Search results for "Abstract data type"
showing 10 items of 1140 documents
Sylow Normalizers and Brauer Character Degrees
2000
Suppose that G is a finite group. In this note, we show that a local condition about Sylow normalizers is equivalent to a global condition on the degrees of certain irreducible Brauer characters of G. Theorem A. Let G be a finite p; q-solvable group, and let Q ∈ SylqG and P ∈ SylpG. Then every irreducible p-Brauer character of G of q′degree has p′-degree if and only if NGQ is contained in some G-conjugate of NGP. Theorem A needs a solvability hypothesis. If p = 7, then the irreducible p-Brauer characters of the group G = PSL2; 27 have degrees 1; 13; 26; 28. If we set q = 2, then each q′-degree is also a p′-degree.
On handling exceptions
1995
The current literature of information systems has dealt extensively with all kinds of exceptions. There are several studies defining the concept of exception and even providing classifications. However, no studies provide a method for verifying the rules in order to handle exceptions and to achieve the goals set by an organization's rules. In this paper, a model employing a set of unique input/output (UIO) sequences is presented for verifying such rules. The model originally presented for Finite State Machines (FSM) has been modified to include concepts of exception handling and will be used to form a tool usable for verifying exception handling rules in OISs.
Applied study on the rotational molding and processing technology of rotational molds
2021
Computer-aided manufacturing involves a set of computerized activities related to the preparation, launch and follow-up of manufacturing. Computer-aided manufacturing is a tool that allows the use of 3D models based on computer-aided design. This paper addresses the process of rotational formation, with an effective focus on the technology of processing a rotational mold using CAM simulation as a research method. In this sense, the right choice of CNC and cutting tools is essential. The use of numerically controlled machine tools and high-performance cutting tools reduces the number of operations. The manufacturing route realized is specific to the parts machining on numerical control machi…
Quantifying Mean Shape and Variability of Footprints Using Mean Sets
2005
This paper1 presents an application of several definitions of a mean set for use in footwear design. For a given size, footprint pressure images corresponding to different individuals constitute our raw data. Appropriate footwear design needs to have knowledge of some kind of typical footprint. Former methods based on contour relevant points are highly sensitive to contour noise; moreover, they lack repeatability because of the need for the intervention of human designers. The method proposed in this paper is based on using mean sets on the thresholded images of the pressure footprints. Three definitions are used, two of them from Vorob’ev and Baddeley-Molchanov and one morphological mean p…
Stochastic frontier models using R
2020
Abstract The production function is usually assumed to specify the maximum output obtainable, from a given set of inputs, describing the boundary or frontier of the obtainable output from each feasible combination of input; it relates the production process of individual units to the efficient border of the production possibilities. The measure of the distance of each unit from the border is the most immediate way to assess its (in)efficiency. However, the production function is not generally known, but it has only a set of information on each production unit and it is therefore essential to develop techniques to estimate the production frontier. Starting from the packages already developed…
A Posteriori Methods
1998
A posteriori methods could also be called methods for generating Pareto optimal solutions. After the Pareto optimal set (or a part of it) has been generated, it is presented to the decision maker, who selects the most preferred among the alternatives. The inconveniences here are that the generation process is usually computationally expensive and sometimes in part, at least, difficult. On the other hand, it is hard for the decision maker to select from a large set of alternatives. One more important question is how to present or display the alternatives to the decision maker in an effective way. The working order in these methods is: 1) analyst, 2) decision maker.
JASP: a program to estimate discovery and exclusion limits in prospective studies of searches
1997
Abstract This program computes the discovery and exclusion limits that can be set in prospective studies of new experiments in the search for new phenomena. It properly takes into account the different outcomes that the experiment can obtain including the possible signal and background fluctuations. The procedure gives in general more conservative limits than those obtained assuming that the experiment will obtain a number of events equal to the expected mean. The difference may be essential in those cases where only one experiment is foreseen to be carried out.
Heuristics for the bi-objective path dissimilarity problem
2009
In this paper the path dissimilarity problem is considered. The problem has previously been studied within several contexts, the most popular of which is motivated by the need to select transportation routes for hazardous materials. The aim of this paper is to formally introduce the problem as a bi-objective optimization problem, in which a single solution consists of a set of p different paths, and two conflicting objectives arise, on one hand the average length of the paths must be kept low, and on the other hand the dissimilarity among the paths in the set should be kept high. Previous methods are reviewed and adapted to this bi-objective problem, thus we can compare the methods using th…
Identification of parameters of dynamic Preisach model by neural networks
2008
In this paper, an approach that allows to identify the parameters of dynamic Preisach model is presented. The fundamental idea of this method is to identify the parameters of a material by using a neural network trained by a collection of hysteresis curves, whose Preisach model is known. After a brief description of dynamic Preisach Model, the neural network that has been used is introduced. The construction of the training data set is illustrated. Finally, the effectiveness of the method is tested on both numerical as well as experimental data.
Parameter Identification of a Winding Function Based Model for Fault Detection of Induction Machines
2018
Prediction of machines' faulty parts is important in industrial applications in order to reduce productivity losses. As far as electrical machines are considered, a model-based fault diagnosis approach is usually used for this purpose. The model is derived from the modified winding function theory and hence, it requires a considerable amount of parameters at various operating conditions in order to be successfully used. However, the complete set of parameters is difficult to be obtained, as manufacturers of electric machines normally provide only the parameters that describe simple motor models (e.g. T-equivalent circuit at rated conditions). Therefore, the current work presents a method th…