The current paradigm of modelling uncertainty in expert systems knowledge bases using Certainty Factors (CF) has been critically evaluated. A way to circumvent the awkwardness, non-intuitiveness and constraints encountered while using CF has been proposed. It is based on introducing Data Marks for askable conditions and Data Marks for conclusions of relational models, followed by choosing the best suited way to propagate those Data Marks into Data Marks of rule conclusions. This is done in a way orthogonal to the inference using Aristotelian Logic. Using Data Marks instead of Certainty Factors removes thus the intellectual discomfort caused by rejecting the notion of truth, falsehood and the Aristotelian law of excluded middle, as is done when using the CF methodology. There is also no need for changing the inference system software (expert system shell): the Data Marks approach can be implemented by simply modifying the knowledge base that should accommodate them. The methodology of using Data Marks to model uncertainty in knowledge bases has been illustrated by an example of SWOT analysis of a small electronic company. A short summary of SWOT analysis has been presented. The basic data used for SWOT analysis of the company are discussed. The rmes_EE SWOT knowledge base consisting of a rule base and model base have been presented and explained. The results of forward chaining for this knowledge base have been presented and critically evaluated.
A new approach to solving realistic car assembly scheduling problems for mixed model assembly line is presented. It is proposed to decompose the problem into two subproblems: 1) a sequencing problem that generates admissible car sequences fulfilling capacity constraints for all car models in the production plan, 2) a scheduling problem that determines an admissible car sequence with shortest makespan. The details of this approach are illustrated by a simple numerical example.
A Constraint Logic Programming (CLP) tool for solving the problem discussed in Part 1 of the paper has been designed. It is outlined and discussed in the paper. The program has been used for solving a real-world car assembly scheduling problem.
Istotą zaproponowanej modyfikacji jest wprowadzenie dwóch rodzajów wielokrotnych reguł o tych samych wnioskach: reguł kumulatywnych i reguł dysjunktywnych. Reguły kumulatywne mają niezależne listy warunków i wypadkowy współczynnik pewności wniosku jest wyznaczany jako kumulacja współczynników pewności wniosków poszczególnych reguł. Reguły dysjunktywne mają zależne listy warunków i tylko jedna z tych reguł określa wypadkowy współczynnik pewności wniosku.
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The modification consists of distinguishing two kind of multiple rules with the same conclusion: cumulative rules and disjunctive rules. Cumulative rules have independent lists of conditions and the overall certainty factor of their common conclusion is determined as a cumulation of certainty factors of the conclusions of all rules. Disjunctive rules have dependent lists of conditions and only one of them is determining the overall certainty factor of their common conclusion.
The design assumptions and principles of two hybrid, rule-and model-based expert system shells for uncertain backward and forward reasoning are presented. The systems may be used to reason with any knowledge base, which consist of an uncertain rule base, partially uncertain model base, exact constraint base, uncertain constraint base and advice base together with advice files. Its semantics is simple and straightforward. Practically unlimited nesting of rules and models is allowed. The systems are equipped with diagnostic facilities automatically checking the rule- and constraint bases for inconsistencies and redundancies and providing warnings and detailed diagnostic messages.
The paper discusses a new trend in the modelling software for combinatorial and mixed combinatorial-continuous decision problems. The trend, aiming at solving those problems by the simple activity of properly describing them, is best exemplified by a constantly inereasing spectrum of Constraint Logic Programming (CLP) languages. The first such language was Prolog. After a short historical survey concentrating mainly on Prolog, main characteristics of a modern, commercially successful CLP language - CHIP - are presented, discussed and illustrated. The CLP approach to problem solving is compared with traditional Operation Research approaches.
W pracy przedstawiono podstawy teoretyczne metody szyfrowania danych z wykorzystaniem wielosinusoidalnych sygnałów losowych. Ideą proponowanej metody jest wykorzystanie kolejnych znaków tekstu do generowania losowych faz sygnałów wielosinusoidalnych. Wygenerowane fazy oraz wybrane ampiltudy poszczególnych składowych sinusoidalnych pozwalają na skonstruowanie widma sygnału wielosinusoidalnego, które jest transformowane do dziedziny czasu za pomocą algorytmu szybkiego przekształcenia Fouriera dając w wyniku zaszyfrowany tekst w postaci wielosinusoidalnego sygnału losowego. Metoda jest zilustrowana przykładem.
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The paper presents theoretical foundations of an encryption method based on multisine randm time-series. Its main idea is to the use consecutive characters of the plaintext to generate random phase shifts for all sine components of the multisine random time-series. These random phase shifts together with chosen amplitudes are used to construct the discrete Fourier transform of the corresponding multisine random timr-series. The obtained spectrum is transformed into the time domain by using any fast Fourier transform algorithm resulting in the encrypted plaintext of the form a multisine random time series. The method is illustrated by an example.
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A new data encryption method based on N-lag white multisine random time-series (WMRTS) is presented. Its essence is that consecutive characters of the cIeartext are used to generate phase shifts for all or for some of the sine components of an N-lag WMRTS. This time-series is defined in the frequency domain by its Discrete Fourier Transform (DFT). It consists of two spectra: the phase-shift spectrum containing encrypted characters and the amplitude spectrum with the same amplitude for all frequencies. This DFT is calculated with the help of the Fast Fourier Transform (FFT) algorithm transformed into the time domain. The result is the cyphertext in the form of an N-lag WMRTS. To decrypt the cyphertext, it is processed by the FFT algorithm, the result being the original DFT, from which all phase shifts are recovered. The paper presents theoretical foundations of the method and a numerical example demonstrating its effectiveness.
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