developed about thirty years ago and has been used up to the present to calculate various physical quantities like hadrons. It has been, however, needed to assume 'pole + continuum' for the spectral function in the conventional analyses. Application of this method therefore came across with difficulties when the above assumption is not satisfied. In order to avoid this difficulty, analysis to make use of the maximum entropy method (MEM) has been developed by the present author. It is reported here how far this new method can be successfully applied. In the first section, the general feature of the QCD sum rule is introduced. In section 2, it is discussed why the analysis by the QCD sum rule based on the MEM is so effective. In section 3, the MEM analysis process is described, and in the subsection 3.1 likelihood function and prior probability are considered then in subsection 3.2 numerical analyses are picked up. In section 4, some cases of applications are described starting with ρ mesons, then charmoniums in the finite temperature and finally recent developments. Some figures of the spectral functions are shown. In section 5, summing up of the present analysis method and future view are given. (S. Funahashi)

  7. Automated detection of pain from facial expressions: a rule-based approach using AAM

    Science.gov (United States)

    Chen, Zhanli; Ansari, Rashid; Wilkie, Diana J.

    2012-02-01

    In this paper, we examine the problem of using video analysis to assess pain, an important problem especially for critically ill, non-communicative patients, and people with dementia. We propose and evaluate an automated method to detect the presence of pain manifested in patient videos using a unique and large collection of cancer patient videos captured in patient homes. The method is based on detecting pain-related facial action units defined in the Facial Action Coding System (FACS) that is widely used for objective assessment in pain analysis. In our research, a person-specific Active Appearance Model (AAM) based on Project-Out Inverse Compositional Method is trained for each patient individually for the modeling purpose. A flexible representation of the shape model is used in a rule-based method that is better suited than the more commonly used classifier-based methods for application to the cancer patient videos in which pain-related facial actions occur infrequently and more subtly. The rule-based method relies on the feature points that provide facial action cues and is extracted from the shape vertices of AAM, which have a natural correspondence to face muscular movement. In this paper, we investigate the detection of a commonly used set of pain-related action units in both the upper and lower face. Our detection results show good agreement with the results obtained by three trained FACS coders who independently reviewed and scored the action units in the cancer patient videos.

  8. Ketamine alters lateral prefrontal oscillations in a rule-based working memory task.

    Science.gov (United States)

    Ma, Liya; Skoblenick, Kevin; Johnston, Kevin; Everling, Stefan

    2018-02-02

    Acute administration of N-methyl-D-aspartate receptor (NMDAR) antagonists in healthy humans and animals produces working memory deficits similar to those observed in schizophrenia. However, it is unclear whether they also lead to altered low-frequency (rule-based prosaccade and antisaccade working memory task, both before and after systemic injections of a subanesthetic dose (delay periods and inter-trial intervals. It also increased task-related alpha-band activities, likely reflecting compromised attention. Beta-band oscillations may be especially relevant to working memory processes, as stronger beta power weakly but significantly predicted shorter saccadic reaction time. Also in beta band, ketamine reduced the performance-related oscillation as well as the rule information encoded in the spectral power. Ketamine also reduced rule information in the spike-field phase consistency in almost all frequencies up to 60Hz. Our findings support NMDAR antagonists in non-human primates as a meaningful model for altered neural oscillations and synchrony, which reflect a disorganized network underlying the working memory deficits in schizophrenia. SIGNIFICANCE STATEMENT Low doses of ketamine-an NMDA receptor blocker-produce working memory deficits similar to those observed in schizophrenia. In the LPFC, a key brain region for working memory, we found that ketamine altered neural oscillatory activities in similar ways that differentiate schizophrenic patients and healthy subjects, during both task and non-task periods. Ketamine induced stronger gamma (30-60Hz) and weaker beta (13-30Hz) oscillations, reflecting local hyperactivity and reduced long-range communications. Furthermore, ketamine reduced performance-related oscillatory activities, as well as the rule information encoded in the oscillations and in the synchrony between single cell activities and oscillations. The ketamine model helps link the molecular and cellular basis of neural oscillatory changes to the working

  9. Real Time Part Input Control of a Pull Production System by Finding IF-THEN Rules

    Science.gov (United States)

    Ramli, Rizauddin; Yamamoto, Hidehiko; Abu Qudeiri, Jaber

    This paper considers the part input problem of a production system where two Flexible Transfer Lines (FTLs) consisting of an up-stream production line and a down-stream production line while operating under Just In Time (JIT) production management. The up-stream production line processes the raw material after receiving them from suppliers, and after processing them, delivers the processed product to a down-stream production line via a conveyer. In this paper, we have proposed a novel idea for a part input real time control system, known as Algorithm for Real Time Control of Part Input Systems (ARTCOPS). The algorithm is useful when FTLs are in operation under a production order that is different from the pre-decided production schedule. Simulations of virtual production systems have been carried out to verify that ARTCOPS is useful in real time control, although the production orders are different from the pre-decided production scheduling.

  10. Prioritized rule based load management technique for residential building powered by PV/battery system

    Directory of Open Access Journals (Sweden)

    T.R. Ayodele

    2017-06-01

    Full Text Available In recent years, Solar Photovoltaic (PV system has presented itself as one of the main solutions to the electricity poverty plaguing the majority of buildings in rural communities with solar energy potential. However, the stochasticity associated with solar PV power output owing to vagaries in weather conditions is a major challenge in the deployment of the systems. This study investigates approach for maximizing the benefits of a Stand-Alone Photovoltaic-Battery (SAPVB system via techniques that provide for optimum energy gleaning and management. A rule-based load management scheme is developed and tested for a residential building. The approach allows load prioritizing and shifting based on certain rules. To achieve this, the residential loads are classified into Critical Loads (CLs and Uncritical Loads (ULs. The CLs are given higher priority and therefore are allowed to operate at their scheduled time while the ULs are of less priority, hence can be shifted to a time where there is enough electric power generation from the PV arrays rather than the loads being operated at the time period set by the user. Four scenarios were created to give insight into the applicability of the proposed rule based load management scheme. The result revealed that when the load management technique is not utilized as in the case of scenario 1 (Base case, the percentage satisfaction of the critical and uncritical loads by the PV system are 49.8% and 23.7%. However with the implementation of the load management scheme in scenarios 2, 3 and 4, the percentage satisfaction of the loads (CLs, ULs are (93.8%, 74.2%, (90.9%, 70.1% and (87.2%, 65.4% for scenarios 2, 3 and 4, respectively.

  11. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  12. Dragee product based on sunflower

    Directory of Open Access Journals (Sweden)

    Pajin Biljana S.

    2003-01-01

    Full Text Available The sunflower kernel is rich in valuable nutritive compounds so it is suitable as a raw material for production of confectionery products. In this paper we evaluated the technological characteristics of the confectionery sunflower kernel with the aim of obtaining dragee products, and determining the final product quality and shelf life. The dragee product was obtained by panning sunflower kernel with savory powder mixture of spices in a dragee pan. The used sunflower seed has an even distribution of linear size and satisfactory dehulling characteristics. The savoury dragee product was in excellent category of sensory quality and showed stable colour and good shelf life in the period of three months.

  13. Spin alignment and violation of the OZI rule in exclusive ω and ϕ production in pp collisions

    Directory of Open Access Journals (Sweden)

    C. Adolph

    2014-09-01

    Full Text Available Exclusive production of the isoscalar vector mesons ω and ϕ is measured with a 190 GeV/c proton beam impinging on a liquid hydrogen target. Cross section ratios are determined in three intervals of the Feynman variable xF of the fast proton. A significant violation of the OZI rule is found, confirming earlier findings. Its kinematic dependence on xF and on the invariant mass MpV of the system formed by fast proton pfast and vector meson V is discussed in terms of diffractive production of pfastV resonances in competition with central production. The measurement of the spin density matrix element ρ00 of the vector mesons in different selected reference frames provides another handle to distinguish the contributions of these two major reaction types. Again, dependences of the alignment on xF and on MpV are found. Most of the observations can be traced back to the existence of several excited baryon states contributing to ω production which are absent in the case of the ϕ meson. Removing the low-mass MpV resonant region, the OZI rule is found to be violated by a factor of eight, independently of xF.

  14. Quality prediction modeling for multistage manufacturing based on classification and association rule mining

    Directory of Open Access Journals (Sweden)

    Kao Hung-An

    2017-01-01

    Full Text Available For manufacturing enterprises, product quality is a key factor to assess production capability and increase their core competence. To reduce external failure cost, many research and methodology have been introduced in order to improve process yield rate, such as TQC/TQM, Shewhart CycleDeming's 14 Points, etc. Nowadays, impressive progress has been made in process monitoring and industrial data analysis because of the Industry 4.0 trend. Industries start to utilize quality control (QC methodology to lower inspection overhead and internal failure cost. Currently, the focus of QC is mostly in the inspection of single workstation and final product, however, for multistage manufacturing, many factors (like equipment, operators, parameters, etc. can have cumulative and interactive effects to the final quality. When failure occurs, it is difficult to resume the original settings for cause analysis. To address these problems, this research proposes a combination of principal components analysis (PCA with classification and association rule mining algorithms to extract features representing relationship of multiple workstations, predict final product quality, and analyze the root-cause of product defect. The method is demonstrated on a semiconductor data set.

  15. Knowledge Representation and Inference for Analysis and Design of Database and Tabular Rule-Based Systems

    Directory of Open Access Journals (Sweden)

    Antoni Ligeza

    2001-01-01

    Full Text Available Rulebased systems constitute a powerful tool for specification of knowledge in design and implementation of knowledge based systems. They provide also a universal programming paradigm for domains such as intelligent control, decision support, situation classification and operational knowledge encoding. In order to assure safe and reliable performance, such system should satisfy certain formal requirements, including completeness and consistency. This paper addresses the issue of analysis and verification of selected properties of a class of such system in a systematic way. A uniform, tabular scheme of single-level rule-based systems is considered. Such systems can be applied as a generalized form of databases for specification of data pattern (unconditional knowledge, or can be used for defining attributive decision tables (conditional knowledge in form of rules. They can also serve as lower-level components of a hierarchical multi-level control and decision support knowledge-based systems. An algebraic knowledge representation paradigm using extended tabular representation, similar to relational database tables is presented and algebraic bases for system analysis, verification and design support are outlined.

  16. Market-based product development

    DEFF Research Database (Denmark)

    Bisp, Søren; Harmsen, Hanne

    1997-01-01

    A large body of research results on successful product development exists. The results are full of normative advice on how to conduct prod-uct development. At the same time studies have shown that product development practice has only to a very li extent been influenced by these research results...

  17. Compensatory Processing During Rule-Based Category Learning in Older Adults

    Science.gov (United States)

    Bharani, Krishna L.; Paller, Ken A.; Reber, Paul J.; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G.

    2016-01-01

    Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex. PMID:26422522

  18. Oil palm fresh fruit bunch ripeness classification based on rule- based expert system of ROI image processing technique results

    International Nuclear Information System (INIS)

    Alfatni, M S M; Shariff, A R M; Marhaban, M H; Shafie, S B; Saaed, O M B; Abdullah, M Z; BAmiruddin, M D

    2014-01-01

    There is a processing need for a fast, easy and accurate classification system for oil palm fruit ripeness. Such a system will be invaluable to farmers and plantation managers who need to sell their oil palm fresh fruit bunch (FFB) for the mill as this will avoid disputes. In this paper,a new approach was developed under the name of expert rules-based systembased on the image processing techniques results of thethree different oil palm FFB region of interests (ROIs), namely; ROI1 (300x300 pixels), ROI2 (50x50 pixels) and ROI3 (100x100 pixels). The results show that the best rule-based ROIs for statistical colour feature extraction with k-nearest neighbors (KNN) classifier at 94% were chosen as well as the ROIs that indicated results higher than the rule-based outcome, such as the ROIs of statistical colour feature extraction with artificial neural network (ANN) classifier at 94%, were selected for further FFB ripeness inspection system

  19. Exposure estimates based on broadband elf magnetic field measurements versus the ICNIRP multiple frequency rule

    International Nuclear Information System (INIS)

    Paniagua, Jesus M.; Rufo, Montana; Jimenez, Antonio; Pachon, Fernando T.; Carrero, Julian

    2015-01-01

    The evaluation of exposure to extremely low-frequency (ELF) magnetic fields using broadband measurement techniques gives satisfactory results when the field has essentially a single frequency. Nevertheless, magnetic fields are in most cases distorted by harmonic components. This work analyses the harmonic components of the ELF magnetic field in an outdoor urban context and compares the evaluation of the exposure based on broadband measurements with that based on spectral analysis. The multiple frequency rule of the International Commission on Non-ionizing Radiation Protection (ICNIRP) regulatory guidelines was applied. With the 1998 ICNIRP guideline, harmonics dominated the exposure with a 55 % contribution. With the 2010 ICNIRP guideline, however, the primary frequency dominated the exposure with a 78 % contribution. Values of the exposure based on spectral analysis were significantly higher than those based on broadband measurements. Hence, it is clearly necessary to determine the harmonic components of the ELF magnetic field to assess exposure in urban contexts. (authors)

  20. Typelets - a rule-based evaluation model for dynamic, statically typed user interfaces

    DEFF Research Database (Denmark)

    Elsman, Martin; Schack-Nielsen, Anders

    2014-01-01

    We present the concept of typelets, a specification technique for dynamic graphical user interfaces (GUIs) based on types. The technique is implemented in a dialect of ML, called MLFi (MLFi is a derivative of OCaml, extended by LexiFi with extensions targeted at the financial industry), which...... specification language allows layout programmers (e.g., end-users) to reorganize layouts in a type-safe way without being allowed to alter the rule machinery. The resulting framework is highly flexible and allows for creating highly maintainable modules. It is used with success in the context of SimCorp's high...

  1. A rule-based approach to model checking of UML state machines

    Science.gov (United States)

    Grobelna, Iwona; Grobelny, Michał; Stefanowicz, Łukasz

    2016-12-01

    In the paper a new approach to formal verification of control process specification expressed by means of UML state machines in version 2.x is proposed. In contrast to other approaches from the literature, we use the abstract and universal rule-based logical model suitable both for model checking (using the nuXmv model checker), but also for logical synthesis in form of rapid prototyping. Hence, a prototype implementation in hardware description language VHDL can be obtained that fully reflects the primary, already formally verified specification in form of UML state machines. Presented approach allows to increase the assurance that implemented system meets the user-defined requirements.

  2. The development of cause analysis system for CPCS trip using the rule-base deduction

    International Nuclear Information System (INIS)

    Park, Hee Seok; Kim, Dong Hoon; Seo, Ho Joon; Koo, In Soo; Park, Suk Joon

    1992-01-01

    The Core Protection Calculator System(CPCS) was developed to initiate a Reactor Trip under the circumstance of certain transients by Combustion Engineering Company. The major function of the CPCS is to generate contact outputs for the Departure from Nucleate Boiling Ratio(DNBR) Trip and Local Power Density(LPD) Trip. But in CPCS the trip causes can not be identified, only trip status is displayed. It may take much time and efforts for plant operator to analyse the trip causes of CPCS. So, the Cause Analysis System for CPCS(CASCPCS) has been developed using the rule-base deduction method to aid the operators in Nuclear Power Plant

  3. A RULE-BASED SYSTEM APPROACH FOR SAFETY MANAGEMENT IN HAZARDOUS WORK SYSTEMS

    Directory of Open Access Journals (Sweden)

    Ercüment N. DİZDAR

    1998-03-01

    Full Text Available Developments in technology increased the importance of safety management in work life. These improvements also resulted in a requirement of more investment and assignment on human in work systems. Here we face this problem: Can we make it possible to forecast the possible accidents that workers can face, and prevent these accidents by taking necessary precautions? In this study made, we aimed at developing an rule-based system to forecast the occupational accidents in coming periods at the departments of the facilities in hazardous work systems. The validity of the developed system was proved by implementing it into practice in hazardous work systems in manufacturing industry.

  4. Fuzzy rule-based forecast of meteorological drought in western Niger

    Science.gov (United States)

    Abdourahamane, Zakari Seybou; Acar, Reşat

    2018-01-01

    Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R 2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α based forecast model shows better forecast skills.

  5. Retail sales of scheduled listed chemical products; self-certification of regulated sellers of scheduled listed chemical products. Interim final rule with request for comment.

    Science.gov (United States)

    2006-09-26

    In March 2006, the President signed the Combat Methamphetamine Epidemic Act of 2005, which establishes new requirements for retail sales of over-the-counter (nonprescription) products containing the List I chemicals ephedrine, pseudoephedrine, and phenylpropanolamine. The three chemicals can be used to manufacture methamphetamine illegally. DEA is promulgating this rule to incorporate the statutory provisions and make its regulations consistent with the new requirements. This action establishes daily and 30-day limits on the sales of scheduled listed chemical products to individuals and requires recordkeeping on most sales.

  6. Rule-Based Reasoning Is Fast and Belief-Based Reasoning Can Be Slow: Challenging Current Explanations of Belief-Bias and Base-Rate Neglect

    Science.gov (United States)

    Newman, Ian R.; Gibb, Maia; Thompson, Valerie A.

    2017-01-01

    It is commonly assumed that belief-based reasoning is fast and automatic, whereas rule-based reasoning is slower and more effortful. Dual-Process theories of reasoning rely on this speed-asymmetry explanation to account for a number of reasoning phenomena, such as base-rate neglect and belief-bias. The goal of the current study was to test this…

  7. The α3S corrections to the Bjorken sum rule for polarized electro-production and to the Gross-Llewellyn Smith sum rule

    International Nuclear Information System (INIS)

    Larin, S.A.; Nationaal Inst. voor Kernfysica en Hoge-Energiefysica; Vermaseren, J.A.M.

    1990-01-01

    The next-next-to-leading order QCD corrections to the Gross-Llewellyn Smith sum rule for deep inelastic neutrino-nucleon scattering and to the Bjorken sum rule for polarized electron-nucleon scattering have been computed. This involved the proper treatment of γ 5 inside the loop integrals with dimensional regularization. It is found that the difference between the two sum rules are entirely due to a class of 6 three loop graphs and is of the order of 1% of the leading QCD term. Hence the Q 2 behavior of both sum rules should be the same if the physics is described adequately by the lower order terms of perturbative QCD. (author). 12 refs.; 2 figs.; 4 tabs

  8. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    Science.gov (United States)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  9. Online Rule Generation Software Process Model

    OpenAIRE

    Sudeep Marwaha; Alka Aroa; Satma M C; Rajni Jain; R C Goyal

    2013-01-01

    For production systems like expert systems, a rule generation software can facilitate the faster deployment. The software process model for rule generation using decision tree classifier refers to the various steps required to be executed for the development of a web based software model for decision rule generation. The Royce’s final waterfall model has been used in this paper to explain the software development process. The paper presents the specific output of various steps of modified wat...

  10. Study on Transfer Rules of Coal Reservoir Pressure Drop Based on Coalbed Methane Well Drainage Experiments

    Science.gov (United States)

    Yuhang, X.

    2017-12-01

    has little influence on the communication between these two systems. The definition of transfer rules in coal reservoir pressure drop, also the understanding of the correlation between the rules and characteristics of the reservoir output has great guiding significance to the establishment of pressure drop system in coalbed methane well as well as the analysis of production problems.

  11. Criterial noise effects on rule-based category learning: the impact of delayed feedback.

    Science.gov (United States)

    Ell, Shawn W; Ing, A David; Maddox, W Todd

    2009-08-01

    Variability in the representation of the decision criterion is assumed in many category-learning models, yet few studies have directly examined its impact. On each trial, criterial noise should result in drift in the criterion and will negatively impact categorization accuracy, particularly in rule-based categorization tasks, where learning depends on the maintenance and manipulation of decision criteria. In three experiments, we tested this hypothesis and examined the impact of working memory on slowing the drift rate. In Experiment 1, we examined the effect of drift by inserting a 5-sec delay between the categorization response and the delivery of corrective feedback, and working memory demand was manipulated by varying the number of decision criteria to be learned. Delayed feedback adversely affected performance, but only when working memory demand was high. In Experiment 2, we built on a classic finding in the absolute identification literature and demonstrated that distributing the criteria across multiple dimensions decreases the impact of drift during the delay. In Experiment 3, we confirmed that the effect of drift during the delay is moderated by working memory. These results provide important insights into the interplay between criterial noise and working memory, as well as providing important constraints for models of rule-based category learning.

  12. Experimental test of Neel's theory of the Rayleigh rule using gradually devitrified Co-based glass

    International Nuclear Information System (INIS)

    Lachowicz, H.K.

    2000-01-01

    It is shown that gradually devitrified Co-based nonmagnetostrictive metallic glass is an excellent model material to verify Louis Neel's theory of the Rayleigh rule. In the course of the calculations, Neel showed that the parameter p=bH c /a (where H c is the coercivity, a and b are the coefficients of a quadratic polynomial expressing the Rayleigh rule) is expected to range between 0.6 (hard magnets) and 1.6 (soft). However, the experimental values of this parameter, reported in the literature for a number of mono- and poly-crystalline magnets, are much greater than those expected from the theory presented by Neel (in some cases even by two orders of magnitude). The measurements, performed for a series of Co-based metallic glass samples annealed at gradually increasing temperature to produce nanocrystalline structures with differentiated density and size of the crystallites, have shown that the calculated values of the parameter p fall within the range expected from Neel's theory

  13. How Politics Shapes the Growth of Rules

    DEFF Research Database (Denmark)

    Jakobsen, Mads Leth Felsager; Mortensen, Peter Bjerre

    2015-01-01

    when, why, and how political factors shape changes in the stock of rules. Furthermore, we test these hypotheses on a unique, new data set based on all Danish primary legislation and administrative rules from 1989 to 2011 categorized into 20 different policy domains. The analysis shows......This article examines the impact of politics on governmental rule production. Traditionally, explanations of rule dynamics have focused on nonpolitical factors such as the self-evolvement of rules, environmental factors, and decision maker attributes. This article develops a set of hypotheses about...... that the traditional Weberian “rules breed rules” explanations must be supplemented with political explanations that take party ideology and changes in the political agenda into account. Moreover, the effect of political factors is indistinguishable across changes in primary laws and changes in administrative rules...

  14. PRINCIPLES- AND RULES-BASED ACCOUNTING DEBATE. IMPLICATIONS FOR AN EMERGENT COUNTRY

    Directory of Open Access Journals (Sweden)

    Deaconu Adela

    2011-07-01

    Full Text Available By a qualitative analysis, this research observes whether a principles-based system or a mixed version of it with the rules-based system, applied in Romania - an emergent country - is appropriate taking into account the mentalities, the traditions, and other cultural elements that were typical of a rules-based system. We support the statement that, even if certain contextual variables are common to other developed countries, their environments significantly differ. To be effective, financial reporting must reflect the firm's context in which it is functioning. The research has a deductive approach based on the analysis of the cultural factors and their influence in the last years. For Romania it is argue a lower accounting professionalism associated with a low level of ambiguity tolerance. For the stage analysed in this study (after the year 2005 the professional reasoning - a proxy for the accounting professional behaviour - took into consideration the fiscal and legal requirements rather than the accounting principles and judgments. The research suggest that the Romanian accounting practice and the professionals are not fully prepared for a principles-based system environment, associated with the ability to find undisclosed events, facing ambiguity, identifying inferred relationships and using intuition, respectively working with uncertainty. We therefore reach the conclusion that in Romania institutional amendments affecting the professional expertise would be needed. The accounting regulations must be chosen with great caution and they must answer and/ or be adjusted, even if the process would be delayed, to national values, behaviour of companies and individual expertise and beliefs. Secondly, the benefits of applying accounting reasoning in this country may be enhanced through a better understanding of their content and through practical exercise. Here regulatory bodies may intervene for organizing professional training programs and acting

  15. Context-Based Tourism Information Filtering with a Semantic Rule Engine

    Science.gov (United States)

    Lamsfus, Carlos; Martin, David; Alzua-Sorzabal, Aurkene; López-de-Ipiña, Diego; Torres-Manzanera, Emilio

    2012-01-01

    This paper presents the CONCERT framework, a push/filter information consumption paradigm, based on a rule-based semantic contextual information system for tourism. CONCERT suggests a specific insight of the notion of context from a human mobility perspective. It focuses on the particular characteristics and requirements of travellers and addresses the drawbacks found in other approaches. Additionally, CONCERT suggests the use of digital broadcasting as push communication technology, whereby tourism information is disseminated to mobile devices. This information is then automatically filtered by a network of ontologies and offered to tourists on the screen. The results obtained in the experiments carried out show evidence that the information disseminated through digital broadcasting can be manipulated by the network of ontologies, providing contextualized information that produces user satisfaction. PMID:22778584

  16. A Stock Trading Recommender System Based on Temporal Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Binoy B. Nair

    2015-04-01

    Full Text Available Recommender systems capable of discovering patterns in stock price movements and generating stock recommendations based on the patterns thus discovered can significantly supplement the decision-making process of a stock trader. Such recommender systems are of great significance to a layperson who wishes to profit by stock trading even while not possessing the skill or expertise of a seasoned trader. A genetic algorithm optimized Symbolic Aggregate approXimation (SAX–Apriori based stock trading recommender system, which can mine temporal association rules from the stock price data set to generate stock trading recommendations, is presented in this article. The proposed system is validated on 12 different data sets. The results indicate that the proposed system significantly outperforms the passive buy-and-hold strategy, offering scope for a layperson to successfully invest in capital markets.

  17. Increasing Supply-Chain Visibility with Rule-Based RFID Data Analysis

    DEFF Research Database (Denmark)

    Ilic, A.; Andersen, Thomas; Michahelles, F.

    2009-01-01

    RFID technology tracks the flow of physical items and goods in supply chains to help users detect inefficiencies, such as shipment delays, theft, or inventory problems. An inevitable consequence, however, is that it generates huge numbers of events. To exploit these large amounts of data, the Sup......RFID technology tracks the flow of physical items and goods in supply chains to help users detect inefficiencies, such as shipment delays, theft, or inventory problems. An inevitable consequence, however, is that it generates huge numbers of events. To exploit these large amounts of data......, the Supply Chain Visualizer increases supply-chain visibility by analyzing RFID data, using a mix of automated analysis techniques and human effort. The tool's core concepts include rule-based analysis techniques and a map-based representation interface. With these features, it lets users visualize...

  18. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    Directory of Open Access Journals (Sweden)

    Hurwitz Eric L

    2008-08-01

    Full Text Available Abstract Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source and 3 (which investigates perpetuating factors of the pain experience. In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed.

  19. Improving the anesthetic process by a fuzzy rule based medical decision system.

    Science.gov (United States)

    Mendez, Juan Albino; Leon, Ana; Marrero, Ayoze; Gonzalez-Cava, Jose M; Reboso, Jose Antonio; Estevez, Jose Ignacio; Gomez-Gonzalez, José F

    2018-01-01

    The main objective of this research is the design and implementation of a new fuzzy logic tool for automatic drug delivery in patients undergoing general anesthesia. The aim is to adjust the drug dose to the real patient needs using heuristic knowledge provided by clinicians. A two-level computer decision system is proposed. The idea is to release the clinician from routine tasks so that he can focus on other variables of the patient. The controller uses the Bispectral Index (BIS) to assess the hypnotic state of the patient. Fuzzy controller was included in a closed-loop system to reach the BIS target and reject disturbances. BIS was measured using a BIS VISTA monitor, a device capable of calculating the hypnosis level of the patient through EEG information. An infusion pump with propofol 1% is used to supply the drug to the patient. The inputs to the fuzzy inference system are BIS error and BIS rate. The output is infusion rate increment. The mapping of the input information and the appropriate output is given by a rule-base based on knowledge of clinicians. To evaluate the performance of the fuzzy closed-loop system proposed, an observational study was carried out. Eighty one patients scheduled for ambulatory surgery were randomly distributed in 2 groups: one group using a fuzzy logic based closed-loop system (FCL) to automate the administration of propofol (42 cases); the second group using manual delivering of the drug (39 cases). In both groups, the BIS target was 50. The FCL, designed with intuitive logic rules based on the clinician experience, performed satisfactorily and outperformed the manual administration in patients in terms of accuracy through the maintenance stage. Copyright © 2018 Elsevier B.V. All rights reserved.

  20. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2011-10-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and costsensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method;candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal parameters

  1. Intelligent Recognition of Lung Nodule Combining Rule-based and C-SVM Classifiers

    Directory of Open Access Journals (Sweden)

    Bin Li

    2012-02-01

    Full Text Available Computer-aided detection(CAD system for lung nodules plays the important role in the diagnosis of lung cancer. In this paper, an improved intelligent recognition method of lung nodule in HRCT combing rule-based and cost-sensitive support vector machine(C-SVM classifiers is proposed for detecting both solid nodules and ground-glass opacity(GGO nodules(part solid and nonsolid. This method consists of several steps. Firstly, segmentation of regions of interest(ROIs, including pulmonary parenchyma and lung nodule candidates, is a difficult task. On one side, the presence of noise lowers the visibility of low-contrast objects. On the other side, different types of nodules, including small nodules, nodules connecting to vasculature or other structures, part-solid or nonsolid nodules, are complex, noisy, weak edge or difficult to define the boundary. In order to overcome the difficulties of obvious boundary-leak and slow evolvement speed problem in segmentatioin of weak edge, an overall segmentation method is proposed, they are: the lung parenchyma is extracted based on threshold and morphologic segmentation method; the image denoising and enhancing is realized by nonlinear anisotropic diffusion filtering(NADF method; candidate pulmonary nodules are segmented by the improved C-V level set method, in which the segmentation result of EM-based fuzzy threshold method is used as the initial contour of active contour model and a constrained energy term is added into the PDE of level set function. Then, lung nodules are classified by using the intelligent classifiers combining rules and C-SVM. Rule-based classification is first used to remove easily dismissible nonnodule objects, then C-SVM classification are used to further classify nodule candidates and reduce the number of false positive(FP objects. In order to increase the efficiency of SVM, an improved training method is used to train SVM, which uses the grid search method to search the optimal

  2. Residents' surgical performance during the laboratory years: an analysis of rule-based errors.

    Science.gov (United States)

    Nathwani, Jay N; Wise, Brett J; Garren, Margaret E; Mohamadipanah, Hossein; Van Beek, Nicole; DiMarco, Shannon M; Pugh, Carla M

    2017-11-01

    Nearly one-third of surgical residents will enter into academic development during their surgical residency by dedicating time to a research fellowship for 1-3 y. Major interest lies in understanding how laboratory residents' surgical skills are affected by minimal clinical exposure during academic development. A widely held concern is that the time away from clinical exposure results in surgical skills decay. This study examines the impact of the academic development years on residents' operative performance. We hypothesize that the use of repeated, annual assessments may result in learning even without individual feedback on participants simulated performance. Surgical performance data were collected from laboratory residents (postgraduate years 2-5) during the summers of 2014, 2015, and 2016. Residents had 15 min to complete a shortened, simulated laparoscopic ventral hernia repair procedure. Final hernia repair skins from all participants were scored using a previously validated checklist. An analysis of variance test compared the mean performance scores of repeat participants to those of first time participants. Twenty-seven (37% female) laboratory residents provided 2-year assessment data over the 3-year span of the study. Second time performance revealed improvement from a mean score of 14 (standard error = 1.0) in the first year to 17.2 (SD = 0.9) in the second year, (F[1, 52] = 5.6, P = 0.022). Detailed analysis demonstrated improvement in performance for 3 grading criteria that were considered to be rule-based errors. There was no improvement in operative strategy errors. Analysis of longitudinal performance of laboratory residents shows higher scores for repeat participants in the category of rule-based errors. These findings suggest that laboratory residents can learn from rule-based mistakes when provided with annual performance-based assessments. This benefit was not seen with operative strategy errors and has important implications for

  3. Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

    Science.gov (United States)

    Zhang, W.; Li, X.; Xiao, W.

    2018-05-01

    The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the

  4. State Identification of Hoisting Motors Based on Association Rules for Quayside Container Crane

    Science.gov (United States)

    Li, Q. Z.; Gang, T.; Pan, H. Y.; Xiong, H.

    2017-07-01

    Quay container crane hoisting motor is a complex system, and the characteristics of long-term evolution and change of running status of there is a rule, and use it. Through association rules analysis, this paper introduced the similarity in association rules, and quay container crane hoisting motor status identification. Finally validated by an example, some rules change amplitude is small, regular monitoring, not easy to find, but it is precisely because of these small changes led to mechanical failure. Therefore, using the association rules change in monitoring the motor status has the very strong practical significance.

  5. Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

    Science.gov (United States)

    Yu, Nanpeng

    As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this

  6. Selecting Tanker Steaming Speeds under Uncertainty: A Rule-Based Bayesian Reasoning Approach

    Directory of Open Access Journals (Sweden)

    N.S.F. Abdul Rahman

    2015-06-01

    Full Text Available In the tanker industry, there are a lot of uncertain conditions that tanker companies have to deal with. For example, the global financial crisis and economic recession, the increase of bunker fuel prices and global climate change. Such conditions have forced tanker companies to change tankers speed from full speed to slow speed, extra slow speed and super slow speed. Due to such conditions, the objective of this paper is to present a methodology for determining vessel speeds of tankers that minimize the cost of the vessels under such conditions. The four levels of vessel speed in the tanker industry will be investigated and will incorporate a number of uncertain conditions. This will be done by developing a scientific model using a rule-based Bayesian reasoning method. The proposed model has produced 96 rules that can be used as guidance in the decision making process. Such results help tanker companies to determine the appropriate vessel speed to be used in a dynamic operational environmental.

  7. Mining algorithm for association rules in big data based on Hadoop

    Science.gov (United States)

    Fu, Chunhua; Wang, Xiaojing; Zhang, Lijun; Qiao, Liying

    2018-04-01

    In order to solve the problem that the traditional association rules mining algorithm has been unable to meet the mining needs of large amount of data in the aspect of efficiency and scalability, take FP-Growth as an example, the algorithm is realized in the parallelization based on Hadoop framework and Map Reduce model. On the basis, it is improved using the transaction reduce method for further enhancement of the algorithm's mining efficiency. The experiment, which consists of verification of parallel mining results, comparison on efficiency between serials and parallel, variable relationship between mining time and node number and between mining time and data amount, is carried out in the mining results and efficiency by Hadoop clustering. Experiments show that the paralleled FP-Growth algorithm implemented is able to accurately mine frequent item sets, with a better performance and scalability. It can be better to meet the requirements of big data mining and efficiently mine frequent item sets and association rules from large dataset.

  8. A rule based method for context sensitive threshold segmentation in SPECT using simulation

    International Nuclear Information System (INIS)

    Fleming, John S.; Alaamer, Abdulaziz S.

    1998-01-01

    Robust techniques for automatic or semi-automatic segmentation of objects in single photon emission computed tomography (SPECT) are still the subject of development. This paper describes a threshold based method which uses empirical rules derived from analysis of computer simulated images of a large number of objects. The use of simulation allowed the factors affecting the threshold which correctly segmented objects to be investigated systematically. Rules could then be derived from these data to define the threshold in any particular context. The technique operated iteratively and calculated local context sensitive thresholds along radial profiles from the centre of gravity of the object. It was evaluated in a further series of simulated objects and in human studies, and compared to the use of a global fixed threshold. The method was capable of improving accuracy of segmentation and volume assessment compared to the global threshold technique. The improvements were greater for small volumes, shapes with large surface area to volume ratio, variable surrounding activity and non-uniform distributions. The method was applied successfully to simulated objects and human studies and is considered to be a significant advance on global fixed threshold techniques. (author)

  9. 19 CFR 102.22 - Rules of origin for textile and apparel products of Israel.

    Science.gov (United States)

    2010-04-01

    ... of Israel. 102.22 Section 102.22 Customs Duties U.S. CUSTOMS AND BORDER PROTECTION, DEPARTMENT OF... textile and apparel products of Israel. (a) Applicability. The provisions of this section will control for... product of Israel for purposes of the customs laws and the administration of quantitative limitations. A...

  10. Agent-based simulation for evaluating flexible and agile business processes : Separating knowledge rules, process rules and information resources

    NARCIS (Netherlands)

    Gong, Y.; Janssen, M.

    2010-01-01

    In today’s ever changing environment organizations need flexibility and agility to be able to deal with changes. Flexibility is necessary to adapt to changes in their environment, whilst agility is needed to rapidly response to changing customer demands. In this paper a mechanism based on the

  11. Turn-taking in cooperative offspring care: by-product of individual provisioning behavior or active response rule?

    Science.gov (United States)

    Savage, James L; Browning, Lucy E; Manica, Andrea; Russell, Andrew F; Johnstone, Rufus A

    2017-01-01

    For individuals collaborating to rear offspring, effective organization of resource delivery is difficult because each carer benefits when the others provide a greater share of the total investment required. When investment is provided in discrete events, one possible solution is to adopt a turn-taking strategy whereby each individual reduces its contribution rate after investing, only increasing its rate again once another carer contributes. To test whether turn-taking occurs in a natural cooperative care system, here we use a continuous time Markov model to deduce the provisioning behavior of the chestnut-crowned babbler ( Pomatostomus ruficeps ), a cooperatively breeding Australian bird with variable number of carers. Our analysis suggests that turn-taking occurs across a range of group sizes (2-6), with individual birds being more likely to visit following other individuals than to make repeat visits. We show using a randomization test that some of this apparent turn-taking arises as a by-product of the distribution of individual inter-visit intervals ("passive" turn-taking) but that individuals also respond actively to the investment of others over and above this effect ("active" turn-taking). We conclude that turn-taking in babblers is a consequence of both their individual provisioning behavior and deliberate response rules, with the former effect arising through a minimum interval required to forage and travel to and from the nest. Our results reinforce the importance of considering fine-scale investment dynamics when studying parental care and suggest that behavioral rules such as turn-taking may be more common than previously thought. Caring for offspring is a crucial stage in the life histories of many animals and often involves conflict as each carer typically benefits when others contribute a greater share of the work required. One way to resolve this conflict is to monitor when other carers contribute and adopt a simple "turn-taking" rule to ensure

  12. Study on the Method of Association Rules Mining Based on Genetic Algorithm and Application in Analysis of Seawater Samples

    Directory of Open Access Journals (Sweden)

    Qiuhong Sun

    2014-04-01

    Full Text Available Based on the data mining research, the data mining based on genetic algorithm method, the genetic algorithm is briefly introduced, while the genetic algorithm based on two important theories and theoretical templates principle implicit parallelism is also discussed. Focuses on the application of genetic algorithms for association rule mining method based on association rule mining, this paper proposes a genetic algorithm fitness function structure, data encoding, such as the title of the improvement program, in particular through the early issues study, proposed the improved adaptive Pc, Pm algorithm is applied to the genetic algorithm, thereby improving efficiency of the algorithm. Finally, a genetic algorithm based association rule mining algorithm, and be applied in sea water samples database in data mining and prove its effective.

  13. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

    Science.gov (United States)

    Li, Yang; Li, Guoqing; Wang, Zhenhao

    2015-01-01

    In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA) methods, a new rule extraction method based on extreme learning machine (ELM) and an improved Ant-miner (IAM) algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

  14. A PROBABILITY BASED APPROACH FOR THE ALLOCATION OF PLAYER DRAFT SELECTIONS IN AUSTRALIAN RULES FOOTBALL

    Directory of Open Access Journals (Sweden)

    Anthony Bedford

    2006-12-01

    Full Text Available Australian Rules Football, governed by the Australian Football League (AFL is the most popular winter sport played in Australia. Like North American team based leagues such as the NFL, NBA and NHL, the AFL uses a draft system for rookie players to join a team's list. The existing method of allocating draft selections in the AFL is simply based on the reverse order of each team's finishing position for that season, with teams winning less than or equal to 5 regular season matches obtaining an additional early round priority draft pick. Much criticism has been levelled at the existing system since it rewards losing teams and does not encourage poorly performing teams to win matches once their season is effectively over. We propose a probability-based system that allocates a score based on teams that win 'unimportant' matches (akin to Carl Morris' definition of importance. We base the calculation of 'unimportance' on the likelihood of a team making the final eight following each round of the season. We then investigate a variety of approaches based on the 'unimportance' measure to derive a score for 'unimportant' and unlikely wins. We explore derivatives of this system, compare past draft picks with those obtained under our system, and discuss the attractiveness of teams knowing the draft reward for winning each match in a season

  15. Fact Sheet - Final Air Toxics Rule for Gold Mine Ore Processing and Production

    Science.gov (United States)

    Fact sheet summarizing main points of National Emissions Standards for Hazardous Air Pollutants for gold ore processing and production facilities, the seventh largest source of mercury air emission in the United States.

  16. Accounting of the knowledge-based actions and the rules-based actions in frames of accident management guidelines development

    International Nuclear Information System (INIS)

    Lankin, M.Yu.; Bukrinskij, A.M.

    2015-01-01

    The main approaches used in the development of the Safety Guide (SG) “Recommendations to the structure and content of the manual for the management of beyond-design-basis accidents, including severe accidents” (BDBA MG) are described. The manual was developed taking into account the provisions of the current IAEA standards relevant to the affected area, taking into account the specifics of the Russian nuclear power industry. In the draft SG, three types of behavior of personnel are considered - based on skills, rules and knowledge. When developing BDBA MG, it is recommended to give priority to a knowledge-based approach. At the same time, when performing well-designed and worked-out activities, work is possible based on rules and skills (for example, using step-by-step procedures). The SG project provides for a unified organizational structure for managing beyond-design-basis accidents, both at the stage of preventing severe damage to the core, and at the stage of managing a heavy accident. In SG the order of management of beyond-design-basis accidents for both of the indicated stages examined in detail [ru

  17. A Rule-Based Local Search Algorithm for General Shift Design Problems in Airport Ground Handling

    DEFF Research Database (Denmark)

    Clausen, Tommy

    We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework with mul......We consider a generalized version of the shift design problem where shifts are created to cover a multiskilled demand and fit the parameters of the workforce. We present a collection of constraints and objectives for the generalized shift design problem. A local search solution framework...... with multiple neighborhoods and a loosely coupled rule engine based on simulated annealing is presented. Computational experiments on real-life data from various airport ground handling organization show the performance and flexibility of the proposed algorithm....

  18. Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling.

    Science.gov (United States)

    Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A

    2008-12-01

    The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

  19. Fuzzy Rule-based Analysis of Promotional Efficiency in Vietnam’s Tourism Industry

    Directory of Open Access Journals (Sweden)

    Nguyen Quang VINH

    2015-06-01

    Full Text Available This study aims to determine an effective method of measuring the efficiency of promotional strategies for tourist destinations. Complicating factors that influence promotional efficiency (PE, such as promotional activities (PA, destination attribute (DA, and destination image (DI, make it difficult to evaluate the effectiveness of PE. This study develops a rule-based decision support mechanism using fuzzy set theory and the Analytic Hierarchy Process (AHP to evaluate the effectiveness of promotional strategies. Additionally, a statistical analysis is conducted using SPSS (Statistics Package for Social Science to confirm the results of the fuzzy AHP analysis. This study finds that government policy is the most important factor for PE and that service staff (internal beauty is more important than tourism infrastructure (external beauty in terms of customer satisfaction and long-term strategy in PE. With respect to DI, experts are concerned first with tourist perceived value, second with tourist satisfaction and finally with tourist loyalty.

  20. A rule-based expert system for generating control displays at the Advanced Photon Source

    International Nuclear Information System (INIS)

    Coulter, K.J.

    1993-01-01

    The integration of a rule-based expert system for generating screen displays for controlling and monitoring instrumentation under the Experimental Physics and Industrial Control System (EPICS) is presented. The expert system is implemented using CLIPS, an expert system shell from the Software Technology Branch at Lyndon B. Johnson Space Center. The user selects the hardware input and output to be displayed and the expert system constructs a graphical control screen appropriate for the data. Such a system provides a method for implementing a common look and feel for displays created by several different users and reduces the amount of time required to create displays for new hardware configurations. Users are able to modify the displays as needed using the EPICS display editor tool

  1. A rule-based expert system for generating control displays at the advanced photon source

    International Nuclear Information System (INIS)

    Coulter, K.J.

    1994-01-01

    The integration of a rule-based expert system for generating screen displays for controlling and monitoring instrumentation under the Experimental Physics and Industrial Control System (EPICS) is presented. The expert system is implemented using CLIPS, an expert system shell from the Software Technology Branch at Lyndon B. Johnson Space Center. The user selects the hardware input and output to be displayed and the expert system constructs a graphical control screen appropriate for the data. Such a system provides a method for implementing a common look and feel for displays created by several different users and reduces the amount of time required to create displays for new hardware configurations. Users are able to modify the displays as needed using the EPICS display editor tool. ((orig.))

  2. Omega version 2.2: Rule-based deterioration identification and management system. Final report

    International Nuclear Information System (INIS)

    Kataoka, S.; Kojima, T.; Pavinich, W.A.; Andrews, J.D.

    1996-06-01

    This report presents the Omega Version 2.2 (Ωs) rule-based computer program for identifying material deteriorations in the metallic structures, systems and components of LWR nuclear power units. The basis of Us is that understanding what material deteriorations might occur as a function of service life is fundamental to: (1) the development and optimization of preventive maintenance programs, (2) ensuring that current maintenance programs recognize applicable degradations, and (3) demonstrating the adequacy of deterioration management to safety regulatory authorities. The system was developed to assist utility engineers in determining which aging degradation mechanisms are acting on specific components. Direction is also provided to extend this system to manage deterioration and evaluate the efficacy of existing age-related degradation mitigation programs. This system can provide support for justification for continued operation and license renewal. It provides traceability to the data sources used in the logic development. A tiered approach is used to quickly isolate potential age-related degradation for components in a particular location. A potential degradation mechanism is then screened by additional rules to establish its plausibility. Ωs includes a user-friendly system interface and provides default environmental data and materials in the event they are unknown to the user. Ωs produces a report, with references, that validates the elimination of a degradation mechanism from further consideration or the determination that a specific degradation mechanism is acting on a specific material. This report also describes logic for identifying deterioration caused by intrusions and inspection-based deteriorations, along with future plans to program and integrate these features with Ωs

  3. Updating OSHA standards based on national consensus standards. final rule; confirmation of effective date.

    Science.gov (United States)

    2008-03-14

    OSHA is confirming the effective date of its direct final rule that revises a number of standards for general industry that refer to national consensus standards. The direct final rule states that it would become effective on March 13, 2008 unless OSHA receives significant adverse comment on these revisions by January 14, 2008. OSHA received no adverse comments by that date and, therefore, is confirming that the rule will become effective on March 13, 2008.

  4. Updating OSHA standards based on national consensus standards. Direct final rule.

    Science.gov (United States)

    2007-12-14

    In this direct final rule, the Agency is removing several references to consensus standards that have requirements that duplicate, or are comparable to, other OSHA rules; this action includes correcting a paragraph citation in one of these OSHA rules. The Agency also is removing a reference to American Welding Society standard A3.0-1969 ("Terms and Definitions") in its general-industry welding standards. This rulemaking is a continuation of OSHA's ongoing effort to update references to consensus and industry standards used throughout its rules.

  5. Three dimensional pattern recognition using feature-based indexing and rule-based search

    Science.gov (United States)

    Lee, Jae-Kyu

    In flexible automated manufacturing, robots can perform routine operations as well as recover from atypical events, provided that process-relevant information is available to the robot controller. Real time vision is among the most versatile sensing tools, yet the reliability of machine-based scene interpretation can be questionable. The effort described here is focused on the development of machine-based vision methods to support autonomous nuclear fuel manufacturing operations in hot cells. This thesis presents a method to efficiently recognize 3D objects from 2D images based on feature-based indexing. Object recognition is the identification of correspondences between parts of a current scene and stored views of known objects, using chains of segments or indexing vectors. To create indexed object models, characteristic model image features are extracted during preprocessing. Feature vectors representing model object contours are acquired from several points of view around each object and stored. Recognition is the process of matching stored views with features or patterns detected in a test scene. Two sets of algorithms were developed, one for preprocessing and indexed database creation, and one for pattern searching and matching during recognition. At recognition time, those indexing vectors with the highest match probability are retrieved from the model image database, using a nearest neighbor search algorithm. The nearest neighbor search predicts the best possible match candidates. Extended searches are guided by a search strategy that employs knowledge-base (KB) selection criteria. The knowledge-based system simplifies the recognition process and minimizes the number of iterations and memory usage. Novel contributions include the use of a feature-based indexing data structure together with a knowledge base. Both components improve the efficiency of the recognition process by improved structuring of the database of object features and reducing data base size

  6. Rule Based Reasoning Untuk Monitoring Distribusi Bahan Bakar Minyak Secara Online dan Realtime menggunakan Radio Frequency Identification

    Directory of Open Access Journals (Sweden)

    Mokhamad Iklil Mustofa

    2017-05-01

    Full Text Available The scarcity of fuel oil in Indonesia often occurs due to delays in delivery caused by natural factors or transportation constraints. Theaim of this  research is to develop systems of fuel distribution monitoring online and realtime using rule base reasoning method and radio frequency identification technology. The rule-based reasoning method is used as a rule-based reasoning model used for monitoring distribution and determine rule-based safety stock. The monitoring system program is run with a web-based computer application. Radio frequency identification technology is used by utilizing radio waves as an media identification. This technology is used as a system of tracking and gathering information from objects automatically. The research data uses data of delayed distribution of fuel from fuel terminal to consumer. The monitoring technique uses the time of departure, the estimated time to arrive, the route / route passed by a fuel tanker attached to the radio frequency Identification tag. This monitoring system is carried out by the radio frequency identification reader connected online at any gas station or specified position that has been designed with study case in Semarang. The results of the research covering  the status of rule based reasoning that sends status, that is timely and appropriate paths, timely and truncated pathways, late and on track, late and cut off, and tank lost. The monitoring system is also used in determining the safety stock warehouse, with the safety stock value determined based on the condition of the stock warehouse rules.

  7. 77 FR 4498 - Rules and Regulations Under the Wool Products Labeling Act of 1939

    Science.gov (United States)

    2012-01-30

    ... achieve their intended purpose without unduly burdening commerce. As part of this systematic review, the Commission requests public comment on the overall costs, benefits, necessity, and regulatory and economic..., and on the costs and benefits of certain provisions of the Wool Products Labeling Act of 1939. DATES...

  8. The field-tested and grounded technological rule as product of mode 2 management research

    NARCIS (Netherlands)

    Aken, van J.E.

    2004-01-01

    The relevance problem of academic management research in organization and management is an old and thorny one. Recent discussions on this issue have resulted in proposals to use more Mode 2 knowledge production in our field. These discussions focused mainly on the process of research itself and less

  9. Romanian legal management rules limit wood production in Norway spruce and beech forests

    Directory of Open Access Journals (Sweden)

    Olivier Bouriaud

    2016-09-01

    Full Text Available Background The quantitative impact of forest management on forests’ wood resource was evaluated for Picea and Fagus mixed forests. The effects on the productivity of tendering operations, thinnings and rotation length have seldom been directly quantified on landscape scale. Methods Two sites of similar fertility but subject to contrasted forest management were studied with detailed inventories: one in Germany, the other in Romania, and compared with the respective national forest inventories. In Romania, regulations impose very long rotations, low thinnings and a period of no-cut before harvest. In contrast, tending and thinnings are frequent and intense in Germany. Harvests start much earlier and must avoid clear cutting but maintain a permanent forest cover with natural regeneration. While Germany has an average annual wood increment representative for Central Europe, Romania represents the average for Eastern Europe. Results The lack of tending and thinning in the Romanian site resulted in twice as many trees per hectare as in the German site for the same age. The productivity in Romanian production forests was 20 % lower than in Germany despite a similar fertility. The results were supported by the data from the national forest inventory of each country, which confirmed that the same differential exists at country scale. Furthermore, provided the difference in rotation length, two crops are harvested in Germany when only one is harvested in Romania. The losses of production due to a lower level of management in Romania where estimated to reach 12.8 million m3.y-1 in regular mountain production forests, and to 15 million m3.y-1 if managed protection forest is included. Conclusions The productivity of Picea and Fagus mountain forests in Romania is severely depressed by the lack of tending and thinning, by overly long rotations and the existence of a 25-years no-cut period prior to harvest. The average standing volume in Germany was 50

  10. Rule-based Approach on Extraction of Malay Compound Nouns in Standard Malay Document

    Science.gov (United States)

    Abu Bakar, Zamri; Kamal Ismail, Normaly; Rawi, Mohd Izani Mohamed

    2017-08-01

    Malay compound noun is defined as a form of words that exists when two or more words are combined into a single syntax and it gives a specific meaning. Compound noun acts as one unit and it is spelled separately unless an established compound noun is written closely from two words. The basic characteristics of compound noun can be seen in the Malay sentences which are the frequency of that word in the text itself. Thus, this extraction of compound nouns is significant for the following research which is text summarization, grammar checker, sentiments analysis, machine translation and word categorization. There are many research efforts that have been proposed in extracting Malay compound noun using linguistic approaches. Most of the existing methods were done on the extraction of bi-gram noun+noun compound. However, the result still produces some problems as to give a better result. This paper explores a linguistic method for extracting compound Noun from stand Malay corpus. A standard dataset are used to provide a common platform for evaluating research on the recognition of compound Nouns in Malay sentences. Therefore, an improvement for the effectiveness of the compound noun extraction is needed because the result can be compromised. Thus, this study proposed a modification of linguistic approach in order to enhance the extraction of compound nouns processing. Several pre-processing steps are involved including normalization, tokenization and tagging. The first step that uses the linguistic approach in this study is Part-of-Speech (POS) tagging. Finally, we describe several rules-based and modify the rules to get the most relevant relation between the first word and the second word in order to assist us in solving of the problems. The effectiveness of the relations used in our study can be measured using recall, precision and F1-score techniques. The comparison of the baseline values is very essential because it can provide whether there has been an improvement

  11. Consortia based production of biochemicals

    DEFF Research Database (Denmark)

    Ingemann Jensen, Sheila; Sukumara, Sumesh; Özdemir, Emre

    2016-01-01

    One of the great challenges facing society is how to sustainably produce food, chemicals and other commodities required to maintain and develop our current life style. To compete with and ultimately replace existing petrochemical-based manufacturing processes, the development of innovative...

  12. Behavior-based rules for fitness-for-duty assessment of nuclear power plant personnel

    International Nuclear Information System (INIS)

    Kennedy, R.S.

    1989-01-01

    The safe and reliable operation of nuclear power plants requires that plant personnel not be under the influence of any substance, legal or illegal, or mentally or physically impaired from any cause that in any way adversely affects their ability to safely and competently perform their duties. This goal has been formalized by the US Nuclear Regulatory Commission in their proposed rule for a fitness-for-duty program. The purpose of this paper is to describe a performance-based tool based on surrogate tests and dose equivalency methodologies that is a viable candidate for fitness-for-duty assessment. The automated performance test system (APTS) is a microcomputer-based human performance test battery that has been developed over a decade of research supported variously by the National Science Foundation, National Aeronautics and Space Administration, US Department of Energy, and the US Navy and Army. Representing the most psychometrically sound test from evaluations of over 150 well-known tests of basic psychomotor and cognitive skills, the battery provides direct prediction of a worker's fitness for duty. Twenty-four tests are suitable for use, and a dozen have thus far been shown to be sensitive to the effects of legal and illegal drugs, alcohol, fatigue, stress, and other causes of impairment

  13. RFID sensor-tags feeding a context-aware rule-based healthcare monitoring system.

    Science.gov (United States)

    Catarinucci, Luca; Colella, Riccardo; Esposito, Alessandra; Tarricone, Luciano; Zappatore, Marco

    2012-12-01

    Along with the growing of the aging population and the necessity of efficient wellness systems, there is a mounting demand for new technological solutions able to support remote and proactive healthcare. An answer to this need could be provided by the joint use of the emerging Radio Frequency Identification (RFID) technologies and advanced software choices. This paper presents a proposal for a context-aware infrastructure for ubiquitous and pervasive monitoring of heterogeneous healthcare-related scenarios, fed by RFID-based wireless sensors nodes. The software framework is based on a general purpose architecture exploiting three key implementation choices: ontology representation, multi-agent paradigm and rule-based logic. From the hardware point of view, the sensing and gathering of context-data is demanded to a new Enhanced RFID Sensor-Tag. This new device, de facto, makes possible the easy integration between RFID and generic sensors, guaranteeing flexibility and preserving the benefits in terms of simplicity of use and low cost of UHF RFID technology. The system is very efficient and versatile and its customization to new scenarios requires a very reduced effort, substantially limited to the update/extension of the ontology codification. Its effectiveness is demonstrated by reporting both customization effort and performance results obtained from validation in two different healthcare monitoring contexts.

  14. European Marketing Authorizations Granted Based on a Single Pivotal Clinical Trial: The Rule or the Exception?

    Science.gov (United States)

    Morant, Anne Vinther; Vestergaard, Henrik Tang

    2018-07-01

    A minimum of two positive, adequate, and well-controlled clinical trials has historically been the gold standard for providing substantial evidence to support regulatory approval of a new medicine. Nevertheless, the present analysis of European Marketing Authorizations granted between 2012 and 2016 showed that 45% of new active substances were approved based on a single pivotal clinical trial. For therapeutic areas such as oncology and cardiovascular diseases, approvals based on a single pivotal trial are the rule rather than the exception, whereas new medicines within the nervous system area were generally supported by two or more pivotal trials. While overall similar trends have been observed in the US, the recent US Food and Drug Administration approvals of nervous system medicines based on a single pivotal trial suggest that a case-by-case scientific evaluation of the totality of evidence is increasingly applied to facilitate faster access of new medicines to patients suffering from serious diseases. © 2017 American Society for Clinical Pharmacology and Therapeutics.

  15. Ontology-based classification of remote sensing images using spectral rules

    Science.gov (United States)

    Andrés, Samuel; Arvor, Damien; Mougenot, Isabelle; Libourel, Thérèse; Durieux, Laurent

    2017-05-01

    Earth Observation data is of great interest for a wide spectrum of scientific domain applications. An enhanced access to remote sensing images for "domain" experts thus represents a great advance since it allows users to interpret remote sensing images based on their domain expert knowledge. However, such an advantage can also turn into a major limitation if this knowledge is not formalized, and thus is difficult for it to be shared with and understood by other users. In this context, knowledge representation techniques such as ontologies should play a major role in the future of remote sensing applications. We implemented an ontology-based prototype to automatically classify Landsat images based on explicit spectral rules. The ontology is designed in a very modular way in order to achieve a generic and versatile representation of concepts we think of utmost importance in remote sensing. The prototype was tested on four subsets of Landsat images and the results confirmed the potential of ontologies to formalize expert knowledge and classify remote sensing images.

  16. ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

    Science.gov (United States)

    Bittig, Arne T; Uhrmacher, Adelinde M

    2017-01-01

    Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

  17. Rule Based Expert System for Monitoring Real Time Drug Supply in Hospital Using Radio Frequency Identification Technology

    Science.gov (United States)

    Driandanu, Galih; Surarso, Bayu; Suryono

    2018-02-01

    A radio frequency identification (RFID) has obtained increasing attention with the emergence of various applications. This study aims to examine the implementation of rule based expert system supported by RFID technology into a monitoring information system of drug supply in a hospital. This research facilitates in monitoring the real time drug supply by using data sample from the hospital pharmacy. This system able to identify and count the number of drug and provide warning and report in real time. the conclusion is the rule based expert system and RFID technology can facilitate the performance in monitoring the drug supply quickly and precisely.

  18. RuleML-Based Learning Object Interoperability on the Semantic Web

    Science.gov (United States)

    Biletskiy, Yevgen; Boley, Harold; Ranganathan, Girish R.

    2008-01-01

    Purpose: The present paper aims to describe an approach for building the Semantic Web rules for interoperation between heterogeneous learning objects, namely course outlines from different universities, and one of the rule uses: identifying (in)compatibilities between course descriptions. Design/methodology/approach: As proof of concept, a rule…

  19. The Cost of Technical Trading Rules in the Forex Market: A Utility-based Evaluation

    NARCIS (Netherlands)

    H.D.R. Dewachter (Hans); M. Lyrio (Marco)

    2003-01-01

    textabstractWe compute the opportunity cost for rational risk averse agents of using technical trading rules in the foreign exchange rate market. Our purpose is to investigate whether these rules can be interpreted as near-rational investment strategies for rational investors. We analyze four

  20. 78 FR 40351 - Procedural Rule To Establish Supervisory Authority Over Certain Nonbank Covered Persons Based on...

    Science.gov (United States)

    2013-07-03

    ... the construction of time limits, change of time limits, and effect of deadlines. Under the final rule... provides transparency and ensures consistency regarding the procedures that the Bureau intends to use in... above, the purpose of the final rule is to provide transparency and ensure consistency regarding the...

  1. Spin alignment and violation of the OZI rule in exclusive $\\omega$ and $\\phi$ production in pp collisions

    CERN Document Server

    Adolph, C; Alexeev, M G; Alexeev, G D; Amoroso, A; Andrieux, V; Anosov, V; Austregesilo, A; Badełek, B; Balestra, F; Barth, J; Baum, G; Beck, R; Bedfer, Y; Berlin, A; Bernhard, J; Bicker, K; Bieling, J; Birsa, R; Bisplinghoff, J; Bodlak, M; Boer, M; Bordalo, P; Bradamante, F; Braun, C; Bressan, A; Büchele, M; Burtin, E; Capozza, L; Chiosso, M; Chung, S U; Cicuttin, A; Crespo, M L; Curiel, Q; Dalla Torre, S; Dasgupta, S S; Dasgupta, S; Denisov, O Yu; Donskov, S V; Doshita, N; Duic, V; Dünnweber, W; Dziewiecki, M; Efremov, A; Elia, C; Eversheim, P D; Eyrich, W; Faessler, M; Ferrero, A; Filin, A; Finger, M; Finger jr , M; Fischer, H; Franco, C; du Fresne von Hohenesche, N; Friedrich, J M; Frolov, V; Gautheron, F; Gavrichtchouk, O P; Gerassimov, S; Geyer, R; Gnesi, I; Gobbo, B; Goertz, S; Gorzellik, M; Grabmüller, S; Grasso, A; Grube, B; Grussenmeyer, T; Guskov, A; Guthörl, T; Haas, F; von Harrach, D; Hahne, D; Hashimoto, R; Heinsius, F H; Herrmann, F; Hinterberger, F; Höppner, Ch; Horikawa, N; d’Hose, N; Huber, S; Ishimoto, S; Ivanov, A; Ivanshin, Yu; Iwata, T; Jahn, R; Jary, V; Jasinski, P; Jörg, P; Joosten, R; Kabuß, E; Ketzer, B; Khaustov, G V; Khokhlov, Yu A; Kisselev, Yu; Klein, F; Klimaszewski, K; Koivuniemi, J H; Kolosov, V N; Kondo, K; Königsmann, K; Konorov, I; Konstantinov, V F; Kotzinian, A M; Kouznetsov, O; Krämer, M; Kroumchtein, Z V; Kuchinski, N; Kunne, F; Kurek, K; Kurjata, R P; Lednev, A A; Lehmann, A; Levillain, M; Levorato, S; Lichtenstadt, J; Maggiora, A; Magnon, A; Makke, N; Mallot, G K; Marchand, C; Martin, A; Marzec, J; Matousek, J; Matsuda, H; Matsuda, T; Meshcheryakov, G; Meyer, W; Michigami, T; Mikhailov, Yu V; Miyachi, Y; Nagaytsev, A; Nagel, T; Nerling, F; Neubert, S; Neyret, D; Nikolaenko, V I; Novy, J; Nowak, W-D; Nunes, A S; Olshevsky, A G; Orlov, I; Ostrick, M; Panknin, R; Panzieri, D; Parsamyan, B; Paul, S; Platchkov, S; Pochodzalla, J; Polyakov, V A; Pretz, J; Quaresma, M; Quintans, C; Ramos, S; Regali, C; Reicherz, G; Rocco, E; Rossiyskaya, N S; Ryabchikov, D I; Rychter, A; Samoylenko, V D; Sandacz, A; Sapozhnikov, M; Sarkar, S; Savin, I A; Sbrizzai, G; Schiavon, P; Schill, C; Schlüter, T; Schmidt, K; Schmieden, H; Schönning, K; Schopferer, S; Schott, M; Shevchenko, O Yu; Silva, L; Sinha, L; Sirtl, S; Slunecka, M; Sosio, S; Sozzi, F; Srnka, A; Steiger, L; Stolarski, M; Sulc, M; Sulej, R; Suzuki, H; Szabelski, A; Szameitat, T; Sznajder, P; Takekawa, S; ter Wolbeek, J; Tessaro, S; Tessarotto, F; Thibaud, F; Uhl, S; Uman, I; Virius, M; Wang, L; Weisrock, T; Wilfert, M; Windmolders, R; Wollny, H; Zaremba, K; Zavertyaev, M; Zemlyanichkina, E; Ziembicki, M; Zink, A

    2014-01-01

    Exclusive production of the isoscalar vector mesons $\\omega$ and $\\phi$ is measured with a 190 GeV$/c$ proton beam impinging on a liquid hydrogen target. Cross section ratios are determined in three intervals of the Feynman variable $x_{F}$ of the fast proton. A significant violation of the OZI rule is found, confirming earlier findings. Its kinematic dependence on $x_{F}$ and on the invariant mass $M_{p\\mathrm{V}}$ of the system formed by fast proton $p_\\mathrm{fast}$ and vector meson $V$ is discussed in terms of diffractive production of $p_\\mathrm{fast}V$ resonances in competition with central production. The measurement of the spin density matrix element $\\rho_{00}$ of the vector mesons in different selected reference frames provides another handle to distinguish the contributions of these two major reaction types. Again, dependences of the alignment on $x_{F}$ and on $M_{p\\mathrm{V}}$ are found. Most of the observations can be traced back to the existence of several excited baryon states contributing to ...

  2. q-state Potts-glass neural network based on pseudoinverse rule

    International Nuclear Information System (INIS)

    Xiong Daxing; Zhao Hong

    2010-01-01

    We study the q-state Potts-glass neural network with the pseudoinverse (PI) rule. Its performance is investigated and compared with that of the counterpart network with the Hebbian rule instead. We find that there exists a critical point of q, i.e., q cr =14, below which the storage capacity and the retrieval quality can be greatly improved by introducing the PI rule. We show that the dynamics of the neural networks constructed with the two learning rules respectively are quite different; but however, regardless of the learning rules, in the q-state Potts-glass neural networks with q≥3 there is a common novel dynamical phase in which the spurious memories are completely suppressed. This property has never been noticed in the symmetric feedback neural networks. Free from the spurious memories implies that the multistate Potts-glass neural networks would not be trapped in the metastable states, which is a favorable property for their applications.

  3. Decision support system for triage management: A hybrid approach using rule-based reasoning and fuzzy logic.

    Science.gov (United States)

    Dehghani Soufi, Mahsa; Samad-Soltani, Taha; Shams Vahdati, Samad; Rezaei-Hachesu, Peyman

    2018-06-01

    Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level. A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels. Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%. Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Irradiation in the production, processing and handling of food. Final rule.

    Science.gov (United States)

    2012-11-30

    The Food and Drug Administration (FDA) is amending the food additive regulations to provide for the safe use of a 4.5 kilogray (kGy) maximum absorbed dose of ionizing radiation to treat unrefrigerated (as well as refrigerated) uncooked meat, meat byproducts, and certain meat food products to reduce levels of foodborne pathogens and extend shelf life. This action is in response to a petition filed by the U.S. Department of Agriculture, Food Safety and Inspection Service (USDA/FSIS).

  5. The Catalytic Diversity of Multimodular Polyketide Synthases: Natural Product Biosynthesis Beyond Textbook Assembly Rules.

    Science.gov (United States)

    Gulder, Tobias A M; Freeman, Michael F; Piel, Jörn

    2011-03-01

    Bacterial multimodular polyketide synthases (PKSs) are responsible for the biosynthesis of a wide range of pharmacologically active natural products. These megaenzymes contain numerous catalytic and structural domains and act as biochemical templates to generate complex polyketides in an assembly line-like fashion. While the prototypical PKS is composed of only a few different domain types that are fused together in a combinatorial fashion, an increasing number of enzymes is being found that contain additional components. These domains can introduce remarkably diverse modifications into polyketides. This review discusses our current understanding of such noncanonical domains and their role in expanding the biosynthetic versatility of bacterial PKSs.

  6. Towards the development of mechanistically based design rules for corrosion fatigue in ductile steels

    International Nuclear Information System (INIS)

    Johnson, R.; McMinn, A.; Tomkins, B.

    1980-08-01

    Design curves for nuclear pressure vessels and off-shore structures are based on air endurance curves that have had a safety factor applied to account for effects such as corrosive environments, frequency and mean stress. These are supported by a limited number of endurance tests on actual pressure vessels, and on welded joints under service conditions. These data-based rules are limited in their ability to cope with environmental effects and as the time dependencies of fatigue and corrosion processes are so different, no sound basis exists for the extrapolation of data to long component lifetimes. The crack-growth behaviour of materials used in nuclear pressure vessels and off-shore structures is examined with a view to determining how it may be used to re-assess the design curves. Even simple integration of crack-growth laws can be seen to be within reasonable agreement with present design curves; with improved methods of stress analysis, etc. this approach could potentially improve these curves. Mechanistic studies are also seen to offer a means of examining and assessing time-dependent process interactions and so, potentially, to form the basis of new guidelines. Finally the areas where further work would be needed to substantiate any changes in design curves are indicated. (author)

  7. An Expert System for Diagnosis of Sleep Disorder Using Fuzzy Rule-Based Classification Systems

    Science.gov (United States)

    Septem Riza, Lala; Pradini, Mila; Fitrajaya Rahman, Eka; Rasim

    2017-03-01

    Sleep disorder is an anomaly that could cause problems for someone’ sleeping pattern. Nowadays, it becomes an issue since people are getting busy with their own business and have no time to visit the doctors. Therefore, this research aims to develop a system used for diagnosis of sleep disorder using Fuzzy Rule-Based Classification System (FRBCS). FRBCS is a method based on the fuzzy set concepts. It consists of two steps: (i) constructing a model/knowledge involving rulebase and database, and (ii) prediction over new data. In this case, the knowledge is obtained from experts whereas in the prediction stage, we perform fuzzification, inference, and classification. Then, a platform implementing the method is built with a combination between PHP and the R programming language using the “Shiny” package. To validate the system that has been made, some experiments have been done using data from a psychiatric hospital in West Java, Indonesia. Accuracy of the result and computation time are 84.85% and 0.0133 seconds, respectively.

  8. A study on development of a rule based expert system for steam generator life extension

    International Nuclear Information System (INIS)

    Park, Jin Kyun

    1994-02-01

    The need of predicting the integrity of the steam generator(SG) tubes and environmental conditions that affect their integrity is growing to secure nuclear power plant(NPP) safety and enhance plant availability. To achieve their objectives it is important to diagnose the integrity of the SG tubes. An expert system called FEMODES(failure mode diagnosis expert system) has been developed for diagnosis of such tube degradation phenomena as denting, intergranular attack(IGA) and stress corrosion cracking(SCC) in the secondary side of the SG. It is possible with use of FEMODES to estimate possibilities of SG tube degradation and diagnosis environmental conditions that influence such tube degradation. The method of certainty factor theory(CFT) and the rule based backward reasoning inference strategy are used to develop FEMODES. The information required for diagnosis is acquired from SG tube degradation experiences of two local reference plants, some limited oversea plants and technical reports/research papers about such tube degradation. Overall results estimated with use of FEMODES are in reasonable agreement with actual SG tube degradation. Some discrepancy observed in several estimated values of SG tube degradation appears to be due to insufficient heuristic knowledge for knowledge data base of FEMODES

  9. 75 FR 20401 - Self-Regulatory Organizations; NYSE Amex LLC; Notice of Filing of Proposed Rule Change, and...

    Science.gov (United States)

    2010-04-19

    .... Proposed NYSE Amex Equities Rule 510 (Derivative Securities Products) The Exchange also proposes some... derivative securities products,'' as defined in Rule 19b-4(e) under the Act and traded pursuant to Rule 19b-4.../or approved by the Commission for the generic trading of derivative securities products based on...

  10. Conformance Testing: Measurement Decision Rules

    Science.gov (United States)

    Mimbs, Scott M.

    2010-01-01

    The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to provide assurance to the customer that end products meet specifications. Measuring devices, often called measuring and test equipment (MTE), are used to provide the evidence of product conformity to specified requirements. Unfortunately, processes that employ MTE can become a weak link to the overall QMS if proper attention is not given to the measurement process design, capability, and implementation. Documented "decision rules" establish the requirements to ensure measurement processes provide the measurement data that supports the needs of the QMS. Measurement data are used to make the decisions that impact all areas of technology. Whether measurements support research, design, production, or maintenance, ensuring the data supports the decision is crucial. Measurement data quality can be critical to the resulting consequences of measurement-based decisions. Historically, most industries required simplistic, one-size-fits-all decision rules for measurements. One-size-fits-all rules in some cases are not rigorous enough to provide adequate measurement results, while in other cases are overly conservative and too costly to implement. Ideally, decision rules should be rigorous enough to match the criticality of the parameter being measured, while being flexible enough to be cost effective. The goal of a decision rule is to ensure that measurement processes provide data with a sufficient level of quality to support the decisions being made - no more, no less. This paper discusses the basic concepts of providing measurement-based evidence that end products meet specifications. Although relevant to all measurement-based conformance tests, the target audience is the MTE end-user, which is anyone using MTE other than calibration service providers. Topics include measurement fundamentals, the associated decision risks, verifying conformance to specifications, and basic measurement

  11. Simple rules can guide whether land- or ocean-based conservation will best benefit marine ecosystems.

    Science.gov (United States)

    Saunders, Megan I; Bode, Michael; Atkinson, Scott; Klein, Carissa J; Metaxas, Anna; Beher, Jutta; Beger, Maria; Mills, Morena; Giakoumi, Sylvaine; Tulloch, Vivitskaia; Possingham, Hugh P

    2017-09-01

    Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment runoff and a downstream coastal marine ecosystem and contrast the cost-effectiveness of marine- and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to 1 of 4 alternative conservation actions-protection on land, protection in the ocean, restoration on land, or restoration in the ocean-to maximise the extent of light-dependent marine benthic habitats across decadal timescales. We apply the model to a case study for a seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal timescales in this system, based on a conservative estimate of the rate at which seagrass can expand into a new habitat. The optimal decision will vary in different social-ecological contexts, but some basic information can guide optimal investments to counteract land- and ocean-based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is greater than 1:1.4, with terrestrial restoration typically the most cost-effective action; and (4) land protection should be prioritised if the catchment is relatively intact but the rate of vegetation decline is high. These rules of thumb illustrate how cost-effective conservation outcomes for connected land-ocean systems can proceed without complex modelling.

  12. Fuzzy rule-based landslide susceptibility mapping in Yığılca Forest District (Northwest of Turkey

    Directory of Open Access Journals (Sweden)

    Abdurrahim Aydın

    2016-07-01

    Full Text Available Landslide susceptibility map of Yığılca Forest District was formed based on developed fuzzy rules using GIS-based FuzzyCell software. An inventory of 315 landslides was updated through fieldworks after inventory map previously generated by the authors. Based on the landslide susceptibility mapping study previously made in the same area, for the comparison of two maps, same 8 landslide conditioning parameters were selected and then fuzzified for the landslide susceptibility mapping: land use, lithology, elevation, slope, aspect, distance to streams, distance to roads, and plan curvature. Mamdani model was selected as fuzzy inference system. After fuzzy rules definition, Center of Area (COA was selected as defuzzification method in model. The output of developed model was normalized between 0 and 1, and then divided five classes such as very low, low, moderate, high, and very high. According to developed model based 8 conditioning parameters, landslide susceptibility in Yığılca Forest District varies between 32 and 67 (in range of 0-100 with 0.703 Area Under the Curve (AUC value. According to classified landslide susceptibility map, in Yığılca Forest District, 32.89% of the total area has high and very high susceptibility while 29.59% of the area has low and very low susceptibility and the rest located in moderate susceptibility. The result of developed fuzzy rule based model compared with previously generated landslide map with logistic regression (LR. According to comparison of the results of two studies, higher differences exist in terms of AUC value and dispersion of susceptibility classes. This is because fuzzy rule based model completely depends on how parameters are classified and fuzzified and also depends on how truly the expert composed the rules. Even so, GIS-based fuzzy applications provide very valuable facilities for reasoning, which makes it possible to take into account inaccuracies and uncertainties.

  13. A new methodology for the study of FAC phenomenon based on a fuzzy rule system

    International Nuclear Information System (INIS)

    Ferreira Guimaraes, Antonio Cesar

    2003-01-01

    This work consists of the representation of the corrosion problem, FAC - 'Flow-Accelerated Corrosion' in components, structures and passive systems in a nuclear power plant with aging, through a fuzzy rules system, in substitution to the conventional modeling and experimental analyses. Using data characteristic of the nature of the problem to be analyzed, a reduced number of rules can be establish to represent the actual problem. The results can be visualized in a very satisfactory way thus providing the engineer with the knowledge to work in the space of solution of rules to do the necessary inferences

  14. Production Rule Systems as an Approach to Interpretation of Ground Sensor Information.

    Science.gov (United States)

    1980-06-01

    Z_4 1. Overview . . .......... . .. 4 2. tesin of the Prototype Knowledee -based "?roluc tior System ..................... 4 I V ’?>NA...operated by the sensor control and management platoon (SCAMP). One SCAMP is allocated per division; each SCAMP functions under the coRnizance of the 414...apprnach. Sienal understandin- tasks, of which the problem under consideration in this thesis is a member, seem well suited to the application of knowlede

  15. Using the Chain Rule as the Key Link in Deriving the General Rules for Differentiation

    Science.gov (United States)

    Sprows, David

    2011-01-01

    The standard approach to the general rules for differentiation is to first derive the power, product, and quotient rules and then derive the chain rule. In this short article we give an approach to these rules which uses the chain rule as the main tool in deriving the power, product, and quotient rules in a manner which is more student-friendly…

  16. Developing product families based on architectures

    DEFF Research Database (Denmark)

    Harlou, Ulf

    2006-01-01

    family master plan (PFMP). The PFMP aims at modelling product families and especially variety of product families. The results of this thesis build on research literature and experiences from the industrial partners. Extensive verifications of the theory contributions, models and tools have been carried......The subject of this PhD thesis is development of product families based on architectures. Companies are introducing more and more product variants to fulfil the market demands. These new variants add complexity to many of the processes and systems in the companies. Reuse of standard designs (i.......e. design entities) and re-use of the way new products are developed can simplify the processes and systems. Case studies show that reuse can lead to reduction of cost and time-to-market of new products. One of the means for managing reuse of standard designs within product families are architectures...

  17. Design and Implementation an Autonomous Humanoid Robot Based on Fuzzy Rule-Based Motion Controller

    Directory of Open Access Journals (Sweden)

    Mohsen Taheri

    2010-04-01

    Full Text Available Research on humanoid robotics in Mechatronics and Automation Laboratory, Electrical and Computer Engineering, Islamic Azad University Khorasgan branch (Isfahan of Iran was started at
    the beginning of this decade. Various research prototypes for humanoid robots have been designed and are going through evolution over these years. This paper describes the hardware and software design of the kid size humanoid robot systems of the PERSIA Team in 2009. The robot has 20 actuated degrees of freedom based on Hitec HSR898. In this paper we have tried to focus on areas such as mechanical structure, Image processing unit, robot controller, Robot AI and behavior
    learning. In 2009, our developments for the Kid size humanoid robot include: (1 the design and construction of our new humanoid robots (2 the design and construction of a new hardware and software controller to be used in our robots. The project is described in two main parts: Hardware and Software. The software is developed a robot application which consists walking controller, autonomous motion robot, self localization base on vision and Particle Filter, local AI, Trajectory Planning, Motion Controller and Network. The hardware consists of the mechanical structure and the driver circuit board. Each robot is able to walk, fast walk, pass, kick and dribble when it catches
    the ball. These humanoids have been successfully participating in various robotic soccer competitions. This project is still in progress and some new interesting methods are described in the current report.

  18. The impact of China's carbon allowance allocation rules on the product prices and emission reduction behaviors of ETS-covered enterprises

    International Nuclear Information System (INIS)

    Zhang, Yue-Jun; Wang, Ao-Dong; Tan, Weiping

    2015-01-01

    It is an important task for China to allocate carbon emission allowance to realize its carbon reduction target and establish carbon trading market. China has designed several allocation rules within seven pilot regions. What influence those rules may cause is closely related with the enthusiasm of emission trading scheme (ETS) covered enterprises' participation in carbon market, and more importantly, with the mechanism design and sustainable development of carbon market. For this purpose, the multi-stage profit model is developed to analyze the ETS-covered enterprises' product prices and emission reduction behaviors under different allocation rules. The results show that, first, under the rules of grandfathering, self-declaration and auctioning, when deciding the optimal product price and optimal carbon emission reduction, those enterprises may focus on maximizing current stage profit; however, under the rule of benchmarking, those enterprises may care more about the impact of current decisions on the profit in next stage. Second, the optimal product price policy is positively correlated with the price of the same kind products, consumers' low-carbon awareness and government subsidy. Finally, along with the increase of carbon price, consumers' low-carbon awareness and government subsidy and the decrease of carbon emission cap, those enterprises tend to reduce carbon emissions. - Highlights: • Analyze the impact of carbon allowance allocation rules on ETS-covered enterprises. • For grandfather, self-declaration and auction, they may maximize current profits. • For benchmark, they care the effect of current decisions on the coming profits. • The optimal product price positively relates to low-carbon awareness and subsidy. • Carbon price, low-carbon awareness and subsidy rise leads their emission reduction.

  19. Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

    Science.gov (United States)

    Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

    2018-01-01

    Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

  20. Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden

    International Nuclear Information System (INIS)

    Zhang, Yang; Lundblad, Anders; Campana, Pietro Elia; Benavente, F.; Yan, Jinyue

    2017-01-01

    Highlights: • Battery sizing and rule-based operation are achieved concurrently. • Hybrid operation strategy that combines different strategies is proposed. • Three operation strategies are compared through multi-objective optimization. • High Net Present Value and Self Sufficiency Ratio are achieved at the same time. - Abstract: The optimal components design for grid-connected photovoltaic-battery systems should be determined with consideration of system operation. This study proposes a method to simultaneously optimize the battery capacity and rule-based operation strategy. The investigated photovoltaic-battery system is modeled using single diode photovoltaic model and Improved Shepherd battery model. Three rule-based operation strategies—including the conventional operation strategy, the dynamic price load shifting strategy, and the hybrid operation strategy—are designed and evaluated. The rule-based operation strategies introduce different operation parameters to run the system operation. multi-objective Genetic Algorithm is employed to optimize the decisional variables, including battery capacity and operation parameters, towards maximizing the system’s Self Sufficiency Ratio and Net Present Value. The results indicate that employing battery with the conventional operation strategy is not profitable, although it increases Self Sufficiency Ratio. The dynamic price load shifting strategy has similar performance with the conventional operation strategy because the electricity price variation is not large enough. The proposed hybrid operation strategy outperforms other investigated strategies. When the battery capacity is lower than 72 kW h, Self Sufficiency Ratio and Net Present Value increase simultaneously with the battery capacity.

  1. Biology Teachers Designing Context-Based Lessons for Their Classroom Practice--The Importance of Rules-of-Thumb

    Science.gov (United States)

    Wieringa, Nienke; Janssen, Fred J. J. M.; Van Driel, Jan H.

    2011-01-01

    In science education in the Netherlands new, context-based, curricula are being developed. As in any innovation, the outcome will largely depend on the teachers who design and implement lessons. Central to the study presented here is the idea that teachers, when designing lessons, use rules-of-thumb: notions of what a lesson should look like if…

  2. Fiber coupled diode laser beam parameter product calculation and rules for optimized design

    Science.gov (United States)

    Wang, Zuolan; Segref, Armin; Koenning, Tobias; Pandey, Rajiv

    2011-03-01

    The Beam Parameter Product (BPP) of a passive, lossless system is a constant and cannot be improved upon but the beams may be reshaped for enhanced coupling performance. The function of the optical designer of fiber coupled diode lasers is to preserve the brightness of the diode sources while maximizing the coupling efficiency. In coupling diode laser power into fiber output, the symmetrical geometry of the fiber core makes it highly desirable to have symmetrical BPPs at the fiber input surface, but this is not always practical. It is therefore desirable to be able to know the 'diagonal' (fiber) BPP, using the BPPs of the fast and slow axes, before detailed design and simulation processes. A commonly used expression for this purpose, i.e. the square root of the sum of the squares of the BPPs in the fast and slow axes, has been found to consistently under-predict the fiber BPP (i.e. better beam quality is predicted than is actually achievable in practice). In this paper, using a simplified model, we provide the proof of the proper calculation of the diagonal (i.e. the fiber) BPP using BPPs of the fast and slow axes as input. Using the same simplified model, we also offer the proof that the fiber BPP can be shown to have a minimum (optimal) value for given diode BPPs and this optimized condition can be obtained before any detailed design and simulation are carried out. Measured and simulated data confirms satisfactory correlation between the BPPs of the diode and the predicted fiber BPP.

  3. Ensemble Classifiers for Predicting HIV-1 Resistance from Three Rule-Based Genotypic Resistance Interpretation Systems.

    Science.gov (United States)

    Raposo, Letícia M; Nobre, Flavio F

    2017-08-30

    Resistance to antiretrovirals (ARVs) is a major problem faced by HIV-infected individuals. Different rule-based algorithms were developed to infer HIV-1 susceptibility to antiretrovirals from genotypic data. However, there is discordance between them, resulting in difficulties for clinical decisions about which treatment to use. Here, we developed ensemble classifiers integrating three interpretation algorithms: Agence Nationale de Recherche sur le SIDA (ANRS), Rega, and the genotypic resistance interpretation system from Stanford HIV Drug Resistance Database (HIVdb). Three approaches were applied to develop a classifier with a single resistance profile: stacked generalization, a simple plurality vote scheme and the selection of the interpretation system with the best performance. The strategies were compared with the Friedman's test and the performance of the classifiers was evaluated using the F-measure, sensitivity and specificity values. We found that the three strategies had similar performances for the selected antiretrovirals. For some cases, the stacking technique with naïve Bayes as the learning algorithm showed a statistically superior F-measure. This study demonstrates that ensemble classifiers can be an alternative tool for clinical decision-making since they provide a single resistance profile from the most commonly used resistance interpretation systems.

  4. Optimizing human-system interface automation design based on a skill-rule-knowledge framework

    International Nuclear Information System (INIS)

    Lin, Chiuhsiang Joe; Yenn, T.-C.; Yang, C.-W.

    2010-01-01

    This study considers the technological change that has occurred in complex systems within the past 30 years. The role of human operators in controlling and interacting with complex systems following the technological change was also investigated. Modernization of instrumentation and control systems and components leads to a new issue of human-automation interaction, in which human operational performance must be considered in automated systems. The human-automation interaction can differ in its types and levels. A system design issue is usually realized: given these technical capabilities, which system functions should be automated and to what extent? A good automation design can be achieved by making an appropriate human-automation function allocation. To our knowledge, only a few studies have been published on how to achieve appropriate automation design with a systematic procedure. Further, there is a surprising lack of information on examining and validating the influences of levels of automation (LOAs) on instrumentation and control systems in the advanced control room (ACR). The study we present in this paper proposed a systematic framework to help in making an appropriate decision towards types of automation (TOA) and LOAs based on a 'Skill-Rule-Knowledge' (SRK) model. From the evaluating results, it was shown that the use of either automatic mode or semiautomatic mode is insufficient to prevent human errors. For preventing the occurrences of human errors and ensuring the safety in ACR, the proposed framework can be valuable for making decisions in human-automation allocation.

  5. An injection-locked OEO based frequency doubler independent of electrical doubler phase noise deteriorating rule

    Science.gov (United States)

    Xie, Zhengyang; Zheng, Xiaoping; Li, Shangyuan; Yan, Haozhe; Xiao, Xuedi; Xue, Xiaoxiao

    2018-06-01

    We propose an injection-locked optoelectronic oscillator (OEO) based wide-band frequency doubler, which is free from phase noise deterioration in electrical doubler, by using a dual-parallel Mach-Zehnder modulator (DPMZM). Through adjusting the optical phase shifts in different arms of the DPMZM, the doubling signal oscillates in the OEO loop while the fundamental signal takes on phase modulation over the light and vanishes at photo-detector (PD) output. By controlling power of fundamental signal the restriction of phase-noise deterioration rule in electrical doubler is totally canceled. Experimental results show that the doubler output has a better phase noise value of, for example, -117 dBc/Hz @ 10 kHz at 6 GHz with an improvement more than 17 dB and 23 dB compared with that of fundamental input and electrical doubler, respectively. Besides, the stability of this doubler output can reach to 1 . 5 × 10-14 at 1000 s averaging time. The frequency range of doubling signal is limited by the bandwidth of electrical amplifier in OEO loop.

  6. Consistency questions in the light cone gauge based on equal time commutation rules

    International Nuclear Information System (INIS)

    Haller, K.

    1989-01-01

    We investigate whether time displacement invariant propagators are compatible canonical formulations in the light cone gauge based on equal time commutation rules. We conclude that, in the light cone gauge, time displacement invariant propagators are not consistent with the requirement that, in canonical formulations of gauge theories, only transversely polarized, massless gauge field excitations (photons, or gluons in perturbative QCD), can contribute to the transverse part of a time displacement invariant propagator. When the time displacement invariant light cone gauge propagator is represented as a four-dimensional momentum space Fourier integral the following is observed: Transverse parts of the propagator obtain time displacement invariant contributions from the (k 3 -k 0 ) pole, as well as from the (vertical strokekvertical stroke 2 -k 0 2 ) pole. But since, in the Schroedinger picture (i.e. at t=0), the divergence-free part of the gauge field consists of transversely polarized gauge field excitations only, the transverse part of the propagator either can have time displacement invariant time dependence determined by the (vertical strokekvertical stroke 2 -k 0 2 ) pole; or, if any part of the transverse propagator has time dependence determined by the (k 3 -k 0 ) pole, it cannot be time displacement invariant. (orig.)

  7. Evolution of Collective Behaviour in an Artificial World Using Linguistic Fuzzy Rule-Based Systems.

    Directory of Open Access Journals (Sweden)

    Jure Demšar

    Full Text Available Collective behaviour is a fascinating and easily observable phenomenon, attractive to a wide range of researchers. In biology, computational models have been extensively used to investigate various properties of collective behaviour, such as: transfer of information across the group, benefits of grouping (defence against predation, foraging, group decision-making process, and group behaviour types. The question 'why,' however remains largely unanswered. Here the interest goes into which pressures led to the evolution of such behaviour, and evolutionary computational models have already been used to test various biological hypotheses. Most of these models use genetic algorithms to tune the parameters of previously presented non-evolutionary models, but very few attempt to evolve collective behaviour from scratch. Of these last, the successful attempts display clumping or swarming behaviour. Empirical evidence suggests that in fish schools there exist three classes of behaviour; swarming, milling and polarized. In this paper we present a novel, artificial life-like evolutionary model, where individual agents are governed by linguistic fuzzy rule-based systems, which is capable of evolving all three classes of behaviour.

  8. Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

    Science.gov (United States)

    Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

    2017-09-25

    Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

  9. Model Servqual Rule Base Asean University Network untuk Penilaian Kualitas Program Studi

    Directory of Open Access Journals (Sweden)

    Esti Wijayanti

    2016-05-01

    Full Text Available As well known that AUN (Asean University Network.AUN and ABET (Accreditation Boardb for Enginnering and Technology are non-profit organitatinon which have. AUN (Asean University Network were using variable with refer to AUN’s criteria’s there consist of fifteen which are: Expected Learning Outcomes, Programme Specification, Programme Structure and Content, Teaching and Learning Strategy, Student Assessment, Academic Staff Quality, Support Staff Quality, Student Quality, Student Advice and Support, Facilities and Infrastructure, Quality Assurance of Teaching/Learning Process, Staff Development Activities, Stakeholders Feedback, Output, Stakeholders Satisfaction,and adopted score's scale 7. In there here, we discuss the fifteen AUN’s of AUN in the criterias. There servqual of as can be into five dimensions, assurance, empathy, responsive, reliability and facilty in order to make the assessment's process easier. This research outcome indicated that this proposed method can be used to evaluate an education program. The validation result by using AUN's data and the analysis of servqual rule base Asean University Network almost have the same pattern with correlation value is 0,985 and this is can be accepted because its validity have reach 97%.

  10. A rule-based verification and control framework in ATLAS Trigger-DAQ

    CERN Document Server

    Kazarov, A; Lehmann-Miotto, G; Sloper, J E; Ryabov, Yu; Computing In High Energy and Nuclear Physics

    2007-01-01

    In order to meet the requirements of ATLAS data taking, the ATLAS Trigger-DAQ system is composed of O(1000) of applications running on more than 2600 computers in a network. With such system size, s/w and h/w failures are quite often. To minimize system downtime, the Trigger-DAQ control system shall include advanced verification and diagnostics facilities. The operator should use tests and expertise of the TDAQ and detectors developers in order to diagnose and recover from errors, if possible automatically. The TDAQ control system is built as a distributed tree of controllers, where behavior of each controller is defined in a rule-based language allowing easy customization. The control system also includes verification framework which allow users to develop and configure tests for any component in the system with different levels of complexity. It can be used as a stand-alone test facility for a small detector installation, as part of the general TDAQ initialization procedure, and for diagnosing the problems ...

  11. Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

    Directory of Open Access Journals (Sweden)

    Y.-M. Chiang

    2011-01-01

    Full Text Available Pumping stations play an important role in flood mitigation in metropolitan areas. The existing sewerage systems, however, are facing a great challenge of fast rising peak flow resulting from urbanization and climate change. It is imperative to construct an efficient and accurate operating prediction model for pumping stations to simulate the drainage mechanism for discharging the rainwater in advance. In this study, we propose two rule-based fuzzy neural networks, adaptive neuro-fuzzy inference system (ANFIS and counterpropagation fuzzy neural network for on-line predicting of the number of open and closed pumps of a pivotal pumping station in Taipei city up to a lead time of 20 min. The performance of ANFIS outperforms that of CFNN in terms of model efficiency, accuracy, and correctness. Furthermore, the results not only show the predictive water levels do contribute to the successfully operating pumping stations but also demonstrate the applicability and reliability of ANFIS in automatically controlling the urban sewerage systems.

  12. A simple rule based model for scheduling farm management operations in SWAT

    Science.gov (United States)

    Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

    2016-04-01

    For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the

  13. Scalability of a Methodology for Generating Technical Trading Rules with GAPs Based on Risk-Return Adjustment and Incremental Training

    Science.gov (United States)

    de La Cal, E. A.; Fernández, E. M.; Quiroga, R.; Villar, J. R.; Sedano, J.

    In previous works a methodology was defined, based on the design of a genetic algorithm GAP and an incremental training technique adapted to the learning of series of stock market values. The GAP technique consists in a fusion of GP and GA. The GAP algorithm implements the automatic search for crisp trading rules taking as objectives of the training both the optimization of the return obtained and the minimization of the assumed risk. Applying the proposed methodology, rules have been obtained for a period of eight years of the S&P500 index. The achieved adjustment of the relation return-risk has generated rules with returns very superior in the testing period to those obtained applying habitual methodologies and even clearly superior to Buy&Hold. This work probes that the proposed methodology is valid for different assets in a different market than previous work.

  14. Sum rules for elements of flavor-mixing matrices based on a non-semisimple symmetry

    International Nuclear Information System (INIS)

    Sogami, Ikuo S.

    2006-01-01

    Sum rules for elements of flavor-mixing matrices (FMMs) are derived within a new algebraic theory for flavor physics, in which the FMMs are identified with elements of the Lie group isomorphic to SU(2) x U(1). The resulting sum rules originating from the unique elaborate structure of the algebra of the group are so simple and explicit that their validity can be confirmed by analyzing properly processed experimental data. (author)

  15. Algorithm for detecting violations of traffic rules based on computer vision approaches

    Directory of Open Access Journals (Sweden)

    Ibadov Samir

    2017-01-01

    Full Text Available We propose a new algorithm for automatic detect violations of traffic rules for improving the people safety on the unregulated pedestrian crossing. The algorithm uses multi-step proceedings. They are zebra detection, cars detection, and pedestrian detection. For car detection, we use faster R-CNN deep learning tool. The algorithm shows promising results in the detection violations of traffic rules.

  16. New Product Development Based on Demand

    OpenAIRE

    Davis-Krook, Shelby

    2015-01-01

    The purpose of this thesis was to determine how to develop a new product based on demand within a target market for an international company. Specifically looking at developing a new product line in an already developed brand, Alpha Performance. The research I have conducted in the following topics may help Alpha Performance if they choose to use my findings to create a one of a kind woman’s clothing line based on the demands of the Finnish market: target market research, product demand rese...

  17. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Directory of Open Access Journals (Sweden)

    Enrico Glaab

    Full Text Available Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  18. Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data.

    Science.gov (United States)

    Glaab, Enrico; Bacardit, Jaume; Garibaldi, Jonathan M; Krasnogor, Natalio

    2012-01-01

    Microarray data analysis has been shown to provide an effective tool for studying cancer and genetic diseases. Although classical machine learning techniques have successfully been applied to find informative genes and to predict class labels for new samples, common restrictions of microarray analysis such as small sample sizes, a large attribute space and high noise levels still limit its scientific and clinical applications. Increasing the interpretability of prediction models while retaining a high accuracy would help to exploit the information content in microarray data more effectively. For this purpose, we evaluate our rule-based evolutionary machine learning systems, BioHEL and GAssist, on three public microarray cancer datasets, obtaining simple rule-based models for sample classification. A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. The obtained models reach accuracies above 90% in two-level external cross-validation, with the added value of facilitating interpretation by using only combinations of simple if-then-else rules. As a further benefit, a literature mining analysis reveals that prioritizations of informative genes extracted from BioHEL's classification rule sets can outperform gene rankings obtained from a conventional ensemble feature selection in terms of the pointwise mutual information between relevant disease terms and the standardized names of top-ranked genes.

  19. 77 FR 19033 - Effect of Adding References to HS 6104.32 To Correct the U.S.-Korea FTA Product-Specific Rules of...

    Science.gov (United States)

    2012-03-29

    ... INTERNATIONAL TRADE COMMISSION [Investigation No. Korea FTA-103-026] Effect of Adding References to HS 6104.32 To Correct the U.S.- Korea FTA Product-Specific Rules of Origin AGENCY: United States... investigation No. Korea FTA-103-026, Effect of Adding References to HS 6104.32 To Correct the U.S.-Korea FTA...

  20. Comparing a rule based vs. statistical system for automatic categorization of MEDLINE documents according to biomedical specialty

    OpenAIRE

    Humphrey, Susanne M.; Névéol, Aurélie; Browne, Allen; Gobeill, Julien; Ruch, Patrick; Darmoni, Stéfan J.

    2010-01-01

    Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing o...

  1. Ontology-based concept map learning path reasoning system using SWRL rules

    Energy Technology Data Exchange (ETDEWEB)

    Chu, K.-K.; Lee, C.-I. [National Univ. of Tainan, Taiwan (China). Dept. of Computer Science and Information Learning Technology

    2010-08-13

    Concept maps are graphical representations of knowledge. Concept mapping may reduce students' cognitive load and extend simple memory function. The purpose of this study was on the diagnosis of students' concept map learning abilities and the provision of personally constructive advice dependant on their learning path and progress. Ontology is a useful method with which to represent and store concept map information. Semantic web rule language (SWRL) rules are easy to understand and to use as specific reasoning services. This paper discussed the selection of grade 7 lakes and rivers curriculum for which to devise a concept map learning path reasoning service. The paper defined a concept map e-learning ontology and two SWRL semantic rules, and collected users' concept map learning path data to infer implicit knowledge and to recommend the next learning path for users. It was concluded that the designs devised in this study were feasible and advanced and the ontology kept the domain knowledge preserved. SWRL rules identified an abstraction model for inferred properties. Since they were separate systems, they did not interfere with each other, while ontology or SWRL rules were maintained, ensuring persistent system extensibility and robustness. 15 refs., 1 tab., 8 figs.

  2. Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

    Science.gov (United States)

    Grimm, Lisa R; Maddox, W Todd

    2013-11-01

    Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

  3. NDSI products system based on Hadoop platform

    Science.gov (United States)

    Zhou, Yan; Jiang, He; Yang, Xiaoxia; Geng, Erhui

    2015-12-01

    Snow is solid state of water resources on earth, and plays an important role in human life. Satellite remote sensing is significant in snow extraction with the advantages of cyclical, macro, comprehensiveness, objectivity, timeliness. With the continuous development of remote sensing technology, remote sensing data access to the trend of multiple platforms, multiple sensors and multiple perspectives. At the same time, in view of the remote sensing data of compute-intensive applications demand increase gradually. However, current the producing system of remote sensing products is in a serial mode, and this kind of production system is used for professional remote sensing researchers mostly, and production systems achieving automatic or semi-automatic production are relatively less. Facing massive remote sensing data, the traditional serial mode producing system with its low efficiency has been difficult to meet the requirements of mass data timely and efficient processing. In order to effectively improve the production efficiency of NDSI products, meet the demand of large-scale remote sensing data processed timely and efficiently, this paper build NDSI products production system based on Hadoop platform, and the system mainly includes the remote sensing image management module, NDSI production module, and system service module. Main research contents and results including: (1)The remote sensing image management module: includes image import and image metadata management two parts. Import mass basis IRS images and NDSI product images (the system performing the production task output) into HDFS file system; At the same time, read the corresponding orbit ranks number, maximum/minimum longitude and latitude, product date, HDFS storage path, Hadoop task ID (NDSI products), and other metadata information, and then create thumbnails, and unique ID number for each record distribution, import it into base/product image metadata database. (2)NDSI production module: includes

  4. A comparison of rule-based and machine learning approaches for classifying patient portal messages.

    Science.gov (United States)

    Cronin, Robert M; Fabbri, Daniel; Denny, Joshua C; Rosenbloom, S Trent; Jackson, Gretchen Purcell

    2017-09-01

    Secure messaging through patient portals is an increasingly popular way that consumers interact with healthcare providers. The increasing burden of secure messaging can affect clinic staffing and workflows. Manual management of portal messages is costly and time consuming. Automated classification of portal messages could potentially expedite message triage and delivery of care. We developed automated patient portal message classifiers with rule-based and machine learning techniques using bag of words and natural language processing (NLP) approaches. To evaluate classifier performance, we used a gold standard of 3253 portal messages manually categorized using a taxonomy of communication types (i.e., main categories of informational, medical, logistical, social, and other communications, and subcategories including prescriptions, appointments, problems, tests, follow-up, contact information, and acknowledgement). We evaluated our classifiers' accuracies in identifying individual communication types within portal messages with area under the receiver-operator curve (AUC). Portal messages often contain more than one type of communication. To predict all communication types within single messages, we used the Jaccard Index. We extracted the variables of importance for the random forest classifiers. The best performing approaches to classification for the major communication types were: logistic regression for medical communications (AUC: 0.899); basic (rule-based) for informational communications (AUC: 0.842); and random forests for social communications and logistical communications (AUCs: 0.875 and 0.925, respectively). The best performing classification approach of classifiers for individual communication subtypes was random forests for Logistical-Contact Information (AUC: 0.963). The Jaccard Indices by approach were: basic classifier, Jaccard Index: 0.674; Naïve Bayes, Jaccard Index: 0.799; random forests, Jaccard Index: 0.859; and logistic regression, Jaccard

  5. A linguistic rule-based approach to extract drug-drug interactions from pharmacological documents.

    Science.gov (United States)

    Segura-Bedmar, Isabel; Martínez, Paloma; de Pablo-Sánchez, César

    2011-03-29

    A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The increasing volume of the scientific literature overwhelms health care professionals trying to be kept up-to-date with all published studies on DDI. This paper describes a hybrid linguistic approach to DDI extraction that combines shallow parsing and syntactic simplification with pattern matching. Appositions and coordinate structures are interpreted based on shallow syntactic parsing provided by the UMLS MetaMap tool (MMTx). Subsequently, complex and compound sentences are broken down into clauses from which simple sentences are generated by a set of simplification rules. A pharmacist defined a set of domain-specific lexical patterns to capture the most common expressions of DDI in texts. These lexical patterns are matched with the generated sentences in order to extract DDIs. We have performed different experiments to analyze the performance of the different processes. The lexical patterns achieve a reasonable precision (67.30%), but very low recall (14.07%). The inclusion of appositions and coordinate structures helps to improve the recall (25.70%), however, precision is lower (48.69%). The detection of clauses does not improve the performance. Information Extraction (IE) techniques can provide an interesting way of reducing the time spent by health care professionals on reviewing the literature. Nevertheless, no approach has been carried out to extract DDI from texts. To the best of our knowledge, this work proposes the first integral solution for the automatic extraction of DDI from biomedical texts.

  6. [Study on Ammonia Emission Rules in a Dairy Feedlot Based on Laser Spectroscopy Detection Method].

    Science.gov (United States)

    He, Ying; Zhang, Yu-jun; You, Kun; Wang, Li-ming; Gao, Yan-wei; Xu, Jin-feng; Gao, Zhi-ling; Ma, Wen-qi

    2016-03-01

    It needs on-line monitoring of ammonia concentration on dairy feedlot to disclose ammonia emissions characteristics accurately for reducing ammonia emissions and improving the ecological environment. The on-line monitoring system for ammonia concentration has been designed based on Tunable Diode Laser Absorption Spectroscopy (TDLAS) technology combining with long open-path technology, then the study has been carried out with inverse dispersion technique and the system. The ammonia concentration in-situ has been detected and ammonia emission rules have been analyzed on a dairy feedlot in Baoding in autumn and winter of 2013. The monitoring indicated that the peak of ammonia concentration was 6.11 x 10(-6) in autumn, and that was 6.56 x 10(-6) in winter. The concentration results show that the variation of ammonia concentration had an obvious diurnal periodicity, and the general characteristic of diurnal variation was that the concentration was low in the daytime and was high at night. The ammonia emissions characteristic was obtained with inverse dispersion model that the peak of ammonia emissions velocity appeared at noon. The emission velocity was from 1.48 kg/head/hr to 130.6 kg/head/hr in autumn, and it was from 0.004 5 kg/head/hr to 43.32 kg/head/hr in winter which was lower than that in autumn. The results demonstrated ammonia emissions had certain seasonal differences in dairy feedlot scale. In conclusion, the ammonia concentration was detected with optical technology, and the ammonia emissions results were acquired by inverse dispersion model analysis with large range, high sensitivity, quick response without gas sampling. Thus, it's an effective method for ammonia emissions monitoring in dairy feedlot that provides technical support for scientific breeding.

  7. Scalable rule-based modelling of allosteric proteins and biochemical networks.

    Directory of Open Access Journals (Sweden)

    Julien F Ollivier

    2010-11-01

    Full Text Available Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology.

  8. A rule-based fault detection method for air handling units

    Energy Technology Data Exchange (ETDEWEB)

    Schein, J.; Bushby, S. T.; Castro, N. S. [National Institute of Standards and Technology, Gaithersburg, MD (United States); House, J. M. [Iowa Energy Center, Ankeny, IA (United States)

    2006-07-01

    Air handling unit performance assessment rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units (AHUs). Control signals are used to determine the mode of operation of the AHU. A subset of the expert rules which correspond to that mode of operation are then evaluated to determine whether a fault exists. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon the sensor data and control signals that are commonly available in these systems. APAR was tested using data sets collected from a 'hardware-in-the-loop' emulator and from several field sites. APAR was also embedded in commercial AHU controllers and tested in the emulator. (author)

  9. Studying Operation Rules of Cascade Reservoirs Based on Multi-Dimensional Dynamics Programming

    Directory of Open Access Journals (Sweden)

    Zhiqiang Jiang

    2017-12-01

    Full Text Available Although many optimization models and methods are applied to the optimization of reservoir operation at present, the optimal operation decision that is made through these models and methods is just a retrospective review. Due to the limitation of hydrological prediction accuracy, it is practical and feasible to obtain the suboptimal or satisfactory solution by the established operation rules in the actual reservoir operation, especially for the mid- and long-term operation. In order to obtain the optimized sample data with global optimality; and make the extracted operation rules more reasonable and reliable, this paper presents the multi-dimensional dynamic programming model of the optimal joint operation of cascade reservoirs and provides the corresponding recursive equation and the specific solving steps. Taking Li Xianjiang cascade reservoirs as a case study, seven uncertain problems in the whole operation period of the cascade reservoirs are summarized after a detailed analysis to the obtained optimal sample data, and two sub-models are put forward to solve these uncertain problems. Finally, by dividing the whole operation period into four characteristic sections, this paper extracts the operation rules of each reservoir for each section respectively. When compared the simulation results of the extracted operation rules with the conventional joint operation method; the result indicates that the power generation of the obtained rules has a certain degree of improvement both in inspection years and typical years (i.e., wet year; normal year and dry year. So, the rationality and effectiveness of the extracted operation rules are verified by the comparative analysis.

  10. Geriatric dietary meat-based products

    OpenAIRE

    Kuzelov, Aco; Agunova, Larisa

    2016-01-01

    The contemporary nutrition pattern referring to different age groups of the population does not meet quantitative and qualitative requirements. In Ukraine the manufacture of geriatric meat-based dietary products is underdeveloped. Therefore, the development of healthy and functional foods is the priority objective for the food industry. The research is devoted to considering the possibility of using quail meat, wheat germ flakes and walnut oil in the production process of the sausages for ...

  11. Rule Extraction Based on Extreme Learning Machine and an Improved Ant-Miner Algorithm for Transient Stability Assessment.

    Directory of Open Access Journals (Sweden)

    Yang Li

    Full Text Available In order to overcome the problems of poor understandability of the pattern recognition-based transient stability assessment (PRTSA methods, a new rule extraction method based on extreme learning machine (ELM and an improved Ant-miner (IAM algorithm is presented in this paper. First, the basic principles of ELM and Ant-miner algorithm are respectively introduced. Then, based on the selected optimal feature subset, an example sample set is generated by the trained ELM-based PRTSA model. And finally, a set of classification rules are obtained by IAM algorithm to replace the original ELM network. The novelty of this proposal is that transient stability rules are extracted from an example sample set generated by the trained ELM-based transient stability assessment model by using IAM algorithm. The effectiveness of the proposed method is shown by the application results on the New England 39-bus power system and a practical power system--the southern power system of Hebei province.

  12. Accounting standards and earnings management : The role of rules-based and principles-based accounting standards and incentives on accounting and transaction decisions

    NARCIS (Netherlands)

    Beest, van F.

    2012-01-01

    This book examines the effect that rules-based and principles-based accounting standards have on the level and nature of earnings management decisions. A cherry picking experiment is conducted to test the hypothesis that a substitution effect is expected from accounting decisions to transaction

  13. How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

    Science.gov (United States)

    Van Norman, Ethan R; Christ, Theodore J

    2016-10-01

    Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

  14. Towards a complete rule-based classification approach for flat fingerprints

    CSIR Research Space (South Africa)

    Webb, L

    2014-12-01

    Full Text Available fingerprints. This work implements an algorithm which includes new rules to account for more instances of flat fingerprints with missing singular points, specifically when the delta of a Right Loop or Left Loop fingerprint is not captured, when one of the loops...

  15. Development of a cause analysis system for a CPCS trip by using the rule-base deduction method.

    Science.gov (United States)

    Park, Je-Yun; Koo, In-Soo; Sohn, Chang-Ho; Kim, Jung-Seon; Cho, Gi-Ho; Park, Hee-Seok

    2009-07-01

    A Core Protection Calculator System (CPCS) was developed to initiate a Reactor Trip under the circumstance of certain transients by a Combustion Engineering Company. The major function of the Core Protection Calculator System is to generate contact outputs for the Departure from Nucleate Boiling Ratio (DNBR) Trip and a Local Power Density (LPD) Trip. But in a Core Protection Calculator System, a trip cause cannot be identified, thus only trip signals are transferred to the Plant Protection System (PPS) and only the trip status is displayed. It could take a considerable amount of time and effort for a plant operator to analyze the trip causes of a Core Protection Calculator System. So, a Cause Analysis System for a Core Protection Calculator System (CASCPCS) has been developed by using the rule-base deduction method to assist operators in a Nuclear Power Plant. CASCPCS consists of three major parts. Inference engine has a role of controlling the searching knowledge base, executing the rules and tracking the inference process by using the depth-first searching method. Knowledge base consists of four major parts: rules, data base constants, trip buffer variables and causes. And a user interface is implemented by using menu-driven and window display techniques. The advantage of CASCPCS is that it saves time and effort to diagnose the trip causes of a Core Protection Calculator System, it increases a plant's availability and reliability, and it makes it easy to manage CASCPCS because of using only a cursor control.

  16. A new intuitionistic fuzzy rule-based decision-making system for an operating system process scheduler.

    Science.gov (United States)

    Butt, Muhammad Arif; Akram, Muhammad

    2016-01-01

    We present a new intuitionistic fuzzy rule-based decision-making system based on intuitionistic fuzzy sets for a process scheduler of a batch operating system. Our proposed intuitionistic fuzzy scheduling algorithm, inputs the nice value and burst time of all available processes in the ready queue, intuitionistically fuzzify the input values, triggers appropriate rules of our intuitionistic fuzzy inference engine and finally calculates the dynamic priority (dp) of all the processes in the ready queue. Once the dp of every process is calculated the ready queue is sorted in decreasing order of dp of every process. The process with maximum dp value is sent to the central processing unit for execution. Finally, we show complete working of our algorithm on two different data sets and give comparisons with some standard non-preemptive process schedulers.

  17. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  18. CBM Resources/reserves classification and evaluation based on PRMS rules

    Science.gov (United States)

    Fa, Guifang; Yuan, Ruie; Wang, Zuoqian; Lan, Jun; Zhao, Jian; Xia, Mingjun; Cai, Dechao; Yi, Yanjing

    2018-02-01

    This paper introduces a set of definitions and classification requirements for coalbed methane (CBM) resources/reserves, based on Petroleum Resources Management System (PRMS). The basic CBM classification criterions of 1P, 2P, 3P and contingent resources are put forward from the following aspects: ownership, project maturity, drilling requirements, testing requirements, economic requirements, infrastructure and market, timing of production and development, and so on. The volumetric method is used to evaluate the OGIP, with focuses on analyses of key parameters and principles of the parameter selection, such as net thickness, ash and water content, coal rank and composition, coal density, cleat volume and saturation and absorbed gas content etc. A dynamic method is used to assess the reserves and recovery efficiency. Since the differences in rock and fluid properties, displacement mechanism, completion and operating practices and wellbore type resulted in different production curve characteristics, the factors affecting production behavior, the dewatering period, pressure build-up and interference effects were analyzed. The conclusion and results that the paper achieved can be used as important references for reasonable assessment of CBM resources/reserves.

  19. Network-based production quality control

    Science.gov (United States)

    Kwon, Yongjin; Tseng, Bill; Chiou, Richard

    2007-09-01

    This study investigates the feasibility of remote quality control using a host of advanced automation equipment with Internet accessibility. Recent emphasis on product quality and reduction of waste stems from the dynamic, globalized and customer-driven market, which brings opportunities and threats to companies, depending on the response speed and production strategies. The current trends in industry also include a wide spread of distributed manufacturing systems, where design, production, and management facilities are geographically dispersed. This situation mandates not only the accessibility to remotely located production equipment for monitoring and control, but efficient means of responding to changing environment to counter process variations and diverse customer demands. To compete under such an environment, companies are striving to achieve 100%, sensor-based, automated inspection for zero-defect manufacturing. In this study, the Internet-based quality control scheme is referred to as "E-Quality for Manufacturing" or "EQM" for short. By its definition, EQM refers to a holistic approach to design and to embed efficient quality control functions in the context of network integrated manufacturing systems. Such system let designers located far away from the production facility to monitor, control and adjust the quality inspection processes as production design evolves.

  20. Network Based High Speed Product Innovation

    DEFF Research Database (Denmark)

    Lindgren, Peter

    In the first decade of the 21st century, New Product Development has undergone major changes in the way NPD is managed and organised. This is due to changes in technology, market demands, and in the competencies of companies. As a result NPD organised in different forms of networks is predicted...... to be of ever-increasing importance to many different kinds of companies. This happens at the same times as the share of new products of total turnover and earnings is increasing at unprecedented speed in many firms and industries. The latter results in the need for very fast innovation and product development...... - a need that can almost only be resolved by organising NPD in some form of network configuration. The work of Peter Lindgren is on several aspects of network based high speed product innovation and contributes to a descriptive understanding of this phenomenon as well as with normative theory on how NPD...

  1. Modeling oil production based on symbolic regression

    International Nuclear Information System (INIS)

    Yang, Guangfei; Li, Xianneng; Wang, Jianliang; Lian, Lian; Ma, Tieju

    2015-01-01

    Numerous models have been proposed to forecast the future trends of oil production and almost all of them are based on some predefined assumptions with various uncertainties. In this study, we propose a novel data-driven approach that uses symbolic regression to model oil production. We validate our approach on both synthetic and real data, and the results prove that symbolic regression could effectively identify the true models beneath the oil production data and also make reliable predictions. Symbolic regression indicates that world oil production will peak in 2021, which broadly agrees with other techniques used by researchers. Our results also show that the rate of decline after the peak is almost half the rate of increase before the peak, and it takes nearly 12 years to drop 4% from the peak. These predictions are more optimistic than those in several other reports, and the smoother decline will provide the world, especially the developing countries, with more time to orchestrate mitigation plans. -- Highlights: •A data-driven approach has been shown to be effective at modeling the oil production. •The Hubbert model could be discovered automatically from data. •The peak of world oil production is predicted to appear in 2021. •The decline rate after peak is half of the increase rate before peak. •Oil production projected to decline 4% post-peak

  2. Replacing fossil based plastic performance products by bio-based plastic products-Technical feasibility

    NARCIS (Netherlands)

    Oever, van den Martien; Molenveld, Karin

    2017-01-01

    Larger scale market introduction of new bio-based products requires a clear advantage regarding sustainability, as well as an adequate techno-economic positioning relative to fossil based products. In a previous paper [Broeren et al., 2016], LCA results per kg and per functionality equivalent of

  3. Environmental interactions of cement-based products

    NARCIS (Netherlands)

    Florea, M.V.A.; Schmidt, W.; Msinjili, N.S.

    2016-01-01

    The environmental interactions of concrete and other cement-based products encompasses both the influence of such materials on their environment, as well as the effects of the environment on the materials in time. There are a number of ways in which the environmental impact of concrete can be

  4. Conditioning of high voltage radio frequency cavities by using fuzzy logic in connection with rule based programming

    CERN Document Server

    Perréard, S

    1993-01-01

    Many processes are controlled by experts using some kind of mental model to decide actions and make conclusions. This model, based on heuristic knowledge, can often be conveniently represented in rules and has not to be particularly accurate. This is the case for the problem of conditioning high voltage radio-frequency cavities: the expert has to decide, by observing some criteria, if he can increase or if he has to decrease the voltage and by how much. A program has been implemented which can be applied to a class of similar problems. The kernel of the program is a small rule base, which is independent of the kind of cavity. To model a specific cavity, we use fuzzy logic which is implemented as a separate routine called by the rule base. We use fuzzy logic to translate from numeric to symbolic information. The example we chose for applying this kind of technique can be implemented by sequential programming. The two versions exist for comparison. However, we believe that this kind of programming can be powerf...

  5. Machine vision based quality inspection of flat glass products

    Science.gov (United States)

    Zauner, G.; Schagerl, M.

    2014-03-01

    This application paper presents a machine vision solution for the quality inspection of flat glass products. A contact image sensor (CIS) is used to generate digital images of the glass surfaces. The presented machine vision based quality inspection at the end of the production line aims to classify five different glass defect types. The defect images are usually characterized by very little `image structure', i.e. homogeneous regions without distinct image texture. Additionally, these defect images usually consist of only a few pixels. At the same time the appearance of certain defect classes can be very diverse (e.g. water drops). We used simple state-of-the-art image features like histogram-based features (std. deviation, curtosis, skewness), geometric features (form factor/elongation, eccentricity, Hu-moments) and texture features (grey level run length matrix, co-occurrence matrix) to extract defect information. The main contribution of this work now lies in the systematic evaluation of various machine learning algorithms to identify appropriate classification approaches for this specific class of images. In this way, the following machine learning algorithms were compared: decision tree (J48), random forest, JRip rules, naive Bayes, Support Vector Machine (multi class), neural network (multilayer perceptron) and k-Nearest Neighbour. We used a representative image database of 2300 defect images and applied cross validation for evaluation purposes.

  6. DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

    Science.gov (United States)

    Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

    2018-04-01

    Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

  7. Exploiting deterministic maintenance opportunity windows created by conservative engineering design rules that result in free time locked into large high-speed coupled production lines with finite buffers

    Directory of Open Access Journals (Sweden)

    Durandt, Casper

    2016-08-01

    Full Text Available Conservative engineering design rules for large serial coupled production processes result in machines having locked-in free time (also called ‘critical downtime’ or ‘maintenance opportunity windows’, which cause idle time if not used. Operators are not able to assess a large production process holistically, and so may not be aware that they form the current bottleneck – or that they have free time available due to interruptions elsewhere. A real-time method is developed to accurately calculate and display free time in location and magnitude, and efficiency improvements are demonstrated in large-scale production runs.

  8. Privacy Protection Method for Multiple Sensitive Attributes Based on Strong Rule

    Directory of Open Access Journals (Sweden)

    Tong Yi

    2015-01-01

    Full Text Available At present, most studies on data publishing only considered single sensitive attribute, and the works on multiple sensitive attributes are still few. And almost all the existing studies on multiple sensitive attributes had not taken the inherent relationship between sensitive attributes into account, so that adversary can use the background knowledge about this relationship to attack the privacy of users. This paper presents an attack model with the association rules between the sensitive attributes and, accordingly, presents a data publication for multiple sensitive attributes. Through proof and analysis, the new model can prevent adversary from using the background knowledge about association rules to attack privacy, and it is able to get high-quality released information. At last, this paper verifies the above conclusion with experiments.

  9. Rule-Based Design of Plant Expression Vectors Using GenoCAD.

    Science.gov (United States)

    Coll, Anna; Wilson, Mandy L; Gruden, Kristina; Peccoud, Jean

    2015-01-01

    Plant synthetic biology requires software tools to assist on the design of complex multi-genic expression plasmids. Here a vector design strategy to express genes in plants is formalized and implemented as a grammar in GenoCAD, a Computer-Aided Design software for synthetic biology. It includes a library of plant biological parts organized in structural categories and a set of rules describing how to assemble these parts into large constructs. Rules developed here are organized and divided into three main subsections according to the aim of the final construct: protein localization studies, promoter analysis and protein-protein interaction experiments. The GenoCAD plant grammar guides the user through the design while allowing users to customize vectors according to their needs. Therefore the plant grammar implemented in GenoCAD will help plant biologists take advantage of methods from synthetic biology to design expression vectors supporting their research projects.

  10. A Rule-Based Policy-Level Model of Nonsuperpower Behavior in Strategic Conflicts.

    Science.gov (United States)

    1982-12-01

    a mechanism. The human mind tends to work linearly and to focus implicitly on a few variables. Experience results in subconscious models with far...which is slower. Alternatives to the current ROSIE implementation include reprogramming Scenario Agent in the C language (the language used for the Red...perception, opportunity perception, opportunity response, and assertiveness. As rules are refined, maintenance and reprogramming of the model will be required

  11. Growth rules based on the modularity of the Canarian Aeonium (Crassulaceae) and their phylogenetic value

    DEFF Research Database (Denmark)

    Jorgensen, T.H.; Olesen, J.M.

    2000-01-01

    Growth forms of 22 species of Aeonium (Crassulaceae) were quantified. Since all species are simple in their modular construction, models were developed to predict module length, branching mode and flowering probability using linear and logistic regression. When combined, the parameters...... of these models are species specific. A discriminant analysis generates a statistically significant separation of species at the level of phylogenetic sections. The results therefore demonstrate the phylogenetic value of growth rules in plants. This dynamic approach strongly contrasts with the traditional static...

  12. Cracking chaos-based encryption systems ruled by nonlinear time delay differential equations

    International Nuclear Information System (INIS)

    Udaltsov, Vladimir S.; Goedgebuer, Jean-Pierre; Larger, Laurent; Cuenot, Jean-Baptiste; Levy, Pascal; Rhodes, William T.

    2003-01-01

    We report that signal encoding with high-dimensional chaos produced by delayed feedback systems with a strong nonlinearity can be broken. We describe the procedure and illustrate the method with chaotic waveforms obtained from a strongly nonlinear optical system that we used previously to demonstrate signal encryption/decryption with chaos in wavelength. The method can be extended to any systems ruled by nonlinear time-delayed differential equations

  13. DEVELOPMENT OF WOOD-BASED PRODUCTS WORLDWIDE

    Directory of Open Access Journals (Sweden)

    Marius C. BARBU

    2015-12-01

    Full Text Available The tendency in recent decades for manufacturing plants of semi-finished products such as composite panels, has been to invest in order to achieve high production capacities (>2,000 m³/day for panels and >3,000 t/day for paper with one line. The trend of concentrating the primary processing capacities and manufacturing wood-based panels will continue for the next few years not only in Europe but in North and South America as well. The ten largest panel manufacturers had a combined manufacturing capacity that exceeded a third of the worldwide production capacity. The financial crisis that started in 2008 has caused the closure of a large number of factories especially in North America and Central Europe. Small- and medium-sized producers will only survive if they will continue to specialize in the manufacture of panel types and sizes (niche products that are “unprofitable” for mega-groups. The installed production capacity worldwide of all wood-based composite panels combined (includes PY, PB, MDF, OSB rose by more than 2.5 times between 1980 and 2005 (225 mil.m³, and continues to increase despite the crises reaching approx. 300 mil.m³ in 2013. The forecast for the coming years varies greatly from continent to continent. In North America and Central Europe, both a consolidation of the available production capacities and the closure of less efficient older lines are expected. The lowest point of the effect of the financial crisis on the building industry seems to have been overcome. The furniture production companies will continue to move from one continent and region to another.

  14. A Methodology for Multiple Rule System Integration and Resolution Within a Singular Knowledge Base

    Science.gov (United States)

    Kautzmann, Frank N., III

    1988-01-01

    Expert Systems which support knowledge representation by qualitative modeling techniques experience problems, when called upon to support integrated views embodying description and explanation, especially when other factors such as multiple causality, competing rule model resolution, and multiple uses of knowledge representation are included. A series of prototypes are being developed to demonstrate the feasibility of automating the process of systems engineering, design and configuration, and diagnosis and fault management. A study involves not only a generic knowledge representation; it must also support multiple views at varying levels of description and interaction between physical elements, systems, and subsystems. Moreover, it will involve models of description and explanation for each level. This multiple model feature requires the development of control methods between rule systems and heuristics on a meta-level for each expert system involved in an integrated and larger class of expert system. The broadest possible category of interacting expert systems is described along with a general methodology for the knowledge representation and control of mutually exclusive rule systems.

  15. Urinary metabolic profiling of asymptomatic acute intermittent porphyria using a rule-mining-based algorithm.

    Science.gov (United States)

    Luck, Margaux; Schmitt, Caroline; Talbi, Neila; Gouya, Laurent; Caradeuc, Cédric; Puy, Hervé; Bertho, Gildas; Pallet, Nicolas

    2018-01-01

    Metabolomic profiling combines Nuclear Magnetic Resonance spectroscopy with supervised statistical analysis that might allow to better understanding the mechanisms of a disease. In this study, the urinary metabolic profiling of individuals with porphyrias was performed to predict different types of disease, and to propose new pathophysiological hypotheses. Urine 1 H-NMR spectra of 73 patients with asymptomatic acute intermittent porphyria (aAIP) and familial or sporadic porphyria cutanea tarda (f/sPCT) were compared using a supervised rule-mining algorithm. NMR spectrum buckets bins, corresponding to rules, were extracted and a logistic regression was trained. Our rule-mining algorithm generated results were consistent with those obtained using partial least square discriminant analysis (PLS-DA) and the predictive performance of the model was significant. Buckets that were identified by the algorithm corresponded to metabolites involved in glycolysis and energy-conversion pathways, notably acetate, citrate, and pyruvate, which were found in higher concentrations in the urines of aAIP compared with PCT patients. Metabolic profiling did not discriminate sPCT from fPCT patients. These results suggest that metabolic reprogramming occurs in aAIP individuals, even in the absence of overt symptoms, and supports the relationship that occur between heme synthesis and mitochondrial energetic metabolism.

  16. Model-based Systems Engineering: Creation and Implementation of Model Validation Rules for MOS 2.0

    Science.gov (United States)

    Schmidt, Conrad K.

    2013-01-01

    Model-based Systems Engineering (MBSE) is an emerging modeling application that is used to enhance the system development process. MBSE allows for the centralization of project and system information that would otherwise be stored in extraneous locations, yielding better communication, expedited document generation and increased knowledge capture. Based on MBSE concepts and the employment of the Systems Modeling Language (SysML), extremely large and complex systems can be modeled from conceptual design through all system lifecycles. The Operations Revitalization Initiative (OpsRev) seeks to leverage MBSE to modernize the aging Advanced Multi-Mission Operations Systems (AMMOS) into the Mission Operations System 2.0 (MOS 2.0). The MOS 2.0 will be delivered in a series of conceptual and design models and documents built using the modeling tool MagicDraw. To ensure model completeness and cohesiveness, it is imperative that the MOS 2.0 models adhere to the specifications, patterns and profiles of the Mission Service Architecture Framework, thus leading to the use of validation rules. This paper outlines the process by which validation rules are identified, designed, implemented and tested. Ultimately, these rules provide the ability to maintain model correctness and synchronization in a simple, quick and effective manner, thus allowing the continuation of project and system progress.

  17. [Analyze prescription rules of Professor Jiang Liangduo treatment for abdominal mass based on traditional Chinese medicine inheritance platform].

    Science.gov (United States)

    Lian, Xiao-Xiao; Guo, Xiao-Xia

    2018-01-01

    To investigate the herbal prescription rules of Professor Jiang Liangduo in the treatment of abdominal mass based on the traditional Chinese medicine inheritance support system software (TCMISS) of version 2.5, find out new herbal formulas for the treatment of abdominal mass, and then provide new reference to its traditional Chinese medicine therapy. By the method of retrospective study, one hundred and thirty-two outpatient prescriptions of Professor Jiang for the treatment of abdominal mass were collected to establish a typical database with TCMISS. Four properties, five tastes, channel tropism, frequency count, Chinese herbal prescriptions rules and the new prescriptions were analyzed so as to dig out the prescription rules. There were 57 herbs with a frequency>=15, and then 91 core combinations of 2-5 herbs were evolved and 9 new prescriptions were created. It was found out that these drugs mainly had the effects of liver nourishing and soothing, soft-moist and dredging-tonifying, supporting right and dispeling evil, cooperating with the method of calming the liver and resolving hard lump according to the actual situation. It reflected the thought of treatment based on syndrome differentiation in TCM, and provided a new reference for its clinical treatment and research. Copyright© by the Chinese Pharmaceutical Association.

  18. Location Prediction Based on Transition Probability Matrices Constructing from Sequential Rules for Spatial-Temporal K-Anonymity Dataset

    Science.gov (United States)

    Liu, Zhao; Zhu, Yunhong; Wu, Chenxue

    2016-01-01

    Spatial-temporal k-anonymity has become a mainstream approach among techniques for protection of users’ privacy in location-based services (LBS) applications, and has been applied to several variants such as LBS snapshot queries and continuous queries. Analyzing large-scale spatial-temporal anonymity sets may benefit several LBS applications. In this paper, we propose two location prediction methods based on transition probability matrices constructing from sequential rules for spatial-temporal k-anonymity dataset. First, we define single-step sequential rules mined from sequential spatial-temporal k-anonymity datasets generated from continuous LBS queries for multiple users. We then construct transition probability matrices from mined single-step sequential rules, and normalize the transition probabilities in the transition matrices. Next, we regard a mobility model for an LBS requester as a stationary stochastic process and compute the n-step transition probability matrices by raising the normalized transition probability matrices to the power n. Furthermore, we propose two location prediction methods: rough prediction and accurate prediction. The former achieves the probabilities of arriving at target locations along simple paths those include only current locations, target locations and transition steps. By iteratively combining the probabilities for simple paths with n steps and the probabilities for detailed paths with n-1 steps, the latter method calculates transition probabilities for detailed paths with n steps from current locations to target locations. Finally, we conduct extensive experiments, and correctness and flexibility of our proposed algorithm have been verified. PMID:27508502

  19. Real-time Geographic Information System (GIS) for Monitoring the Area of Potential Water Level Using Rule Based System

    Science.gov (United States)

    Anugrah, Wirdah; Suryono; Suseno, Jatmiko Endro

    2018-02-01

    Management of water resources based on Geographic Information System can provide substantial benefits to water availability settings. Monitoring the potential water level is needed in the development sector, agriculture, energy and others. In this research is developed water resource information system using real-time Geographic Information System concept for monitoring the potential water level of web based area by applying rule based system method. GIS consists of hardware, software, and database. Based on the web-based GIS architecture, this study uses a set of computer that are connected to the network, run on the Apache web server and PHP programming language using MySQL database. The Ultrasound Wireless Sensor System is used as a water level data input. It also includes time and geographic location information. This GIS maps the five sensor locations. GIS is processed through a rule based system to determine the level of potential water level of the area. Water level monitoring information result can be displayed on thematic maps by overlaying more than one layer, and also generating information in the form of tables from the database, as well as graphs are based on the timing of events and the water level values.

  20. An Application of the Phosphorus Consistent Rule for Environmentally Acceptable Cost-Efficient Management of Broiler Litter in Crop Production

    Science.gov (United States)

    Paudel, Krishna P.; Limaye, Ashutosh; Adhikari, Murali; Martin, Neil R., Jr.

    2004-01-01

    We calculated the profitability of using broiler litter as a source of plant nutrients using the phosphorus consistent litter application rule. The cost saving by using litter is 37% over the use of chemical fertilizer-only option to meet the nutrient needs of major crops grown in Alabama. In the optimal solution, only a few routes of all the possible routes developed were used for inter- and intra- county litter hauling. If litter is not adopted as the sole source of crop nutrients, the best environmental policy may be to pair the phosphorus consistent rule with taxes, marketable permits, and subsidies.flaws

  1. Effects of the Memorization of Rule Statements on Performance, Retention, and Transfer in a Computer-Based Learning Task.

    Science.gov (United States)

    Towle, Nelson J.

    Research sought to determine whether memorization of rule statements before, during or after instruction in rule application skills would facilitate the acquisition and/or retention of rule-governed behavior as compared to no-rule statement memorization. A computer-assisted instructional (CAI) program required high school students to learn to a…

  2. Implementasi Rule Base System dan Fuzzy Logic Artifical Intelligence pada Game Kartu Capsa

    OpenAIRE

    Pangkatodi, Edo; Liliana, Liliana; Budhi, Gregorius Satia

    2016-01-01

    In the era of globalization today, science and technology is developing very fast, particularly in entertainment media, specifically in the gaming world. Today, games are not only used as an entertainment, but also can be used as an alternative in the world of work, education, and even sports. In the world of gaming, artificial intelligence, or AI is a factor that cannot be separated. With the right methods and the specific rules of the AI can walk like a human being doing a job. So it is not...

  3. A comparison of cost-based pricing rules for natural gas distribution utilities

    International Nuclear Information System (INIS)

    Klein, C.C.

    1993-01-01

    Partial-equilibrium social welfare deadweight losses under uniform Ramsey pricing, a cost allocation pricing method, and the actual average revenues by customer class for two natural gas distribution utilities are calculated and compared. Marginal cost estimates are derived from a multiple-output translog variable cost function and used, along with three sets of demand elasticities, to generate the Ramsey prices and welfare losses. The actual and cost-allocation prices are taken directly from rate case files. The largest social welfare losses are associated with the cost-allocation rule, as high as 10-25% of revenue, despite suggestions in the literature to the contrary. (Author)

  4. A PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2012-01-01

    Full Text Available Most existing research on the job shop scheduling problem has been focused on the minimization of makespan (i.e., the completion time of the last job. However, in the fiercely competitive market nowadays, delivery punctuality is more important for maintaining a high service reputation. So in this paper, we aim at solving job shop scheduling problems with the total weighted tardiness objective. Several dispatching rules are adopted in the Giffler-Thompson algorithm for constructing active schedules. It is noticeable that the rule selections for scheduling consecutive operations are not mutually independent but actually interrelated. Under such circumstances, a probabilistic model-building genetic algorithm (PMBGA is proposed to optimize the sequence of selected rules. First, we use Bayesian networks to model the distribution characteristics of high-quality solutions in the population. Then, the new generation of individuals is produced by sampling the established Bayesian network. Finally, some elitist individuals are further improved by a special local search module based on parameter perturbation. The superiority of the proposed approach is verified by extensive computational experiments and comparisons.

  5. Systematic generation of rules for nuclear power plant diagnostics

    International Nuclear Information System (INIS)

    Reifman, J.; Lee, J.C.

    1988-01-01

    The knowledge base of an expert system is generally represented by a set of heuristic rules derived from the expert's own experience and judgmental knowledge. These heuristic or production rules are cast as if (condition), then (consequence) statements, and represent, for nuclear power plant diagnostic systems, information connecting symptoms to failures. In this paper, the authors apply an entropy minimax pattern recognition algorithm to automate the process of extracting and encoding knowledge into a set of rules. Knowledge is extracted by recognizing patterns in plant parameters or symptoms associated with failures or transient events, and is encoded by casting the discovered patterns as production rules. The paper discusses how the proposed method can systematically generate rules that characterize failure of pressurizer components based on transient events analyzed with a pressurizer components based on transient events analyzed with a pressurizer water reactor simulator program

  6. Spin alignment and violation of the OZI rule in exclusive omega and phi production in pp collisions

    Czech Academy of Sciences Publication Activity Database

    Adolph, C.; Akhunzyanov, R.; Alekseev, M.; Alexeev, G. D.; Amoroso, A.; Andrieux, V.; Anosov, V. A.; Austregisilio, A.; Badelek, B.; Balestra, F.; Barth, J.; Baum, G.; Beck, R.; Bedfer, Y.; Berlin, A.; Bernhard, J.; Bicker, K.; Bieling, J.; Birsa, R.; Bisplinghoff, J.; Bodlak, M.; Boer, M.; Bordalo, P.; Bradamante, F.; Braun, C.; Bressan, A.; Büchele, M.; Burtin, E.; Capozza, L.; Chiosso, M.; Chung, S.U.; Cicuttin, A.; Crespo, M.; Curiel, Q.; Dalla Torre, S.; Dasgupta, S. S.; Dasgupta, S.; Denisov, O.; Donskov, S.; Doshita, N.; Duic, V.; Dünnweber, W.; Dziewiecki, M.; Efremov, A.V.; Elia, C.; Eversheim, P.; Eyrich, W.; Faessler, M.; Ferrero, A.; Filin, A.; Finger, M.; Finger jr., M.; Fischer, H.; Franco, C.; Fresne von Hohenesche, N.; Friedrich, J.; Frolov, V.; Gautheron, F.; Gavrichtchouk, O.; Gerassimov, S.; Geyer, R.; Gnesi, I.; Gobbo, B.; Goertz, S.; Gorzellik, M.; Grabmüller, S.; Grasso, A.; Grube, B.; Grussemmeyer, T.; Guskov, A.; Guthörl, T.; Haas, F.; von Harrach, D.; Hahne, D.; Hashimoto, R.; Heinsius, F.; Herrmann, F.; Hinterberger, F.; Höppner, Ch.; Horikawa, N.; d'Hose, N.; Huber, S.; Ishimoto, S.; Ivanov, A.; Ivanshin, Yu.; Iwata, T.; Jahn, R.; Jary, V.; Jasinski, P.; Joerg, P.; Joosten, R.; Kabuss, E.; Ketzer, B.; Khaustov, G.; Khokhlov, Y.; Kisselev, Y.; Klein, F.; Klimaszewski, K.; Koivuniemi, J.; Kolosov, V.; Kondo, K.; Königsmann, K.; Konorov, I.; Konstantinov, V.; Kotzinian, A.; Kouznetsov, O.; Král, Z.; Krämer, M.; Kroumchtein, Z.; Kuchinski, N.; Kunne, F.; Kurek, K.; Kurjata, R. P.; Lednev, A.; Lehmann, A.; Levillain, M.; Levorato, S.; Lichtenstadt, J.; Maggiora, A.; Magnon, A.; Makke, N.; Mallot, G.; Marchand, C.; Martin, A.; Marzec, J.; Matoušek, J.; Matsuda, H.; Matsuda, T.; Meshcheryakov, G.; Meyer, W.; Michigami, T.; Mikhailov, Y.; Miyachi, Y.; Nagaytsev, A.; Nagel, T.; Nerling, F.; Neubert, S.; Neyret, D.; Nový, J.; Nikolaenko, V.; Nowak, W. D.; Nunes, A.S.; Orlov, I.; Olshevsky, A.; Ostrick, M.; Panknin, R.; Panzieri, D.; Parsamyan, B.; Paul, S.; Pešek, M.; Platchkov, S.; Pochodzalla, J.; Polyakov, V.; Pretz, J.; Quaresma, M.; Quintans, C.; Ramos, S.; Regali, C.; Reicherz, G.; Rocco, E.; Rossiyskaya, N. S.; Ryabchikov, D.; Rychter, A.; Samoylenko, V.; Sandacz, A.; Sapozhnikov, M.; Sarkar, S.; Savin, I.; Sbrizzai, G.; Schiavon, P.; Schill, C.; Schlütter, T.; Schmidt, A.; Schmidt, K.; Schmiden, H.; Schönning, K.; Schopferer, S.; Schott, M.; Shevchenko, O.; Silva, L.; Sinha, L.; Sirtl, S.; Slunecka, M.; Sosio, S.; Sozzi, F.; Steiger, L.; Srnka, Aleš; Stolarski, M.; Sulc, M.; Suzuki, H.; Sulej, R.; Szabelski, A.; Szameitat, T.; Sznajder, P.; Takekawa, S.; Ter Wolbeek, J.; Tessaro, S.; Tessarotto, F.; Thibaud, F.; Uhl, S.; Uman, I.; Virius, M.; Wang, L.; Weisrock, T.; Wilfert, M.; Windmolders, R.; Wollny, H.; Zaremba, K.; Zavertyaev, M.; Zemlyanichkina, E.; Ziembicki, M.; Zink, A.

    2014-01-01

    Roč. 886, SEP 2014 (2014), s. 1078-1101 ISSN 0550-3213 R&D Projects: GA MŠk(CZ) LO1212 Keywords : OZI rule * vector meson * pp collision * liquid hydrogen target Subject RIV: BG - Nuclear, Atomic and Molecular Physics, Colliders Impact factor: 3.929, year: 2014

  7. Evaluation of a rule-based method for epidemiological document classification towards the automation of systematic reviews.

    Science.gov (United States)

    Karystianis, George; Thayer, Kristina; Wolfe, Mary; Tsafnat, Guy

    2017-06-01

    Most data extraction efforts in epidemiology are focused on obtaining targeted information from clinical trials. In contrast, limited research has been conducted on the identification of information from observational studies, a major source for human evidence in many fields, including environmental health. The recognition of key epidemiological information (e.g., exposures) through text mining techniques can assist in the automation of systematic reviews and other evidence summaries. We designed and applied a knowledge-driven, rule-based approach to identify targeted information (study design, participant population, exposure, outcome, confounding factors, and the country where the study was conducted) from abstracts of epidemiological studies included in several systematic reviews of environmental health exposures. The rules were based on common syntactical patterns observed in text and are thus not specific to any systematic review. To validate the general applicability of our approach, we compared the data extracted using our approach versus hand curation for 35 epidemiological study abstracts manually selected for inclusion in two systematic reviews. The returned F-score, precision, and recall ranged from 70% to 98%, 81% to 100%, and 54% to 97%, respectively. The highest precision was observed for exposure, outcome and population (100%) while recall was best for exposure and study design with 97% and 89%, respectively. The lowest recall was observed for the population (54%), which also had the lowest F-score (70%). The generated performance of our text-mining approach demonstrated encouraging results for the identification of targeted information from observational epidemiological study abstracts related to environmental exposures. We have demonstrated that rules based on generic syntactic patterns in one corpus can be applied to other observational study design by simple interchanging the dictionaries aiming to identify certain characteristics (i.e., outcomes

  8. Image based SAR product simulation for analysis

    Science.gov (United States)

    Domik, G.; Leberl, F.

    1987-01-01

    SAR product simulation serves to predict SAR image gray values for various flight paths. Input typically consists of a digital elevation model and backscatter curves. A new method is described of product simulation that employs also a real SAR input image for image simulation. This can be denoted as 'image-based simulation'. Different methods to perform this SAR prediction are presented and advantages and disadvantages discussed. Ascending and descending orbit images from NASA's SIR-B experiment were used for verification of the concept: input images from ascending orbits were converted into images from a descending orbit; the results are compared to the available real imagery to verify that the prediction technique produces meaningful image data.

  9. A New Approach of Multi-robot Cooperative Pursuit Based on Association Rule Data Mining

    Directory of Open Access Journals (Sweden)

    Jun Li

    2010-02-01

    Full Text Available An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.

  10. A New Approach of Multi-Robot Cooperative Pursuit Based on Association Rule Data Mining

    Directory of Open Access Journals (Sweden)

    Jun Li

    2009-12-01

    Full Text Available An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuit process into forming the pursuit teams and capturing the targets. The data sets of attribute relationship is built by consulting all of factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuit teams. Through doping out the positions of targets, the pursuit game can be transformed into multi-robot path planning. Reinforcement learning is used to find the best path. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under a dynamic environment.

  11. Updating OSHA Standards Based on National Consensus Standards; Eye and Face Protection. Final rule.

    Science.gov (United States)

    2016-03-25

    On March 13, 2015, OSHA published in the Federal Register a notice of proposed rulemaking (NPRM) to revise its eye and face protection standards for general industry, shipyard employment, marine terminals, longshoring, and construction by updating the references to national consensus standards approved by the American National Standards Institute (ANSI). OSHA received no significant objections from commenters and therefore is adopting the amendments as proposed. This final rule updates the references in OSHA's eye and face standards to reflect the most recent edition of the ANSI/International Safety Equipment Association (ISEA) eye and face protection standard. It removes the oldest-referenced edition of the same ANSI standard. It also amends other provisions of the construction eye and face protection standard to bring them into alignment with OSHA's general industry and maritime standards.

  12. Fuzzy-rule-based Adaptive Resource Control for Information Sharing in P2P Networks

    Science.gov (United States)

    Wu, Zhengping; Wu, Hao

    With more and more peer-to-peer (P2P) technologies available for online collaboration and information sharing, people can launch more and more collaborative work in online social networks with friends, colleagues, and even strangers. Without face-to-face interactions, the question of who can be trusted and then share information with becomes a big concern of a user in these online social networks. This paper introduces an adaptive control service using fuzzy logic in preference definition for P2P information sharing control, and designs a novel decision-making mechanism using formal fuzzy rules and reasoning mechanisms adjusting P2P information sharing status following individual users' preferences. Applications of this adaptive control service into different information sharing environments show that this service can provide a convenient and accurate P2P information sharing control for individual users in P2P networks.

  13. Security Situation Assessment of All-Optical Network Based on Evidential Reasoning Rule

    Directory of Open Access Journals (Sweden)

    Zhong-Nan Zhao

    2016-01-01

    Full Text Available It is important to determine the security situations of the all-optical network (AON, which is more vulnerable to hacker attacks and faults than other networks in some cases. A new approach of the security situation assessment to the all-optical network is developed in this paper. In the new assessment approach, the evidential reasoning (ER rule is used to integrate various evidences of the security factors including the optical faults and the special attacks in the AON. Furthermore, a new quantification method of the security situation is also proposed. A case study of an all-optical network is conducted to demonstrate the effectiveness and the practicability of the new proposed approach.

  14. Strategy as simple rules.

    Science.gov (United States)

    Eisenhardt, K M; Sull, D N

    2001-01-01

    The success of Yahoo!, eBay, Enron, and other companies that have become adept at morphing to meet the demands of changing markets can't be explained using traditional thinking about competitive strategy. These companies have succeeded by pursuing constantly evolving strategies in market spaces that were considered unattractive according to traditional measures. In this article--the third in an HBR series by Kathleen Eisenhardt and Donald Sull on strategy in the new economy--the authors ask, what are the sources of competitive advantage in high-velocity markets? The secret, they say, is strategy as simple rules. The companies know that the greatest opportunities for competitive advantage lie in market confusion, but they recognize the need for a few crucial strategic processes and a few simple rules. In traditional strategy, advantage comes from exploiting resources or stable market positions. In strategy as simple rules, advantage comes from successfully seizing fleeting opportunities. Key strategic processes, such as product innovation, partnering, or spinout creation, place the company where the flow of opportunities is greatest. Simple rules then provide the guidelines within which managers can pursue such opportunities. Simple rules, which grow out of experience, fall into five broad categories: how- to rules, boundary conditions, priority rules, timing rules, and exit rules. Companies with simple-rules strategies must follow the rules religiously and avoid the temptation to change them too frequently. A consistent strategy helps managers sort through opportunities and gain short-term advantage by exploiting the attractive ones. In stable markets, managers rely on complicated strategies built on detailed predictions of the future. But when business is complicated, strategy should be simple.

  15. ALPHABET SIGN LANGUAGE RECOGNITION USING LEAP MOTION TECHNOLOGY AND RULE BASED BACKPROPAGATION-GENETIC ALGORITHM NEURAL NETWORK (RBBPGANN

    Directory of Open Access Journals (Sweden)

    Wijayanti Nurul Khotimah

    2017-01-01

    Full Text Available Sign Language recognition was used to help people with normal hearing communicate effectively with the deaf and hearing-impaired. Based on survey that conducted by Multi-Center Study in Southeast Asia, Indonesia was on the top four position in number of patients with hearing disability (4.6%. Therefore, the existence of Sign Language recognition is important. Some research has been conducted on this field. Many neural network types had been used for recognizing many kinds of sign languages. However, their performance are need to be improved. This work focuses on the ASL (Alphabet Sign Language in SIBI (Sign System of Indonesian Language which uses one hand and 26 gestures. Here, thirty four features were extracted by using Leap Motion. Further, a new method, Rule Based-Backpropagation Genetic Al-gorithm Neural Network (RB-BPGANN, was used to recognize these Sign Languages. This method is combination of Rule and Back Propagation Neural Network (BPGANN. Based on experiment this pro-posed application can recognize Sign Language up to 93.8% accuracy. It was very good to recognize large multiclass instance and can be solution of overfitting problem in Neural Network algorithm.

  16. Flour production from shrimp by-products and sensory evaluation of flour-based products

    Directory of Open Access Journals (Sweden)

    Thiago Mendes Fernandes

    2013-08-01

    Full Text Available The objective of this work was to evaluate the production of flour using by-products (cephalothorax obtained from the shrimp (Litopenaeus vannamei industry, and to perform a sensory analysis of shrimp flour-based products. Physicochemical and microbiological analyses on fresh cephalothorax and on manufactured flour were performed, as well as the determination of cholesterol content of this flour, and the sensorial evaluation of soup and pastry made with this flour. By the microbiological analyses, no pathogenic microorganism was detected in the samples. Physicochemical analyses of flour showed high levels of protein (50.05% and minerals (20.97%. Shrimp cephalothorax flour showed high levels of cholesterol. The sensory evaluation indicated a good acceptance of the products, with satisfactory acceptability index (81% for soup, and 83% for pastry, which indicates that shrimp cephalothorax in the form of flour has a potential for developing new products.

  17. National contingency plan product schedule data base

    International Nuclear Information System (INIS)

    Putukian, J.; Hiltabrand, R.R.

    1993-01-01

    During oil spills there are always proposals by the technical community and industry to use chemical agents to help in oil spill cleanups. Federal Clean Water Act regulations require that any chemical agents that the federal on-scene coordinator (FOSC) wants to use for oil cleanup be listed on the US Environmental Protection Agency (EPA) National Contingency Plan (NCP) Product Schedule. Chemical countermeasures are among the most controversial, complex, and time-critical issues facing decision-making officials choosing response methods to use on coastal oil spills. There are situations in which dispersants are likely to be one of the most appropriate counter-measure strategies. Dispersants are most effective when applied to fresh oil, and their effectiveness dramatically decreases as the oil weathers, which can begin in as little as 24 hours. To logistically implement dispersant use, a decision would need to be made within roughly the first 4 hours after the release. Most of the information that the FOSC needs to make the determination to use a specific chemical agent exists in manuals, EPA bulletins, and the published literature. This information is not in an easy-to-use format under field emergency conditions. Hence the need to collect and disseminate the information in an automated data base. The sources for the information in this data base are the following. Published results of tests performed by Environment Canada; EPA bulletins associated with the NCP Product Schedule; Published results of tests by the chemical industry. The data base resides on a Macintosh computer and contains information about 70 NCP products, including dispersants, surface collecting agents, and biological additives. It contains information on physical properties, toxicity, heavy metal content, safety precautions, use conditions, etc

  18. Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

    Science.gov (United States)

    Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

    2017-03-01

    This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.

    Science.gov (United States)

    Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie

    2018-06-04

    Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.

  20. Hydrogen production by methane reforming based on micro-gap discharge

    International Nuclear Information System (INIS)

    Liu, N N; Wang, M X; Liu, K Y; Bai, M D

    2013-01-01

    Based on micro-gap strong ionization discharge, this paper presents a study of hydrogen production by methane reforming at room temperature and atmospheric pressure without catalyst. Influence rules of conversion of methane and production of hydrogen were studied by changing discharge power and feed gas flow rate. Results show that when the discharge power was about 341 W, the discharge gap was 0.47 mm and the flow rate of feed gas was 100 mL min −1 , the conversion of methane and yield of hydrogen reached optimization. The conversion rate of methane and the highest yield of hydrogen were 68.14 % and 51.34 %, respectively.

  1. Delayed rule following.

    Science.gov (United States)

    Schmitt, D R

    2001-01-01

    Although the elements of a fully stated rule (discriminative stimulus [S(D)], some behavior, and a consequence) can occur nearly contemporaneously with the statement of the rule, there is often a delay between the rule statement and the S(D). The effects of this delay on rule following have not been studied in behavior analysis, but they have been investigated in rule-like settings in the areas of prospective memory (remembering to do something in the future) and goal pursuit. Discriminative events for some behavior can be event based (a specific setting stimulus) or time based. The latter are more demanding with respect to intention following and show age-related deficits. Studies suggest that the specificity with which the components of a rule (termed intention) are stated has a substantial effect on intention following, with more detailed specifications increasing following. Reminders of an intention, too, are most effective when they refer specifically to both the behavior and its occasion. Covert review and written notes are two effective strategies for remembering everyday intentions, but people who use notes appear not to be able to switch quickly to covert review. By focusing on aspects of the setting and rule structure, research on prospective memory and goal pursuit expands the agenda for a more complete explanation of rule effects.

  2. Undulator-Based Production of Polarized Photons

    International Nuclear Information System (INIS)

    McDonald, Kirk

    2008-01-01

    'Project Title: Undulator-Based Production of Polarized Photons' DOE Contract Number: FG02-04ER41355 Principal Investigator: Prof. Kirk McDonald Period of Performance: 09/10/2004 thru 08/31/2006 This award was to fund Princeton's activity on SLAC experiment E166, 'Undulator-Based Production of Polarized Positrons' which was performed at SLAC during June and September 2005. Princeton U. fabricated a magnetic spectrometer for this experiment, and participated in the commissioning, operation, and analysis of the experiment, for which Prof. McDonald was a co-spokesperson. The experiment demonstrated that an intense positron beam with 80% longitudinal polarization could be generated by conversion of MeVenergy circularly polarized photons in a thin target, which photons were generated by passage of high-energy electrons through a helical undulator. This technique has since been adopted as the baseline for the polarized positron source of the proposed International Linear Collider. Results of the experiment have been published in Physical Review Letters, vol 100, p 210801 (2008) (see attached .pdf file), and a longer paper is in preparation.

  3. The impact of egocentric vs. allocentric agency attributions on the neural bases of reasoning about social rules.

    Science.gov (United States)

    Canessa, Nicola; Pantaleo, Giuseppe; Crespi, Chiara; Gorini, Alessandra; Cappa, Stefano F

    2014-09-18

    We used the "standard" and "switched" social contract versions of the Wason Selection-task to investigate the neural bases of human reasoning about social rules. Both these versions typically elicit the deontically correct answer, i.e. the proper identification of the violations of a conditional obligation. Only in the standard version of the task, however, this response corresponds to the logically correct one. We took advantage of this differential adherence to logical vs. deontical accuracy to test the different predictions of logic rule-based vs. visuospatial accounts of inferential abilities in 14 participants who solved the standard and switched versions of the Selection-task during functional-Magnetic-Resonance-Imaging. Both versions activated the well known left fronto-parietal network of deductive reasoning. The standard version additionally recruited the medial parietal and right inferior parietal cortex, previously associated with mental imagery and with the adoption of egocentric vs. allocentric spatial reference frames. These results suggest that visuospatial processes encoding one's own subjective experience in social interactions may support and shape the interpretation of deductive arguments and/or the resulting inferences, thus contributing to elicit content effects in human reasoning. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. Quality prediction modeling for multistage manufacturing based on classification and association rule mining

    OpenAIRE

    Kao Hung-An; Hsieh Yan-Shou; Chen Cheng-Hui; Lee Jay

    2017-01-01

    For manufacturing enterprises, product quality is a key factor to assess production capability and increase their core competence. To reduce external failure cost, many research and methodology have been introduced in order to improve process yield rate, such as TQC/TQM, Shewhart CycleDeming's 14 Points, etc. Nowadays, impressive progress has been made in process monitoring and industrial data analysis because of the Industry 4.0 trend. Industries start to utilize quality control (QC) methodo...

  5. Verification of business rules programs

    CERN Document Server

    Silva, Bruno Berstel-Da

    2013-01-01

    Rules represent a simplified means of programming, congruent with our understanding of human brain constructs. With the advent of business rules management systems, it has been possible to introduce rule-based programming to nonprogrammers, allowing them to map expert intent into code in applications such as fraud detection, financial transactions, healthcare, retail, and marketing. However, a remaining concern is the quality, safety, and reliability of the resulting programs.  This book is on business rules programs, that is, rule programs as handled in business rules management systems. Its

  6. An association rule mining-based framework for understanding lifestyle risk behaviors.

    Directory of Open Access Journals (Sweden)

    So Hyun Park

    Full Text Available OBJECTIVES: This study investigated the prevalence and patterns of lifestyle risk behaviors in Korean adults. METHODS: We utilized data from the Fourth Korea National Health and Nutrition Examination Survey for 14,833 adults (>20 years of age. We used association rule mining to analyze patterns of lifestyle risk behaviors by characterizing non-adherence to public health recommendations related to the Alameda 7 health behaviors. The study variables were current smoking, heavy drinking, physical inactivity, obesity, inadequate sleep, breakfast skipping, and frequent snacking. RESULTS: Approximately 72% of Korean adults exhibited two or more lifestyle risk behaviors. Among women, current smoking, obesity, and breakfast skipping were associated with inadequate sleep. Among men, breakfast skipping with additional risk behaviors such as physical inactivity, obesity, and inadequate sleep was associated with current smoking. Current smoking with additional risk behaviors such as inadequate sleep or breakfast skipping was associated with physical inactivity. CONCLUSION: Lifestyle risk behaviors are intercorrelated in Korea. Information on patterns of lifestyle risk behaviors could assist in planning interventions targeted at multiple behaviors simultaneously.

  7. Negation handling in sentiment classification using rule-based adapted from Indonesian language syntactic for Indonesian text in Twitter

    Science.gov (United States)

    Amalia, Rizkiana; Arif Bijaksana, Moch; Darmantoro, Dhinta

    2018-03-01

    The presence of the word negation is able to change the polarity of the text if it is not handled properly it will affect the performance of the sentiment classification. Negation words in Indonesian are ‘tidak’, ‘bukan’, ‘belum’ and ‘jangan’. Also, there is a conjunction word that able to reverse the actual values, as the word ‘tetapi’, or ‘tapi’. Unigram has shortcomings in dealing with the existence of negation because it treats negation word and the negated words as separate words. A general approach for negation handling in English text gives the tag ‘NEG_’ for following words after negation until the first punctuation. But this may gives the tag to un-negated, and this approach does not handle negation and conjunction in one sentences. The rule-based method to determine what words negated by adapting the rules of Indonesian language syntactic of negation to determine the scope of negation was proposed in this study. With adapting syntactic rules and tagging “NEG_” using SVM classifier with RBF kernel has better performance results than the other experiments. Considering the average F1-score value, the performance of this proposed method can be improved against baseline equal to 1.79% (baseline without negation handling) and 5% (baseline with existing negation handling) for a dataset that all tweets contain negation words. And also for the second dataset that has the various number of negation words in document tweet. It can be improved against baseline at 2.69% (without negation handling) and 3.17% (with existing negation handling).

  8. A rule-based expert system for control rod pattern of boiling water reactors by hovering around haling exposure shape

    International Nuclear Information System (INIS)

    Kao, P.-W.; Lin, L.-S.; Yang, J.-T.

    2004-01-01

    Feasible strategies for automatic BWR control rod pattern generation have been implemented in a rule-based expert system. These strategies are majorly based on a concept for which exposure distributions are hovering around the Haling exposure distribution through a cycle while radial and axial power distributions are dominantly controlled by some abstracted factors indicating the desired distributions. The system can either automatically generate expert-level control rod patterns or search for criteria-satisfied patterns originated from user's input. It has successfully been demonstrated by generating control rod patterns for the the 1775 MWth Chinshan plant in Unit I Cycle 13 alternate loading pattern and Unit 2 Cycle 8 but with longer cycle length. All rod patterns for two cycles result in all-rod-out at EOC and no violation against the four criteria. The demonstrations show that the system is considerably good in choosing initial trial rod patterns and adjusting rod patterns to satisfy the design criteria. (author)

  9. Commercial production of metal hafnium and hafnium-based products

    International Nuclear Information System (INIS)

    Negodin, D.A.; Shtutsa, M.G.; Akhtonov, S.G.; Il'enko, E.V.; Kobyzev, A.M.

    2012-01-01

    Hafnium possesses a unique complex of physical and chemical properties which allow the application of products on its basis in various industries. Joint Stock Company 'Chepetsky Mechanical Plant' is the single enterprise which produces hafnium on the territory of Russia. The manufacture of metal hafnium with the total content of zirconium and hafnium, at least, 99,8 % of weights is developed at the present time at Joint Stock Company CHMZ. The weight of melted hafnium ingots is up to 1 ton. Manufacture of wide range of products from hafnium is implemented. The plates from a hafnium with thickness of 0.60 mm which are used for emergency control cartridges of VVER-440 reactors are the most critical product. It is shown that ingots and products obtained from metal hafnium correspond to the Russian and international standards for reactor materials in chemical composition, mechanical and corrosion properties.

  10. Clinical classification in low back pain: best-evidence diagnostic rules based on systematic reviews.

    Science.gov (United States)

    Petersen, Tom; Laslett, Mark; Juhl, Carsten

    2017-05-12

    Clinical examination findings are used in primary care to give an initial diagnosis to patients with low back pain and related leg symptoms. The purpose of this study was to develop best evidence Clinical Diagnostic Rules (CDR] for the identification of the most common patho-anatomical disorders in the lumbar spine; i.e. intervertebral discs, sacroiliac joints, facet joints, bone, muscles, nerve roots, muscles, peripheral nerve tissue, and central nervous system sensitization. A sensitive electronic search strategy using MEDLINE, EMBASE and CINAHL databases was combined with hand searching and citation tracking to identify eligible studies. Criteria for inclusion were: persons with low back pain with or without related leg symptoms, history or physical examination findings suitable for use in primary care, comparison with acceptable reference standards, and statistical reporting permitting calculation of diagnostic value. Quality assessments were made independently by two reviewers using the Quality Assessment of Diagnostic Accuracy Studies tool. Clinical examination findings that were investigated by at least two studies were included and results that met our predefined threshold of positive likelihood ratio ≥ 2 or negative likelihood ratio ≤ 0.5 were considered for the CDR. Sixty-four studies satisfied our eligible criteria. We were able to construct promising CDRs for symptomatic intervertebral disc, sacroiliac joint, spondylolisthesis, disc herniation with nerve root involvement, and spinal stenosis. Single clinical test appear not to be as useful as clusters of tests that are more closely in line with clinical decision making. This is the first comprehensive systematic review of diagnostic accuracy studies that evaluate clinical examination findings for their ability to identify the most common patho-anatomical disorders in the lumbar spine. In some diagnostic categories we have sufficient evidence to recommend a CDR. In others, we have only

  11. Thermochemical hydrogen production based on magnetic fusion

    International Nuclear Information System (INIS)

    Krikorian, O.H.; Brown, L.C.

    1982-01-01

    Conceptual design studies have been carried out on an integrated fusion/chemical plant system using a Tandem Mirror Reactor fusion energy source to drive the General Atomic Sulfur-Iodine Water-Splitting Cycle and produce hydrogen as a future feedstock for synthetic fuels. Blanket design studies for the Tandem Mirror Reactor show that several design alternatives are available for providing heat at sufficiently high temperatures to drive the General Atomic Cycle. The concept of a Joule-boosted decomposer is introduced in one of the systems investigated to provide heat electrically for the highest temperature step in the cycle (the SO 3 decomposition step), and thus lower blanket design requirements and costs. Flowsheeting and conceptual process designs have been developed for a complete fusion-driven hydrogen plant, and the information has been used to develop a plot plan for the plant and to estimate hydrogen production costs. Both public and private utility financing approaches have been used to obtain hydrogen production costs of $12-14/GJ based on July 1980 dollars

  12. The songbird as a percussionist: syntactic rules for non-vocal sound and song production in Java sparrows.

    Directory of Open Access Journals (Sweden)

    Masayo Soma

    Full Text Available Music and dance are two remarkable human characteristics that are closely related. Communication through integrated vocal and motional signals is also common in the courtship displays of birds. The contribution of songbird studies to our understanding of vocal learning has already shed some light on the cognitive underpinnings of musical ability. Moreover, recent pioneering research has begun to show how animals can synchronize their behaviors with external stimuli, like metronome beats. However, few studies have applied such perspectives to unraveling how animals can integrate multimodal communicative signals that have natural functions. Additionally, studies have rarely asked how well these behaviors are learned. With this in mind, here we cast a spotlight on an unusual animal behavior: non-vocal sound production associated with singing in the Java sparrow (Lonchura oryzivora, a songbird. We show that male Java sparrows coordinate their bill-click sounds with the syntax of their song-note sequences, similar to percussionists. Analysis showed that they produced clicks frequently toward the beginning of songs and before/after specific song notes. We also show that bill-clicking patterns are similar between social fathers and their sons, suggesting that these behaviors might be learned from models or linked to learning-based vocalizations. Individuals untutored by conspecifics also exhibited stereotypical bill-clicking patterns in relation to song-note sequence, indicating that while the production of bill clicking itself is intrinsic, its syncopation appears to develop with songs. This paints an intriguing picture in which non-vocal sounds are integrated with vocal courtship signals in a songbird, a model that we expect will contribute to the further understanding of multimodal communication.

  13. Consistence of Network Filtering Rules

    Institute of Scientific and Technical Information of China (English)

    SHE Kun; WU Yuancheng; HUANG Juncai; ZHOU Mingtian

    2004-01-01

    The inconsistence of firewall/VPN(Virtual Private Network) rule makes a huge maintainable cost.With development of Multinational Company,SOHO office,E-government the number of firewalls/VPN will increase rapidly.Rule table in stand-alone or network will be increased in geometric series accordingly.Checking the consistence of rule table manually is inadequate.A formal approach can define semantic consistence,make a theoretic foundation of intelligent management about rule tables.In this paper,a kind of formalization of host rules and network ones for auto rule-validation based on SET theory were proporsed and a rule validation scheme was defined.The analysis results show the superior performance of the methods and demonstrate its potential for the intelligent management based on rule tables.

  14. An Association Rule Based Method to Integrate Metro-Public Bicycle Smart Card Data for Trip Chain Analysis

    Directory of Open Access Journals (Sweden)

    De Zhao

    2018-01-01

    Full Text Available Smart card data provide valuable insights and massive samples for enhancing the understanding of transfer behavior between metro and public bicycle. However, smart cards for metro and public bicycle are often issued and managed by independent companies and this results in the same commuter having different identity tags in the metro and public bicycle smart card systems. The primary objective of this study is to develop a data fusion methodology for matching metro and public bicycle smart cards for the same commuter using historical smart card data. A novel method with association rules to match the data derived from the two systems is proposed and validation was performed. The results showed that our proposed method successfully matched 573 pairs of smart cards with an accuracy of 100%. We also validated the association rules method through visualization of individual metro and public bicycle trips. Based on the matched cards, interesting findings of metro-bicycle transfer have been derived, including the spatial pattern of the public bicycle as first/last mile solution as well as the duration of a metro trip chain.

  15. A tweaking principle for executive control: neuronal circuit mechanism for rule-based task switching and conflict resolution.

    Science.gov (United States)

    Ardid, Salva; Wang, Xiao-Jing

    2013-12-11

    A hallmark of executive control is the brain's agility to shift between different tasks depending on the behavioral rule currently in play. In this work, we propose a "tweaking hypothesis" for task switching: a weak rule signal provides a small bias that is dramatically amplified by reverberating attractor dynamics in neural circuits for stimulus categorization and action selection, leading to an all-or-none reconfiguration of sensory-motor mapping. Based on this principle, we developed a biologically realistic model with multiple modules for task switching. We found that the model quantitatively accounts for complex task switching behavior: switch cost, congruency effect, and task-response interaction; as well as monkey's single-neuron activity associated with task switching. The model yields several testable predictions, in particular, that category-selective neurons play a key role in resolving sensory-motor conflict. This work represents a neural circuit model for task switching and sheds insights in the brain mechanism of a fundamental cognitive capability.

  16. Fuzzy rule-based modelling for human health risk from naturally occurring radioactive materials in produced water

    International Nuclear Information System (INIS)

    Shakhawat, Chowdhury; Tahir, Husain; Neil, Bose

    2006-01-01

    Produced water, discharged from offshore oil and gas operations, contains chemicals from formation water, condensed water, and any chemical added down hole or during the oil/water separation process. Although, most of the contaminants fall below the detection limits within a short distance from the discharge port, a few of the remaining contaminants including naturally occurring radioactive materials (NORM) are of concern due to their bioavailability in the media and bioaccumulation characteristics in finfish and shellfish species used for human consumption. In the past, several initiatives have been taken to model human health risk from NORM in produced water. The parameters of the available risk assessment models are imprecise and sparse in nature. In this study, a fuzzy possibilistic evaluation using fuzzy rule based modeling has been presented. Being conservative in nature, the possibilistic approach considers possible input parameter values; thus provides better environmental prediction than the Monte Carlo (MC) calculation. The uncertainties of the input parameters were captured with fuzzy triangular membership functions (TFNs). Fuzzy if-then rules were applied for input concentrations of two isotopes of radium, namely 226 Ra, and 228 Ra, available in produced water and bulk dilution to evaluate the radium concentration in fish tissue used for human consumption. The bulk dilution was predicted using four input parameters: produced water discharge rate, ambient seawater velocity, depth of discharge port and density gradient. The evaluated cancer risk shows compliance with the regulatory guidelines; thus minimum risk to human health is expected from NORM components in produced water

  17. Proof Rules for Recursive Procedures

    NARCIS (Netherlands)

    Hesselink, Wim H.

    1993-01-01

    Four proof rules for recursive procedures in a Pascal-like language are presented. The main rule deals with total correctness and is based on results of Gries and Martin. The rule is easier to apply than Martin's. It is introduced as an extension of a specification format for Pascal-procedures, with

  18. Endogeneously arising network allocation rules

    NARCIS (Netherlands)

    Slikker, M.

    2006-01-01

    In this paper we study endogenously arising network allocation rules. We focus on three allocation rules: the Myerson value, the position value and the component-wise egalitarian solution. For any of these three rules we provide a characterization based on component efficiency and some balanced

  19. Developing situation-aware applications for disaster management with a distributed rule-based platform

    NARCIS (Netherlands)

    Moreira, João; Moreira, Joao; Ferreira Pires, Luis; van Sinderen, Marten J.; Dockhorn Costa, P.

    2015-01-01

    In order to enhance interoperability and productivity in the develop-ment of situation-aware applications for disaster management, proper mecha-nisms and guidelines are required. They must address the lack of semantics in modelling emergency situations. In addition, the ever changing and

  20. A study on the optimal fuel loading pattern design in pressurized water reactor using the artificial neural network and the fuzzy rule based system

    International Nuclear Information System (INIS)

    Kim, Han Gon; Chang, Soon Heung; Lee, Byung

    2004-01-01

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. In this paper, an optimal loading pattern is defined that the local power peaking factor is lower than predetermined value during one cycle and the effective multiplication factor is maximized in order to extract maximum energy. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (author)