Abstract: The alumosilicate ceramics with mullite crystalline phase are used in various branches of science and technique. The mullite refractory ceramics with high porosity serve as a heat insulator and as a constructional materials [1], [2]. The purpose of the work was to sinter high porosity ceramic and to increase the quantity of mullite phase in this mullite, mullite-corundum ceramics. Two types of compositions were prepared at during the experiment. The first type is compositions with commercial alumina and silica oxides. The second type is from mixing these oxides with 10, 20 and 30 wt.%. of kaolin. In all samples the Al2O3 and SiO2 were in 2.57:1 ratio, because that was conformed to mullite stechiometric compositions (3Al2O3.2SiO2). The types of alumina oxides were α-Al2O3 (d50=4µm) and γ-Al2O3 (d50=80µm). Ratios of α-: γ-Al2O3 were (1:1) or (1:3). The porous materials were prepared by slip casting of suspension of raw materials. The aluminium paste (0.18 wt.%) was used as a pore former. Water content in the suspensions was 26-47 wt.%. Pore formation occurred as a result of hydrogen formation in chemical reaction between aluminium paste and water [2]. The samples were sintered at the temperature of 1650°C and 1750°C for one hour. The increasing amount of kaolin, α-: γ-Al2O3 at the ratio (1:3) and sintering at the highest temperature raised the quantity of mullite phase. The mullite phase began to dominate over the corundum phase.
Abstract: In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.
Abstract: This paper presents a new method for estimating the nonstationary
noise power spectral density given a noisy signal. The
method is based on averaging the noisy speech power spectrum using
time and frequency dependent smoothing factors. These factors are
adjusted based on signal-presence probability in individual frequency
bins. Signal presence is determined by computing the ratio of the
noisy speech power spectrum to its local minimum, which is updated
continuously by averaging past values of the noisy speech power
spectra with a look-ahead factor. This method adapts very quickly to
highly non-stationary noise environments. The proposed method
achieves significant improvements over a system that uses voice
activity detector (VAD) in noise estimation.
Abstract: The study aims to investigate the impact on board and
audit committee characteristics and firm performance before and
after the revision of MCCG (2007) on GLCs over the period 2005-2010. We used Return on Assets (ROA) as a proxy for firm performance. The data consists of two groups; data collected before
and after the amendments of MCCG (2007). Findings show that
boards of directors with accounting / finance qualifications (BEXP)
are statistically significant with performance for period before the amendments. As for audit committee members with accounting or
finance qualifications (ACEXP), correlation results indicate a
negative association and non-significant results for the years before
amendments. However, the years after the amendments show
positive relationship with highly significant correlations (1%) to ROA. This indicates that the amendments of MCCG 2007 on the
audit committee members- literacy in accounting have impacted the governance structures and performance of GLCs.
Abstract: Drought is one of the most damaging climate-related
hazards, it is generally considered as a prolonged absence of
precipitation. This normal and recurring climate phenomenon had
plagued civilization throughout history because of the negative
impacts on economical, environmental and social sectors. Drought
characteristics are thus recognized as important factors in water
resources planning and management. The purpose of this study is to
detect the changes in drought frequency, persistence and severity
in the Ruhr river basin. The frequency of drought events was
calculated using the Standardized Precipitation Index (SPI). Used
data are daily precipitation records from seven meteorological
stations covering the period 1961-2007. The main benefit of the
application of this index is its versatility, only rainfall data is required
to deliver five major dimensions of a drought : duration, intensity,
severity, magnitude, and frequency. Furthermore, drought can be
calculated in different time steps. In this study SPI was calculated for
1, 3, 6, 9, 12, and 24 months. Several drought events were detected
in the covered period, these events contain mild, moderate and severe
droughts. Also positive and negative trends in the SPI values were
observed.
Abstract: Data clustering is an important data exploration
technique with many applications in data mining. The k-means
algorithm is well known for its efficiency in clustering large data
sets. However, this algorithm is suitable for spherical shaped clusters
of similar sizes and densities. The quality of the resulting clusters
decreases when the data set contains spherical shaped with large
variance in sizes. In this paper, we introduce a competent procedure
to overcome this problem. The proposed method is based on shifting
the center of the large cluster toward the small cluster, and recomputing
the membership of small cluster points, the experimental
results reveal that the proposed algorithm produces satisfactory
results.
Abstract: In the present study, a support vector machine (SVM) learning approach to character recognition is proposed. Simple
feature detectors, similar to those found in the human visual system, were used in the SVM classifier. Alphabetic characters were rotated
to 8 different angles and using the proposed cognitive model, all characters were recognized with 100% accuracy and specificity.
These same results were found in psychiatric studies of human character recognition.
Abstract: Iran has diverse climates and each have established distinct properties in their area. The extent and intensity of climatic factors effects on the lives of people living in various regions of Iran is so great that it cannot be simply ignored. In a large part of Iran known as the Central Plateau there is no precipitation for more than half of the year and dry weather and scarcity of fresh water pose an ever present problem for the people of these regions while in north of Iran upon the southern shores of the Caspian Sea the people face 80% humidity caused by the sea and 2 meters of annual precipitation. This article tries to review the past experiences of local architecture of Iran-s various regions so that they can be used to reshape and redirect the urban areas and structure of Iran-s current cities to provide environmental comfort by minimum use of fossil fuels.
Abstract: The presented work is motivated by a french law regarding nuclear waste management. In order to avoid the limitation coming with the usage of the existing scenario codes, as COSI, VISION or FAMILY, the Core Library for Advance Scenario Simulation (CLASS) is being develop. CLASS is an open source tool, which allows any user to simulate an electronuclear scenario. The main CLASS asset, is the possibility to include any type of reactor, even a complitely new concept, through the generation of its ACSII evolution database. In the present article, the CLASS working basis will be presented as well as a simple exemple in order to show his potentiel. In the considered exemple, the effect of the transmutation will be assessed on Minor Actinide Inventory produced by PWR reactors.
Abstract: A set of Artificial Neural Network (ANN) based methods
for the design of an effective system of speech recognition of
numerals of Assamese language captured under varied recording
conditions and moods is presented here. The work is related to
the formulation of several ANN models configured to use Linear
Predictive Code (LPC), Principal Component Analysis (PCA) and
other features to tackle mood and gender variations uttering numbers
as part of an Automatic Speech Recognition (ASR) system in
Assamese. The ANN models are designed using a combination of
Self Organizing Map (SOM) and Multi Layer Perceptron (MLP)
constituting a Learning Vector Quantization (LVQ) block trained in a
cooperative environment to handle male and female speech samples
of numerals of Assamese- a language spoken by a sizable population
in the North-Eastern part of India. The work provides a comparative
evaluation of several such combinations while subjected to handle
speech samples with gender based differences captured by a microphone
in four different conditions viz. noiseless, noise mixed, stressed
and stress-free.
Abstract: The purpose of this research was to study the
influence of learning efficiency on local accountants’ job
performance effectiveness. This paper drew upon the survey data
collected from 335 local accountants survey conducted at Nakhon
Ratchasima province, Thailand. The statistics utilized in this paper
included percentage, mean, standard deviation, and regression
analysis. The findings revealed that the majority of samples were
between 31-40 years old, married, held an undergraduate degree, and
had an average income between 10,000-15,000 baht. The majority of
respondents had less than five years of accounting experience and
worked for local administrations. The overall learning efficiency
score was in the highest level while the local accountants’ job
performance effectiveness score was also in the high level. The
hypothesis testing’s result disclosed that learning efficiency factors
which were knowledge, Skill, and Attitude had an influence on local
accountants’ job the performance effectiveness.
Abstract: Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.
Abstract: As a result of the daily workflow in the design
development departments of companies, databases containing huge
numbers of 3D geometric models are generated. According to the
given problem engineers create CAD drawings based on their design
ideas and evaluate the performance of the resulting design, e.g. by
computational simulations. Usually, new geometries are built either
by utilizing and modifying sets of existing components or by adding
single newly designed parts to a more complex design.
The present paper addresses the two facets of acquiring
components from large design databases automatically and providing
a reasonable overview of the parts to the engineer. A unified
framework based on the topographic non-negative matrix
factorization (TNMF) is proposed which solves both aspects
simultaneously. First, on a given database meaningful components
are extracted into a parts-based representation in an unsupervised
manner. Second, the extracted components are organized and
visualized on square-lattice 2D maps. It is shown on the example of
turbine-like geometries that these maps efficiently provide a wellstructured
overview on the database content and, at the same time,
define a measure for spatial similarity allowing an easy access and
reuse of components in the process of design development.
Abstract: Riprap is mostly used to prevent erosion by flows
down the steep slopes in river engineering. A total of 53 stability tests
performed on angular riprap with a median stone size ranging from
15 to 278 mm and slope ranging from 1 to 40% are used in this study.
The existing equations for the prediction of medium size of angular
stones are checked for their accuracy using the available data.
Predictions of median size using these equations are not satisfactory
and results show deviation by more than ±20% from the observed
values. A multivariable power regression analysis is performed to
propose a new equation relating the median size with unit discharge,
bed slope, riprap thickness and coefficient of uniformity. The
proposed relationship satisfactorily predicts the median angular stone
size with ±20% error. Further, the required size of the rounded stone
is more than the angular stone for the same unit discharge and the
ratio increases with unit discharge and also with embankment slope
of the riprap.
Abstract: In the hardening energy context, the transport sector
which constitutes a large worldwide energy demand has to be
improving for decrease energy demand and global warming impacts.
In a controversial situation where subsists an increasing demand for
long-distance and high-speed travels, high-speed trains offer many
advantages, as consuming significantly less energy than road or air
transports.
At the project phase of new rail infrastructures, it is nowadays
important to characterize accurately the energy that will be induced
by its operation phase, in addition to other more classical criteria as
construction costs and travel time.
Current literature consumption models used to estimate railways
operation phase are obsolete or not enough accurate for taking into
account the newest train or railways technologies.
In this paper, an updated model of consumption for high-speed is
proposed, based on experimental data obtained from full-scale tests
performed on a new high-speed line. The assessment of the model
is achieved by identifying train parameters and measured power
consumptions for more than one hundred train routes. Perspectives
are then discussed to use this updated model for accurately assess
the energy impact of future railway infrastructures.
Abstract: Discovery schools in Jordan are connected in one flat
ATM bridge network. All Schools connected to the network will hear
broadcast traffic. High percentage of unwanted traffic such as
broadcast, consumes the bandwidth between schools and QRC.
Routers in QRC have high CPU utilization. The number of
connections on the router is very high, and may exceed recommend
manufacturing specifications. One way to minimize number of
connections to the routers in QRC, and minimize broadcast traffic is
to use PPPoE. In this study, a PPPoE solution has been presented
which shows high performance for the clients when accessing the
school server resources. Despite the large number of the discovery
schools at MoE, the experimental results show that the PPPoE
solution is able to yield a satisfactory performance for each client at
the school and noticeably reduce the traffic broadcast to the QRC.
Abstract: Malaysia 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 is because in our realties student who excellent
is only excel in academic. This evaluation becomes a problem
because it not balances in our real life interm of to get an excellent
student in whole area in their involvement of curiculum and cocuriculum.
To overcome this scenario, we designed a module for
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 conclusion this system module will helps the development
of student evaluation more accurate and valid in Student Idol.
Abstract: Optimization and control of reactive power
distribution in the power systems leads to the better operation of the
reactive power resources. Reactive power control reduces
considerably the power losses and effective loads and improves the
power factor of the power systems. Another important reason of the
reactive power control is improving the voltage profile of the power
system. In this paper, voltage and reactive power control using
Neural Network techniques have been applied to the 33 shines-
Tehran Electric Company. In this suggested ANN, the voltages of PQ
shines have been considered as the input of the ANN. Also, the
generators voltages, tap transformers and shunt compensators have
been considered as the output of ANN. Results of this techniques
have been compared with the Linear Programming. Minimization of
the transmission line power losses has been considered as the
objective function of the linear programming technique. The
comparison of the results of the ANN technique with the LP shows
that the ANN technique improves the precision and reduces the
computation time. ANN technique also has a simple structure and
this causes to use the operator experience.
Abstract: A combined three-microphone voice activity detector (VAD) and noise-canceling system is studied to enhance speech recognition in an automobile environment. A previous experiment clearly shows the ability of the composite system to cancel a single noise source outside of a defined zone. This paper investigates the performance of the composite system when there are frequently moving noise sources (noise sources are coming from different locations but are not always presented at the same time) e.g. there is other passenger speech or speech from a radio when a desired speech is presented. To work in a frequently moving noise sources environment, whilst a three-microphone voice activity detector (VAD) detects voice from a “VAD valid zone", the 3-microphone noise canceller uses a “noise canceller valid zone" defined in freespace around the users head. Therefore, a desired voice should be in the intersection of the noise canceller valid zone and VAD valid zone. Thus all noise is suppressed outside this intersection of area. Experiments are shown for a real environment e.g. all results were recorded in a car by omni-directional electret condenser microphones.
Abstract: Surface currents play a major role in the distribution
of contaminants, the connectivity of marine populations, and can
influence the vertical and horizontal distribution of nutrients within
the water column. This paper aims to determine the effects of sea
breeze-wind patterns on the climatology of the surface currents on the
continental shelf surrounding Rottnest Island, WA Australia. The
alternating wind patterns allow for full cyclic rotations of wind
direction, permitting the interpretation of the effect of the wind on the
surface currents. It was found that the surface currents only clearly
follow the northbound Capes Current in times when the Fremantle
Doctor sets in. Surface currents react within an hour to a change of
direction of the wind, allowing southerly currents to dominate during
strong northerly sea breezes, often followed by mixed currents
dominated by eddies in the inter-lying times.