Abstract: Investment in a constructed facility represents a cost in
the short term that returns benefits only over the long term use of the
facility. Thus, the costs occur earlier than the benefits, and the owners
of facilities must obtain the capital resources to finance the costs of
construction. A project cannot proceed without an adequate
financing, and the cost of providing an adequate financing can be
quite large. For these reasons, the attention to the project finance is an
important aspect of project management. Finance is also a concern to
the other organizations involved in a project such as the general
contractor and material suppliers. Unless an owner immediately and
completely covers the costs incurred by each participant, these
organizations face financing problems of their own. At a more
general level, the project finance is the only one aspect of the general
problem of corporate finance. If numerous projects are considered
and financed together, then the net cash flow requirements constitute
the corporate financing problem for capital investment. Whether
project finance is performed at the project or at the corporate level
does not alter the basic financing problem .In this paper, we will first
consider facility financing from the owner's perspective, with due
consideration for its interaction with other organizations involved in a
project. Later, we discuss the problems of construction financing
which are crucial to the profitability and solvency of construction
contractors. The objective of this paper is to present the steps utilized
to determine the best combination of minimum project financing.
The proposed model considers financing; schedule and maximum net
area .The proposed model is called Project Financing and Schedule
Integration using Genetic Algorithms "PFSIGA". This model
intended to determine more steps (maximum net area) for any project
with a subproject. An illustrative example will demonstrate the
feature of this technique. The model verification and testing are put
into consideration.
Abstract: Perspective of food security in 21 century showed
shortage of food that production is faced to vital problem. Food
security strategy is applied longtime method to assess required food.
Meanwhile, nanotechnology revolution changes the world face.
Nanotechnology is adequate method utilize of its characteristics to
decrease environmental problems and possible further access to food
for small farmers. This article will show impact of production and
adoption of nanocrops on food security. Population is researchers of
agricultural research center of Esfahan province. The results of study
show that there was a relationship between uses, conversion,
distribution, and production of nanocrops, operative human
resources, operative circumstance, and constrains of usage of
nanocrops and food security. Multivariate regression analysis by
enter model shows that operative circumstance, use, production and
constrains of usage of nanocrops had positive impact on food security
and they determine in four steps 20 percent of it.
Abstract: An advanced composite flywheel rotor consisting of
intra and inter hybrid rims was designed to optimally increase the energy capacity, and was manufactured using filament winding with
in-situ curing. The flywheel has recently attracted considerable attention from many investigators since it possesses great potential in
many energy storage applications, including electric utilities, hybrid or
electric automobiles, and space vehicles. In this investigation, a comprehensive study was conducted with the intent to implement
composites in high performance flywheel applications.The inner two
intra-hybrid rims (rims 1 and 2) were manufactured as a whole part
through continuous filament winding under in-situ curing conditions,
and so were the outer two rims (rims 3 and 4). The outer surface of rim
2 and the inner surface of rim 3 were CNC-tapered for press-fitting. Machined rims were finally press-fitted using a hydraulic press with a
maximum compressive force of approximately 1000 ton.
Abstract: The necessity of updating the numerical models inputs, because of geometrical and resistive variations in rivers subject to solid transport phenomena, requires detailed control and monitoring activities. The human employment and financial resources of these activities moves the research towards the development of expeditive methodologies, able to evaluate the outflows through the measurement of more easily acquirable sizes. Recent studies highlighted the dependence of the entropic parameter on the kinematical and geometrical flow conditions. They showed a meaningful variability according to the section shape, dimension and slope. Such dependences, even if not yet well defined, could reduce the difficulties during the field activities, and also the data elaboration time. On the basis of such evidences, the relationships between the entropic parameter and the geometrical and resistive sizes, obtained through a large and detailed laboratory experience on steady free surface flows in conditions of macro and intermediate homogeneous roughness, are analyzed and discussed.
Abstract: The aim of this paper is to present a methodology in
three steps to forecast supply chain demand. In first step, various data
mining techniques are applied in order to prepare data for entering
into forecasting models. In second step, the modeling step, an
artificial neural network and support vector machine is presented
after defining Mean Absolute Percentage Error index for measuring
error. The structure of artificial neural network is selected based on
previous researchers' results and in this article the accuracy of
network is increased by using sensitivity analysis. The best forecast
for classical forecasting methods (Moving Average, Exponential
Smoothing, and Exponential Smoothing with Trend) is resulted based
on prepared data and this forecast is compared with result of support
vector machine and proposed artificial neural network. The results
show that artificial neural network can forecast more precisely in
comparison with other methods. Finally, forecasting methods'
stability is analyzed by using raw data and even the effectiveness of
clustering analysis is measured.
Abstract: Mobile agent has motivated the creation of a new
methodology for parallel computing. We introduce a methodology
for the creation of parallel applications on the network. The proposed
Mobile-Agent parallel processing framework uses multiple Javamobile
Agents. Each mobile agent can travel to the specified
machine in the network to perform its tasks. We also introduce the
concept of master agent, which is Java object capable of
implementing a particular task of the target application. Master agent
is dynamically assigns the task to mobile agents. We have developed
and tested a prototype application: Mobile Agent Based Parallel
Computing. Boosted by the inherited benefits of using Java and
Mobile Agents, our proposed methodology breaks the barriers
between the environments, and could potentially exploit in a parallel
manner all the available computational resources on the network.
This paper elaborates performance issues of a mobile agent for
parallel computing.
Abstract: Saudi Arabia is an arid country which depends on
costly desalination plants to satisfy the growing residential water
demand. Prediction of water demand is usually a challenging task
because the forecast model should consider variations in economic
progress, climate conditions and population growth. The task is
further complicated knowing that Mecca city is visited regularly by
large numbers during specific months in the year due to religious
occasions. In this paper, a neural networks model is proposed to
handle the prediction of the monthly and yearly water demand for
Mecca city, Saudi Arabia. The proposed model will be developed
based on historic records of water production and estimated visitors-
distribution. The driving variables for the model include annuallyvarying
variables such as household income, household density, and
city population, and monthly-varying variables such as expected
number of visitors each month and maximum monthly temperature.
Abstract: Modeling of a heterogeneous industrial fixed bed
reactor for selective dehydrogenation of heavy paraffin with Pt-Sn-
Al2O3 catalyst has been the subject of current study. By applying
mass balance, momentum balance for appropriate element of reactor
and using pressure drop, rate and deactivation equations, a detailed
model of the reactor has been obtained. Mass balance equations have
been written for five different components. In order to estimate
reactor production by the passage of time, the reactor model which is
a set of partial differential equations, ordinary differential equations
and algebraic equations has been solved numerically.
Paraffins, olefins, dienes, aromatics and hydrogen mole percent as
a function of time and reactor radius have been found by numerical
solution of the model. Results of model have been compared with
industrial reactor data at different operation times. The comparison
successfully confirms validity of proposed model.
Abstract: One of the criteria in production scheduling is Make
Span, minimizing this criteria causes more efficiently use of the
resources specially machinery and manpower. By assigning some
budget to some of the operations the operation time of these activities
reduces and affects the total completion time of all the operations
(Make Span). In this paper this issue is practiced in parallel flow
shops. At first we convert parallel flow shop to a network model and
by using a linear programming approach it is identified in order to
minimize make span (the completion time of the network) which
activities (operations) are better to absorb the predetermined and
limited budget. Minimizing the total completion time of all the
activities in the network is equivalent to minimizing make span in
production scheduling.
Abstract: This paper presents results of empirical studies that were conducted in enterprises from Podkarpackie Voivodeship (Poland). It shows the experiences of those enterprises resulting from implementing and improving the eco-innovativeness management that is formal Environmental Management System (EMS). This study shows the expected and obtained internal benefits which are the effects of a functioning EMS. The aim of this paper is to determine whether the information included in international theoretical studies concerning the benefits of implementing, functioning and improving formal EMS (which is based on the international standard ISO 14001) are confirmed by the effects of the enterprises- activities.
Abstract: Synthesis gas manufacturing by steam reforming of hydrocarbons is an important industrial process. High endothermic nature of the process makes it one of the most cost and heat intensive processes. In the present work, composite effect of different inert gases on synthesis gas yield, feed gas conversion and temperature distribution along the reactor length has been studied using a heterogeneous model. Mathematical model was developed as a first stage and validated against the existing process models. With the addition of inert gases, a higher yield of synthesis gas is observed. Simultaneously the rector outlet temperature drops to as low as 810 K. It was found that Xenon gives the highest yield and conversion while Helium gives the lowest temperature. Using Xenon inert gas 20 percent reduction in outlet temperature was observed compared to traditional case.
Abstract: This research was conducted for the first time at the
southeastern coasts of the Caspian Sea in order to evaluate the
performance of osteichthyes cooperatives through production (catch)
function. Using one of the indirect valuation methods in this research,
contributory factors in catch were identified and were inserted into
the function as independent variables. In order to carry out this
research, the performance of 25 Osteichthyes catching cooperatives
in the utilization year of 2009 which were involved in fishing in
Miankale wildlife refuge region. The contributory factors in catch
were divided into groups of economic, ecological and biological
factors. In the mentioned function, catch rate of the cooperative were
inserted into as the dependant variable and fourteen partial variables
in terms of nine general variables as independent variables. Finally,
after function estimation, seven variables were rendered significant at
99 percent reliably level. The results of the function estimation
indicated that human resource (fisherman quantity) had the greatest
positive effect on catch rate with an influence coefficient of 1.7 while
weather conditions had the greatest negative effect on the catch rate
of cooperatives with an influence coefficient of -2.07. Moreover,
factors like member's share, experience and fisherman training and
fishing effort played the main roles in the catch rate of cooperative
with influence coefficients of 0.81, 0.5 and 0.21, respectively.
Abstract: Choosing the right metadata is a critical, as good
information (metadata) attached to an image will facilitate its
visibility from a pile of other images. The image-s value is enhanced
not only by the quality of attached metadata but also by the technique
of the search. This study proposes a technique that is simple but
efficient to predict a single human image from a website using the
basic image data and the embedded metadata of the image-s content
appearing on web pages. The result is very encouraging with the
prediction accuracy of 95%. This technique may become a great
assist to librarians, researchers and many others for automatically and
efficiently identifying a set of human images out of a greater set of
images.
Abstract: Nowadays, engineering ceramics have significant
applications in different industries such as; automotive, aerospace,
electrical, electronics and even martial industries due to their
attractive physical and mechanical properties like very high hardness
and strength at elevated temperatures, chemical stability, low friction
and high wear resistance. However, these interesting properties plus
low heat conductivity make their machining processes too hard,
costly and time consuming. Many attempts have been made in order
to make the grinding process of engineering ceramics easier and
many scientists have tried to find proper techniques to economize
ceramics' machining processes. This paper proposes a new diamond
plunge grinding technique using ultrasonic vibration for grinding
Alumina ceramic (Al2O3). For this purpose, a set of laboratory
equipments have been designed and simulated using Finite Element
Method (FEM) and constructed in order to be used in various
measurements. The results obtained have been compared with the
conventional plunge grinding process without ultrasonic vibration
and indicated that the surface roughness and fracture strength
improved and the grinding forces decreased.
Abstract: This study applied Theory of Planned Behaviour
(TPB) to explain the knowledge sharing behaviour among academic
staff at a Public Higher Education Institution (HEI) in Malaysia. The
main objectives of this study are; to identify the components that
influence knowledge sharing behaviour and to determine the levels of
knowledge sharing behaviour among academic staff. A total of 200
respondents were participated in answering questionnaires. The
findings of this study revealed that level of perceiving and
implementing knowledge sharing behaviour among academic staff at
a Public HEI in Malaysia exist but not openly or strongly practiced.
The findings were discussed and recommendations for the future
research were also addressed.
Abstract: The necessity of accurate and timely field data is
shared among organizations engaged in fundamentally different
activities, public services or commercial operations. Basically, there
are three major components in the process of the qualitative research:
data collection, interpretation and organization of data, and analytic
process. Representative technological advancements in terms of
innovation have been made in mobile devices (mobile phone, PDA-s,
tablets, laptops, etc). Resources that can be potentially applied on the
data collection activity for field researches in order to improve this
process.
This paper presents and discuss the main features of a mobile
phone based solution for field data collection, composed of basically
three modules: a survey editor, a server web application and a client
mobile application. The data gathering process begins with the
survey creation module, which enables the production of tailored
questionnaires. The field workforce receives the questionnaire(s) on
their mobile phones to collect the interviews responses and sending
them back to a server for immediate analysis.
Abstract: In this paper, we propose a Perceptually Optimized Foveation based Embedded ZeroTree Image Coder (POEFIC) that introduces a perceptual weighting to wavelet coefficients prior to control SPIHT encoding algorithm in order to reach a targeted bit rate with a perceptual quality improvement with respect to a given bit rate a fixation point which determines the region of interest ROI. The paper also, introduces a new objective quality metric based on a Psychovisual model that integrates the properties of the HVS that plays an important role in our POEFIC quality assessment. Our POEFIC coder is based on a vision model that incorporates various masking effects of human visual system HVS perception. Thus, our coder weights the wavelet coefficients based on that model and attempts to increase the perceptual quality for a given bit rate and observation distance. The perceptual weights for all wavelet subbands are computed based on 1) foveation masking to remove or reduce considerable high frequencies from peripheral regions 2) luminance and Contrast masking, 3) the contrast sensitivity function CSF to achieve the perceptual decomposition weighting. The new perceptually optimized codec has the same complexity as the original SPIHT techniques. However, the experiments results show that our coder demonstrates very good performance in terms of quality measurement.
Abstract: The increased number of automobiles in recent years
has resulted in great demand for fossil fuel. This has led to the
development of automobile by using alternative fuels which include
gaseous fuels, biofuels and vegetables oils as fuel. Energy from
biomass and more specific bio-diesel is one of the opportunities that
could cover the future demand of fossil fuel shortage. Biomass in the
form of cashew nut shell represents a new energy source and
abundant source of energy in India. The bio-fuel is derived from
cashew nut shell oil and its blend with diesel are promising
alternative fuel for diesel engine. In this work the pyrolysis Cashew
Nut Shell Liquid (CNSL)-Diesel Blends (CDB) was used to run the
Direct Injection (DI) diesel engine. The experiments were conducted
with various blends of CNSL and Diesel namely B20, B40, B60, B80
and B100. The results are compared with neat diesel operation. The
brake thermal efficiency was decreased for blends of CNSL and
Diesel except the lower blends of B20. The brake thermal efficiency
of B20 is nearly closer to that of diesel fuel. Also the emission level
of the all CNSL and Diesel blends was increased compared to neat
diesel. The higher viscosity and lower volatility of CNSL leads to
poor mixture formation and hence lower brake thermal efficiency and
higher emission levels. The higher emission level can be reduced by
adding suitable additives and oxygenates with CNSL and Diesel
blends.
Abstract: The overall penumbra is usually defined as the
distance, p20–80, separating the 20% and 80% of the dose on the beam axis at the depth of interest. This overall penumbra accounts
also for the fact that some photons emitted by the distal parts of the source are only partially attenuated by the collimator. Medulloblastoma is the most common type of childhood brain tumor
and often spreads to the spine. Current guidelines call for surgery to remove as much of the tumor as possible, followed by radiation of the brain and spinal cord, and finally treatment with chemotherapy.
The purpose of this paper was to present results on an Uniformity of dose distribution in radiation fields surrounding the spine using film
dosimetry and comparison with 3D treatment planning software.
Abstract: In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.