Abstract: In this paper is investigated a possible
optimization of some linear algebra problems which can be
solved by parallel processing using the special arrays called
systolic arrays. In this paper are used some special types of
transformations for the designing of these arrays. We show
the characteristics of these arrays. The main focus is on
discussing the advantages of these arrays in parallel
computation of matrix product, with special approach to the
designing of systolic array for matrix multiplication.
Multiplication of large matrices requires a lot of
computational time and its complexity is O(n3 ). There are
developed many algorithms (both sequential and parallel) with
the purpose of minimizing the time of calculations. Systolic
arrays are good suited for this purpose. In this paper we show
that using an appropriate transformation implicates in finding
more optimal arrays for doing the calculations of this type.
Abstract: The present work compares the performance of three
turbulence modeling approach (based on the two-equation k -ε
model) in predicting erosive wear in multi-size dense slurry flow
through rotating channel. All three turbulence models include
rotation modification to the production term in the turbulent kineticenergy
equation. The two-phase flow field obtained numerically
using Galerkin finite element methodology relates the local flow
velocity and concentration to the wear rate via a suitable wear model.
The wear models for both sliding wear and impact wear mechanisms
account for the particle size dependence. Results of predicted wear
rates using the three turbulence models are compared for a large
number of cases spanning such operating parameters as rotation rate,
solids concentration, flow rate, particle size distribution and so forth.
The root-mean-square error between FE-generated data and the
correlation between maximum wear rate and the operating
parameters is found less than 2.5% for all the three models.
Abstract: Self-Excited Induction Generator (SEIG) builds up voltage while it enters in its magnetic saturation region. Due to non-linear magnetic characteristics, the performance analysis of SEIG involves cumbersome mathematical computations. The dependence of air-gap voltage on saturated magnetizing reactance can only be established at rated frequency by conducting a laboratory test commonly known as synchronous run test. But, there is no laboratory method to determine saturated magnetizing reactance and air-gap voltage of SEIG at varying speed, terminal capacitance and other loading conditions. For overall analysis of SEIG, prior information of magnetizing reactance, generated frequency and air-gap voltage is essentially required. Thus, analytical methods are the only alternative to determine these variables. Non-existence of direct mathematical relationship of these variables for different terminal conditions has forced the researchers to evolve new computational techniques. Artificial Neural Networks (ANNs) are very useful for solution of such complex problems, as they do not require any a priori information about the system. In this paper, an attempt is made to use cascaded neural networks to first determine the generated frequency and magnetizing reactance with varying terminal conditions and then air-gap voltage of SEIG. The results obtained from the ANN model are used to evaluate the overall performance of SEIG and are found to be in good agreement with experimental results. Hence, it is concluded that analysis of SEIG can be carried out effectively using ANNs.
Abstract: Seemingly simple probabilities in the m-player game bingo have never been calculated. These probabilities include expected game length and the expected number of winners on a given turn. The difficulty in probabilistic analysis lies in the subtle interdependence among the m-many bingo game cards in play. In this paper, the game i got it!, a bingo variant, is considered. This variation provides enough weakening of the inter-player dependence to allow probabilistic analysis not possible for traditional bingo. The probability of winning in exactly k turns is calculated for a one-player game. Given a game of m-many players, the expected game length and tie probability are calculated. With these calculations, the game-s interesting payout scheme is considered.
Abstract: Although achieving zero-defect software release is
practically impossible, software industries should take maximum
care to detect defects/bugs well ahead in time allowing only bare
minimums to creep into released version. This is a clear indicator of
time playing an important role in the bug detection. In addition to
this, software quality is the major factor in software engineering
process. Moreover, early detection can be achieved only through
static code analysis as opposed to conventional testing.
BugCatcher.Net is a static analysis tool, which detects bugs in .NET®
languages through MSIL (Microsoft Intermediate Language)
inspection. The tool utilizes a Parser based on Finite State Automata
to carry out bug detection. After being detected, bugs need to be
corrected immediately. BugCatcher.Net facilitates correction, by
proposing a corrective solution for reported warnings/bugs to end
users with minimum side effects. Moreover, the tool is also capable
of analyzing the bug trend of a program under inspection.
Abstract:
Innovation is becoming more and more important in
modern society. There are a lot of researches on different kinds of
innovation but marketing innovation is one kind of innovation that
has not been studied frequently before. Marketing innovation is
defined as a new way in which companies can market themselves to
potential or existing customers.
The study shows some key elements for marketing innovation that
are worth paying attention to when implementing marketing
innovation projects. Examples of such key elements are: paying
attention to the neglected market, suitable market segmentatio
reliable market information, public relationship, increased customer
value, combination of market factors, explore different marketing
channels and the use of technology in combination with what? Beside
the key elements for marketing innovation, we also present some
risks that may occur, such as cost, market uncertainty, information
leakage, imitation and overdependence on experience.
By proposing a set of indicators to measure marketing innovation,
the article offers solutions for marketing innovation implementation
so that any organization can achieve optimal results.
Abstract: In recent years, copulas have become very popular in
financial research and actuarial science as they are more flexible in
modelling the co-movements and relationships of risk factors as compared
to the conventional linear correlation coefficient by Pearson.
However, a precise estimation of the copula parameters is vital in
order to correctly capture the (possibly nonlinear) dependence structure
and joint tail events. In this study, we employ two optimization
heuristics, namely Differential Evolution and Threshold Accepting to
tackle the parameter estimation of multivariate t distribution models
in the EML approach. Since the evolutionary optimizer does not rely
on gradient search, the EML approach can be applied to estimation of
more complicated copula models such as high-dimensional copulas.
Our experimental study shows that the proposed method provides
more robust and more accurate estimates as compared to the IFM
approach.
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: Since after the historical moment of Malaysia
Independence Day on the year of 1957, the government had been trying hard in order to find the most efficient methods in learning.
However, it is hard to actually access and evaluate students whom will then be called an excellent student. It because in our realtime
student who excellent is only excel in academic. This evaluation
become a problem because it not balance in our real life interm of to get an excellent student in whole area in their involvement of curiculum and co-curiculum. To overcome this scenario, we
proposed a method called Student Idol to evaluate student through
three categories which are academic, co-curiculum and leadership.
All the categories have their own merit point. Using this method, student will be evaluated more accurate compared to the previously.
So, teacher can easily evaluate their student without having any emotion factor, relation factor and others. As conclustion this method will helps student evaluation more accurate and valid.
Abstract: Temperature dependence of force of gravitation is one
of the fundamental problems of physics. This problem has got special
value in connection with that the general theory of relativity,
supposing the weakest positive influence of a body temperature on its
weight, actually rejects an opportunity of measurement of negative
influence of temperature on gravity in laboratory conditions. Really,
the recognition of negative temperature dependence of gravitation,
for example, means basic impossibility of achievement of a
singularity («a black hole») at a gravitational collapse. Laboratory
experiments with exact weighing the heated up metal samples,
indicating negative influence temperatures of bodies on their physical
weight are described. Influence of mistakes of measurements is
analyzed. Calculations of distribution of temperature in volume of the
bar, agreed with experimental data of time dependence of weight of
samples are executed. The physical substantiation of negative
temperature dependence of weight of the bodies, based on correlation
of acceleration at thermal movement of micro-particles of a body and
its absolute temperature, are given.
Abstract: It is known that an analog Hopfield neural network
with time delay can generate the outputs which are similar to the
human electroencephalogram. To gain deeper insights into the
mechanisms of rhythm generation by the Hopfield neural networks
and to study the effects of noise on their activities, we investigated
the behaviors of the networks with symmetric and asymmetric
interneuron connections. The neural network under the study consists
of 10 identical neurons. For symmetric (fully connected) networks all
interneuron connections aij = +1; the interneuron connections for
asymmetric networks form an upper triangular matrix with non-zero
entries aij = +1. The behavior of the network is described by 10
differential equations, which are solved numerically. The results of
simulations demonstrate some remarkable properties of a Hopfield
neural network, such as linear growth of outputs, dependence of
synchronization properties on the connection type, huge
amplification of oscillation by the external uniform noise, and the
capability of the neural network to transform one type of noise to
another.
Abstract: In the past many uneconomic solutions for limitation
and interruption of short-circuit currents in low power applications
have been introduced, especially polymer switch based on the
positive temperature coefficient of resistance (PCTR) concept.
However there are many limitations in the active material, which
consists of conductive fillers. This paper presents a significantly
improved and simplified approach that replaces the existing current
limiters with faster switching elements. Its elegance lies in the
remarkable simplicity and low-cost processes of producing the device
using polyaniline (PANI) doped with methane-sulfonic acid (MSA).
Samples characterized as lying in the metallic and critical regimes of
metal insulator transition have been studied by means of electrical
performance in the voltage range from 1V to 5 V under different
environmental conditions. Moisture presence is shown to increase the
resistivity and also improved its current limiting performance.
Additionally, the device has also been studied for electrical resistivity
in the temperature range 77 K-300 K. The temperature dependence of
the electrical conductivity gives evidence for a transport mechanism
based on variable range hopping in three dimensions.
Abstract: Transition prediction of boundary layers has always
been an important problem in fluid mechanics both theoretically and
practically, yet notwithstanding the great effort made by many
investigators, there is no satisfactory answer to this problem. The most
popular method available is so-called e-N method which is heavily
dependent on experiments and experience. The author has proposed
improvements to the e-N method, so to reduce its dependence on
experiments and experience to a certain extent. One of the key
assumptions is that transition would occur whenever the velocity
amplitude of disturbance reaches 1-2% of the free stream velocity.
However, the reliability of this assumption needs to be verified. In this
paper, transition prediction on a flat plate is investigated by using both
the improved e-N method and the parabolized stability equations (PSE)
methods. The results show that the transition locations predicted by
both methods agree reasonably well with each other, under the above
assumption. For the supersonic case, the critical velocity amplitude in
the improved e-N method should be taken as 0.013, whereas in the
subsonic case, it should be 0.018, both are within the range 1-2%.
Abstract: In many data mining applications, it is a priori known
that the target function should satisfy certain constraints imposed
by, for example, economic theory or a human-decision maker. In this
paper we consider partially monotone prediction problems, where the
target variable depends monotonically on some of the input variables
but not on all. We propose a novel method to construct prediction
models, where monotone dependences with respect to some of
the input variables are preserved by virtue of construction. Our
method belongs to the class of mixture models. The basic idea is to
convolute monotone neural networks with weight (kernel) functions
to make predictions. By using simulation and real case studies,
we demonstrate the application of our method. To obtain sound
assessment for the performance of our approach, we use standard
neural networks with weight decay and partially monotone linear
models as benchmark methods for comparison. The results show that
our approach outperforms partially monotone linear models in terms
of accuracy. Furthermore, the incorporation of partial monotonicity
constraints not only leads to models that are in accordance with the
decision maker's expertise, but also reduces considerably the model
variance in comparison to standard neural networks with weight
decay.
Abstract: Longitudinal data typically have the characteristics of
changes over time, nonlinear growth patterns, between-subjects
variability, and the within errors exhibiting heteroscedasticity and
dependence. The data exploration is more complicated than that of
cross-sectional data. The purpose of this paper is to organize/integrate
of various visual-graphical techniques to explore longitudinal data.
From the application of the proposed methods, investigators can
answer the research questions include characterizing or describing the
growth patterns at both group and individual level, identifying the time
points where important changes occur and unusual subjects, selecting
suitable statistical models, and suggesting possible within-error
variance.
Abstract: Removal of PCP by a system combining
biodegradation by biofilm and adsorption was investigated here.
Three studies were conducted employing batch tests, sequencing
batch reactor (SBR) and continuous biofilm activated carbon
column reactor (BACCOR). The combination of biofilm-GAC
batch process removed about 30% more PCP than GAC adsorption
alone. For the SBR processes, both the suspended and attached
biomass could remove more than 90% of the PCP after
acclimatisation. BACCOR was able to remove more than 98% of
PCP-Na at concentrations ranging from 10 to 100 mg/L, at empty
bed contact time (EBCT) ranging from 0.75 to 4 hours. Pure and
mixed cultures from BACCOR were tested for use of PCP as sole
carbon and energy source under aerobic conditions. The isolates
were able to degrade up to 42% of PCP under aerobic conditions in
pure cultures. However, mixed cultures were found able to degrade
more than 99% PCP indicating interdependence of species.
Abstract: This study reports the preparation of soft magnetic ribbons of Fe-based amorphous alloys using the single-roller melt-spinning technique. Ribbon width varied from 142 mm to 213 mm and, with a thickness of approximately 22 μm 2 μm. The microstructure and magnetic properties of the ribbons were characterized by differential scanning calorimeter (DSC), X-ray diffraction (XRD), vibrating sample magnetometer (VSM), and electrical resistivity measurements (ERM). The amorphous material properties dependence of the cooling rate and nozzle pressure have uneven surface in ribbon thicknesses are investigated. Magnetic measurement results indicate that some region of the ribbon exhibits good magnetic properties, higher saturation induction and lower coercivity. However, due to the uneven surface of 213 mm wide ribbon, the magnetic responses are not uniformly distributed. To understand the transformer magnetic performances, this study analyzes the measurements of a three-phase 2 MVA amorphous-cored transformer. Experimental results confirm that the transformer with a ribbon width of 142 mm has better magnetic properties in terms of lower core loss, exciting power, and audible noise.
Abstract: As the Internet continues to grow at a rapid pace as
the primary medium for communications and commerce and as
telecommunication networks and systems continue to expand their
global reach, digital information has become the most popular and
important information resource and our dependence upon the
underlying cyber infrastructure has been increasing significantly.
Unfortunately, as our dependency has grown, so has the threat to the
cyber infrastructure from spammers, attackers and criminal
enterprises. In this paper, we propose a new machine learning based
network intrusion detection framework for cyber security. The
detection process of the framework consists of two stages: model
construction and intrusion detection. In the model construction stage,
a semi-supervised machine learning algorithm is applied to a
collected set of network audit data to generate a profile of normal
network behavior and in the intrusion detection stage, input network
events are analyzed and compared with the patterns gathered in the
profile, and some of them are then flagged as anomalies should these
events are sufficiently far from the expected normal behavior. The
proposed framework is particularly applicable to the situations where
there is only a small amount of labeled network training data
available, which is very typical in real world network environments.
Abstract: In Iran, due to abundance of energy resources, energy consumption is extraordinarily higher than international standards and transportation sector is considered to be one of the major consumers of energy. Moreover, air pollution in urban areas as a result of high dependence on private vehicle and lower standards of vehicles, high subsidies spent on fuel and time waste due to traffic congestion in urban areas all have led to speculations on new strategies and policies in order to control energy consumption in transportation sector. These strategies and policies will be introduced in this paper and their consequences will be analyzed with consideration to socio-economic factors affecting the urban society of Iran. Besides, the intention is to suggest and analyze new approaches such as broader application of public transportation system, demand management in transport sector, replacement of deteriorated vehicles, quality improvement in car manufacture and introduction of substitute fuels.
Abstract: In this paper, study on carbonation process of several types of advanced plasters on lime basis is presented. The movement of carbonation head was measured by colorimetric method using phenolphtalein. The rate of carbonation was accessed also by gravimetric method. Samples of studied materials were placed into the climatic chamber for simulation of environment with high concentration of CO2. The particular samples were on all lateral sides and on the bottom side provided by epoxy resin in order to arrange 1-D transport of CO2 into the studied samples. The carbonation rates of particular materials pointed to the time dependence of diffusion process of CO2 for all the studied plasters. From the quantitative point of view, the carbonation of advanced modified plasters was much faster than for the reference lime plaster, what is beneficial for the practical application of the tested newly developed materials.