Very true operators in effect algebras

We introduce the concept of very true operator on an effect algebra. Although an effect algebra is only partial, we define it in the way which is in accordance with traditional definitions in residuated lattices or basic algebras. This is possible if we require monotonicity as an additional condition. We prove that very true operators on effect algebras can be characterized by means of certain subsets which are conditionally complete.     

A case of using the Semantic Interoperability Framework for custom orthopedic implants manufacturing

The efficiency and effectiveness of the daily practice in orthopedic surgery depend on the availability, interoperability and unique access to a wide set of information, related to the patient’s medical record and diagnosis, domain knowledge and available resources and staff. The most important of the tangible resources, needed for the therapeutic or preventive actions are orthopedic implants. In some cases, the implants may be highly complex and customized products, which need to be manufactured (assembled) on basis of the above information in a shortest possible timeframe. In this paper, the case of the custom orthopedic implants manufacturing is described from the perspective of the collaborative enterprising, with special consideration of the interoperability issues of the involved enterprise collaboration. It is shown how the previously developed Semantic Interoperability Framework can be used to improve the efficiency of the manufacturing and other relevant processes.     

Adaptive output-feedback stabilization of non-local hyperbolic PDEs

We address the problem of adaptive output-feedback stabilization of general first-order hyperbolic partial integro-differential equations (PIDE). Such systems are also referred to as PDEs with non-local (in space) terms. We apply control at one boundary, take measurements on the other boundary, and allow the system’s functional coefficients to be unknown. To deal with the absence of both full-state measurement and parameter knowledge, we introduce a pre-transformation (which happens to be based on backstepping) of the system into an observer canonical form. In that form, the problem of adaptive observer design becomes tractable. Both the parameter estimator and the control law employ only the input and output signals (and their histories over one unit of time). Prior to presenting the adaptive design, we present the non-adaptive/baseline controller, which is novel in its own right and facilitates the understanding of the more complex, adaptive system. The parameter estimator is of the gradient type, based on a parametric model in the form of an integral equation relating delayed values of the input and output. For the closed-loop system we establish boundedness of all signals, pointwise in space and time, and convergence of the PDE state to zero pointwise in space. We illustrate our result with a simulation.     

Predicting Missing Items in Shopping Carts

Existing research in association mining has focused mainly on how to expedite the search for frequently co-occurring groups of items in “shopping cart” type of transactions; less attention has been paid to methods that exploit these “frequent itemsets” for prediction purposes. This paper contributes to the latter task by proposing a technique that uses partial information about the contents of a shopping cart for the prediction of what else the customer is likely to buy. Using the recently proposed data structure of itemset trees (IT-trees), we obtain, in a computationally efficient manner, all rules whose antecedents contain at least one item from the incomplete shopping cart. Then, we combine these rules by uncertainty processing techniques, including the classical Bayesian decision theory and a new algorithm based on the Dempster-Shafer (DS) theory of evidence combination.     

The effect of hydrodynamic conditions on the detection of aqueous solutions of toluene by means of an inverted graded-index fiber

This paper deals with the effect of hydrodynamic conditions on the detection of toluene dissolved in water by means of fibers with a truncated parabolic inverted-graded index (IGI) profile. The detection is based on refractive-index changes of a detection layer of polydimethylsiloxane (PDMS) applied on the fiber which are induced by penetration of toluene into the layer. The dependence of the response of the sensing fiber placed in a flow cell on the flow velocity of the detected aqueous solution of toluene has been investigated. The sensing fiber was successively exposed to flows of distilled water and aqueous solutions of toluene. The fiber responses were measured for three chosen concentrations of the toluene solutions and for five flow velocities of the solutions. From these results the dependence of the relative decrease of the output signal on the flow velocity was determined. It has been found that the magnitude of output signal changes is approximately proportional to the solution concentration and the rate of the signal changes in the tested concentration range depends approximately linearly on the solution flow velocity.     

Application of predictive control methods for Radio telescope disk rotation control

Radio telescope (RT) installations are highly valuable assets and during the period of their service life they need regular repair and maintenance to be carried out for delivering satisfactory performance and minimizing downtime. Same down time can be expected during machinery usage. Constant control of telescope rotation angle is done manually using visual inspection of hardware. The accuracy of this procedure is very low, therefore, automation and computer control systems are required. With the growing automation technologies, predictive control can prove to be a better approach than the traditionally applied visual inspection policy and linear control models. In this paper, Irbene Radio telescope RT-16 disk rotation control motors are analysed using control voltage from the converters. Retrieved data from the small DC motor is used for the predictive control approach using two different methods: a neural network trained with Basic Levenberg-Marquardt method and a linear model. A multilayer perceptron network approach is used for prediction of the indicator voltage output which affects the monitoring of the disk rotating angle. Finally, an experimental control system was proposed and installed using National Instruments equipment.     

NICE h : a higher-order explicit numerical scheme for integration of constitutive models in plasticity

The article introduces, as a result of further development of the first-order scheme NICE, a simple and efficient higher-order explicit numerical scheme for the integration of a system of ordinary differential equations which is constrained by an algebraic condition (DAE). The scheme is based on the truncated Taylor expansion of the constraint equation with order h of the scheme being determined by the highest exponent in the truncated Taylor series. The integration scheme thus conceived will be named NICE ^h , considering both principal premises of its construction. In conjunction with a direct solution technique used to solve the boundary value problem, the NICE ^h scheme is very convenient for integrating constitutive models in plasticity. The plasticity models are defined mostly by a system of algebraic and differential equations in which the yield criterion represents the constraint condition. To study the properties of the new integration scheme, which, like the forward-Euler scheme, is characterised by its implementation simplicity due to the explicitness of its formulations, a damage constitutive model (Gurson–Tvergaard–Needleman model) is considered. The general opinion that the implicit backward-Euler scheme is much more accurate than the thus-far known explicit schemes is challenged by the introduction of the NICE ^h scheme. The accuracy of the higher-order explicit scheme in the studied cases is significantly higher than the accuracy of the classical backward-Euler scheme, if we compare them under the condition of a similar CPU time consumption.     

A new method for computing fuzzy functional dependencies in relational database systems

In this paper, we present a new method for computing fuzzy functional dependencies between attributes in fuzzy relational database systems. The method is based on the use of fuzzy implications. A literature analysis has shown that there is no algorithm that would enable the identification of attribute relationships in fuzzy relational schemas. This fact was the motive for development a new methodology in the analysis of fuzzy functional dependencies over a given set of attributes. Solving this, not so new problem, is not only research challenge having theoretical importance, but it also has practical significance. Possible applications of the proposed methodology include GIS, data mining, information retrieval, reducing data redundancy in fuzzy relations through implementation of logical database model, estimation of missing values etc.