Modal Kalman filtering based impedance relaying

An algorithm is presented for computer distance relaying. It is based on modal Kalman filtering (MKF) to estimate fundamental phasors, MKF exploits all the measurement information available from a three-phase line and is founded on enhanced models of the electromagnetic transients noise. To support the modeling of noise for different faults, a study of nontrivial electrical networks with accurate electromagnetic transients modeling is made for 400 kV transmission lines. MKF fits the behavior of the different modal noise for the Clarke phasors, but it is invariant for each type of fault, assuring robustness and minimum error variance. To computer distance, Clarke αB phasors are transformed to +/- symmetrical components, and then a well-known expression is used to computer the positive impedance. Statistical analysis if presented to assess observation time versus estimation accuracy for the different types of line faults     

A study of Nd2Fe14B and a neodymium-rich phase in sintered NdFeB magnets

The microstructure and properties of NdFeB sintered permanent magnets were analysed by different methods. Samples analysed were sintered and thermally treated. The hard magnetic Nd₂Fe₁₄B phase and amorphous neodymium-rich phase were observed by TEM. The neodymium-rich phase contained iron and boron, in elemental and in B₂O₃ form, which is known as a glass former. At the sintering temperature, Nd₂Fe₁₄B and the neodymium-rich phase are supersaturated with iron, which should be dissolved at the annealing temperature to react with neodymium and boron and form additional Nd₂Fe₁₄B phase. Iron precipitates of size up to 2 nm were detected in the Nd₂Fe₁₄B phase. These superparamagnetic precipitates of -Fe could affect the hard magnetic properties of NdFeB magnets.     

Network regression with predictive clustering trees

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. This phenomenon is a direct violation of the assumption that data are independently and identically distributed. At the same time, it offers an unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. Regression inference in network data is a challenging task. While many approaches for network classification exist, there are very few approaches for network regression. In this paper, we propose a data mining algorithm, called NCLUS, that explicitly considers autocorrelation when building regression models from network data. The algorithm is based on the concept of predictive clustering trees (PCTs) that can be used for clustering, prediction and multi-target prediction, including multi-target regression and multi-target classification. We evaluate our approach on several real world problems of network regression, coming from the areas of social and spatial networks. Empirical results show that our algorithm performs better than PCTs learned by completely disregarding network information, as well as PCTs that are tailored for spatial data, but do not take autocorrelation into account, and a variety of other existing approaches.     

OPTIMIZATION OF PRESSURE SWING ADSORPTION EQUIPMENT PART II OPTIMIZATION OF TWO BED OXYGEN GENERATORS

Local equilibrium model described in Part I is used to stimulate both, the steady state operation conditions and transient regime after the start of PSA equipment. The effect of axial dispersion, adsorption isotherm nonlinearity and high pressure level is simulated. On the basis of numerical analysis, the operation of a classical two-bed oxygen generator is compared with two configurations having pressure equalizing step. The optimization strategy of the given PSA equipment has been proposed and the procedure is demonstrated on an example. The scaling-up condition for PSA equipments which can be described by local equilibrium model has been proposed on the basis of the theoretical analysis.     

Silicon neuron: digital hardware implementation of the quartic model

This paper presents an FPGA implementation of the quartic neuron model. This approach uses digital computation to emulate individual neuron behavior. We implemented the neuron model using fixed-point arithmetic operation. The neuron model’s computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. We show that the proposed FPGA implementation of the quartic neuron model can emulate the electrophysiological activities in various types of cortical neurons and is capable of producing a variety of different behaviors, with diversity similar to that of neuronal cells. The neuron family of this digital neuron can be modified by appropriately adjusting the neuron model’s parameters.     

Theory of porous electrodes—XI. The positive plate of the lead-acid battery

Partial differential equations describing the transport of mass and electricity in the pores of the positive electrode of a lead acid battery were derived. The theory is based on exact transport equations and on the assumption that the solid porous matrix has a metallic conductivity. Volume changes in both phases are taken into account. Numerical solutions obtained on a computer are presented for the case where the influence of electrolyte between the electrodes can be neglected. The solutions depend on the product of electrode thickness times current density, and on the initial porosity.     

Conceptualization,measurement, and application of semantic transparency in visual notations

Numerous visual notations are present in technical and business domains. Notations have to be cognitively effective to ease the planning, documentation, and communication of the domains’ concepts. Semantic transparency (ST) is one of the elementary principles that influence notations’ cognitive effectiveness. However, the principle is criticized for not being well defined and challenges arise in the evaluations and applications of ST. Accordingly, this research’s objectives were to answer how the ST principle is defined, operationalized, and evaluated in present notations as well as applied in the design of new notations in ICT and related areas. To meet these objectives, a systematic literature review was conducted with 94 studies passing the selection process criteria. The results reject one of the three aspects, which define semantic transparency, namely “ST is achieved with the use of icons.” Besides, taxonomies of related concepts and research methods, evaluation metrics, and other findings from this study can help to conduct verifiable ST-related experiments and applications, consequently improving the visual vocabularies of notations and effectiveness of the resulting diagrams.