Top PDF A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

A Vectorial modeling for the pentaphase Permanent Magnet Synchronous Machine based on multimachine approach

The polyphase [1] machines are developed mainly in the field of variable speed drives of high power because increasing the number of phases on the one hand allows to reduce the dimensions of the components in power modulators energy and secondly to improve the operating safety. By a vector approach (vector space), it is possible to find a set of single-phase machine and / or two-phase fictitious equivalent to polyphase synchronous machine.These fictitious machines are coupled electrically and mechanically but decoupled magnetically. This approach leads to introduce the concept of the equivalent machine (multimachine multiconverter system MMS) which aims to analyze systems composed of multiple machines (or multiple converters) in electric drives. A first classification multimachine multiconverter system follows naturally from MMS formalism. We present an example of a synchronous machine pent phase.
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Assessment of Electromagnetic Stress in a Permanent Magnet Synchronous Machine with Commutable Poles

Assessment of Electromagnetic Stress in a Permanent Magnet Synchronous Machine with Commutable Poles

The permanent magnet synchronous machine is an adequate solution in a large range of power in high performance electrical drives and energy conversion systems. I n this paper has been assessed the per- manent magnet synchronous machine electromagnetic stress for the case of stator winding with commutable poles. Based on simplified as- sumptions, an analytic relationship of the dependence of electromag- netic stress has been obtained. Numerical simulation performed for a case study confirms the validity of the theoretical approach developed.
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Modelling of a Line-Start Permanent Magnet Synchronous Motor, Using Empirical Parameters

Modelling of a Line-Start Permanent Magnet Synchronous Motor, Using Empirical Parameters

Line-started permanent magnet synchronous motors emerged in the market in response to strict efficiency goals. Despite being a synchronous motor, the rotor of a line-started permanent magnet synchronous motor contains a squirrel cage and, consequently, the behaviour under transient periods and/or faulty operation is not the same as for a conventional synchronous motor. In order to study this kind of electrical machine, it is proposed in this paper an equivalent circuit model and a set of experimental tests to extract the parameters of the equivalent circuit of a line-started permanent magnet synchronous motor. To validate the presented approach, a computer model of the machine, based on the obtained parameters, was developed, and the simulation results were compared with the experimental motor performance.
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Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery.

Only certain variables of the Rorschach test were analyzed, according to the psychopathology of the epileptic patients, namely: the schizophrenia index (Sczi), social ability index (Cdi) and depression index (Depi). To evaluate problem resolution and decision making in which emotionality and ideation are involved, the personality style of all patients was assessed. The personality style (P. Style), or erlebnistypus (EB), is a relevant variable in the Rorschach test, which quantifies the cognitive-perceptive respons- es of the subject [14]. The responses to perception of movement of introversive subjects are two points higher than their responses to weighted color, while extratensive subjects are those whose responses to color are greater than their responses to movement. Finally, ambitents are individuals for whom the difference between the two variables is less than two points. Thus, patients were classified as introversive (EB1), extratensive (EB2) or ambitent (EB3). The Rorschach protocols followed were those included in the Rorschach H Interpretation Assistance Program (RIAP5: John E. Exner Jr., Irving B. Weiner, and Par Staff; Psychological Assessment Resources Inc. Lutz, FL, USA). In order to group patients, the Sczi, Cdi and Depi indices were evaluated and classified as positive or negative (Table 2).
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Naval Power System Dynamics with Proportional Type Regulators

Naval Power System Dynamics with Proportional Type Regulators

This work analyzes the dynamic behavior of naval power system using proportional type controllers, system which provides energy for consumers on the vessel so that the voltage and frequency is always in nominal value limits. Essential problems of the work relates to the tuning of controllers, because the system is nonlinear and we can’t apply known criteria. Analyzing type P controllers we found that oscillations known to occur in proportional type controller can put out the naval power system.

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Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties

Prediction of cancer cell sensitivity to natural products based on genomic and chemical properties

To further illustrate the effectiveness of our approach for detecting cancer cell sensitivity to natural products, we present two additional natural products examples. By searching CancerHSP database (Tao et al., 2015) and natural products-related studies from the PubMed database (http://www.ncbi.nih.gov/pubmed), we obtained 2 natural products screened on 29 cancer cell lines: Curcumin (Bush et al., 2001; Choudhuri et al., 2002; Khor et al., 2006; Radhakrishna Pillai et al., 2004; Wang et al., 2006) and Resveratrol (Chen et al., 2004; Cl´ement et al., 1998; Ding & Adrian, 2002; Hsieh & Wu, 1999; Lu & Serrero, 1999; Niles et al., 2003; Whyte et al., 2007 ), which have been proven effective in prevention and treatment of various kinds of cancers, including melanoma, lung cancer, ovarian cancer and so on (Tao et al., 2015). After eliminating cancer cell lines for which we could not find the corresponding gene expression information in GDSC, we finally obtained 7 and 8 cancer cell line-natural product interactions for Curcumin and Resveratrol, respectively. The prediction results in these two natural products are shown in Table 2.
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J. Braz. Soc. Mech. Sci. & Eng.  vol.26 número3

J. Braz. Soc. Mech. Sci. & Eng. vol.26 número3

This paper introduces a methodology for modeling and analyzing fault-tolerant manufacturing systems that not only optimizes normal productive processes, but also performs detection and treatment of faults. This approach is based on the hierarchical and modular integration of Petri Nets. The modularity provides the integration of three types of processes: those representing the productive process, fault detection, and fault treatment. The hierarchical aspect of the approach permits us to consider processes on different levels of detail (i.e. factory, manufacturing cell, or machine). Case studies considering detection and treatment of faults are presented, and a simulation tool is applied for verifying the models.
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Forecasting human entrances at a commercial store using facial recognition data

Forecasting human entrances at a commercial store using facial recognition data

Due to advances in Information Technology, there is a growing interest in the use of data mining to extract useful patterns from raw data in order to support decision making. In this work, a data mining approach was conducted aiming at the prediction of human entrances at a commercial store, as measured by an automatic video face detection system. In particular, a large number of experiments were held, targeting distinct types of human entrances (i.e., Female, Male, Both), forecasting periods (i.e., hourly and daily) and lookahead (horizon) predictions. Moreover, several forecasting methods were tested: conventional time series methods and time series models based on machine learning; a regression approach (e.g. using weather and special event data); and a hybrid approach that uses both time series (human entrances time lags) and regression variables. To achieve a robust evaluation, a rolling window scheme was adopted, which impled the use of a large number of model updates (trainings) and testing. For short term predictions (horizon of 1), the best performances were in general obtained by the hybrid approach, resulting in a mean absolute percentage error (MAPE) that ranges from 16.9% (all human daily entrances) to 24.8% (female hourly entrances). Such forecasting models are potentially valuable for commercial store managers. For instance, they can help in the supporting decisions related with the management of the retail store human resources and marketing campaigns.
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Study on modelling and simulation of permanent magnet stepping motor by MATLAB/SIMULINK

Study on modelling and simulation of permanent magnet stepping motor by MATLAB/SIMULINK

The permanent magnet stepper motor shown in Fig.1 , only has two windings, yet has 24-poles in each of two phases[6][7]. This style of construction is known as can stack. A phase winding is wrapped with a mild steel shell, with fingers brought to the centre. One phase, on a transient basis, will have a north side and a south side. Each side wraps around to the centre of the doughnut with twelve interdigitated fingers for a total of 24 poles. These alternating north-south fingers will attract the permanent magnet rotor. If the polarity of the phase were reversed, the rotor would jump 360 o /24 = 15 o . We do not know which direction, which is not usefully. However, if we energize φ-1 followed by φ-2, the rotor will move 7.5 o
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Evaluating a guest satisfaction model through data mining

Evaluating a guest satisfaction model through data mining

Tourism researchers acknowledge the value of data mining for leveraging understanding of a myriad of problems within tourism. Thus, the recent years have witnessed a large increase in data mining applications to hospitality and tourism. A decision tree (DT) is a simple yet effective data mining modeling technique that creates a tree-like model where each node represents a decision using the input features until a leaf with a prediction is reached. Shapoval et al. (2018) adopted a DT to analyze secondary data on 4,000 tourists obtained from the Japan Tourism Agency about tourists visiting Japan. Features such as food and nationality were found relevant to explain tourist satisfaction. Alternatively, artificial neural networks (ANN) attempt to mimic the neurons and synapses that form the complexity of the human brain (Heidari et al., 2016). Thus, layers of nodes (neurons) make simple decisions that are combined through connections between nodes, resulting in models that can apprehend non-linear relations and therefore usually have better predictive performance. Phillips et al. (2015) adopted ANN to understand the effects of 60k online reviews in the performance of 235 Swiss hotels using ten features related to hotel characteristics and revenue. Another effective data mining technique that has been applied to tourism is support vector machines (SVM). SVM transforms the complex 𝑥 ∈ 𝑅 𝑀 input space into a high m-dimensional feature space by applying a nonlinear mapping. Then it finds the best hyperplane that separates the input feature space by using points which define a support vector (Moro et al., 2017). Trpkovski et al. (2018) used SVM to evaluate photo quality using 9,448 photos posted on TripAdvisor and characteristics such as contrast and brightness. Thus, data mining can help in shaping new horizons in the tourism research landscape by leveraging understanding of problems within tourism based on data.
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Operating characteristics of turbine mixers based on the analysis of power demand of the mixer’s drive

Operating characteristics of turbine mixers based on the analysis of power demand of the mixer’s drive

Mixing processes involve the blending of silica sand, bentonite, coal dust (or mixture) and water. The purpose of mixing is to homogenise the mixture and ensure that the rebonding agent should be uniformly distributed over the grains. This unit was designed for separating casts from the runner system. the number of casts in a batch ranges from 1 to 4 on the given level, there are 1-48 of them on 1-12 levels. The mass of the batch varies from 5 to 12 kg.

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Conceptual Design of Power Electronics, Control Strategies and Electrical Machines within Variable Speed Drives

Conceptual Design of Power Electronics, Control Strategies and Electrical Machines within Variable Speed Drives

k ∈ ℕ of the wide spectrum in Fig.11 are obtained. There exists a lot of ordinal numbers with even different magnitudes. However, only the invoked fourteenth component with B ˆ 14 = 0.045 T can interact with the rotor part in order to generate a constant mechanical average torque. Other harmonic waves are therefore undesired and cause losses. In order to restrict such effects, the geometric air gap distance is limited to be minimal of about 0.34 mm. Due to the used surface magnet design the magnetic air gap distance is wide enough to restrict additional losses within the rotor magnets due to excessively eddy current effects. This is also obviously from Fig.9 due to the very weak penetration of the stator field into the magnets and the rotor yoke.
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Limnoperna fortunei in the Upper Paraguay River system using

Limnoperna fortunei in the Upper Paraguay River system using

Environmental layers (georeferenced chemical and physical data) and records of presence (latitude/longitude) of L. fortunei in the Pantanal wetland were used to model its potential distribution in the UPB. Environmental layers were built using the software Arc View 3.2 (Environmental Systems Research Institute, 1999). A drainage map of the UPB was obtained from the National Water Agency (Agência Nacional de Águas). In order to generate continuous pixel lines along the rivers we interpolated values every 10 km in the UPB from the 130 primary sample sites, as explained in Latini (2006), totalling 943 geographic points. Grid cells of 0.07 degrees were used in the case of UPB. From a total of 130 sites in the UPB, 24 sites had occurrence records located in the Pantanal wetland (Figure 1). We used 50% of this data for training and 50% for validation in both GARP and Maxent models.
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Fast Moving Objects Detection Using iLBP Background Model

Fast Moving Objects Detection Using iLBP Background Model

However, LBP descriptors with all its advantages have some significant drawbacks. The main drawback is a complete ignoring of intensity information when comparing LBP descriptors. Because of this, there could be a paradoxical situation (wrong pixel comparison result) when intensity values of pixels differ drastically, but their LBP descriptors are identical. On the other hand, it is obvious that within a chosen scene the fact of a local intensity change in the point of interest is very important. To overcome this drawback, we define ����(�, �) descriptor as a collection of ���(�, �) descriptor values and intensity �(�, �) values of the image:
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Utopia University: A Faculty Member Reflects on Recommendations for the Future of SoTL

Utopia University: A Faculty Member Reflects on Recommendations for the Future of SoTL

The st udent ev aluat ion process for facult y is anot her place where SoTL has pr ovided insight int o st udent lear ning. Galbr ait h, Mer r ill, and Kline ( 2012) exam ined t he t eaching evaluat ions of 116 business classes. Thr ee different analyses failed t o dem onst rat e t hat st udent evaluat ions of t eaching effect iveness ( SETEs) direct ly relat ed t o t eaching effect iveness or st udent learning. Perhaps in addit ion t o ev aluat ing facult y, st udent s should also be encouraged t o evaluat e t hem selv es and t heir accom plishm ent s each sem est er. Our univ ersit y’s evaluat ion quest ions include t he degree t o which t he inst r uct or is st im ulat ing, know ledgeable, ent husiast ic, responsiv e, w ell- pr epared, clear, fair, et c. Changing course evaluat ions from facult y- cent ered “ w hat k ind of person is he or she” t o a st udent - cent er ed “ here is w hat I learned” could bet t er offer inst ruct or s, t heir depart m ent chair s, and ot her adm inist r at ors a t rue gauge of t he course’s success. This addit ional evaluat ion could occur during t he regular evaluat ion process of a course by adding t hese quest ions t o t he st andar d evaluat ion form or during academ ic advising. The lat t er could use t he sam e form , but st udent s would hav e a conversat ion wit h t heir facult y adv isor concerning t heir courses and w het her t hese courses m eet t heir expect at ions. There ar e m any w ay s t o assess a course, and facult y m em bers, depar t m ent s, and ot her subdiv isions can t urn t o t he depart m ent of assessm ent for assist ance wit h t his process.
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A novel support vector machine-based approach for rare variant detection.

A novel support vector machine-based approach for rare variant detection.

Advances in next-generation sequencing technologies have enabled the identification of multiple rare single nucleotide polymorphisms involved in diseases or traits. Several strategies for identifying rare variants that contribute to disease susceptibility have recently been proposed. An important feature of many of these statistical methods is the pooling or collapsing of multiple rare single nucleotide variants to achieve a reasonably high frequency and effect. However, if the pooled rare variants are associated with the trait in different directions, then the pooling may weaken the signal, thereby reducing its statistical power. In the present paper, we propose a backward support vector machine (BSVM)-based variant selection procedure to identify informative disease-associated rare variants. In the selection procedure, the rare variants are weighted and collapsed according to their positive or negative associations with the disease, which may be associated with common variants and rare variants with protective, deleterious, or neutral effects. This nonparametric variant selection procedure is able to account for confounding factors and can also be adopted in other regression frameworks. The results of a simulation study and a data example show that the proposed BSVM approach is more powerful than four other approaches under the considered scenarios, while maintaining valid type I errors.
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Pesqui. Oper.  vol.36 número2

Pesqui. Oper. vol.36 número2

We observe that for the Weibull regression, the three covariates that comprise the final model increased the sale hazard of lots and can be considered valuation factors during the sale of the lots. For example, the sale hazard of a lot located adjacent to the agglomeration of the City Center was exp(0.82) = 2.27 times higher compared to a lot located in rural installments. The hazard sale of a lot located within the Central Hill was, exp(0.41) = 1.51 that is, for a lot inside the Central Hill there was a 51% increase in the sale hazard in relation to a lot located outside of the Central Hill. For a lot whose accessibility to the City Center is not affected by Highway SP-310 (Washington Luiz Highway), the sale hazard was around 2 times higher in relation to a lot whose accessibility to the City Center is affected by Highway SP-310. Another interesting interpretation is to compare the sale hazard of lots contiguous to the agglomeration of City Center (“NUC PRINC”) with the lots located within the Central Hill (“PLN CENTRAL”). To estimate this hazard, exp[−(−0.82 + 0.41)] = 1.51 is calculated. Thus, there was an increase of sale hazard of 51% for lots contiguous to agglomeration of City Center compared to lots located within the Central Hill. In other words, the lots located in the agglomeration of the City Center had an appreciation of 51% compared to lots located in within the Central Hill. More details about the discussion on implications from the perspective of urban planning are presented in Ferreira (2007).
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Stochastic Estimation Methods for Induction Motor Transient Thermal Monitoring Under Non Linear Condition

Stochastic Estimation Methods for Induction Motor Transient Thermal Monitoring Under Non Linear Condition

The induction machine, because of its robustness and low-cost, is commonly used in the industry. Nevertheless, as every type of electrical machine, this machine suffers of some limitations. The most important one is the working temperature which is the dimensioning parameter for the definition of the nominal working point and the machine lifetime. Due to a strong demand concerning thermal monitoring methods appeared in the industry sector. In this context, the adding of temperature sensors is not acceptable and the studied methods tend to use sensorless approaches such as observators or parameters estimators like the extended Kalman Filter (EKF). Then the important criteria are reliability, computational cost ad real time implementation.¶
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A novel approach for modeling users short-term interests, based on user queries

A novel approach for modeling users short-term interests, based on user queries

by a user results in the list of returned results. Document and query terms are linked to the concepts, derived from reference ontology. The current user’s interests are identified by a current query submitted to the system before the results are presented. After sending the query, the system tries to identify whether that same query was issued in the system before. In such case, the results that were drawn before are presented to a user as a result of a current query. Otherwise, the system determines the degree of similarity between the concepts of the current query and the documents previously classified under different concepts of reference ontology. Thus, the authors model both long- term and short-term interests of a user and by combining both, calculates the user’s interests. The relevance of the retrieved documents is a function of user ’s interests and is calculated as the sum of long-term interests, short-term interests and the weight of the document [30].
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