Definition of a composite [1] describes an ideal composite material with perfect structure. In real composite materials, structure is usually imperfect – composites contain various types of defects [2, 3–5], especially as the casted composites are of concern. The reason for this is a specific structure of castings, related to course of the manufacturing process. In case of metal matrix composite castings, especially regarding these manufactured by saturation, there is no classification of these defects [2, 4]. Classification of defects in castings of classic materials (cast iron, cast steel, non-ferrous alloys) is insufficient and requires completion of specific defects of mentioned materials. This problem (noted during manufacturing metal matrix composite castings with saturated reinforcement in Institute of Basic Technical Sciences of Maritime University Szczecin) has become a reason of starting work aimed at creating such classification. As a result, this paper was prepared. It can contribute to improvement of quality of studied materials and, as a consequence, improve the environment protection level.
The work proposes a new method for vehicle classification, which allows treating vehicles uniformly at the stage of defining the vehicle classes, as well as during the classification itself and the assessment of its correctness. The sole source of information about a vehicle is its magnetic signature normalised with respect to the amplitude and duration. The proposed method allows defining a large number (even several thousand) of classes comprising vehicles whose magnetic signatures are similar according to the assumed criterion with precisely determined degree of similarity. The decision about the degree of similarity and, consequently, about the number of classes, is taken by a user depending on the classification purpose. An additional advantage of the proposed solution is the automated defining of vehicle classes for the given degree of similarity between signatures determined by a user. Thus the human factor, which plays a significant role in currently used methods, has been removed from the classification process at the stage of defining vehicle classes. The efficiency of the proposed approach to the vehicle classification problem was demonstrated on the basis of a large set of experimental data.
This study addresses the problem of magnetic field emission produced by the laptop computers. Although, the magnetic field is spread over the entire frequency spectrum, the most dangerous part of it to the laptop users is the frequency range from 50 to 500 Hz, commonly called the extremely low frequency magnetic field. In this frequency region the magnetic field is characterized by high peak values. To examine the influence of laptop’s magnetic field emission in the office, a specific experiment is proposed. It includes the measurement of the magnetic field at six laptop’s positions, which are in close contact to its user. The results obtained from ten different laptop computers show the extremely high emission at some positions, which are dependent on the power dissipation or bad ergonomics. Eventually, the experiment extracts these dangerous positions of magnetic field emission and suggests possible solutions.
A review of mechanical models of road pavements in the form of a proposal of classification of these models is presented. It is assumed an autonomy of the following elements of pavement model: the models of structural layers, the subgrade model, the interlayer bonding models, including bonding of pavement structure with its subgrade, the models of external impacts on pavement layers, including load of heavy traffic, the models of pavement environment impacts on structural layers’ borders (lateral) and subgrade borders (including the lower one) – according to the selected criteria such as structural criterion, material criterion (physical criterion), dimension criterion and model scope (purpose) criterion − in the frame of assumptions of the classical Newtonian deterministic mechanics. The presented attempt to classify mechanical models of road pavements supports to orientate the roadmen community within a scope of the mechanistic modelling of these structures.
The article presents the results of research, the aim of which was to determine the qualitative and quantitative structure of the causes of accidents that were a result of falling from scaffolding. An original methodology for the classification of accidents with regards to their causes was developed and was based on cluster analysis. An example of using the proposed methodology is provided. 187 post-accident protocols of occupational accidents involving construction scaffolding, which occurred between 2010 and 2017 in selected Polish voivodeships, were analyzed. Afterwards, the matrix of accident causes, for which the calculations were made, was created. Five subsets of accidents were obtained and the accidents were classified to a subset with similar causes.
Classification of water masses in the area investigated during the 1981 FIBEX Expedition and two winter expeditions at the "H. Arctowski" Station using the method of Empirical Orthogonal Functions (EOF) is presented. Four basic water masses (warm and cold Bellinghausen Sea surface waters, surface Weddell Sea waters, Circumpolar Warm Deep Water (CWDW) and the transitional zone) were observed in the area and a significant dependence of water masses distribution ón depth was found. A strong winter increase in the Weddell Sea waters influence was recorded.
Business Process Modelling Notation (BPMN) is a visual specification language without well-defined concepts for equivalences. This necessitates the establishment of fundamental notions that underpin the equivalences of BPMN processes. The main body of the paper is centered around the principle of substitutibility in which different types of equivalences of BPMN processes are formally described. Additionally, these results provide a basis for defining the behavioural equivalence of BPMN models. Our research investigation contributes to the field of business process management by developing a tight con-nection between BPMN and its associated equivalence notions.
In general, currently employed vehicle classification algorithms based on the magnetic signature can distinguish among only a few vehicle classes. The work presents a new approach to this problem. A set of characteristic parameters measurable from the magnetic signature and limits of their uncertainty intervals are determined independently for each predefined class. The source of information on the vehicle parameters is its magnetic signature measured in a system that enables independent measurement of two signals, i.e. changes in the active and reactive component of the inductive loop impedance caused by a passing vehicle. These innovations result in high selective classification system, which utilizes over a dozen vehicle classes. The evaluation of the proposed approach was carried out for good vehicles consisting of 2-axle tractor and a 3-axle semi-trailer.
The systematic position of Sorbus population occurring in the Pieniny Mts. is controversial. To verify its taxonomic status we studied the ITS sequence of closely related species of the S. aria group: Sorbus sp. from the Pieniny Mts., S. aria from the Tatra Mts., S. graeca from the Balkans, and other well-distinguished native Polish Sorbus species (S. aria, S. aucuparia, S. intermedia and S. torminalis). As a reference we examined Sorbus populations closest to the Pieniny Mts. where S. graeca was reported to occur, in Slovakia. The results indicate that the Sorbus plants found in the Pieniny Mts. differ genetically from those in the Tatra Mts. but are identical to those collected from the Vihorlat Mts. in Slovakia and are closely related to S. graeca from the Balkans
A purpose of the present study is an evaluation of various models of classification of the South branch of the Cushitic languages. The South Cushitic languages are studied in their narrow sense here, i.e. without Dahalo and Ma’a, although their probable cognates are registered.
Today’s human-computer interaction systems have a broad variety of applications in which automatic human emotion recognition is of great interest. Literature contains many different, more or less successful forms of these systems. This work emerged as an attempt to clarify which speech features are the most informative, which classification structure is the most convenient for this type of tasks, and the degree to which the results are influenced by database size, quality and cultural characteristic of a language. The research is presented as the case study on Slavic languages.
This paper presents results of object-oriented classification of Landsat ETM+ satellite im-age conducted using eCognition software. The classified image was acquired on 7 May 2000. In this particular study, an area of 423 km2 within the borders of Legionowo Community near Warsaw is considered.
Prior to classification, segmentation of the Landsat ETM+ image is performed using panchro-matic channel, fused multispectral and panchromatic data. The applied methods of classification en-abled the identification of 18 land cover and land use classes. After the classification, generalization and raster to vector conversion, verification and accuracy assessment are performed by means of vis-ual interpretation. Overall accuracy of the classification reached 94.6%. The verification and classifi-cation results are combined to form the final database.
This is followed by comparing the object-oriented with traditional pixel-based classification. The latter is performed using the so-called hybrid classification based on both supervised and unsuper-vised classification approaches. The traditional pixel-based approach identified only 8 classes. Com-parison of the pixel-based classification with the database obtained using the object-oriented ap-proach revealed that the former reached 72% and 61% accuracy, according to the applied method.