Modeling tool wear in end-milling using enhanced GMDH learning networks

This paper presents an enhanced approach to predictive modeling for determining tool-wear in end-milling operations based on enhanced-group method of data handling (e-GMDH). Using milling input parameters (speed, feed, and depth-of-cut) and response (tool wear), the data for the model is partitioned into training and testing datasets, and the training dataset is used to realize a predictive model that is a function of the input parameters and the coefficients determined. In our approach, we first present a methodology for modeling, and then develop predictive model(s) of the problem being solved in the form of second-order equations based on the input data and coefficients realized. This approach leads to some generalization because it becomes possible to predict not only the test data obtained during experimentation, but other test data outside the experimental results can also be used. Moreover, this approach makes it easy to present the realized solution in a form that can be further optimized for the input parameters using some optimization techniques. The results realized using our e-GMDH method are promising, and the comparative study presented shows that the e-GMDH outperforms polynomial neural network (PNN); moreover, it is more flexible than the conventional GMDH, which tends to produce nonlinear solutions even for simple problems. In the investigation, the extended particle swarm optimization (PSO) technique was applied to obtain the optimal parameters. Consequently, the modeling approach is extremely useful in realizing a computer-aided process-planning system in an advanced manufacturing environment.     

Hemorrhagic fever with renal syndrome

The authors describe the illness of a Czech soldier who while serving in the UNPROFOR forces in an area with the endemic occurrence of hantaviruses became infected with this agent and developed haemorrhagic fever with renal syndrome. The severe clinical course which called for seven haemodialyzation procedures led to the patient's recovery. The authors describe the course of the disease and epidemiological circumstances.     

Rotating magnetic field-driven flows in conductive inhomogeneous media: Part I—Numerical study

This paper presents a numerical study of the Lorentz force and fluid flow induced by a rotating magnetic field in a medium with a nonhomogeneous electric conductivity placed in a cylindrical vessel with insulated walls. The nonhomogeneity is modeled by the presence of a solid and a liquid phase of different electrical conductivity. The solid phase is located orthogonally to the axis of rotation, which corresponds to the case of unidirectional solidification. The simulations were performed for different locations of the solid front and different ratios of the electrical conductivity, σ _s /σ _l =0.2... 10. Here σ _s and σ _l are the electric conductivity of the solid and liquid phases, respectively. The results showed that the difference between electrical conductivity of solid and liquid phases has a noticeable effect on the mean-time Lorentz force and the velocity: namely, the presence of the solid phase (σ _s >σ _l ) leads to an increase of the Lorentz force and fluid flow in the cylinder.     

Stoichiometric dye-binding procedure for the determination of the reactive lysine content of soya bean protein

A new analytical method has been developed for the determination of the reactive lysine content of soya bean protein. The method is based on the reaction of the free basic groups of the protein with 1-phenylazo-2 naphthol-6,8 disulphonic acid. With regard to the stoichiometry of the procedure, it has been proved, contrary to earlier reports, that the basic amino acids, histidine, arginine and lysine, each combine with one mole of the dye. After acylation with propionic anhydride lysine alone loses its dye reactivity. The usefulness of the proposed method has been demonstrated by the determination of the reactive lysine content of several untreated, heat-treated and acid-treated soya bean samples. The results show that heat damage of about 5% in reactive lysine content can be measured in 1·5 h with good reproducibility.     

On copulas, quasicopulas and fuzzy logic

We investigate (quasi)copulas as possible truth functions of fuzzy conjunction which is not necessarily associative and present some axiom systems for such fuzzy logics. In particular, we study an expansion of Łukasiewicz (infinite valued propositional) logic by a new connective interpreted as an arbitrary quasicopula (and also by a new connective interpreted as the residuum of the copula). Main results concern standard completeness.     

Supported nickel catalyst from hydroxycarbonate of nickel and aluminium

The hydroxycarbonate of nickel and aluminium (Ni/ Al = 3) with a hydrotalcite-like structure is an outstanding precursor of the active component of supported nickel catalysts. Good mechanical strength and suitable nickel content of these catalysts, which are necessary for practical applications, can be achieved by mechanical mixing of this compound with an additional support. The catalyst prepared from a mixture of 56.5 wt-% of nickel-aluminium hydroxycarbonate and 43.5 wt-% of γ-alumina was proven to have a stable catalytic activity in the methanation reaction at 2 MPa and 800 K.     

A new ECG beat clustering method based on kernelized fuzzy c-means and hybrid ant colony optimization for continuous domains

The kernelized fuzzy c-means algorithm uses kernel methods to improve the clustering performance of the well known fuzzy c-means algorithm by mapping a given dataset into a higher dimensional space non-linearly. Thus, the newly obtained dataset is more likely to be linearly seprable. However, to further improve the clustering performance, an optimization method is required to overcome the drawbacks of the traditional algorithms such as, sensitivity to initialization, trapping into local minima and lack of prior knowledge for optimum paramaters of the kernel functions. In this paper, to overcome these drawbacks, a new clustering method based on kernelized fuzzy c-means algorithm and a recently proposed ant based optimization algorithm, hybrid ant colony optimization for continuous domains, is proposed. The proposed method is applied to a dataset which is obtained from MIT–BIH arrhythmia database. The dataset consists of six types of ECG beats including, Normal Beat (N), Premature Ventricular Contraction (PVC), Fusion of Ventricular and Normal Beat (F), Artrial Premature Beat (A), Right Bundle Branch Block Beat (R) and Fusion of Paced and Normal Beat (f). Four time domain features are extracted for each beat type and training and test sets are formed. After several experiments it is observed that the proposed method outperforms the traditional fuzzy c-means and kernelized fuzzy c-means algorithms.     

Annotation of sentence structure

The focus of this article is on the creation of a collection of sentences manually annotated with respect to their sentence structure. We show that the concept of linear segments—linguistically motivated units, which may be easily detected automatically—serves as a good basis for the identification of clauses in Czech. The segment annotation captures such relationships as subordination, coordination, apposition and parenthesis; based on segmentation charts, individual clauses forming a complex sentence are identified. The annotation of a sentence structure enriches a dependency-based framework with explicit syntactic information on relations among complex units like clauses. We have gathered a collection of 3,444 sentences from the Prague Dependency Treebank, which were annotated with respect to their sentence structure (these sentences comprise 10,746 segments forming 6,341 clauses). The main purpose of the project is to gain a development data—promising results for Czech NLP tools (as a dependency parser or a machine translation system for related languages) that adopt an idea of clause segmentation have been already reported. The collection of sentences with annotated sentence structure provides the possibility of further improvement of such tools.