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The terms “Oracle Problem” and “Non-testable system” interchangeably refer to programs in which the application of test oracles is infeasible. Test oracles are an integral part of conventional testing techniques; thus, such techniques are inoperable in these programs. The prevalence of the oracle problem has inspired the research community to develop several automated testing techniques that can detect functional software faults in such programs. These techniques include N-Version testing, Metamorphic Testing, Assertions, Machine Learning Oracles, and Statistical Hypothesis Testing. This paper presents a Mapping Study that covers these techniques. The Mapping Study presents a series of discussions about each technique, from different perspectives, e.g. effectiveness, efficiency, and usability. It also presents a comparative analysis of these techniques in terms of these perspectives. Finally, potential research opportunities within the non-testable systems problem domain are highlighted within the Mapping Study. We believe that the aforementioned discussions and comparative analysis will be invaluable for new researchers that are attempting to familiarise themselves with the field, and be a useful resource for practitioners that are in the process of selecting an appropriate technique for their context, or deciding how to apply their selected technique. We also believe that our own insights, which are embedded throughout these discussions and the comparative analysis, will be useful for researchers that are already accustomed to the field. It is our hope that the potential research opportunities that have been highlighted by the Mapping Study will steer the direction of future research endeavours. [ABSTRACT FROM AUTHOR]

This paper presents a reverse mapping based space vector pulse-width modulation strategy for five- and seven-level diode-clamped multilevel inverters. In this method, the space vector is expressed as a sum of a contender vector and an error vector. Here, the actual sector, which contains the tip of the reference space vector, needs not to be found. The vector nearest to the reference space vector is the contender vector. By calculating the vector difference of the contender vector from the reference vector, the error vector is determined. Using translation method, the error vector is translated to the origin of space vector diagram. There will be (n–1) steps in space vector diagram for an n-level inverter. As the error vector amplitude will be less than one step of the space vector diagram, the two-level space vector method can be applied. To obtain a vector that is very close to the reference vector, the determined switching states can be added to the contender vector. This technique can be extended to any n-level multilevel inverter. The performance of five-level and seven-level diode-clamped multilevel inverters is presented using MATLAB/Simulink. The performance of inverters is evaluated by using induction motor load. The experimental results using field programmable gate array are presented for seven-level diode-clamped multilevel inverter. [ABSTRACT FROM PUBLISHER]

Space vector modulation (SVM) is a widely used method for multilevel inverters. Most of the SVM methods are nearest three vector (N3V) based schemes. Therefore, several researchers have proposed advanced implementation algorithms with reduced complexity for N3V methods. However, topologies like neutral point (NP) clamped inverter (NPCI) require some distinctive methods (called as non-N3V methods) to balance NP voltage for high modulation index and low power factor operations. Currently, the existing non-N3V methods exercise highly complex algorithms for duty ratio calculation and subtriangle identification. This paper presents a new approach, suitable for both N3V and non-N3V methods, with reduced implementation complexity. The proposed algorithm is based on an equivalent two-level space vector diagram and does not require any trigonometry, coordinate transformation, or volt-second balance solution. Unlike other carrier-based methods, it can change the switching sequence as well as the duration of redundant vectors. Moreover, the proposed approach does not require extra steps for implementing hybrid modulation and it can also be extended to multilevel topologies. One N3V, two non-N3V, and hybrid methods are developed using the proposed modulation algorithm, and are compared in detail. Simulation and experimentation on a three-level NPCI verify the validity of the proposed algorithm. [ABSTRACT FROM PUBLISHER]

In this paper, we review some commonly used data structures and algorithms. We then review two important problems: the creation of the vector-space model that is widely used in the design of information retrieval systems, and the mining of frequent itemsets using the apriori algorithm. We consider two variations of the apriori algorithm: the first is the classical algorithm which computes candidate k-itemsets by first joining frequent (k-1)-itemsets to themselves, and applying the apriori property to prune the generated candidate k-itemsets; the second avoids the join stage in the classical algorithm, and instead, generates candidate k-itemsets directly from rows of the transactions database, followed by application of the apriori property to prune each itemset so determined. Finally, we illustrate appropriate data structures and algorithms that when put together, provide efficient implementations of our solution to the problems mentioned. [ABSTRACT FROM AUTHOR]

Due to the volume of texts available in digital form, the organization, management and knowledge extraction are laborious and frequently impossible to be handled. To automatically cope with these tasks, usually classification models are generated through supervised learning techniques. Unfortunately, this type of learning usually demands a huge human effort to label large volume of texts to build accurate classification models. Since collecting unlabeled texts is easy and inexpensive in several domains, the generation of classification models through inductive semi-supervised learning has been highlighted in recent years. Inductive semi-supervised learning allows to build a classification model using labeled and unlabeled texts. In this scenario, the goal is to augment the set of labeled documents with unlabeled documents to better discriminate class patterns. Hence, fewer texts must be previously labeled. However, semi-supervised learning algorithms that consider texts represented in a vector space model usually obtain unsatisfactory classification performances and are surpassed by semi-supervised learning algorithms that consider texts represented in a network. Nevertheless, despite the classification performances, effective approaches based on networks are generated through the similarities among documents and the classification of a new document are also based on the computation of similarities. This implies to set parameters and compute similarities to both generation the networks and classification of new documents. This approach is not feasible to generate fast responses and consequently to classify a huge volume of texts. In this article, we propose an approach to induce a classification model through semi-supervised learning considering text collections represented by bipartite heterogeneous networks. Bipartite networks are easily and quickly generated, leading to classification performance equivalent or better than other approaches based on network or vector space model and allows a fast classification of new documents. The results presented in this article demonstrate that the proposed approach is able to (i) speed up semi-supervised learning, (ii) speed up the classification of new documents and (iii) surpass classification performance of other existing inductive semi-supervised learning techniques. [ABSTRACT FROM AUTHOR]

The rapid development of digitization and data storage techniques resulted in images volume increase. In order to cope with this increasing amount of informations, it is necessary to develop tools to accelerate and facilitate the access to information and to ensure the relevance of information available to users. These tools must minimize the problems related to the image indexing used to represent content query information. In this paper, we present a new retrieval model called vectorization. The idea is to transform any similarity matching model (between images) to a vector space model providing a score. A study on several methodologies to obtain the vectorization is presented. Some experiments have been undertaken on Oxford5k and Inria Holidays datasets to show the performance of our proposed system. [ABSTRACT FROM AUTHOR]

To understand the user experience in social media or to facilitate the design of human-centric services by social media, users' opinions about specific entities in text messages should be captured. A fine-grained named entity recognizer (NER) is an essential module for identifying opinion targets in text messages, and a named-entity (NE) dictionary is a major resource that affects the performance of an NER. However, it is not easy to construct an NE dictionary manually, because human annotation is time-consuming and labor-intensive. To reduce construction time and labor, we propose a semi-automatic system to construct an NE dictionary from the free online resource, Wikipedia. The proposed system constructs a pseudo-document for each Wikipedia NE by using an active-learning technique. It then classifies Wikipedia entries into NE classes based on similarities between the entries and pseudo-documents located in a vector space. In experiments, the proposed system classified 92.3 % of Wikipedia entries into 29 NE classes. It showed a high performance, with a macro-averaging F1-measure of 0.872 and micro-averaging F1-measure of 0.935. [ABSTRACT FROM AUTHOR]

Many applications are developed on education domain. Information and data for each application are stored in distributed locations with different data representations on each database. This situation leads to heterogeneity at the level of integration data. Heterogeneity data may cause many problems. One major issue is about the semantic relationships data among applications on education domain, in which the learning data may have the same name but with a different meaning, or learning data that has a different name with same meaning. This paper discusses on semantic data mapping process to handle semantic relationships problem on education domain. There are two main parts in the semantic data mapping process. The first part is the semantic data mapping engine to produce data mapping language with turtle (.ttl) file format as a standard XML file schema, that can be used for Local Java Application using Jena Library and Triple Store. The Turtle file contains detail information about data schema of every application inside the database system. The second part is to provide D2R Server that can be accessed from outside environment using HTTP Protocol. This can be done using SPARQL Clients, Linked Data Clients (RDF Formats) and HTML Browser. To implement the semantic data process, this paper focuses on the student grading system in the learning environment of education domain. By following the proposed semantic data mapping process, the turtle file format is produced as a result of the first part of the process. Finally, this file is used to be combined and integrated with other turtle files in order to map and link with other data representation of other applications. [ABSTRACT FROM AUTHOR]

Surface electromyography (EMG) signals have been studied extensively in the last years aiming at the automatic classification of hand gestures and movements as well as the early identification of latent neuromuscular disorders. In this paper, we investigate the potentials of the conjoint use of relevance vector machines (RVM) and fractal dimension (FD) for automatically identifying EMG signals related to different classes of limb motion. The adoption of FD as the mechanism for feature extraction is justified by the fact that EMG signals usually show traces of self-similarity. In particular, four well-known FD estimation methods, namely box-counting, Higuchi's, Katz's and Sevcik's methods, have been considered in this study. With respect to RVM, besides the standard formulation for binary classification, we also investigate the performance of two recently proposed variants, namely constructive mRVM and top-down mRVM, that deal specifically with multiclass problems. These classifiers operate solely over the features extracted by the FD estimation methods, and since the number of such features is relatively small, the efficiency of the classifier induction process is ensured. Results of experiments conducted on a publicly available dataset involving seven distinct types of limb motions are reported whereby we assess the performance of different configurations of the proposed RVM+FD approach. Overall, the results evidence that kernel machines equipped with the FD feature values can be useful for achieving good levels of classification performance. In particular, we have empirically observed that the features extracted by the Katz's method is of better quality than the features generated by other methods. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle (UAV) systems are nowadays a valuable source of data for mapping, surveillance and 3D modelling issues. It is a low-cost alternative to the classical manned aerial photogrammetry. With a typical photogrammetric pipeline. 3D results like DSM/DTM. contour lines, textured 3D models, vector data, etc, can be produced, in a reasonable automated way. Rotary or fixed-wing UAVs, capable of performing the photogrammetric data acquisition with amateur or professional cameras, can fly in manual (manual), semi-automated (loiter or altitude hold), and autonomous (auto) modes. The paper reports a review on UAV for geomatics applications, giving an overview of different UAV platforms, applications and case studies. [ABSTRACT FROM AUTHOR]

In this paper, we introduce the polarization of Koszul cycles and use it to study the depth function of powers of edge ideals of whisker graphs. [ABSTRACT FROM AUTHOR]

Power converters using deterministic switching frequency schemes have switching noise concentrated at harmonic frequencies, resulting in enhanced electromagnetic emission. To suppress the harmonic spikes in three-phase multilevel voltage source converters, a digital control scheme based on dithered sigma–delta modulation (SDM) is proposed in this paper. Introducing a dithered sequence in an SDM varies the switching frequency randomly, resulting in the suppression of the spurious harmonic spikes in the output spectrum even with a regular control input. Although the switching frequency varies randomly, the minimum pulsewidth of the proposed scheme is the sampling time period, avoiding the minimum pulsewidth problem. Instead of a conventional scalar quantizer, the quantizer in the proposed dithered sigma–delta converter uses the principle of space vector quantization. The proposed scheme is experimentally verified on a constant $v/f$ open-loop induction motor drive for a three-level inverter realized by cascading two two-level inverters. The performance of the proposed scheme is compared with different pulsewidth modulation schemes in the entire modulation index, including the overmodulation region. [ABSTRACT FROM PUBLISHER]

We assess a recent paper by Durand and Vaara (2009) that advances causal graph modeling as a tool for inferring causes in strategy research. We focus on the Markov condition, a key assumption on which causal graph modeling is based, and show why this condition is invariably violated in strategic management in general and the resource-based view of the firm in particular. We then introduce vector space modeling as a quantitative alternative to causal graph modeling, and consider how improved methods of causal inference might enhance our ability to test some of the central propositions of the resource-based view. [ABSTRACT FROM AUTHOR]

We propose a collaborative filtering (CF) method that uses behavioral data provided as propositions having the RDF-compliant form of (user X, likes, item Y ) triples. The method involves the application of a novel self-configuration technique for the generation of vector-space representations optimized from the information-theoretic perspective. The method, referred to as Holistic Probabilistic Modus Ponendo Ponens (HPMPP), enables reasoning about the likelihood of unknown facts. The proposed vector-space graph representation model is based on the probabilistic apparatus of quantum Information Retrieval and on the compatibility of all operators representing subjects, predicates, objects and facts. The dual graph-vector representation of the available propositional data enables the entropy-reducing transformation and supports the compositionality of mutually compatible representations. As shown in the experiments presented in the paper, the compositionality of the vector-space representations allows an HPMPP-based recommendation system to identify which of the unknown facts having the triple form (user X, likes, item Y ) are the most likely to be true in a way that is both effective and, in contrast to methods proposed so far, fully automatic. [ABSTRACT FROM AUTHOR]

Common mode voltage (CMV) is responsible for electromagnetic noise and bearing damage of an ac motor. This study presents the consistency between double line voltage synthesis (DLVS) and space vector pulse width modulation (SVPWM) on matrix converter, and proposes two improved DLVSs based on SVPWM, which can effectively reduce the maximum CMV. Both methods can reduce the peak value by 42.3% while keeping the local average values of the output voltage and the input current unaffected. In addition, compared with the existing optimised zero vector modulation, two strategies can improve the output and input current qualities, respectively. Simulation and experimental results verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

In this study, an artificial neural-network (ANN)-based space-vector pulse-width modulation (SVPWM) for capacitor voltage balancing of a three-phase three-level neutral-point clamped converter with improved power quality is presented. The neural-network-based controller offers the advantage of very fast implementation of the SVPWM algorithm. This makes it possible to use an application specific integrated circuit chip in place of a digital signal processor. The proposed scheme employs single layer feed-forward neural-networks at different stages along with a control algorithm using modified reference vector for capacitor voltage balancing of an improved power quality three-phase neutral-point clamped converter. In other words, the neural-network receives three-phase voltages and currents as input and generates symmetrical pulse-width modulation waves for three phases of the converter. A simulated digital signal processor (DSP)-based modulator generates the data which are used to train the network by a back-propagation algorithm in the MATLAB Neural Network Toolbox. The simulation of converter with ANN-based space-vector modulator shows excellent performance when compared with that of conventional DSP-based modulator. [ABSTRACT FROM AUTHOR]

We provide a survey of the field of Music Information Retrieval (MIR), in particular paying attention to latest developments, such as semantic auto-tagging and user-centric retrieval and recommendation approaches. We first elaborate on well-established and proven methods for feature extraction and music indexing, from both the audio signal and contextual data sources about music items, such as web pages or collaborative tags. These in turn enable a wide variety of music retrieval tasks, such as semantic music search or music identification (“query by example"). Subsequently, we review current work on user analysis and modeling in the context of music recommendation and retrieval, addressing the recent trend towards user-centric and adaptive approaches and systems. A discussion follows about the important aspect of how various MIR approaches to different problems are evaluated and compared. Eventually, a discussion about the major open challenges concludes the survey. [ABSTRACT FROM AUTHOR]

SUMMARY This paper presents a novel predictive direct torque control for doubly fed induction machine based on indirect matrix converter (IMC), which is characterized by its simple structure, minimal-torque ripple, and constant switching frequency. Nowadays, the control strategies based on predictive methods have proved their efficiency to improve drive systems capabilities. So, in this paper, one of the best predictive methods that have recently been suggested for doubly fed induction machine drive systems is applied to IMC. The purpose of this combination is to modify the control parameters and size/volume reduction of drive system structure, which is difficult to achieve in conventional systems based on voltage source inverters. The good tracking behavior with reduced torque and flux ripple for both motoring and generating modes as well as removing bulky electrolytic capacitor from the DC link of a converter resulted by using three vectors, two active vectors together with one zero vector per switching period, and applying these vectors to the inverter stage of IMC. To improve the motor drive system performance and reduce losses caused by snubber circuits, the rectifier four-step commutation method in rectifier bridge is used. In the inverter stage, the predictive direct torque control method is employed. The simulation results of the proposed model confirm its effectiveness and accuracy. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: The wide adoption of agile manufacturing systems has necessitated the design and use of fixtures or work holding devices that have in-built flexibility to rapidly respond to part design changes. Despite the availability of reconfigurable fixtures, practical fixture configuration largely remains an experience driven manual activity to enable customization for varying workpiece geometry, and most automated solutions do not scale well to accommodate such variation. In this paper, we address the problem of rapidly synthesizing a realistic fixture that will guarantee stability and immobility of a specified polyhedral work-part. We propose that the problem of automated fixture layout may be approached in two distinct stages. First, we determine the spatial locations of clamping points on the work piece boundary using the principles of force and form closure, to ensure immobility of the fixtured part under external perturbation. In particular, we show that the candidate restraints mapped to the six dimensional vector space of wrenches (force–moment pairs) may be hashed in a straightforward manner to efficiently generate force closure configurations that restrain part movement against large external wrenches. When clamps are allowed to exert arbitrarily high reaction forces on the part, the spatial arrangement of the clamping locations ensures the part is in form closure. On generating force/form closure configurations, the chosen locations are matched against a user-specified library of reconfigurable clamps to synthesize a valid fixture layout comprising clamps that are accessible and collision free with each other and the part. Additionally, in the case of determining machining setups the clamps are chosen to avoid collisions with the moving cutting tool. We demonstrate fast algorithms to perform both location selection and fixture matching, and show several results that underscore the practical application of our solution in automated manufacturing process planning. [Copyright &y& Elsevier]

Multi-phase machines with six-phases are preferred due to their inherent advantages. The symmetrical configuration having a single neutral has certain disadvantages over the asymmetrical six-phase machines. Mostly they are supplied with six-phase inverters. The front-end inverter with a different approach in space vector modulation has limitations in utilization of maximum DC bus voltage, as it produces phase voltages with harmonics. These lower-order harmonics in supply also cause de-rating of the machines. Space vector controlled inverters offer a suitable improvement because of multiple choices of the switching states. The single neutral in a six-phase configuration leads to lower-order harmonics, and an attempt was recently made to control these harmonics by varying selection of the switching space vectors. This article presents the comparative analysis of these space vector pulse-width modulation techniques and proposes third harmonic elimination and control of the lower-order harmonics generation in the six-phase inverters. The improved performance of the inverter in space vector controlled mode with 6 and 12 sector selections are compared. The suggested operational method gives the added advantage compared with the asymmetrical six-phase machines. The six-phase inverter operation in space vector pulse-width modulation is investigated with simulation and substantiated with laboratory investigation. [ABSTRACT FROM AUTHOR]

Abstract: Ray tracing is the foundation of optical system design and analysis. Matrix method is one of the classical methods for ray tracing, while quaternion method gradually becomes an important means to trace ray. However the expression forms of ray are so complex that matrix method and quaternion method are hard to be applied in ray tracing in complicated optical system. In this work, a ray tracing method which uses space vector to describe beams in three-dimensional space directly is demonstrated. First, rotation transformation formula for space vector is derived, then, the direct vector formulae for optical laws are set up. At last, in a ray-tracing example of universal 3D optical system, the direct vector method is much clearer and simpler, comparing with the quaternion method and matrix method. What's more, it is proved that through a complex derivation the quaternion method can be translated into the direct vector method finally. [Copyright &y& Elsevier]

Highlights: [•] A new version of generalized gradient flow (GGVF) snakes involving multiple features of the vector field. [•] Polynomial diffusion based on prescribed clusters of the edge map. [•] A new, directional (orientation) feature integrated into the GGVF snake model. [•] Preprocessing based on hierarchical clustering. [•] A large series of numerical experiments with an in-depth analysis and tests against recent modifications of GGVF. [ABSTRACT FROM AUTHOR]

In this paper, a six-phase voltage source inverter with a single-neutral star connected load is investigated. A space vector PWM (SVPWM), which uses largest magnitude vectors is proposed and implemented. Simulation results of the six-phase voltage source inverter (VSI), which uses the proposed SVPWM method, are compared to the results when a standard sinusoidal PWM scheme is used. Analysis of the results shows that proposed SVPWM scheme is suitable to form a six-phase sinusoidal output voltage. The main advantage of proposed SVPWM scheme is that it requires the same computational resources as the three-phase SVPWM. [ABSTRACT FROM AUTHOR]

Highlights: [•] SVPWM technique for a two-phase VSI with reduced number of static switches and high phase voltage. [•] Use space vector voltages in the complex plane to calculate dwelling time and switching sequence. [•] Represent desired phase output voltages by reference voltage vector, which is used for modulation. [ABSTRACT FROM AUTHOR]

Let E ∋ x ↦? A(x) be a ℓ -mapping with its values being unbounded normal operators with common domain of definition and compact resolvent. Here C stands for C8, C? (real analytic), C[M] (Denjoy-Carleman of Beurling or Roumieu type), C0,1 (locally Lipschitz), or Ck,a. The parameter domain E is either R or Rn or an infinite dimensional convenient vector space. We completely describe the ℓ -dependence on x of the eigenvalues and the eigenvectors of A(x). Thereby we extend previously known results for selfadjoint operators to normal operators, partly improve them, and show that they are best possible. For normal matrices A(x) we obtain partly stronger results. [ABSTRACT FROM AUTHOR]

Abstract: Probabilistic finite state automata (PFSA) have been widely used as an analysis tool for signal representation and modeling of physical systems. This paper presents a new method to address these issues by bringing in the notion of vector-space formulation of symbolic systems in the setting of PFSA. In this context, a link is established between the formal language theory and functional analysis by defining an inner product space over a class of stochastic regular languages, represented by PFSA models that are constructed from finite-length symbol sequences. The norm induced by the inner product is interpreted as a measure of the information contained in the respective PFSA. Numerical examples are presented to illustrate the computational steps in the proposed method and to demonstrate model order reduction via orthogonal projection from a general Hilbert space of PFSA onto a (closed) Markov subspace that belongs to a class of shifts of finite type. These concepts are validated by analyzing time series of ultrasonic signals, collected from an experimental apparatus, for fatigue damage detection in polycrystalline alloys. [Copyright &y& Elsevier]

In this paper, an approach to reduce the common-mode voltage and to eliminate narrow pulse for implemented AC-DC matrix converters is presented. An improved space vector modulation (SVM) strategy is developed by replacing the zero space vectors with suitable pairs of active ones. Further, while considering the commutation time, the probability of narrow pulse in the conventional and proposed SVM methods are derived and compared. The advantages of the proposed scheme include: a 50% reduction in the peak value of the common-mode voltage; improved input and output performances; a reduction in the switching loss by a reduced number of switching commutations and a simplified implementation via software. Experimental results are presented to demonstrate the correctness of the theoretical analysis, as well as the feasibility of the proposed strategy. [ABSTRACT FROM AUTHOR]

Given a nonempty convex set X in a locally convex Hausdorff topological vector space, a nonempty set Y and two set-valued mappings T: X ⇉ X, S: Y ⇉ X we prove that under suitable conditions one can find an x ∈ X which is simultaneously a fixed point for T and a common point for the family of values of S. Applying our intersection theorem, we establish a common fixed point theorem, a saddle point theorem, as well as existence results for the solutions of some equilibrium and complementarity problems. [ABSTRACT FROM AUTHOR]

We construct a discrete quantum mechanics (QM) using a vector space over the Galois field GF(q). We find that the correlations in our model do not violate the Clauser-Horne-Shimony-Holt (CHSH) version of Bell's inequality, despite the fact that the predictions of this discrete QM cannot be reproduced with any hidden variable theory. [ABSTRACT FROM AUTHOR]

Abstract: Assembly searching technologies are important for the improvement of design reusability. However, existing methods require that assemblies possess high-level information, and thus cannot be applied in lightweight assemblies. In this paper, we propose a novel relaxed lightweight assembly retrieval approach based on a vector space model (VSM). By decomposing the assemblies represented in a watertight polygon mesh into bags of parts, and considering the queries as a vague specification of a set of parts, the resilient ranking strategy in VSM is successfully applied in the assembly retrieval. Furthermore, we take the scale-sensitive similarities between parts into the evaluation of matching values, and extend the original VSM to a relaxed matching framework. This framework allows users to input any fuzzy queries, is capable of measuring the results quantitatively, and performs well in retrieving assemblies with specified characteristics. To accelerate the online matching procedure, a typical parts based matching process, as well as a greedy strategy based matching algorithm is presented and integrated in the framework, which makes our system achieve interactive performance. We demonstrate the efficiency and effectiveness of our approach through various experiments on the prototype system. [Copyright &y& Elsevier]

Abstract: This paper presents online components calculation techniques for stator and rotor of the induction machine. Four techniques have been developed for online components calculation; the first one starts the calculation of the negative component of stator current space vector using the Discrete Fourier Transform (DFT) in order to detect the stator fault. The second technique is dealing with the detection of rotor fault by the Recursive Fourier Transform (RFT), This technique improves the signal acquisition and enhanced detection of components near the fundamental. The third technique allows improving of the rotor fault detection by the spectrum of analytical signal. The fourth and the last technique is the frequency analysis of the instantaneous power, which allows obtaining a singular signature of faults. These techniques have shown better detection, where each fault is characterized by a singular signature and therefore they improve the detection and diagnosis of faults. Experimental results applied on an asynchronous machine 5.5kW, approve and validate these calculation techniques. [Copyright &y& Elsevier]

Since the disadvantages of a lot of calculation for the traditional SVPWM algorithm in the three-level neutral-point-clamped (NPC) inverter, which is not easy to real-time control, a space vector PWM (SVPWM) algorithm based on 60° coordinate system is proposed. The space vector coordinates is combined by a simple coordinate transformation, and the basic vectors are achieved by the reference vector coordinate upward and rounded down respectively, whose effective time is calculated by the principle of Volt-seconds balance. The switching state equation is introduced to control the neutral-point voltage balance and the appropriate degrees of freedom are chosen. Because of the simplified SVPWM algorithm requires no judgment of sectors and avoids the complex trigonometric equations for real-time control of three-level inverter, the results of experiment show that this algorithm has less calculation amount than the traditional algorithm, and reduces the rotation of the motor pulse. [ABSTRACT FROM AUTHOR]

Continuous need for an increased power density leads to a growing demand for high speed motors. Due to the quasi linear relation between rotational speed and shaft power of an electrical machine, increasing the rated speed is an effective way to boost power density and efficiency. Thus, high speed motor elements contribute partly to the ongoing development of green energy applications. This paper proposes high frequency power generation using cyclo-inverter with field programmable gate array (FPGA) based controller. Trigger pulses for the cycloinverter are generated using Hardware Description Language VHDL. Space vector modulation (SVM) technique, usually applied for inverters and matrix converters is modified for applying it in cycloinverter so as to obtain an output with reduced harmonic distortion. The software package MATLAB (Simulink) is used to determine the harmonics in the output and to calculate total harmonic distortion factor (THD). Lowest THD has been achieved to be 4.068 % when output frequency of cycloinverter is varied from 50 Hz to 1 MHz. Simulated results are validated experimentally using a low-cost Xilinx Spartan-3E FPGA kit. The trigger circuit is tested qualitatively by observing various waveforms on oscilloscope. The experimental results are found in close agreement to the simulated results. [ABSTRACT FROM AUTHOR]

Abstract: This article presents a vector space model approach to representing documents and queries, based on concepts instead of terms and using WordNet as a light ontology. Such representation reduces information overlap with respect to classic semantic expansion techniques. Experiments carried out on the MuchMore benchmark and on the TREC-7 and TREC-8 Ad-Hoc collections demonstrate the effectiveness of the proposed approach. [Copyright &y& Elsevier]

A study of an interesting meteorological episode over the Owens Valley, California, USA during the Terrain-Induced Rotor EXperiment was conducted using a recently adapted statistical interpolation method to retrieve wind-velocity vectors from Doppler lidar data. This vector retrieval method has been adapted from radar data assimilation techniques. Results show that the method allows better preservation of local variations in the flow field than other techniques. In addition, a high resolution Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) run is used to understand the large-scale flow within the valley and compared with lidar retrievals. Observations from 1030 UTC to 1230 UTC (0230 local time to 0430 local time) on March 27, 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from COAMPS and other in-situ instrumentation are used to corroborate and complement these observations. The optimal interpolation technique for Doppler lidar data vector retrieval appears well suited for scenarios with complex spatial variations in the flow field. [ABSTRACT FROM AUTHOR]

An (N, K) codebook is a set of N unit-norm code vectors in a K-dimensional vector space. For its applications, it is desired that the maximum magnitude of inner products between a pair of distinct code vectors should be as small as possible, meeting the Welch bound equality strictly or asymptotically. In this paper, an (N, K) codebook is constructed from a K \times N partial matrix with K < N, where each code vector is equivalent to a column of the matrix. To obtain the K \times N matrix, K rows are selected from a J \times N matrix \bm\Phi , associated with a binary sequence of length J and Hamming weight K, where a set of the selected row indices is equivalent to the index set of nonzero entries of the binary sequence. It is then discovered that the maximum magnitude of inner products between a pair of distinct code vectors is determined by the maximum magnitude of \bm\Phi -transform of the binary sequence. Thus, constructing a codebook with small magnitude of inner products is equivalent to finding a binary sequence where the maximum magnitude of its \bm\Phi -transform is as small as possible. From the discovery, new classes of codebooks with nontrivial bounds on the maximum inner products are constructed from Fourier and Hadamard matrices associated with binary sequences. [ABSTRACT FROM PUBLISHER]

In the real world data isn't flat and well structured. Data is often modeled into complex models and the cost for finding relevant information and to achieve sustainable results is becoming very high for companies. In this paper, we explain some attributes of the vector space model and we present the idea of incorporating text mining technologies, in our case index searching as part of a standard information retrieval system. We create an index based on text files in a directory, and then we perform several searches on that index for various search terms. To test our concepts we use governing/business documents from Knauf Radika AD, a leading Macedonian plasterboard manufacturer located in Dibër. As a result the query performance was reduced as more documents were added to the index, and consequently the growth factor becomes very low. [ABSTRACT FROM AUTHOR]

Pulse Width Modulation (PWM) inverters play a major role in the field of power electronics. Space Vector Modulated PWM (SVPWM) is the popular PWM method and possibly the best among all the PWM techniques as it generates higher voltages with low total harmonic distortion and works very well with field oriented (vector control) schemes for motor control. High quality output spectra can be obtained by eliminating several low order harmonics by adopting a suitable harmonic elimination technique. In this paper, a mathematical model of space vector modulated three phase inverter is formulated and an offline method for generation of Harmonic Eliminated PWM (HEPWM) by eliminating the low order harmonics of the output waveform is prepared. A systematic online method based on Curve Fitting Technique (CFT) and modification of SVPWM output waveform to a harmonic eliminated waveform is developed for practical implementation. The harmonic spectrum analysis of the proposed model is carried out to ensure the effectiveness. The correctness of the proposed online method is verified by comparing the simulation results with the offline method. [ABSTRACT FROM AUTHOR]

Quantum theory has the property of 'local tomography': the state of any composite system can be reconstructed from the statistics of measurements on the individual components. In this respect the holism of quantum theory is limited. We consider in this paper a class of theories more holistic than quantum theory in that they are constrained only by 'bilocal tomography': the state of any composite system is determined by the statistics of measurements on pairs of components. Under a few auxiliary assumptions, we derive certain general features of such theories. In particular, we show how the number of state parameters can depend on the number of perfectly distinguishable states. We also show that real-vector-space quantum theory, while not locally tomographic, is bilocally tomographic. [ABSTRACT FROM AUTHOR]

Abstract: Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms and phishing. More than 85% of received e-mails are spam. Historical approaches to combat these messages including simple techniques such as sender blacklisting or the use of e-mail signatures, are no longer completely reliable. Currently, many solutions feature machine-learning algorithms trained using statistical representations of the terms that usually appear in the e-mails. Still, these methods are merely syntactic and are unable to account for the underlying semantics of terms within the messages. In this paper, we explore the use of semantics in spam filtering by representing e-mails with a recently introduced Information Retrieval model: the enhanced Topic-based Vector Space Model (eTVSM). This model is capable of representing linguistic phenomena using a semantic ontology. Based upon this representation, we apply several well-known machine-learning models and show that the proposed method can detect the internal semantics of spam messages. [Copyright &y& Elsevier]

The large torque ripples exist in induction motors based on conventional direct torque control (DTC) system, especially at a low speed. For the problem of DTC, fuzzy Control theory (Mathematics) is applied to DTC system. Based on fuzzy control of induction motor direct torque control system model is constructed in this paper. Fuzzy controller in the system selects the voltage space vector. The control system is simulated on the platform of Matlab/simulink. The results of the simulation prove that the method of the fuzzy DTC controller can effectively improve the low-speed performance of the induction motor, reduce the torque ripple, and have a good dynamic response performance. [ABSTRACT FROM AUTHOR]

Abstract: Security issues of space information network can’t be ignored, and it is necessary to construct proper models when researching on security protocols of space information network. This paper studies three modeling methods of security protocol based on OPNET, including process model, custom multi-tier application and ACE whiteboard. All of these three methods are discussed in details by introducing the modeling procedure of Diffie-Hellman key exchange protocol. Performance of these three methods are analyzed and compared from the aspects of modeling capability, protocol layer and realizing complexities. One of the methods is validated in the simulation platform of space information network. [Copyright &y& Elsevier]

Abstract: Various aspects related to controlling induction motors are investigated. Different control strategies are explored. The direct torque control (DTC) strategy is studied in details and its relation to space vector modulation (SVM) is emphasized. An SVM-based DTC strategy is suggested and a controller design based on this strategy is presented. A Simulink model representing the controller is developed and verified using MATLAB-7. The model exhibits high modularity which makes it suitable for use in different induction motor control systems simulation scenarios. Each block in the model is developed from the very basic capabilities of Simulink which makes the model very suitable for testing and debugging. A modular model for the induction motor based on Krause''s model is developed. This model is used in the simulation instead of the built-in Simulink induction motor block, in order to enable testing of various parts of the induction motor model and to gain a deep insight in machine''s operation. This model is tested separately and showed to be working properly through simulating direct AC startup in Simulink. The performance of control is evaluated through simulating the whole system in Simulink and the suggested SVM-based DTC controlling system is shown to be superior to other controlling strategies investigated in the literature. It also shows that the induction motor settles down faster when using the suggested strategy compared to other previously studied strategies. [Copyright &y& Elsevier]

This paper presents a comprehensive analytical investigation of the four-switch three-phase (B4) voltage source inverter. The double Fourier integral analysis is used as an analytical approach to determine the phase-leg switched voltage spectrum under condition of natural sampling. The performance of two proposed switching sequences are subsequently evaluated when the harmonic copper losses are chosen as performance criterion. For a clear identification of dc-link voltage, the spectrum of dc-link current is characterized by convolution of switching function spectrum and corresponding phase current spectrum, in which fundamental component appears causing offset and fluctuation in dc-link two-capacitor voltages. The offset can be suppressed by certain switching states, whereas the effect of fluctuation must be neutralized through analytical compensation for modulating waveforms. Otherwise, symmetry of three-phase output currents and reliable operation of the system will not be retained. Finally, the analytically calculated spectrum of output voltage and dc-link current are demonstrated by comparing with those obtained by fast Fourier transform (FFT) analysis of simulated waveforms in MATLAB/SIMULINK. The capacitor voltage offset suppression and fluctuation effect neutralization are carried out by simulations and experiments, in which the results confirm the validity of the analytical investigation. [ABSTRACT FROM AUTHOR]

This paper proposes a generalized space vector pulse width modulation (SVPWM) technique for hybrid multilevel inverters for minimizing total harmonic distortion (THD). The proposed method easily determines the actual location of the instantaneous reference space vector and the corresponding switching sequence of a multilevel inverter. The proposed algorithm offers a novel method for minimizing the total harmonic distortion (THD) of the output voltage of the inverter and uses simple arithmetic for determining the sector and does not require lookup tables. The proposed method can be extended to any n-level inverter, and a generalized algorithm is also proposed. Finally, the algorithm was implemented on a Digital Signal Processor (DSP) and the scheme is explained for a five level inverter, and experimental results are presented for a five level inverter. [ABSTRACT FROM AUTHOR]