Search results for: optimum weight vector

Authors: Ronak Khosravi, Mahmood Abbasi Layegh, Siamak Haghipour, Avin Esmaili

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In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function.

Keywords: coefficient features, relevance vector machines, spectral features, support vector machines, temporal features

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Authors: Qiuxiao Chen, Yan Hou, Ning Wu

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As there are deficiencies of the classic Douglas-Peucker Algorithm (DPA), such as high risks of deleting key nodes by mistake, high complexity, time consumption and relatively slow execution speed, a new Deletion-Cost Based Compression Algorithm (DCA) for linear vector data was proposed. For each curve — the basic element of linear vector data, all the deletion costs of its middle nodes were calculated, and the minimum deletion cost was compared with the pre-defined threshold. If the former was greater than or equal to the latter, all remaining nodes were reserved and the curve’s compression process was finished. Otherwise, the node with the minimal deletion cost was deleted, its two neighbors' deletion costs were updated, and the same loop on the compressed curve was repeated till the termination. By several comparative experiments using different types of linear vector data, the comparison between DPA and DCA was performed from the aspects of compression quality and computing efficiency. Experiment results showed that DCA outperformed DPA in compression accuracy and execution efficiency as well.

Keywords: Douglas-Peucker algorithm, linear vector data, compression, deletion cost

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Authors: Ju-Hong Lee, Ching-Wei Liao

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Adaptive beamforming using antenna array of sensors is useful in the process of adaptively detecting and preserving the presence of the desired signal while suppressing the interference and the background noise. For conventional adaptive array beamforming, we require a prior information of either the impinging direction or the waveform of the desired signal to adapt the weights. The adaptive weights of an antenna array beamformer under a steered-beam constraint are calculated by minimizing the output power of the beamformer subject to the constraint that forces the beamformer to make a constant response in the steering direction. Hence, the performance of the beamformer is very sensitive to the accuracy of the steering operation. In the literature, it is well known that the performance of an adaptive beamformer will be deteriorated by any steering angle error encountered in many practical applications, e.g., the wireless communication systems with massive antennas deployed at the base station and user equipment. Hence, developing effective signal processing techniques to deal with the problem due to steering angle error for array beamforming systems has become an important research work. In this paper, we present an effective signal processing technique for constructing an adaptive beamformer against the steering angle error. The proposed array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. Based on the presumed steering vector and a preset angle range for steering mismatch tolerance, we first create a matrix related to the direction vector of signal sources. Two projection matrices are generated from the matrix. The projection matrix associated with the desired signal information and the received array data are utilized to iteratively estimate the actual direction vector of the desired signal. The estimated direction vector of the desired signal is then used for appropriately finding the quiescent weight vector. The other projection matrix is set to be the signal blocking matrix required for performing adaptive beamforming. Accordingly, the proposed beamformer consists of adaptive quiescent weights and partially adaptive weights. Several computer simulation examples are provided for evaluating and comparing the proposed technique with the existing robust techniques.

Keywords: adaptive beamforming, robustness, signal blocking, steering angle error

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Authors: Surinder Deswal, Mahesh Pal

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The paper investigates the potential of support vector machines based regression approach to model the mass transfer capacity of multiple plunging jets, both vertical (θ = 90°) and inclined (θ = 60°). The data set used in this study consists of four input parameters with a total of eighty eight cases. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 (root mean square error values of 0.0025 and 0.0020) were achieved by using polynomial and radial basis kernel functions based support vector regression respectively. Results suggest an improved performance by radial basis function in comparison to polynomial kernel based support vector machines. The estimated overall mass transfer coefficient, by both the kernel functions, is in good agreement with actual experimental values (within a scatter of ±15 %); thereby suggesting the utility of support vector machines based regression approach.

Keywords: mass transfer, multiple plunging jets, support vector machines, ecological sciences

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Authors: Kamel Belammi, Houria Fatrim

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imbalanced data set, a problem often found in real world application, can cause seriously negative effect on classification performance of machine learning algorithms. There have been many attempts at dealing with classification of imbalanced data sets. In medical diagnosis classification, we often face the imbalanced number of data samples between the classes in which there are not enough samples in rare classes. In this paper, we proposed a learning method based on a cost sensitive extension of Least Mean Square (LMS) algorithm that penalizes errors of different samples with different weight and some rules of thumb to determine those weights. After the balancing phase, we applythe different classifiers (support vector machine (SVM), k- nearest neighbor (KNN) and multilayer neuronal networks (MNN)) for balanced data set. We have also compared the obtained results before and after balancing method.

Keywords: multilayer neural networks, k- nearest neighbor, support vector machine, imbalanced medical data, least mean square algorithm, diabetes

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Authors: Ersilio Tushaj

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The efficient solution that satisfies the optimal condition is an important issue in the structural engineering design problem. The new codes of structural design consist in design methodology that looks after the exploitation of the total resources of the construction material. In recent years some non-deterministic or meta-heuristic structural optimization algorithms have been developed widely in the research community. These methods search the optimum condition starting from the simulation of a natural phenomenon, such as survival of the fittest, the immune system, swarm intelligence or the cooling process of molten metal through annealing. Among these techniques the most known are: the genetic algorithms, simulated annealing, evolution strategies, particle swarm optimization, tabu search, ant colony optimization, harmony search and big bang crunch optimization. In this study, five of these algorithms are applied for the optimum weight design of a steel truss structure with variable geometry but fixed topology. The design process selects optimum distances and size sections from a set of commercial steel profiles. In the formulation of the design problem are considered deflection limitations, buckling and allowable stress constraints. The approach is repeated starting from different initial populations. The design problem topology is taken from an existing steel structure. The optimization process helps the engineer to achieve good final solutions, avoiding the repetitive evaluation of alternative designs in a time consuming process. The algorithms used for the application, the results of the optimal solutions, the number of iterations and the minimal weight designs, will be reported in the paper. Based on these results, it would be estimated, the amount of the steel that could be saved by applying structural analysis combined with non-deterministic optimization methods.

Keywords: structural optimization, non-deterministic methods, truss structures, steel truss

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generators (DFIG) due to their advantages like speed variation and four-quadrant operation, find its application in wind turbines. DFIG besides supplying power to the grid has to support reactive power (kvar) under grid voltage variations, should contribute minimum fault current during faults, have high efficiency, minimum weight, adequate rotor protection during crow-bar-operation from +20% to -20% of rated speed.  To achieve the optimum performance, a good electromagnetic design of DFIG is required. In this paper, a simple and heuristic global optimization – Differential Evolution has been used. Variables considered are lamination details such as slot dimensions, stack diameters, air gap length, and generator stator and rotor stack length. Two operating conditions have been considered - voltage and speed variations. Constraints included were reactive power supplied to the grid and limiting fault current and torque. The optimization has been executed separately for three objective functions - maximum efficiency, weight reduction, and grid fault stator currents. Subsequent calculations led to the conclusion that designs determined through differential evolution help in determining an optimum electrical design for each objective function.

Keywords: design optimization, performance, DFIG, differential evolution

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Authors: Vahid Zeighami, Mohsen Ghsemi, Reza Akbari

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In this work, a Multi-Level Artificial Bee Colony (called MLABC) is presented. In MLABC two species are used. The first species employs n colonies in which each of the them optimizes the complete solution vector. The cooperation between these colonies is carried out by exchanging information through a leader colony, which contains a set of elite bees. The second species uses a cooperative approach in which the complete solution vector is divided to k sub-vectors, and each of these sub-vectors is optimized by a a colony. The cooperation between these colonies is carried out by compiling sub-vectors into the complete solution vector. Finally, the cooperation between two species is obtained by exchanging information between them. The proposed algorithm is tested on a set of well known test functions. The results show that MLABC algorithms provide efficiency and robustness to solve numerical functions.

Keywords: artificial bee colony, cooperative, multilevel cooperation, vector

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Authors: Justin Nwabanne, Sam Omenyi, Jeremiah Chukwuneke

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This work presents structural nonlinear static analysis of a horizontal taut cable using Finite Element Analysis (FEA) method. The FEA was performed analytically to determine the tensions at each nodal point and subsequently, performed based on finite element displacement method computationally using the FEA software, ANSYS 14.0 to determine their behaviour under the influence of aerodynamic forces imposed on the cable. The convergence procedure is adapted into the method to prevent excessive displacements through the computations. The work compared the two FEA cases by examining the effectiveness of the analytical model in describing the response with few degrees of freedom and the ability of the nonlinear finite element procedure adopted to capture the complex features of cable dynamics with reference to the aerodynamic external influence. Results obtained from this work explain that the analytic FEM results without aerodynamic influence show a parabolic response with an optimum deflection at nodal points 12 and 13 with the cable weight at nodes 12 and 13 having the value -1.002936N while for the cable tension shows an optimum deflection value for nodes 12 and 13 at -189396.97kg/km. The maximum displacement for the cable system was obtained from ANSYS 14.0 as 4483.83 mm for X, Y and Z components of displacements at node number 2 while the maximum displacement obtained is 4218.75mm for all the directional components. The dynamic behaviour of a taut cable investigated has application in a typical power transmission line. Aerodynamic influences on the cables were considered using FEA approach by employing ANSYS 14.0 showed a complex modal behaviour as expected.

Keywords: aerodynamics, cable tension and weight, finite element analysis, nodal, non-linear model, optimum deflection, suspended cable, transmission line

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Authors: Filipa Cortez, Vanessa Pereira

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Introduction: The main challenge of obesity treatment is long-term weight loss maintenance. The 3 phases method is a weight loss program that combines a low carb and moderately high-protein diet, food supplements and a weekly one-to-one consultation with a certified nutritionist. Sustained weight control is the ultimate goal of phase 3. Success criterion was the minimum loss of 10% of initial weight and its maintenance after 12 months. Objective: The aim of this study was to identify factors associated with successful weight loss maintenance after 12 months at the end of 3 phases method. Methods: The study included 199 subjects that achieved their weight loss goal (phase 3). Weight and body mass index (BMI) were obtained at the baseline and every week until the end of the program. Therapeutic adherence was measured weekly on a Likert scale from 1 to 5. Subjects were considered in compliance with nutritional recommendation and supplementation when their classification was ≥ 4. After 12 months of the method, the current weight and number of previous weight-loss attempts were collected by telephone interview. The statistical significance was assumed at p-values < 0.05. Statistical analyses were performed using SPSS TM software v.21. Results: 65.3% of subjects met the success criterion. The factors which displayed a significant weight loss maintenance prediction were: greater initial percentage weight loss (OR=1.44) during the weight loss intervention and a higher number of consultations in phase 3 (OR=1.10). Conclusion: These findings suggest that the percentage weight loss during the weight loss intervention and the number of consultations in phase 3 may facilitate maintenance of weight loss after the 3 phases method.

Keywords: obesity, weight maintenance, low-carbohydrate diet, dietary supplements

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Authors: Raed Hameed Allawi

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Wellbore instability problems are considered the majority challenge for several wells in the Ratawi shale formation. However, it results in non-productive (NPT) time and increased well-drilling expenditures. This work aims to construct an integrated mechanical earth model (MEM) to predict the wellbore failure and design optimum mud weight to improve the drilling efficiency of future wells. The MEM was based on field data, including open-hole wireline logging and measurement data. Several failure criteria were applied in this work, including Modified Lade, Mogi-Coulomb, and Mohr-Coulomb that utilized to calculate the proper mud weight and practical drilling paths and orientations. Results showed that the leading cause of wellbore instability problems was inadequate mud weight. Moreover, some improper drilling practices and heterogeneity of Ratawi formation were additional causes of the increased risk of wellbore instability. Therefore, the suitable mud weight for safe drilling in the Ratawi shale formation should be 11.5-13.5 ppg. Furthermore, the mud weight should be increased as required depending on the trajectory of the planned well. The outcome of this study is as practical tools to reduce non-productive time and well costs and design future neighboring deviated wells to get high drilling efficiency. In addition, the current results serve as a reference for similar fields in that region because of the lacking of published studies regarding wellbore instability problems of the Ratawi Formation in southern Iraqi oilfields.

Keywords: wellbore stability, hole collapse, horizontal stress, MEM, mud window

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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Authors: Nadia Ben Youssef, Aicha Bouzid

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Gradient estimation is one of the most fundamental tasks in the field of image processing in general, and more particularly for color images since that the research in color image gradient remains limited. The widely used gradient method is Di Zenzo’s gradient operator, which is based on the measure of squared local contrast of color images. The proposed gradient mechanism, presented in this paper, is based on the principle of the Di Zenzo’s approach using quaternion representation. This edge detector is compared to a marginal approach based on multiscale product of wavelet transform and another vector approach based on quaternion convolution and vector gradient approach. The experimental results indicate that the proposed color gradient operator outperforms marginal approach, however, it is less efficient then the second vector approach.

Keywords: gradient, edge detection, color image, quaternion

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Authors: Hesam Sedaghat Nejad, Navid Hosseini, Arash Nikvar Hassani

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Determination of the optimum block size with high profitability is one of the significant parameters in designation of the building stone mines. The aim of this study was to determine the optimum dimensions of building stone blocks in Delichai travertine mine of Damavand in Tehran province through combining the effective parameters proven in determination of the optimum dimensions in building stones such as the spacing of joints and gaps, extraction tools constraints with the help of modeling by Gemcom software. To this end, following simulation of the topography of the mine, the block model was prepared and then in order to use spacing joints and discontinuities as a limiting factor, the existing joints set was added to the model. Since only one almost horizontal joint set with a slope of 5 degrees was available, this factor was effective only in determining the optimum height of the block, and thus to determine the longitudinal and transverse optimum dimensions of the extracted block, the power of available loader in the mine was considered as the secondary limiting factor. According to the aforementioned factors, the optimal block size in this mine was measured as 3.4×4×7 meter.

Keywords: building stone, optimum block size, Delichay travertine mine, loader power

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Authors: Chayanon Boonyuid

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This paper experiments the effects of low-density polyethylene (LDPE) on the structural strength and permeability of hot-mix-asphalt (HMA) pavements. Different proportions of bitumen (4%, 4.5%, 5%, 5.5% and 6% of total aggregates) and plastic (5%, 10% and 15% of bitumen) contents in HMA mixtures were investigated to estimate the optimum mixture of bitumen and plastic in HMA pavement with long-term performance. Marshall Tests and Falling Head Tests were performed to experiment the structure strength and permeability of HMA mixtures with different percentages of plastic materials and bitumen. The laboratory results show that the optimum binder content was 5.5% by weight of aggregates with higher contents of plastic materials, increase structural stability, reduce permanent deformation, increase ductility, and improve fatigue life of HMA pavements. The use of recycled plastic shopping bags can reduce the use of bitumen content by 0.5% - 1% in HMA mixtures resulting in cheaper material costs with better long-term performance. The plastic materials increase the impermeability of HMA pavements. This study has two-fold contributions: optimum contents of both bitumen and plastic materials in HMA mixtures and the impacts of plastic materials on the permeability of HMA pavements.

Keywords: plastic bags, bitumen, structural strength, permeability

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

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Authors: K. A. Bindu, T. V. Raja, P. M. Rojan, A. Siby

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The multivariate path coefficient approach was employed to study the effects of various production and reproduction traits on the slaughter body weight of rabbits. Information on 562 rabbits maintained at the university rabbit farm attached to the Centre for Advanced Studies in Animal Genetics, and Breeding, Kerala Veterinary and Animal Sciences University, Kerala State, India was utilized. The manifest variables used in the study were age and weight of dam, birth weight, litter size at birth and weaning, weight at first, second and third months. The linear multiple regression analysis was performed by keeping the slaughter weight as the dependent variable and the remaining as independent variables. The model explained 48.60 percentage of the total variation present in the market weight of the rabbits. Even though the model used was significant, the standardized beta coefficients for the independent variables viz., age and weight of the dam, birth weight and litter sizes at birth and weaning were less than one indicating their negligible influence on the slaughter weight. However, the standardized beta coefficient of the second-month body weight was maximum followed by the first-month weight indicating their major role on the market weight. All the other factors influence indirectly only through these two variables. Hence it was concluded that the slaughter body weight can be predicted using the first and second-month body weights. The principal components were also developed so as to achieve more accuracy in the prediction of market weight of rabbits.

Keywords: component analysis, multivariate, slaughter, regression

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Authors: Saroj Bijarnia, Preety Singh

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We propose a simple and effective biometrics system based on face verification across aging using a new variant of texture feature, Pyramid Binary Pattern. This employs Local Binary Pattern along with its hierarchical information. Dimension reduction of generated texture feature vector is done using Principal Component Analysis. Support Vector Machine is used for classification. Our proposed method achieves an accuracy of 92:24% and can be used in an automated age-invariant face verification system.

Keywords: biometrics, age invariant, verification, support vector machine

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Authors: Ju-Hong Lee, Ching-Wei Liao

Abstract:

An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

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Authors: P. Sawatnatee, S. Udomsuk, K-N. Areerak, K-L. Areerak, A. Srikaew

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The paper presents how to design the indirect vector control of three-phase induction motor drive systems using the artificial intelligence technique called the adaptive tabu search. The results from the simulation and the experiment show that the drive system with the controller designed from the proposed method can provide the best output speed response compared with those of the conventional method. The controller design using the proposed technique can be used to create the software package for engineers to achieve the optimal controller design of the induction motor speed control based on the indirect vector concept.

Keywords: indirect vector control, induction motor, adaptive tabu search, control design, artificial intelligence

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Authors: M. Attom, F. Abed, M. Elemam, M. Nazal, N. ElMessalami

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—The main objective of this paper is to study the effect of treated waste-water (TWW) on the compaction and compressibility properties of fine soil. Two types of fine soils (clayey soils) were selected for this study and classified as CH soil and Cl type of soil. Compaction and compressibility properties such as optimum water content, maximum dry unit weight, consolidation index and swell index, maximum past pressure and volume change were evaluated using both tap and treated waste water. It was found that the use of treated waste water affects all of these properties. The maximum dry unit weight increased for both soils and the optimum water content decreased as much as 13.6% for highly plastic soil. The significant effect was observed in swell index and swelling pressure of the soils. The swell indexed decreased by as much as 42% and 33% for highly plastic and low plastic soils, respectively, when TWW is used. Additionally, the swelling pressure decreased by as much as 16% for both soil types. The result of this research pointed out that the use of treated waste water has a positive effect on compaction and compression properties of clay soil and promise for potential use of this water in engineering applications. Keywords—Consolidation, proctor compaction, swell index, treated waste-water, volume change.

Keywords: consolidation, proctor compaction, swell index, treated waste-water, volume change

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Authors: Mahvish Maqbool, Muhmmad Sohail Sajid

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Ticks (Acari: Ixodidae); bloodsucking parasites of domestic animals, have significant importance in the transmission of diseases and causing huge economic losses. This study aimed to screen endophilic ticks for the Piroplasms using polymerase chain reaction in three districts Sialkot, Gujranwala and Gujarat of Punjab, Pakistan. Ticks were dissected under a stereomicroscope, and internal organs (midguts& salivary glands) were procured to generate pools of optimum weights. DNA extraction was done through standard protocol followed by primer specific PCR for Piroplasma spp. A total of 22.95% tick pools were found positive for piroplasma spp. In districts, Sialkot and Gujranwala Piroplasma prevalence are higher in riverine animals while in Gujarat Prevalence is higher in non-riverine animals. Female animals were found more prone to piroplasma as compared to males. This study will provide useful data on the distribution of Piroplasma in the vector population of the study area and devise future recommendations for better management of ruminants to avoid subclinical and clinical infections and vector transmitted diseases.

Keywords: babesia, hyalomma, piroplasmposis, tick infectivity

Procedia PDF Downloads 151

Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

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In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

Procedia PDF Downloads 229

Authors: Hala Hzam Al Otaibi

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Background: Obesity is more common among Saudi women compared to men, with 75–88% of adult women suffering from overweight or obesity and most of them married. Weight status and body appreciation are an important factor in maintaining or loss weight behaviors and for husbands satisfaction. Aims: To assess weight status, body appreciation and related factors, including age, level of education, occupation status husbands satisfaction in adult women. Methods: A cross-sectional study conducted among 326 married women, aged 18 to 60 years old in Eastern of Saudi Arabia. Data were collected by face to face interview, height and weight were measured to calculate body mass index (BMI). Body Appreciation Scale (BAS) and husbands satisfied were evaluated through questioning. Results: The majority of women has a university education, not employed and less than 40 years old (66.5%, 69.9%, 67.5%; respectively). Fifty-four percent of women overweight/obese and the rest were normal weight, BAS mean score was lower in younger women (>40 years) 7.39+2.20 and obese women (6.83+2.16) which is reflected lower body appreciation. Husbands' satisfaction regarding the weight status shows 47.6% of normal weight believed their husbands were dissatisfied with their weight and consider them as overweight/obese, 28.3% of overweight/obese thought their husbands satisfied with their weight and consider them as normal weight. Body appreciation correlated with age (r.139,p<0.05) and no correlation found for level of education and employed status. Husbands satisfaction strongly correlated with body appreciation (r.189,p<0.01) and weight status (r .570,p <0.01). Conclusion: Our findings indicate that women had a low body appreciation related to age, weight status and husbands' dissatisfaction. Future interventions aimed to weight reduction, it is important to consider husband satisfaction, as well as we need more assessment of weight satisfaction in younger women.

Keywords: body appreciation, husbands satisfaction, weight status, women

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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In this paper, we present a comparative assessment of Space Vector Pulse Width Modulation (SVPWM) and Model Predictive Control (MPC) for two-level three phase (2L-3P) Voltage Source Inverter (VSI). VSI with associated system is subjected to both control techniques and the results are compared. Matlab/Simulink was used to model, simulate and validate the control schemes. Findings of this study show that MPC is superior to SVPWM in terms of total harmonic distortion (THD) and implementation.

Keywords: voltage source inverter, space vector pulse width modulation, model predictive control, comparison

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Authors: Afsheen Aman, Shah Ali Ul Qader

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Dextransucrase [EC 2.4.1.5] is a glucosyltransferase that catalysis the biosynthesis of a natural biopolymer called dextran. It can catalyze the transfer of D-glucopyranosyl residues from sucrose to the main chain of dextran. This unique biopolymer has multiple applications in several industries and the key utilization of dextran lies on its molecular weight and the type of branching. Extracellular dextransucrase from Leuconostoc mesenteroides is most extensively studied and characterized. Limited data is available regarding cell-bound or intracellular dextransucrase and on the characterization of dextran produced by in-vitro reaction of intracellular dextransucrase. L. mesenteroides AA1 is reported to produce extracellular dextransucrase that catalyzes biosynthesis of a high molecular weight dextran with only α-(1→6) linkage. Current study deals with the characterization of an intracellular dextransucrase and in vitro biosynthesis of low molecular weight dextran from L. mesenteroides AA1. Intracellular dextransucrase was extracted from cytoplasm and purified to homogeneity for characterization. Kinetic constants, molecular weight and N-terminal sequence analysis of intracellular dextransucrase reveal unique variation with previously reported extracellular dextransucrase from the same strain. In vitro synthesized biopolymer was characterized using NMR spectroscopic techniques. Intracellular dextransucrase exhibited Vmax and Km values of 130.8 DSU ml-1 hr-1 and 221.3 mM, respectively. Optimum catalytic activity was detected at 35°C in 0.15 M citrate phosphate buffer (pH-5.5) in 05 minutes. Molecular mass of purified intracellular dextransucrase is approximately 220.0 kDa on SDS-PAGE. N-terminal sequence of the intracellular enzyme is: GLPGYFGVN that showed no homology with previously reported sequence for the extracellular dextransucrase. This intracellular dextransucrase is capable of in vitro synthesis of dextran under specific conditions. This intracellular dextransucrase is capable of in vitro synthesis of dextran under specific conditions and this biopolymer can be hydrolyzed into different molecular weight fractions for various applications.

Keywords: characterization, dextran, dextransucrase, leuconostoc mesenteroides

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Authors: Navid Khayat

Abstract:

Drained shear strength of saturated soils is fully understood. Shear strength of unsaturated soils is usually expressed in terms of soil suction. Evaluation of shear strength of compacted mixtures of sand–clay at optimum water content is main purpose of this research. To prepare the required samples, first clay and sand are mixed in 10, 30, 50, and 70 percent by dry weight and then compacted at the proper optimum water content according to the standard proctor test. The samples were sheared in direct shear machine. Stress –strain relationship of samples indicated a ductile behavior. Most of the samples showed a dilatancy behavior during the shear and the tendency for dilatancy increased with the increase in sand proportion. The results show that with the increase in percentage of sand a decrease in cohesion intercept c' for mixtures and an increase in the angle of internal friction Φ’is observed.

Keywords: clay, sand, drained shear strength, cohesion intercept

Procedia PDF Downloads 412

Authors: Herlena Hayati, Diyan Reni Jayathi, Hairida Anggun, Citra Amelia

Abstract:

This systematic review research is aimed to find out anemia maternal during pregnancy as a risk factor of low birth weight. This research was done by searching some journals which have associated to maternal anemia during pregnancy with low birth weight that had been published in journal accreditation and scopus index. Study literature that researcher had been done by March – April 2016 through online library of UI. The journals that had been selected according to inclusive criteria and exclusive criteria had been through the critial appraisal process. This systematic review towards 4 journals that had been selected and published showed the significant result statistically that anemia maternal is one of the risk factors which causes low birth weight. Anemia maternal on the first-trimester pregnancy showed significant association with low birth weight. Moderate anemia and severe anemia also showed significant association with low birth weight. Meanwhile, mild anemia doesn’t have an association with low birth weight. The conclusion of this study is anemia maternal (as an independent risk factor) have an influence towards low birth weight.

Keywords: anemia maternal, low birth weight, pregnancy, systematic review

Procedia PDF Downloads 255

Authors: Hassnen M. Jafer, W. Atherton, F. Ruddock, E. Loffil

Abstract:

Waste materials or sometimes called by-product materials have been increasingly used as construction material to reduce the usage of cement in different construction projects. In the field of soil stabilisation, waste materials such as pulverised fuel ash (PFA), biomass fly ash (BFA), sewage sludge ash (SSA), etc., have been used since 1960s in last century. In this study, a particular type of a waste material (WM) was used in soft soil stabilisation as a cement replacement, as well as, the effect of mechanical activation, using grinding, on the performance of this WM was also investigated. The WM used in this study is a by-product resulted from the incineration processes between 1000 and 1200oc in domestic power generation plant using a fluidized bed combustion system. The stabilised soil in this study was an intermediate plasticity silty clayey soil with medium organic matter content. The experimental works were conducted first to find the optimum content of WM by carrying out Atterberg limits and unconfined compressive strength (UCS) tests on soil samples contained (0, 3, 6, 9, 12, and 15%) of WM by the dry weight of soil. The UCS test was carried out on specimens provided to different curing periods (zero, 7, 14, and 28 days). Moreover, the optimum percentage of the WM was subject to different periods of grinding (10, 20, 30, 40mins) using mortar and pestle grinder to find the effect of grinding and its optimum time by conducting UCS test. The results indicated that the WM used in this study improved the physical properties of the soft soil where the index of plasticity (IP) was decreased significantly from 21 to 13.10 with 15% of WM. Meanwhile, the results of UCS test indicated that 12% of WM was the optimum and this percentage developed the UCS value from 202kPa to 700kPa for 28 days cured samples. Along with the time of grinding, the results revealed that 10 minutes of grinding was the best for mechanical activation for the WM used in this study.

Keywords: soft soil stabilisation, waste materials, grinding, and unconfined compressive strength

Procedia PDF Downloads 251

Authors: Hosseini Siahi Zohreh, Sana Mohammad Jafar

Abstract:

With increase in fat and over weight in children and its undesirable effects on different organisms of the body and since many of the sicknesses are due to over weight and with losing weight these sicknesses disappear, and on the other hand with mal nutrition and under weight in children other kind of sicknesses such as derogation of body's security system, frequent infection, insufficient growth, shortness, and delay in maturity etc. are some of the signs of being under weight. Therefore recognition of signs of over weight and under weight and their prevalence in children are important. To determine this difficulty we have used the body mass index as screening tool since it is very prevalent and a good and important guide and has very good relation with body fat in children. In this study 2321 students from primary schools in Behbahan have been chosen randomly and evaluated by height and weight and their body mass index have been calculated and then recorded on the BMI percentile diagram which is for age and gender. The following results obtained: The amount of total fat, over weight and slimness are 9.3, 12.1 and 12.32 percent respectively. Therefore 21.4% of the children were over weighted. It did not show any meaningful statistical relation in fat conditions among boys and girls, but there has been a meaningful statistical relation in slimness among boys and girls.

Keywords: assessment, students, Behbahan, Body Mass Index

Procedia PDF Downloads 490