Research of the Unity Theory Between Three-level Space Vector and Carrier-based PWM Modulation Strategy

两电平空间矢量脉宽调制（space vector pulse widthmodulation,SVPWM）与正弦脉宽调制（sinusoidal pulse widthmodulation,SPWM）存有一定的本质关系,对于三电平,在常见的8段式SVPWM序列中可以证明,SVPWM与SPWM本质上也存在某种统一。实际的SVPWM调制中,由于要考虑中点电压平衡、减少谐波等其它性能问题,一般会利用开关冗余状态得到8段以上的开关调制序列。目前的文献中还未曾有对这些情况进行统一性地验证,因此三电平SVPWM与SPWM的统一理论存在一定的不足。研究发现,可通过严格地理论推导将传统意义上的调制波分解为2个子调制波,再进行SPWM调制,可以得到与SVPWM完全吻合的序列。该文在此方法基础上深入研究了8段以上（10、12、14段）的SVPWM调制序列与SPWM的统一。经过严格地理论推导,成功实现了含任意段数的SVPWM序列与SPWM的统一。仿真结果证明了该理论的正确性。

Reliability-based multidisciplinary design optimization using incremental shifting vector strategy and its application in electronic product design

Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the efficiency and convergence of the overall solution process,a decoupling algorithm for RBMDO is proposed herein.Firstly, to decouple the multidisciplinary analysis using the individual disciplinary feasible(IDF) approach, the RBMDO is converted into a conventional form of RBDO. Secondly,the incremental shifting vector(ISV) strategy is adopted to decouple the nested optimization of RBDO into a sequential iteration process composed of design optimization and reliability analysis, thereby improving the efficiency significantly. Finally, the proposed RBMDO method is applied to the design of two actual electronic products: an aerial camera and a car pad. For these two applications, two RBMDO models are created, each containing several finite element models(FEMs) and relatively strong coupling between the involved disciplines. The computational results demonstrate the effectiveness of the proposed method.

A Space Vector PWM Scheme for Multilevel Inverters Based on Two-Level Space Vector PWM

Ⅰ. INTRODUCTION MULTILEVEL inverters are increasingly being used in high-power medium voltage applications due to their superior performance compared to two-level inverters, such as lower common-mode voltage, lower dv/dt, lower harmonics in output voltage and current, and reduced voltage on the power switches.

Corner-Based Image Alignment using Pyramid Structure with Gradient Vector Similarity

This paper presents a corner-based image alignment algorithm based on the procedures of corner-based template matching and geometric parameter estimation. This algorithm consists of two stages: 1) training phase, and 2) matching phase. In the training phase, a corner detection algorithm is used to extract the corners. These corners are then used to build the pyramid images. In the matching phase, the corners are obtained using the same corner detection algorithm. The similarity measure is then determined by the differences of gradient vector between the corners obtained in the template image and the inspection image, respectively. A parabolic function is further applied to evaluate the geometric relationship between the template and the inspection images. Results show that the corner-based template matching outperforms the original edge-based template matching in efficiency, and both of them are robust against non-liner light changes. The accuracy and precision of the corner-based image alignment are competitive to that of edge-based image alignment under the same environment. In practice, the proposed algorithm demonstrates its precision, efficiency and robustness in image alignment for real world applications.

A C-Based Variable Length and Vector Pipeline Architecture Design Methodology and Its Application

The size and performance of a System LSI depend heavily on the architecture which is chosen. As a result, the architecture design phase is one of the most important steps in the System LSI development process and is critical to the commercial success of a device. In this paper, we propose a C-based variable length and vector pipeline (VVP) architecture design methodology and apply it to the design of the output probability computation circuit for a speech recognition system. VVP processing accelerated by loop optimization, memory access methods, and application-specific cir- cuit design was implemented to calculate the Hidden Markov Model (HMM) output probability at high speed and its performance is evaluated. It is shown that designers can explore a wide range of design choices and generate complex circuits in a short time by using a C-based pipeline architecture design method.

An Agent-Based Model for Studying the Impact of Herd Mobility on the Spread of Vector-Borne Diseases: The Case of Rift Valley Fever (Ferlo Senegal)

Vector-borne diseases are highly sensitive to environment and to environmental changes. Rift Valley Fever (RFV) is a mosquito-borne zootic virus associated with severe diseases in human beings and economic consequences to livestock sector. Animal and human movements have a fundamental impact on RVF transmission. In recent years, there has been a growing interest in the use of mathematics and agent based models to represent and analyze the dynamic of RFV transmission. However, no previous study has taken into consideration animal herds’ mobility and precipitation factors to understand the disease spread. This limitation underlines the necessity to use computational model approach based on multi-agent system in the study of vector-borne diseases transmission and diffusion. In this paper, a multi-agent system combining conceptual model expressiveness is used to study animal herds’ mobility and the precipitation parameter impact on the Rift Valley Fever outbreak in Ferlo Barkedji in Northern Senegal. Simulation scenarios with various parameters, including rain quality, hosts, vectors, camp dispersal around ponds, etc., are unrolled. The different results we have obtained show that the evolution of the number of infected hosts and infected vectors depend on the degree of animal herds’ mobility and on precipitations. Our model provides a framework that permits predicting the spread of the disease associated with the mobility of animal herds.

Multimode Process Monitoring Based on the Density-Based Support Vector Data Description

Complex industry processes often need multiple operation modes to meet the change of production conditions. In the same mode,there are discrete samples belonging to this mode. Therefore,it is important to consider the samples which are sparse in the mode.To solve this issue,a new approach called density-based support vector data description( DBSVDD) is proposed. In this article,an algorithm using Gaussian mixture model( GMM) with the DBSVDD technique is proposed for process monitoring. The GMM method is used to obtain the center of each mode and determine the number of the modes. Considering the complexity of the data distribution and discrete samples in monitoring process,the DBSVDD is utilized for process monitoring. Finally,the validity and effectiveness of the DBSVDD method are illustrated through the Tennessee Eastman( TE) process.

A 330-500 GHz Zero-Biased Broadband Tripler Based on Terahertz Monolithic Integrated Circuits

A 330-500 GHz zero-biased broadband monolithic integrated tripler is reported. The measured results show that the maximum efficiency and the maximum output power are 2% and 194μW at 348 GHz. The saturation characteristic test shows that the output i dB compression point is about -8.5 dBm at 334 GHz and the maximum efficiency is obtained at the point, which is slightly below the 1 dB compression point. Compared with the conventional hybrid integrated circuit, a major advantage of the monolithic integrated circuit is the significant improvement of reliability and consistency. In this work, a terahertz monolithic frequency multiplier at this band is designed and fabricated.

An E-Commerce Recommender System Based on Content-Based Filtering

Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.

Formability of Rare Earth-Containing Solid Solution Based on Compounds with Scheelite-Type Structure

The regularities of the solid solutions between the scheelite-type compounds and rare earth molybdates or tungstates were investigated by the atomic parameter-support vector machine method and the intelligent database of phase diagrams of molten salt systems. The crystal structure of scheelite-type compounds having M^1M^′Ⅲ （XO4）2（X = Mo, W） as common formula and the formability of the continuous solid solution between these compounds and rare earth molybdates or tungstates were also investigated. Besides, the cell constants of these compounds can be calculated by some semi-empirical equations. Based on the obtained relationships, the results of computerized prediction of the solid solubility of T1Pr （MoO4）2-Pr2 （MoO4）3 system have good agreement with experimental results.

Identification of Question and Non-Question Segments in Arabic Monologues Using Prosodic Features: Novel Type-2 Fuzzy Logic and Sensitivity-Based Linear Learning Approaches

In this paper, we extend our previous study of addressing the important problem of automatically identifying question and non-question segments in Arabic monologues using prosodic features. We propose here two novel classification approaches to this problem: one based on the use of the powerful type-2 fuzzy logic systems (type-2 FLS) and the other on the use of the discriminative sensitivity-based linear learning method (SBLLM). The use of prosodic features has been used in a plethora of practical applications, including speech-related applications, such as speaker and word recognition, emotion and accent identification, topic and sentence segmentation, and text-to-speech applications. In this paper, we continue to specifically focus on the Arabic language, as other languages have received a lot of attention in this regard. Moreover, we aim to improve the performance of our previously-used techniques, of which the support vector machine (SVM) method was the best performing, by applying the two above-mentioned powerful classification approaches. The recorded continuous speech is first segmented into sentences using both energy and time duration parameters. The prosodic features are then extracted from each sentence and fed into each of the two proposed classifiers so as to classify each sentence as a Question or a Non-Question sentence. Our extensive simulation work, based on a moderately-sized database, showed the two proposed classifiers outperform SVM in all of the experiments carried out, with the type-2 FLS classifier consistently exhibiting the best performance, because of its ability to handle all forms of uncertainties.

SELECTING CLUSTER MODEL IN Sn - BASED SOLDER ALLOY DESIGN WITH DV - X_α CALCULATION METHOD

Applying calculation method in alloy design should be an important tendency due to its characters of inexpensive cost, high efficiency and prediction. DOS calculations of AuSn, AsSn and SbSn Sn- based alloys have been investigated by employing DV - Xa method, in which different cluster models were adopted to calculate electron structure.It is proved that some regulations must be taken into ac- count in order to carry out alloy design calculation successfully,which are described in this paper in detail.

Content-based image retrieval applied to BI-RADS tissue classification in screening mammography

AIM:To present a content-based image retrieval(CBIR) system that supports the classification of breast tissue density and can be used in the processing chain to adapt parameters for lesion segmentation and classification.METHODS:Breast density is characterized by image texture using singular value decomposition(SVD) and histograms.Pattern similarity is computed by a support vector machine(SVM) to separate the four BI-RADS tissue categories.The crucial number of remaining singular values is varied(SVD),and linear,radial,and polynomial kernels are investigated(SVM).The system is supported by a large reference database for training and evaluation.Experiments are based on 5-fold cross validation.RESULTS:Adopted from DDSM,MIAS,LLNL,and RWTH datasets,the reference database is composed of over 10000 various mammograms with unified and reliable ground truth.An average precision of 82.14% is obtained using 25 singular values(SVD),polynomial kernel and the one-against-one(SVM).CONCLUSION:Breast density characterization using SVD allied with SVM for image retrieval enable the development of a CBIR system that can effectively aid radiologists in their diagnosis.

Preparation and the Pore Structure of Viscose-based Activated Carbon Fibers Treated with Pretreatment Reagents

The viscose rayon was pretreated with four different pre-treatment reagents respectively, and the preparation ofactivated carbon fibers (ACF) was performed undersame carbonizing and activating conditions. The poresize distribution, the specific surface area, and the porestructure parameter of these viscose - based ACF werestudied by using quartz spring balance BET- weightmethod. The experiment result indicates that the poresize distribution and the pore structure parameter ofACF is varied by using different pretreatment reagents.

GRAPHICAL COMPUTING METHOD ON FOUR-BAR LINKAGE(1)——Inflexion Circle,Focal Axis,Ball's Point,Centering-point Curve and Circling-point Curve For Four ISPs,Coupler Curves Based on Ball's Points——

By means of programs GTMPAC based- on generalized triangle method,analysis and synthesis of mechanism design in accordance with absolutely graphicalmethod( absolutely germetrical method) are developed.In this paper,we make aspecial study about centering- point curve and circling- point curve and couplercurves based on Ball’s points.

Beamforming analysis based on CSB sin-FDA

This paper studies the adaptive beamforming algorithm based on the frequency diverse array(FDA)array where the interference is located at the same angle(but different range)with the target.We take the cross subarray-based FDA with sinusoidal frequency offset(CSB sin-FDA)as the receiving array instead of the basic FDA.The sampling covariance matrix under insufficient snapshot can be corrected by the automatic diagonal loading method.On the basis of decomposing the mismatched steering vector error into a vertical component and a parallel one,this paper searches the vertical component of the error by the quadratic constraint method.The numerical simulation verifies that the beamformer based on the CSB sin-FDA can effectively hold the mainlobe at the target position when the snapshot is insufficient or the steering vector is mismatched.

Some Group Runs Based Multivariate Control Charts for Monitoring the Process Mean Vector

In this article, we propose two control charts namely, the “Multivariate Group Runs’ (MV-GR-M)” and the “Multivariate Modified Group Runs’ (MV-MGR-M)” control charts, based on the multivariate normal processes, for monitoring the process mean vector. Methods to obtain the design parameters and operations of these control charts are discussed. Performances of the proposed charts are compared with some existing control charts. It is verified that, the proposed charts give a significant reduction in the out-of-control “Average Time to Signal” (ATS) in the zero state, as well in the steady state compared to the Hotelling’s T2 and the synthetic T2 control charts.

Autonomous Kernel Based Models for Short-Term Load Forecasting

The application of support vector machines to forecasting problems is becoming popular, lately. Several comparisons between neural networks trained with error backpropagation and support vector machines have shown advantage for the latter in different domains of application. However, some difficulties still deteriorate the performance of the support vector machines. The main one is related to the setting of the hyperparameters involved in their training. Techniques based on meta-heuristics have been employed to determine appropriate values for those hyperparameters. However, because of the high noneonvexity of this estimation problem, which makes the search for a good solution very hard, an approach based on Bayesian inference, called relevance vector machine, has been proposed more recently. The present paper aims at investigating the suitability of this new approach to the short-term load forecasting problem.

Efficient Reliability-Based Optimization Scheme for Piezoelectric Composite Beams with Delamination under Axial Compression

An efficient computational framework for reliability analysis and reliability-based design optimization of piezoelectric composite beam with delamination is presented.In the proposed approach,the transverse shear deformation,delamination and piezoelectricity of the beam are taken into account.By introducing the Heaviside step function into the displacement components and using the Rayleigh-Ritz method,and the buckling governing equations for the piezoelectric composite beams is obtained.The reliability of the beams is obtained by integrating the support vector machine method and first order reliability method,further the reliability-based optimization is executed through employing genetic algorithm.The effects of ply style,delamination length and voltage are discussed in details.Numerical results indicate that the comprehensive computational scheme provides a unified numerical framework to analysis the nondeterministic buckling and reliability efficiently.

Key Technology in Developing Web-Based Engineering Drawing CAI Software

Key techniques to improve the quality of developing Web-based engineering drawing CAI software are discussed and some experience in applying commercial tools for generating vector drawing, concise representation of 3D solids, real-time interactive animation, data management etc. is illustrated. A Web-based Engineering Drawing CAI software 'Solid Projection' has been implemented by using these techniques.