The problem of video monitoring of laboratory rodents by the means of object-oriented logic programming is considered. The videos are produced in neurophysiological experiments on the study of convulsive electrical ac...
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ISBN:
(纸本)9781538642832
The problem of video monitoring of laboratory rodents by the means of object-oriented logic programming is considered. The videos are produced in neurophysiological experiments on the study of convulsive electrical activity of the brain cortex. Videos of behaviour of laboratory rats were recorded simultaneously with electroencephalograms (EEG) in the animals. A comparison of EEG data with the behaviour of the animals is necessary because sharp motions of the animals can result in EEG signals that are very similar to the epileptic discharges. Thus, the first task of the video monitoring is recognition of the sharp motions of the animals and using this information for proper interpretation of the results of the experiments. The second task of the video monitoring is analysis of behaviour of animals in cognitive testing. Essential feature of the video records is in that the experiments are conducted in the same cage where the animal lives, that is, the background of the cage is sawdust. The colour of the animals is about the same as the colour of the sawdust;thus the detection of the animals is not a simple task. In the paper, development of low-level algorithms for video analysis as well as logical methods for the analysis of the animal behaviour is discussed. The methods and algorithms are implemented in the Actor Prolog object-orientedlogic language.
This paper presents the declarative extension of the deductive database system LOLA to the object-oriented deductive database system OI-LOLA. The model used for O!-LOLA is "objects as theories", extended by ...
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This paper presents the declarative extension of the deductive database system LOLA to the object-oriented deductive database system OI-LOLA. The model used for O!-LOLA is "objects as theories", extended by state evolution. O!-LOLA combines logicprogramming and OO programming in two different ways: First, methods are implemented as logic programs. These methods can be inherited, encapsulated and overloaded. Second, logic programs can be defined over classes, meta-classes, instances, attributes and values. Dynamic updates of attributes of objects and dynamic instantiations of classes are supported. O!-LOLA is implemented as a preprocessor. O!-LOLA programs are transformed into LOLA rules and facts, which are evaluated set-oriented and bottom-up, using fixpoint semantics. Some object-oriented features concerning dynamic aspects are handled via built-in predicates in LOLA. We describe the applied theory, the system and the preprocessor, including an example of how methods are translated and we discuss dynamic updates of objects in O!-LOLA. The benefits of our system in contrast to others are: a single integrated language, clear semantics and a set-oriented evaluation. O!-LOLA uses fixpoint semantics (not any procedural semantics like other systems) and still evaluates set-oriented (and not in a mixed manner like other systems). Thus, we can fully use all optimization techniques developed for deductive databases and gain a very efficient system.
Critical infrastructures must be able to mitigate, at run-time, suspected ongoing cyberattacks that have eluded preventive security measures. To tackle this issue, we first propose an autonomic computing architecture ...
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ISBN:
(纸本)9783031020674;9783031020667
Critical infrastructures must be able to mitigate, at run-time, suspected ongoing cyberattacks that have eluded preventive security measures. To tackle this issue, we first propose an autonomic computing architecture for a Cyber-Security Incident Response Team Intelligent Decision Support System (CSIRT-IDSS) with a precise set of technologies for each of its components. We then zoom in on the component responsible for proposing to the CSIRT, automatically ranked sets of runtime actions to mitigate suspected ongoing cyber-attacks. We formalize its task as a Constraint Optimization Problem (COP). We then propose to implement it by a Constraint object-orientedlogic Program (COOLP) deployed as a containerized web service through the integration of three orthogonal extensions of logicprogramming (LP): Web Service oriented LP (WSOLP), Constraint LP (CLP) and object-oriented LP (OOLP). This integration supports seamlessly reusing platform and task independent cybersecurity ontological knowledge to dynamically build a mitigation action search COP that is customized to an input suspected cyberattack action set. This customization then allows the COP, to be solved by a generic CLP engine efficiently enough to propose mitigation actions to the CSIRT team while they can still be effective. To validate this approach, we implemented a prototype called CARMAS (Cyber Attack Runtime Mitigation Action Search) and ran scalability tests on simulated attacks with various COP construction strategies.
We propose Concurrent Transaction Frame logic (CTFL) as a language to provide formal semantics to UML activity and class diagrams. CTFL extends first-order Horn logic with object-oriented class hierarchy and object de...
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We propose Concurrent Transaction Frame logic (CTFL) as a language to provide formal semantics to UML activity and class diagrams. CTFL extends first-order Horn logic with object-oriented class hierarchy and object definition terms, and with five new logical connectives that declaratively capture temporal and concurrency constraints on updates and transactions. CTFL has coinciding, sound and refutation complete proof and model theories. CTFL allows using a single language to (1) formally describe the semantics of both activity and class diagrams, (2) verify UML models based on these two diagrams using theorem proving and (3) implement the model as an executable, object-orientedlogic program.
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