Abstract: A family of improved secant-like method is proposed in this paper. Further, the analysis of the convergence shows that this method has super-linear convergence. Efficiency are demonstrated by numerical experiments when the choice of α is correct.
Abstract: The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.
Abstract: This paper presents a new true RMS-to-DC converter
circuit based on a square-root-domain squarer/divider. The circuit is
designed by employing up-down translinear loop and using of
MOSFET transistors that operate in strong inversion saturation
region. The converter offer advantages of two-quadrant input current,
low circuit complexity, low supply voltage (1.2V) and immunity
from the body effect. The circuit has been simulated by HSPICE.
The simulation results are seen to conform to the theoretical analysis
and shows benefits of the proposed circuit.
Abstract: Analysis for the propagation of elastic waves in
arbitrary anisotropic plates is investigated, commencing with a
formal analysis of waves in a layered plate of an arbitrary anisotropic
media, the dispersion relations of elastic waves are obtained by
invoking continuity at the interface and boundary of conditions on
the surfaces of layered plate. The obtained solutions can be used for
material systems of higher symmetry such as monoclinic,
orthotropic, transversely isotropic, cubic, and isotropic as it is
contained implicitly in the analysis. The cases of free layered plate
and layered half space are considered separately. Some special cases
have also been deduced and discussed. Finally numerical solution of
the frequency equations for an aluminum epoxy is carried out, and
the dispersion curves for the few lower modes are presented. The
results obtained theoretically have been verified numerically and
illustrated graphically.
Abstract: The research objective of the project and article “The impact of Structural Funds on the growth of competitiveness of Polish agriculture" is to assess competitiveness of regions in Poland from the perspective of Polish agriculture by analysing the efficiency of the use of Structural Funds, the economic procedure of their distribution and the regulatory and organisational framework under the Rural Development Programme (RDP). It must be stressed that defining the scope of research in the above manner limits the analysis only to the part of Structural Funds directed to support Polish agriculture.
Abstract: In this paper effect of stator slots structure and
switching angle on a cylindrical single-phase brushless direct current
motor (BLDC) is analyzed. BLDC motor with three different
structures for stator slots is designed by using RMxprt software and
efficiency of BLDC motor for different structures in full-load
condition has been presented. Then the BLDC motor in different
conditions by using Maxwell 3D software is designed and with finite
element method is analyzed electromagnetically. At the end with the
use of MATLAB software influence of switching angle on motor
performance investigated and optimal angle has been determined.
The results indicate that with correct choosing of stator slots structure
and switching angle, maximum efficiency can be found.
Abstract: The concurrent era is characterised by strengthened interactions among financial markets and increased capital mobility globally. In this frames we examine the effects the international financial integration process has on the European bond markets. We perform a comparative study of the interactions of the European and international bond markets and exploit Cointegration analysis results on the elimination of stochastic trends and the decomposition of the underlying long run equilibria and short run causal relations. Our investigation provides evidence on the relation between the European integration process and that of globalisation, viewed through the bond markets- sector. Additionally the structural formulation applied, offers significant implications of the findings. All in all our analysis offers a number of answers on crucial queries towards the European bond markets integration process.
Abstract: Sickness absence represents a major economic and
social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is
often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient
and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using
a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model
selection and a critical analysis of the temporal trends, the occurrence
and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large
sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to
select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model
applicability to complicated longitudinal data.
Abstract: the research was conducted using the self report of
shoplifters who apprehended in the supermarket while stealing. 943
shoplifters in three years were interviewed right after the stealing act
and before calling the police. The aim of the study is to know the
shoplifting characteristics in Saudi Arabia, including the trait of
shoplifters and the situation of the supermarkets where the stealing
takes place. The analysis based on the written information about each
thief as the documentary research method. Descriptive statistics as
well as some inferential statistics were employed. The result shows
that there are differences between genders, age groups, occupations,
time of the day, days of the week, months, way of stealing, individual
or group of thieves and other supermarket situations in the type of
items stolen, total price and the count of items. The result and the
recommendation will serve as a guide for retailers where, when and
who to look at to prevent shoplifting.
Abstract: An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.
Abstract: The purposes of this research are to study and develop
the algorithm of Thai spoonerism words by semi-automatic computer
programs, that is to say, in part of data input, syllables are already
separated and in part of spoonerism, the developed algorithm is
utilized, which can establish rules and mechanisms in Thai
spoonerism words for bi-syllables by utilizing analysis in elements of
the syllables, namely cluster consonant, vowel, intonation mark and
final consonant. From the study, it is found that bi-syllable Thai
spoonerism has 1 case of spoonerism mechanism, namely
transposition in value of vowel, intonation mark and consonant of
both 2 syllables but keeping consonant value and cluster word (if
any).
From the study, the rules and mechanisms in Thai spoonerism
word were applied to develop as Thai spoonerism word software,
utilizing PHP program. the software was brought to conduct a
performance test on software execution; it is found that the program
performs bi-syllable Thai spoonerism correctly or 99% of all words
used in the test and found faults on the program at 1% as the words
obtained from spoonerism may not be spelling in conformity with
Thai grammar and the answer in Thai spoonerism could be more than
1 answer.
Abstract: In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.
Abstract: The traditional Failure Mode and Effects Analysis
(FMEA) uses Risk Priority Number (RPN) to evaluate the risk level
of a component or process. The RPN index is determined by
calculating the product of severity, occurrence and detection indexes.
The most critically debated disadvantage of this approach is that
various sets of these three indexes may produce an identical value of
RPN. This research paper seeks to address the drawbacks in
traditional FMEA and to propose a new approach to overcome these
shortcomings. The Risk Priority Code (RPC) is used to prioritize
failure modes, when two or more failure modes have the same RPN.
A new method is proposed to prioritize failure modes, when there is a
disagreement in ranking scale for severity, occurrence and detection.
An Analysis of Variance (ANOVA) is used to compare means of
RPN values. SPSS (Statistical Package for the Social Sciences)
statistical analysis package is used to analyze the data. The results
presented are based on two case studies. It is found that the proposed
new methodology/approach resolves the limitations of traditional
FMEA approach.
Abstract: This study presents a systematic analysis of the
dynamic behaviors of a gear-bearing system with porous squeeze film
damper (PSFD) under nonlinear suspension, nonlinear oil-film force
and nonlinear gear meshing force effect. It can be found that the
system exhibits very rich forms of sub-harmonic and even the chaotic
vibrations. The bifurcation diagrams also reveal that greater values of
permeability may not only improve non-periodic motions effectively,
but also suppress dynamic amplitudes of the system. Therefore, porous
effect plays an important role to improve dynamic stability of
gear-bearing systems or other mechanical systems. The results
presented in this study provide some useful insights into the design
and development of a gear-bearing system for rotating machinery that
operates in highly rotational speed and highly nonlinear regimes.
Abstract: This paper deals optimized model to investigate the
effects of peak current, pulse on time and pulse off time in EDM performance on material removal rate of titanium alloy utilizing copper tungsten as electrode and positive polarity of the electrode. The experiments are carried out on Ti6Al4V. Experiments were
conducted by varying the peak current, pulse on time and pulse off time. A mathematical model is developed to correlate the influences of these variables and material removal rate of workpiece. Design of
experiments (DOE) method and response surface methodology
(RSM) techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through
analysis of variance (ANOVA). The obtained results evidence that as
the material removal rate increases as peak current and pulse on time
increases. The effect of pulse off time on MRR changes with peak ampere. The optimum machining conditions in favor of material removal rate are verified and compared. The optimum machining
conditions in favor of material removal rate are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about
4%) when compared to experimental results. This result leads to desirable material removal rate and economical industrial machining to optimize the input parameters.
Abstract: The study of the geometric shape of the plunging wave enclosed vortices as a possible indicator for the breaking intensity of ocean waves has been ongoing for almost 50 years with limited success. This paper investigates the validity of using the vortex ratio and vortex angle as methods of predicting breaking intensity. Previously published works on vortex parameters, based on regular wave flume results or solitary wave theory, present contradictory results and conclusions. Through the first complete analysis of field collected irregular wave breaking vortex parameters it is illustrated that the vortex ratio and vortex angle cannot be accurately predicted using standard breaking wave characteristics and hence are not suggested as a possible indicator for breaking intensity.
Abstract: Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.
Abstract: It was analyzed of fatty acid composition of 16 strains
of microalgae lipid fractions isolated from different basins of
Kazakhstan and characterized by stable active growth in the
laboratory. Three species of green microalgae (Oocystis
rhomboideus, Chlorococcum infusionum, Dictyochlorella globosa)
and three species of diatoms (Synedra sp., Nitzshia sp., Pleurosigma
attenuatum) are characterized by a high content of lipids and are
promising for further study as a source of polyunsaturated fatty acids.
Abstract: Complex networks have been intensively studied across
many fields, especially in Internet technology, biological engineering,
and nonlinear science. Software is built up out of many interacting
components at various levels of granularity, such as functions, classes,
and packages, representing another important class of complex networks.
It can also be studied using complex network theory. Over the
last decade, many papers on the interdisciplinary research between
software engineering and complex networks have been published.
It provides a different dimension to our understanding of software
and also is very useful for the design and development of software
systems. This paper will explore how to use the complex network
theory to analyze software structure, and briefly review the main
advances in corresponding aspects.
Abstract: According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.