1,172,402 research outputs found

    Method for Detecting Anomalous States of a Control Object in Information Systems Based on the Analysis of Temporal Data and Knowledge

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    The problem of finding the anomalous states of the control object in the management information system under conditions of uncertainty caused by the incompleteness of knowledge about this object is considered. The method of classifying the current state of the control object in real time, allowing to identify the current anomalous state. The method uses temporal data and knowledge. Data is represented by sequences of events with timestamps. Knowledge is represented as weighted temporal rules and constraints. The method includes the following key phases: the formation of sequences of logical facts; selection of temporal rules and constraints; classification based on a comparison of rules and constraints. Logical facts are represented as predicates on event attributes and reflect the state of the control object. Logical rules define valid sequences of logical facts. Performing a classification by successive comparisons of constraints and weights of the rules makes it possible to more effectively identify the anomalous state since the comparison of the constraints reduces the subset of facts comparing to the current state. The method creates conditions for improving management efficiency in the context of incomplete information on the state of a complex object by using logical inference in knowledge bases for anomalous states of such control objects

    METHOD OF DETERMINING WEIGHTS OF TEMPORAL RULES IN MARKOV LOGIC NETWORK FOR BUILDING KNOWLEDGE BASE IN INFORMATION CONTROL SYSTEMS

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    The problem of constructing and expanding the temporal knowledge base for the information-control system is considered. This knowledge base is formally represented by the Markov logic network. It is shown that the behavior of the control object of a given class can be reflected in the form of a set of weighted temporal rules. These rules are formed on the basis of identifying links between events that reflect known variants of the behavior of the control object. A method is proposed for calculating the weights of temporal rules in a Markov logic network for a given level of detail of the control object. The level of detail is determined by the context for executing the sequences of control actions and for weighted temporal rules is specified by selecting subsets of the event attributes. The method includes such basic phases: preparation of a subset of temporal rules for a given level of detail; finding the weights of the rules taking into account the a priori probabilities of the event traces. The method creates conditions for supporting management decisions in information management systems at various levels of detail of complex management objects. Decision support is provided by predicting the probability of success in executing a sequence of actions that implement the management function in the current situation. These probabilities are determined using the weights of the temporal rules

    METHOD FOR DETECTING ANOMALOUS STATES OF A CONTROL OBJECT IN INFORMATION SYSTEMS BASED ON THE ANALYSIS OF TEMPORAL DATA AND KNOWLEDGE

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    The problem of finding the anomalous states of the control object in the management information system under conditions of uncertainty caused by the incompleteness of knowledge about this object is considered. The method of classifying the current state of the control object in real time, allowing to identify the current anomalous state. The method uses temporal data and knowledge. Data is represented by sequences of events with timestamps. Knowledge is represented as weighted temporal rules and constraints. The method includes the following key phases: the formation of sequences of logical facts; selection of temporal rules and constraints; classification based on a comparison of rules and constraints. Logical facts are represented as predicates on event attributes and reflect the state of the control object. Logical rules define valid sequences of logical facts. Performing a classification by successive comparisons of constraints and weights of the rules makes it possible to more effectively identify the anomalous state since the comparison of the constraints reduces the subset of facts comparing to the current state. The method creates conditions for improving management efficiency in the context of incomplete information on the state of a complex object by using logical inference in knowledge bases for anomalous states of such control objects

    EFFECT OF INTERNAL CONTROL EFFECTIVENESS, COMPENSATION SYSTEM, INFORMATION ASYMMETRY AND ACCOUNTING RULES, ACCOUNTING MORALITY TO JENDING ACCOUNTING TENDENCY OF ACCOUNTING SHORT BEHAVIOR WITH ENTERVENING VARIABLES (Empirical Study at Adventist Schools in

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    The purpose of this research to study the effect of the effectiveness of internal control, compensation systems, information asymmetry and compliance with accounting rules with unethical behavior towards fraudulent accounting trends. This study is to examine the extent to which the influence of the effectiveness of internal control and unethical behavior on accounting fraud tendencies. This research was conducted on the population of Adventist Schools in Jakarta with Random Sampling in 15 schools and 5 respondents from each sample. The method used by the Structural Equation Model (SEM) approach uses Partial Least Square (PLS) software. The results of the study show: there is a significant and positive influence; The effectiveness of internal control on unethical behavior, the effectiveness of internal control on Accounting Fraud Trends, Compensation System for Unethical Behavior, Compensation System for Accounting Fraud Trends, Information Asymmetry for Unethical Behavior, Compliance with Accounting Rules for Unethical Behavior, Management Morality against Behavior is not Ethical, Management Morality towards Accounting Fraud Trends, Unethical Behavior towards Accounting Fraud Trends, but Information Asymmetry on Accounting Fraud Trends, and Obedience of Accounting Rules to Accounting Fraud Trends has a positive but insignificant effect From the results of these studies, the authors make all positive influences. However, there are two insignificant hypotheses, namely the influence of information asymmetry on accounting fraud and compliance with accounting rules for accounting fraud tendencies. And the relationship between variables is very good for improving internal control in preventing accounting fraud tendencies

    The composite load spectra project

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    Probabilistic methods and generic load models capable of simulating the load spectra that are induced in space propulsion system components are being developed. Four engine component types (the transfer ducts, the turbine blades, the liquid oxygen posts and the turbopump oxidizer discharge duct) were selected as representative hardware examples. The composite load spectra that simulate the probabilistic loads for these components are typically used as the input loads for a probabilistic structural analysis. The knowledge-based system approach used for the composite load spectra project provides an ideal environment for incremental development. The intelligent database paradigm employed in developing the expert system provides a smooth coupling between the numerical processing and the symbolic (information) processing. Large volumes of engine load information and engineering data are stored in database format and managed by a database management system. Numerical procedures for probabilistic load simulation and database management functions are controlled by rule modules. Rules were hard-wired as decision trees into rule modules to perform process control tasks. There are modules to retrieve load information and models. There are modules to select loads and models to carry out quick load calculations or make an input file for full duty-cycle time dependent load simulation. The composite load spectra load expert system implemented today is capable of performing intelligent rocket engine load spectra simulation. Further development of the expert system will provide tutorial capability for users to learn from it

    Distributed traffic signal control using fuzzy logic

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    We present a distributed approach to traffic signal control, where the signal timing parameters at a given intersection are adjusted as functions of the local traffic condition and of the signal timing parameters at adjacent intersections. Thus, the signal timing parameters evolve dynamically using only local information to improve traffic flow. This distributed approach provides for a fault-tolerant, highly responsive traffic management system. The signal timing at an intersection is defined by three parameters: cycle time, phase split, and offset. We use fuzzy decision rules to adjust these three parameters based only on local information. The amount of change in the timing parameters during each cycle is limited to a small fraction of the current parameters to ensure smooth transition. We show the effectiveness of this method through simulation of the traffic flow in a network of controlled intersections

    Comprehensive Life Cycle Support for Access Rules in Information Systems: The CEOSIS Project

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    The definition and management of access rules (e.g., to control access to business documents and business functions) is a fundamental task in any enterprise information system (EIS). While there exists considerable work on how to specify and represent access rules, only little research has been spent on access rule changes. Examples include the evolution of organizational models with need for subsequent adaptation of related access rules as well as direct access rule modifications (e.g., to state a previously defined rule more precisely). This paper presents a comprehensive change framework for the controlled evolution of role-based access rules in EIS. First, we consider changes of organizational models and elaborate how they affect existing access rules. Second, we define change operations which enable direct adaptations of access rules. In the latter context, we define the formal semantics of access rule changes based on operator trees. Particularly, this enables their unambiguous application; i.e., we can precisely determine which effects are caused by respective rule changes. This is important, for example, to be able to efficiently and correctly adapt user worklists in process-aware information systems. Altogether this paper contributes to comprehensive life cycle support for access rules in (adaptive) EIS

    Ontology for Call Control

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    An ontology provides a common vocabulary through which to share information in a particular area of knowledge, including the key terms, their semantic interconnections and certain rules of inference. Using OWL (The Web Ontology Language), an ontology has been developed describing the domain of (Internet) call control. In particular, the ontology focuses on the use of call control in conjunction with its application within the ACCENT policy-based management system. The structure of the ontology builds heavily on previously developed ontologies genpol [4] and wizpol [20]. These describe generic aspects of the system, including the core policy description language on which it is based. This report presents a technical overview of the ontology for (Internet) call control, illustrated by way of graphical depictions of OWL class and property implementation

    Policy-Based Management Natural Language Parser

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    The Policy-Based Management Natural Language Parser (PBEM) is a rules-based approach to enterprise management that can be used to automate certain management tasks. This parser simplifies the management of a given endeavor by establishing policies to deal with situations that are likely to occur. Policies are operating rules that can be referred to as a means of maintaining order, security, consistency, or other ways of successfully furthering a goal or mission. PBEM provides a way of managing configuration of network elements, applications, and processes via a set of high-level rules or business policies rather than managing individual elements, thus switching the control to a higher level. This software allows unique management rules (or commands) to be specified and applied to a cross-section of the Global Information Grid (GIG). This software embodies a parser that is capable of recognizing and understanding conversational English. Because all possible dialect variants cannot be anticipated, a unique capability was developed that parses passed on conversation intent rather than the exact way the words are used. This software can increase productivity by enabling a user to converse with the system in conversational English to define network policies. PBEM can be used in both manned and unmanned science-gathering programs. Because policy statements can be domain-independent, this software can be applied equally to a wide variety of applications
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