Abstract: One of the primary uses of higher order statistics in
signal processing has been for detecting and estimation of non-
Gaussian signals in Gaussian noise of unknown covariance. This is
motivated by the ability of higher order statistics to suppress additive
Gaussian noise. In this paper, several methods to test for non-
Gaussianity of a given process are presented. These methods include
histogram plot, kurtosis test, and hypothesis testing using cumulants
and bispectrum of the available sequence. The hypothesis testing is
performed by constructing a statistic to test whether the bispectrum
of the given signal is non-zero. A zero bispectrum is not a proof of
Gaussianity. Hence, other tests such as the kurtosis test should be
employed. Examples are given to demonstrate the performance of the
presented methods.
Abstract: An innovative approach utilizing highly alkaline oil
shale waste ash and carbon dioxide gas (CO2), associated with power
production, as a resource for production of precipitated calcium
carbonate (PCC) is introduced in this paper. The specifics and
feasibility of the integrated ash valorization and CO2 sequestration
process by indirect aqueous carbonation of lime-consisting ash were
elaborated and the main parameters established. Detailed description
of the formed precipitates was included. Complimentary carbonation
experiments with commercial CaO fine powder were conducted for
comparative characterization of the final products obtained on the
basis of two different raw materials. Finally, the expected CO2
uptake was evaluated.
Abstract: The objective of positioning the fixture elements in
the fixture is to make the workpiece stiff, so that geometric errors in
the manufacturing process can be reduced. Most of the work for
optimal fixture layout used the minimization of the sum of the nodal
deflection normal to the surface as objective function. All deflections
in other direction have been neglected. We propose a new method for
fixture layout optimization in this paper, which uses the element
strain energy. The deformations in all the directions have been
considered in this way. The objective function in this method is to
minimize the sum of square of element strain energy. Strain energy
and stiffness are inversely proportional to each other. The
optimization problem is solved by the sequential quadratic
programming method. Three different kinds of case studies are
presented, and results are compared with the method using nodal
deflections as objective function to verify the propose method.
Abstract: This paper examines the impact of information and
communication technology (ICT) usage, internal relationship,
supplier-retailer relationship, logistics services and inventory
management on convenience store suppliers- performance. Data was
collected from 275 convenience store managers in Malaysia using a
set of questionnaire. The multiple linear regression results indicate
that inventory management, supplier-retailer relationship, logistics
services and internal relationship are predictors of supplier
performance as perceived by convenience store managers. However,
ICT usage is not a predictor of supplier performance. The study
focuses only on convenience stores and petrol station convenience
stores and concentrates only on managers. The results provide
insights to suppliers who serve convenience stores and possibly
similar retail format on factors to consider in improving their service
to retailers. The results also provide insights to government in its
aspiration to improve business operations of convenience store to
consider ways to enhance the adoption of ICT by retailers and
suppliers.
Abstract: The state of the art in instructional design for
computer-assisted learning has been strongly influenced by advances
in information technology, Internet and Web-based systems. The
emphasis of educational systems has shifted from training to
learning. The course delivered has also been changed from large
inflexible content to sequential small chunks of learning objects. The
concepts of learning objects together with the advanced technologies
of Web and communications support the reusability, interoperability,
and accessibility design criteria currently exploited by most learning
systems. These concepts enable just-in-time learning. We propose to
extend theses design criteria further to include the learnability
concept that will help adapting content to the needs of learners. The
learnability concept offers a better personalization leading to the
creation and delivery of course content more appropriate to
performance and interest of each learner. In this paper we present a
new framework of learning environments containing knowledge
discovery as a tool to automatically learn patterns of learning
behavior from learners' profiles and history.
Abstract: Laser soldering is based on applying some soldering material (albumin) onto the approximated edges of the cut and heating the solder (and the underlying tissues) by a laser beam. Endogenous and exogenous materials such as indocyanine green (ICG) are often added to solders to enhance light absorption. Gold nanoshells are new materials which have an optical response dictated by the plasmon resonance. The wavelength at which the resonance occurs depends on the core and shell sizes, allowing nanoshells to be tailored for particular applications. The purposes of this study was use combination of ICG and different concentration of gold nanoshells for skin tissue soldering and also to examine the effect of laser soldering parameters on the properties of repaired skin. Two mixtures of albumin solder and different combinations of ICG and gold nanoshells were prepared. A full thickness incision of 2×20 mm2 was made on the surface and after addition of mixtures it was irradiated by an 810nm diode laser at different power densities. The changes of tensile strength σt due to temperature rise, number of scan (Ns), and scan velocity (Vs) were investigated. The results showed at constant laser power density (I), σt of repaired incisions increases by increasing the concentration of gold nanoshells in solder, Ns and decreasing Vs. It is therefore important to consider the tradeoff between the scan velocity and the surface temperature for achieving an optimum operating condition. In our case this corresponds to σt =1800 gr/cm2 at I~ 47 Wcm-2, T ~ 85ºC, Ns =10 and Vs=0.3mms-1.
Abstract: A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.
Abstract: Color categorization is shared among members in a
society. This allows communication of color, especially when using
natural language such as English. Hence sociable robot, to live
coexist with human in human society, must also have the shared
color categorization. To achieve this, many works have been done
relying on modeling of human color perception and mathematical
complexities. In contrast, in this work, the computer as brain of the
robot learns color categorization through interaction with humans
without much mathematical complexities.
Abstract: In this study, we investigated the effects of ginger and
L-carnitine on the reproductive performance of male rats with respect
to semen parameters, male sex hormones and the testicular
antioxidant system. A total of sixty mature male albino rats were
divided into four groups of fifteen rats. The control group received
saline, whereas the other three groups received ginger (100 mg kg-1 d-
1.), L-carnitine (150 mg kg-1 d-1.) or a combination of both ginger
(100 mg kg-1 d-1.) and L-carnitine (150 mg kg-1 d-1.) via a stomach
tube daily for one month. At the end of the treatment period, the rats
were sacrificed, and their sperm characteristics (count, motility and
viability), antioxidant enzyme factors levels (reduced glutathione,
catalase, superoxide dismutase and total antioxidant capacity) and sex
hormone levels (testosterone, Follicle stimulating hormone(FSH) and
luteinizing hormone (LH) were analysed. Our results showed that the
three experimental treatments improved sperm parameters,
antioxidant enzyme activity and testosterone hormone levels; the
most pronounced positive effects were observed in the group that
received a combination of both ginger and L-carnitine. Therefore, the
administration of a combination of ginger and L-carnitine may be
beneficial for improving male sexual performance.
Abstract: ECG analysis method was developed using ROC
analysis of PVC detecting algorithm. ECG signal of MIT-BIH
arrhythmia database was analyzed by MATLAB. First of all, the
baseline was removed by median filter to preprocess the ECG signal.
R peaks were detected for ECG analysis method, and normal VCG
was extracted for VCG analysis method. Four PVC detecting
algorithm was analyzed by ROC curve, which parameters are
maximum amplitude of QRS complex, width of QRS complex, r-r
interval and geometric mean of VCG. To set cut-off value of
parameters, ROC curve was estimated by true-positive rate
(sensitivity) and false-positive rate. sensitivity and false negative rate
(specificity) of ROC curve calculated, and ECG was analyzed using
cut-off value which was estimated from ROC curve. As a result, PVC
detecting algorithm of VCG geometric mean have high availability,
and PVC could be detected more accurately with amplitude and width
of QRS complex.
Abstract: Named Entity Recognition (NER) aims to classify each word of a document into predefined target named entity classes and is now-a-days considered to be fundamental for many Natural Language Processing (NLP) tasks such as information retrieval, machine translation, information extraction, question answering systems and others. This paper reports about the development of a NER system for Bengali and Hindi using Support Vector Machine (SVM). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Indian languages (ILs) is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named (NE) classes, such as Person name, Location name, Organization name and Miscellaneous name. We have used the annotated corpora of 122,467 tokens of Bengali and 502,974 tokens of Hindi tagged with the twelve different NE classes 1, defined as part of the IJCNLP-08 NER Shared Task for South and South East Asian Languages (SSEAL) 2. In addition, we have manually annotated 150K wordforms of the Bengali news corpus, developed from the web-archive of a leading Bengali newspaper. We have also developed an unsupervised algorithm in order to generate the lexical context patterns from a part of the unlabeled Bengali news corpus. Lexical patterns have been used as the features of SVM in order to improve the system performance. The NER system has been tested with the gold standard test sets of 35K, and 60K tokens for Bengali, and Hindi, respectively. Evaluation results have demonstrated the recall, precision, and f-score values of 88.61%, 80.12%, and 84.15%, respectively, for Bengali and 80.23%, 74.34%, and 77.17%, respectively, for Hindi. Results show the improvement in the f-score by 5.13% with the use of context patterns. Statistical analysis, ANOVA is also performed to compare the performance of the proposed NER system with that of the existing HMM based system for both the languages.
Abstract: We present on the method of inverse coherence matrix for the estimation of network connectivity from multivariate time series of a complex system. In a model system of coupled chaotic oscillators, it is shown that the inverse coherence matrix defined as the inverse of cross coherence matrix is proportional to the network connectivity. Therefore the inverse coherence matrix could be used for the distinction between the directly connected links from indirectly connected links in a complex network. We compare the result of network estimation using the method of the inverse coherence matrix with the results obtained from the coherence matrix and the partial coherence matrix.
Abstract: The present study was done primarily to address two major research gaps: firstly, development of an empirical measure of life meaningfulness for substance users and secondly, to determine the psychosocial determinants of life meaningfulness among the substance users. The study is classified into two phases: the first phase which dealt with development of Life Meaningfulness Scale and the second phase which examined the relationship between life meaningfulness and social support, abstinence self efficacy and depression. Both qualitative and quantitative approaches were used for framing items. A Principal Component Analysis yielded three components: Overall Goal Directedness, Striving for healthy lifestyle and Concern for loved ones which collectively accounted for 42.06% of the total variance. The scale and its subscales were also found to be highly reliable. Multiple regression analyses in the second phase of the study revealed that social support and abstinence self efficacy significantly predicted life meaningfulness among 48 recovering inmates of a de-addiction center while level of depression failed to predict life meaningfulness.
Abstract: To satisfy the need of outfield tests of star sensors, a
method is put forward to construct the reference attitude benchmark.
Firstly, its basic principle is introduced; Then, all the separate
conversion matrixes are deduced, which include: the conversion
matrix responsible for the transformation from the Earth Centered
Inertial frame i to the Earth-centered Earth-fixed frame w according to
the time of an atomic clock, the conversion matrix from frame w to the
geographic frame t, and the matrix from frame t to the platform frame
p, so the attitude matrix of the benchmark platform relative to the
frame i can be obtained using all the three matrixes as the
multiplicative factors; Next, the attitude matrix of the star sensor
relative to frame i is got when the mounting matrix from frame p to the
star sensor frame s is calibrated, and the reference attitude angles for
star sensor outfield tests can be calculated from the transformation
from frame i to frame s; Finally, the computer program is finished to
solve the reference attitudes, and the error curves are drawn about the
three axis attitude angles whose absolute maximum error is just 0.25ÔÇ│.
The analysis on each loop and the final simulating results manifest that
the method by precise timing to acquire the absolute reference attitude
is feasible for star sensor outfield tests.
Abstract: The photoluminescence (PL) at 1.55 μm from
semiconducting β-FeSi2 has attracted a noticeable interest for
silicon-based optoelectronic applications. Moreover, its high optical
absorption coefficient (higher than 105 cm-1 above 1.0 eV) allows this
semiconducting material to be used as photovoltanics devices.
A clear PL spectrum for β-FeSi2 was observed by Cu or Au coating
on Si(001). High-crystal-quality β-FeSi2 with a low-level nonradiative
center was formed on a Cu- or Au- reated Si layer. This method of
deposition can be applied to other materials requiring high crystal
quality.
Abstract: This research is aimed to compare the percentages of correct classification of Empirical Bayes method (EB) to Classical method when data are constructed as near normal, short-tailed and long-tailed symmetric, short-tailed and long-tailed asymmetric. The study is performed using conjugate prior, normal distribution with known mean and unknown variance. The estimated hyper-parameters obtained from EB method are replaced in the posterior predictive probability and used to predict new observations. Data are generated, consisting of training set and test set with the sample sizes 100, 200 and 500 for the binary classification. The results showed that EB method exhibited an improved performance over Classical method in all situations under study.
Abstract: In recent years, rapid advances in software and hardware in the field of information technology along with a digital imaging revolution in the medical domain facilitate the generation and storage of large collections of images by hospitals and clinics. To search these large image collections effectively and efficiently poses significant technical challenges, and it raises the necessity of constructing intelligent retrieval systems. Content-based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images[5]. Medical CBIR (content-based image retrieval) applications pose unique challenges but at the same time offer many new opportunities. On one hand, while one can easily understand news or sports videos, a medical image is often completely incomprehensible to untrained eyes.
Abstract: The problem of natural convection about a cone embedded in a porous medium at local Rayleigh numbers based on the boundary layer approximation and the Darcy-s law have been studied before. Similarity solutions for a full cone with the prescribed wall temperature or surface heat flux boundary conditions which is the power function of distance from the vertex of the inverted cone give us a third-order nonlinear differential equation. In this paper, an approximate method for solving higher-order ordinary differential equations is proposed. The approach is based on a rational Chebyshev Tau (RCT) method. The operational matrices of the derivative and product of rational Chebyshev (RC) functions are presented. These matrices together with the Tau method are utilized to reduce the solution of the higher-order ordinary differential equations to the solution of a system of algebraic equations. We also present the comparison of this work with others and show that the present method is applicable.
Abstract: Nonlinear finite element method with eight noded
isoparametric quadrilateral element is used for prediction of loaddeformation
behavior including bearing capacity of foundations.
Modified generalized plasticity model with non-associated flow rule
is applied for analysis of soil-footing system. Also Von Mises and
Tresca criterions are used for simulation of soil behavior. Modified
generalized plasticity model is able to simulate load-deformation
including softening behavior. Localization phenomena are considered
by different meshes. Localization phenomena have not been seen in
the examples. Predictions by modified generalized plasticity model
show good agreement with laboratory data and theoretical prediction
in comparison the other models.
Abstract: The analysis of Acoustic Emission (AE) signal
generated from metal cutting processes has often approached
statistically. This is due to the stochastic nature of the emission
signal as a result of factors effecting the signal from its generation
through transmission and sensing. Different techniques are applied in
this manner, each of which is suitable for certain processes. In metal
cutting where the emission generated by the deformation process is
rather continuous, an appropriate method for analysing the AE signal
based on the root mean square (RMS) of the signal is often used and
is suitable for use with the conventional signal processing systems.
The aim of this paper is to set a strategy in tool failure detection in
turning processes via the statistic analysis of the AE generated from
the cutting zone. The strategy is based on the investigation of the
distribution moments of the AE signal at predetermined sampling.
The skews and kurtosis of these distributions are the key elements in
the detection. A normal (Gaussian) distribution has first been
suggested then this was eliminated due to insufficiency. The so
called Beta distribution was then considered, this has been used with
an assumed β density function and has given promising results with
regard to chipping and tool breakage detection.