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The comminution process, particularly grinding, is very important in the mineral processing industry. Some characteristics of ore particles, which occur as a product of grinding process, have a significant impact on the effects of further ore processing. At the same time, this process requires a significant amount of energy which significantly affects the overall processing costs. Therefore, in this paper, we propose new multiple criteria decision making model, based on the Ratio system part of the MOORA method, which should enable an efficient selection of the adequate comminution circuit design.

Lithuanian vowel and semivowel phoneme modelling framework is proposed. Using this framework, the phoneme signal is described as the output of a linear multiple-input and single-output (MISO) system. The MISO system is a parallel connection of single-input and single-output (SISO) systems whose input impulse amplitudes vary in time. Within this framework two synthesis methods are proposed: harmonic and formant. The synthesized sounds obtained by the harmonic synthesis method are compared with those obtained by the formant method. Application of this modelling framework to all of Lithuanian vowel and semivowel synthesis gives naturally sounding result.

The paper deals with a parallel processor scheduling problem with changeable job values. Contrary to other papers in this area, we assume that job values are characterized by a non-monotonic stepwise functions of job completion times (previously only non-increasing functions have been considered). We give examples of real-life systems that can be modelled in such a way, in order to show that the problem is interesting from practical point of view. The problem is shown to be NP-hard and a pseudo-polynomial time algorithm for its special case is constructed. Moreover, a number of heuristic algorithms is provided and experimentally tested.

In multi criteria Decision Making, the decision maker wants to find the best alternative among a set of alternatives in order to satisfy a set of criteria. Traditionally, decision making models are based on crisp data. The shortcoming of these data in capturing the reality and lack of information persuaded researchers to develop decision making methods with uncertain data. In this paper, the ELECTRE method is extended with black numbers, under ambiguous environment. The proposed method is applied in a supplier selection problem. It's an outstanding method that can be used in real world problems with ill-defined and incomplete data.

In order to survive in the present day global competitive environment, it now becomes essential for the manufacturing organizations to take prompt and correct decisions regarding effective use of their scarce resources. Various multi-criteria decision-making (MCDM) methods are now available to help those organizations in choosing the best decisive course of actions. In this paper, the applicability of weighted aggregated sum product assessment (WASPAS) method is explored as an effective MCDM tool while solving eight manufacturing decision making problems, such as selection of cutting fluid, electroplating system, forging condition, arc welding process, industrial robot, milling condition, machinability of materials, and electro-discharge micro-machining process parameters. It is observed that this method has the capability of accurately ranking the alternatives in all the considered selection problems. The effect of the parameter λ on the ranking performance of WASPAS method is also studied.

In this paper, a modified version of the discrete wavelet transform (DWT), distinguishing itself with visibly improved space localization properties and noticeably extended potential capabilities, is proposed. The key point of this proposal is the full decorrelation of wavelet coefficients across the lower scales. This proposal can be applied to any DWT of higher orders (Le Gall, Daubechies D4, CDF 9/7, etc.). To open up new areas of practical applicability of the modified DWT, a novel exceptionally fast algorithm for computing the DWT spectra of the selected signal (image) blocks is presented. In parallel, some considerations and experimental results concerning the energy compaction property of the modified DWT are discussed.

Underperformance in higher frequency signal regions denoising is a common problem for many denoising methods. Wavelet transforms are, generally, less prone to the problem than the pure spatial or frequency domain transforms, but there is still much room for improvements. In this paper, we propose a point-wise adaptive wavelet transform for signal denoising applications. It is very efficient in denoising higher frequency regions, without compromising the performance on smooth, lower frequency, regions. The transform uses statistical method of intersection of confidence intervals rule to adapt to local signal properties. Its performance was extensively tested on various signal classes. The results proved validity of theoretical assumptions and showed significant performance improvements when compared to other denoising methods.

“Strategy implementation” is an inseparable part of strategic management process. Transformation strategies to typical operations and daily functions of staff exert a significant role in organization success. Balanced scorecard (BSC) and strategy map help senior managers to perfectly implement and monitor the accomplishment of the strategies by transforming strategies into operational programs. Using BSC and strategy map, the strategies are translated into some action plans which help the achievement of organizational goals and strategies. Due to shortage of resources, usually all organization's action plans cannot be implemented completely; therefore, managers should make use of some tools for assigning and selecting more efective action plans. In this paper, a procedure is suggested on the basis of grey TOPSIS to determine the preference of action plans to better aid managers in selection of the most effective action plans in a group decision making process.

Image synthesis techniques are present in a wide range of applications as they leverage the amount of information required for creating realistic visualizations. For fast hardware rendering they usually employ a triangle-based representation describing the geometry of the scene. In this paper, we introduce a new and simple framework for performing on-the-fly refinement and simplification of meshes completely on the GPU. As we aim at making easy the integration of level-of-detail management into the creation workflow of artists, the presented method is easy to be implemented. We only need a coarse mesh, its displacement map and a geometry shader. At rendering time, we employ a geometry shader to parallelize the tessellation and displacement steps. The tessellation step performs uniform refinement or simplification operations by applying a fixed subdivision criterion. Our method also exploits coherence by taking advantage of the last computed mesh. We provide a method which offers a flexible integration with standard 3D tools, easy to be implemented, coherence exploitation and wholly processed by the GPU.

In this paper we focus on a specific class of XML schema inference approaches – so-called heuristic approaches. Contrary to grammar-inferring approaches, their result does not belong to any specific class of grammars and, hence, we cannot say anything about their features from the point of view of theory of languages. However, the heuristic approaches still form a wider and more popular set of approaches due to natural and user-friendly strategies. We describe a general framework of the inference algorithms and we show how its particular phases can be further enhanced and optimized to get more reasonable and realistic output. The aim of the paper is (1) to provide a general overview of the heuristic inference process and existing approaches, (2) to sum up the improvements and optimizations we have proposed so far in our research group, and (3) to discuss possible extensions and open problems which need to be solved. Hence, it enables the reader to get acquainted with the field fast.