Abstract: This paper has presented research in progress
concerning the contribution of target costing approach to
achievement competitive price in the Iraqi firm. The title of the
paper is one of the subjects that get large concerns in the finance and
business world in the present time. That is because many competitive
firms have appeared in the regional and global markets and the rapid
changes that covered all fields of life. On the other hand, this paper
concentrated on lack knowledge of the industrial firms, regarding the
significant role of target cost for achieving the competitive prices.
The paper depends on the main supposition, using the competitive
price to get the target cost in the industrial firms. In order to achieve
competitive advantage in business world the firms should rely on
modern methods to manage cost and profit. From strategic
perspective the target cost achieves a so powerful competitive
advantage represented in cost reduction. Nevertheless the target cost
does not exclude the calculation and survey of costs during the
production process. Products- estimated costs are calculated and
compared with the target costs.
Abstract: We evaluated the effect of sensory (direct current
(DC), 600μA) and motor (monophasic current, pulse duration 300μs,
100 Hz, 2.5-3mA) intensities of cathodal electrical stimulation (ES)
current to release VEGF and biomechanical properties of wound. 54
male Sprague-dawley rats were randomly assigned into one control
and two experimental groups. A full thickness skin incision was
made on animals- dorsal region. The experimental groups received
ES for 1h/day and every other day. VEGF expression was measured
in skin on the 7th day after surgical incision and tensile strength was
measured on 21st day. On the 7th day, the values of skin VEGF in the
sensory group were significantly greater than those of the other
groups (p < 0.05). Sensory and Motor intensity stimulation, can not
improve the biomechanical properties of the repaired wounds.
It seems the mechanical environment induced by sensory and
motor intensity of electrical stimulation, could not simulate the role
of normal daily stress and strain to maturation of collagen fibers and
their cross links. Further work is needed to determine the relationship
between VEGF expression after ES and its effect on tensile strength
of healed wound.
Abstract: This paper investigates the application of large scale (LS-PV) two-axis tracking photovoltaic power plant in Al-Jagbob, Libya. A 50MW PV-grid connected (two-axis tracking) power plant design in Al-Jagbob, Libya has been carried out presently. A hetero-junction with intrinsic thin layer (HIT) type PV module has been selected and modeled. A Microsoft Excel-VBA program has been constructed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency for this system, for tracking system. The results for energy production show that the total energy output is 128.5 GWh/year. The average module efficiency is 16.6%. The electricity generation capacity factor (CF) and solar capacity factor (SCF) were found to be 29.3% and 70.4% respectively. A 50MW two axis tracking power plant with a total energy output of 128.5 GWh/year would reduce CO2 pollution by 85,581 tonnes of each year. The payback time for the proposed LS-PV photovoltaic power plant was found to be 4 years.
Abstract: The greenhouse effect and limitations on carbon
dioxide emissions concern engine maker and the future of the
internal combustion engines should go toward substantially and
improved thermal efficiency engine. Homogeneous charge
compression ignition (HCCI) is an alternative high-efficiency
technology for combustion engines to reduce exhaust emissions and
fuel consumption. However, there are still tough challenges in the
successful operation of HCCI engines, such as controlling the
combustion phasing, extending the operating range, and high
unburned hydrocarbon and CO emissions. HCCI and the exploitation
of ethanol as an alternative fuel is one way to explore new frontiers
of internal combustion engines with an eye towards maintaining its
sustainability. This study was done to extend database knowledge
about HCCI with ethanol a fuel.
Abstract: Intensive changes of environment and strong market
competition have raised management of information and knowledge
to the strategic level of companies. In a knowledge based economy
only those organizations are capable of living which have up-to-date,
special knowledge and they are able to exploit and develop it.
Companies have to know what knowledge they have by taking a
survey of organizational knowledge and they have to fix actual and
additional knowledge in organizational memory. The question is how
to identify, acquire, fix and use knowledge effectively. The paper will
show that over and above the tools of information technology
supporting acquisition, storage and use of information and
organizational learning as well as knowledge coming into being as a
result of it, fixing and storage of knowledge in the memory of a
company play an important role in the intelligence of organizations
and competitiveness of a company.
Abstract: Smoothing or filtering of data is first preprocessing step
for noise suppression in many applications involving data analysis.
Moving average is the most popular method of smoothing the data,
generalization of this led to the development of Savitzky-Golay filter.
Many window smoothing methods were developed by convolving
the data with different window functions for different applications;
most widely used window functions are Gaussian or Kaiser. Function
approximation of the data by polynomial regression or Fourier
expansion or wavelet expansion also gives a smoothed data. Wavelets
also smooth the data to great extent by thresholding the wavelet
coefficients. Almost all smoothing methods destroys the peaks and
flatten them when the support of the window is increased. In certain
applications it is desirable to retain peaks while smoothing the data
as much as possible. In this paper we present a methodology called
as peak-wise smoothing that will smooth the data to any desired level
without losing the major peak features.
Abstract: This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.
Abstract: The transient thermoelastic response of thick hollow cylinder made of functionally graded material under thermal loading is studied. The generalized coupled thermoelasticity based on the Green-Lindsay model is used. The thermal and mechanical properties of the functionally graded material are assumed to be varied in the radial direction according to a power law variation as a function of the volume fractions of the constituents. The thermal and elastic governing equations are solved by using Galerkin finite element method. All the finite element calculations were done by using commercial finite element program FlexPDE. The transient temperature, radial displacement, and thermal stresses distribution through the radial direction of the cylinder are plotted.
Abstract: In the present simulation work, an attempt is made to study the switching dynamics of an optically controlled 4HSiC thyristor power semiconductor device with the use of GaAs optically triggered power transistor. The half-cell thyristor has the forward breakdown of 200 V and reverse breakdown of more than 1000 V. The optically controlled thyristor has a rise time of 0.14 μs and fall time of 0.065 μs. The turn-on and turn-off delays are 0.1 μs and 0.06 μs, respectively. In addition, this optically controlled thyristor is used as a control switch for the DC-DC Boost converter. The pn-diode used for the converter has the forward drop of 2.8 V and reverse breakdown of around 400 V.
Abstract: Human activity is a major concern in a wide variety of
applications, such as video surveillance, human computer interface
and face image database management. Detecting and recognizing
faces is a crucial step in these applications. Furthermore, major
advancements and initiatives in security applications in the past years
have propelled face recognition technology into the spotlight. The
performance of existing face recognition systems declines significantly
if the resolution of the face image falls below a certain level.
This is especially critical in surveillance imagery where often, due to
many reasons, only low-resolution video of faces is available. If these
low-resolution images are passed to a face recognition system, the
performance is usually unacceptable. Hence, resolution plays a key
role in face recognition systems. In this paper we introduce a new
low resolution face recognition system based on mixture of expert
neural networks. In order to produce the low resolution input images
we down-sampled the 48 × 48 ORL images to 12 × 12 ones using
the nearest neighbor interpolation method and after that applying
the bicubic interpolation method yields enhanced images which is
given to the Principal Component Analysis feature extractor system.
Comparison with some of the most related methods indicates that
the proposed novel model yields excellent recognition rate in low
resolution face recognition that is the recognition rate of 100% for
the training set and 96.5% for the test set.
Abstract: The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.
Abstract: The mineral having chemical compositional formula MgAl2O4 is called “spinel". The ferrites crystallize in spinel structure are known as spinel-ferrites or ferro-spinels. The spinel structure has a fcc cage of oxygen ions and the metallic cations are distributed among tetrahedral (A) and octahedral (B) interstitial voids (sites). The X-ray diffraction (XRD) intensity of each Bragg plane is sensitive to the distribution of cations in the interstitial voids of the spinel lattice. This leads to the method of determination of distribution of cations in the spinel oxides through XRD intensity analysis. The computer program for XRD intensity analysis has been developed in C language and also tested for the real experimental situation by synthesizing the spinel ferrite materials Mg0.6Zn0.4AlxFe2- xO4 and characterized them by X-ray diffractometry. The compositions of Mg0.6Zn0.4AlxFe2-xO4(x = 0.0 to 0.6) ferrites have been prepared by ceramic method and powder X-ray diffraction patterns were recorded. Thus, the authenticity of the program is checked by comparing the theoretically calculated data using computer simulation with the experimental ones. Further, the deduced cation distributions were used to fit the magnetization data using Localized canting of spins approach to explain the “recovery" of collinear spin structure due to Al3+ - substitution in Mg-Zn ferrites which is the case if A-site magnetic dilution and non-collinear spin structure. Since the distribution of cations in the spinel ferrites plays a very important role with regard to their electrical and magnetic properties, it is essential to determine the cation distribution in spinel lattice.
Abstract: How to coordinate the behaviors of the agents through
learning is a challenging problem within multi-agent domains.
Because of its complexity, recent work has focused on how
coordinated strategies can be learned. Here we are interested in using
reinforcement learning techniques to learn the coordinated actions of a
group of agents, without requiring explicit communication among
them. However, traditional reinforcement learning methods are based
on the assumption that the environment can be modeled as Markov
Decision Process, which usually cannot be satisfied when multiple
agents coexist in the same environment. Moreover, to effectively
coordinate each agent-s behavior so as to achieve the goal, it-s
necessary to augment the state of each agent with the information
about other existing agents. Whereas, as the number of agents in a
multiagent environment increases, the state space of each agent grows
exponentially, which will cause the combinational explosion problem.
Profit sharing is one of the reinforcement learning methods that allow
agents to learn effective behaviors from their experiences even within
non-Markovian environments. In this paper, to remedy the drawback
of the original profit sharing approach that needs much memory to
store each state-action pair during the learning process, we firstly
address a kind of on-line rational profit sharing algorithm. Then, we
integrate the advantages of modular learning architecture with on-line
rational profit sharing algorithm, and propose a new modular
reinforcement learning model. The effectiveness of the technique is
demonstrated using the pursuit problem.
Abstract: Obtaining labeled data in supervised learning is often
difficult and expensive, and thus the trained learning algorithm tends
to be overfitting due to small number of training data. As a result,
some researchers have focused on using unlabeled data which may
not necessary to follow the same generative distribution as the labeled
data to construct a high-level feature for improving performance on
supervised learning tasks. In this paper, we investigate the impact of
the relationship between unlabeled and labeled data for classification
performance. Specifically, we will apply difference unlabeled data
which have different degrees of relation to the labeled data for
handwritten digit classification task based on MNIST dataset. Our
experimental results show that the higher the degree of relation
between unlabeled and labeled data, the better the classification
performance. Although the unlabeled data that is completely from
different generative distribution to the labeled data provides the lowest
classification performance, we still achieve high classification performance.
This leads to expanding the applicability of the supervised
learning algorithms using unsupervised learning.
Abstract: With the development of virtual communities, there is
an increase in the number of members in Virtual Communities (VCs).
Many join VCs with the objective of sharing their knowledge and
seeking knowledge from others. Despite the eagerness of sharing
knowledge and receiving knowledge through VCs, there is no
standard of assessing ones knowledge sharing capabilities and
prospects of knowledge sharing. This paper developed a vector space
model to assess the knowledge sharing prospect of VC users.
Abstract: Vibrations of circular cylindrical shells made of
layered composite materials are considered. The shells are weakened
by circumferential cracks. The influence of circumferential cracks
with constant depth on the vibration of the shell is prescribed with the
aid of a matrix of local flexibility coupled with the coefficient of the
stress intensity known in the linear elastic fracture mechanics.
Numerical results are presented for the case of the shell with one
circular crack.
Abstract: This paper concerns about the experimental and
numerical investigations of energy absorption and axial tearing
behaviour of aluminium 6060 circular thin walled tubes under static
axial compression. The tubes are received in T66 heat treatment
condition with fixed outer diameter of 42mm, thickness of 1.5mm
and length of 120mm. The primary variables are the conical die
angles (15°, 20° and 25°). Numerical simulations are carried on
ANSYS/LS-DYNA software tool, for investigating the effect of
friction between the tube and the die.
Abstract: In recent years, IT convergence technology has been developed to get creative solution by combining robotics or sports science technology. Object detection and recognition have mainly applied to sports science field that has processed by recognizing face and by tracking human body. But object detection and recognition using vision sensor is challenge task in real world because of illumination. In this paper, object detection and recognition using vision sensor applied to sports simulator has been introduced. Face recognition has been processed to identify user and to update automatically a person athletic recording. Human body has tracked to offer a most accurate way of riding horse simulator. Combined image processing has been processed to reduce illumination adverse affect because illumination has caused low performance in detection and recognition in real world application filed. Face has recognized using standard face graph and human body has tracked using pose model, which has composed of feature nodes generated diverse face and pose images. Face recognition using Gabor wavelet and pose recognition using pose graph is robust to real application. We have simulated using ETRI database, which has constructed on horse riding simulator.
Abstract: Perth will run out of available sustainable natural
water resources by 2015 if nothing is done to slow usage rates,
according to a Western Australian study [1]. Alternative water
technology options need to be considered for the long-term
guaranteed supply of water for agricultural, commercial, domestic
and industrial purposes. Seawater is an alternative source of water for
human consumption, because seawater can be desalinated and
supplied in large quantities to a very high quality.
While seawater desalination is a promising option, the technology
requires a large amount of energy which is typically generated from
fossil fuels. The combustion of fossil fuels emits greenhouse gases
(GHG) and, is implicated in climate change. In addition to
environmental emissions from electricity generation for desalination,
greenhouse gases are emitted in the production of chemicals and
membranes for water treatment. Since Australia is a signatory to the
Kyoto Protocol, it is important to quantify greenhouse gas emissions
from desalinated water production.
A life cycle assessment (LCA) has been carried out to determine
the greenhouse gas emissions from the production of 1 gigalitre (GL)
of water from the new plant. In this LCA analysis, a new desalination
plant that will be installed in Bunbury, Western Australia, and known
as Southern Seawater Desalinization Plant (SSDP), was taken as a
case study. The system boundary of the LCA mainly consists of three
stages: seawater extraction, treatment and delivery. The analysis
found that the equivalent of 3,890 tonnes of CO2 could be emitted
from the production of 1 GL of desalinated water. This LCA analysis
has also identified that the reverse osmosis process would cause the
most significant greenhouse emissions as a result of the electricity
used if this is generated from fossil fuels
Abstract: There are many kinds of metal borates found not only
in nature but also synthesized in the laboratory such as magnesium
borates. Due to its excellent properties, as remarkable ceramic
materials, they have also application areas in anti-wear and friction
reducing additives as well as electro-conductive treating agents. The
synthesis of magnesium borate powders can be fulfilled simply with
two different methods, hydrothermal and thermal synthesis.
Microwave assisted method, also another way of producing
magnesium borate, can be classified into thermal synthesis because of
using the principles of solid state synthesis. It also contributes
producing particles with small size and high purity in nano-size
material synthesize. In this study the production of magnesium
borates, are aimed using MgCl2.6H2O and H3BO3. The identification
of both starting materials and products were made by the equipments
of, X-Ray Diffraction (XRD) and Fourier Transform Infrared
Spectroscopy (FT-IR). After several synthesis steps magnesium
borates were synthesized and characterized by XRD and FT-IR, as
well.