Abstract: This paper present a circular patch microstrip array antenna operate in KU-band (10.9GHz – 17.25GHz). The proposed circular patch array antenna will be in light weight, flexible, slim and compact unit compare with current antenna used in KU-band. The paper also presents the detail steps of designing the circular patch microstrip array antenna. An Advance Design System (ADS) software is used to compute the gain, power, radiation pattern, and S11 of the antenna. The proposed Circular patch microstrip array antenna basically is a phased array consisting of 'n' elements (circular patch antennas) arranged in a rectangular grid. The size of each element is determined by the operating frequency. The incident wave from satellite arrives at the plane of the antenna with equal phase across the surface of the array. Each 'n' element receives a small amount of power in phase with the others. There are feed network connects each element to the microstrip lines with an equal length, thus the signals reaching the circular patches are all combined in phase and the voltages add up. The significant difference of the circular patch array antenna is not come in the phase across the surface but in the magnitude distribution.
Abstract: In this study, solid phase micro-extraction (SPME)
was optimized to improve the sensitivity and accuracy in
formaldehyde determination for plywood panels. Further work has
been carried out to compare the newly developed technique with
existing method which reacts formaldehyde collected in desiccators
with acetyl acetone reagent (DC-AA). In SPME, formaldehyde was
first derivatized with O-(2,3,4,5,6 pentafluorobenzyl)-hydroxylamine
hydrochloride (PFBHA) and analysis was then performed by gas
chromatography in combination with mass spectrometry (GC-MS).
SPME data subjected to various wood species gave satisfactory
results, with relative standard deviations (RSDs) obtained in the
range of 3.1-10.3%. It was also well correlated with DC values,
giving a correlation coefficient, RSQ, of 0.959. The quantitative
analysis of formaldehyde by SPME was an alternative in wood
industry with great potential
Abstract: In this paper we describe our efforts to design and
implement an agent development framework that has the potential to
scale to the size of any underlying network suitable for various ECommerce
activities. The main novelty in our framework is it-s
capability to allow the development of sophisticated, secured agents
which are simple enough to be practical.
We have adopted FIPA agent platform reference Model as
backbone for implementation along with XML for agent
Communication and Java Cryptographic Extension and architecture
to realize the security of communication information between agents.
The advantage of our architecture is its support of agents
development in different languages and Communicating with each
other using a more open standard i.e. XML
Abstract: Building conservation work generally involves complex and non-standard work different from new building construction processes. In preparing tenders for building conservation projects, therefore, the quantity surveyor must carefully consider the specificity of non-standard items and demarcate the scope of unique conservation work. While the quantity surveyor must appreciate the full range of works to prepare a good tender document, he typically manages many unfamiliar elements, including practical construction methods, restoration techniques and work sequences. Only by fulfilling the demanding requirements of building conservation work can the quantity surveyor enhance his professionalism an area of growing cultural value and economic importance. By discussing several issues crucial to tender preparations for building conservation projects in Malaysia, this paper seeks a deeper understanding of how quantity surveying can better standardize tender preparation work and more successfully manage building conservation processes.
Abstract: This work aims to test the application of computational fluid dynamics (CFD) modeling to fixed bed catalytic cracking reactors. Studies of CFD with a fixed bed design commonly use a regular packing with N=2 to define bed geometry. CFD allows us to obtain a more accurate view of the fluid flow and heat transfer mechanisms present in fixed bed equipment. Naphtha was used as feedstock and the reactor length was 80cm. It is divided in three sections that catalyst bed packed in the middle section of the reactor. The reaction scheme was involved one primary reaction and 24 secondary reactions. Because of high CPU times in these simulations, parallel processing have been used. In this study the coke formation process in fixed bed and empty tube reactor was simulated and coke in these reactors are compared. In addition, the effect of steam ratio and feed flow rate on coke formation was investigated.
Abstract: The paper deals with the kinematics and automated
calculation of intermittent mechanisms with radial cams. Currently,
electronic cams are increasingly applied in the drives of working link
mechanisms. Despite a huge advantage of electronic cams in their reprogrammability
or instantaneous change of displacement diagrams,
conventional cam mechanisms have an irreplaceable role in
production and handling machines. With high frequency of working
cycle periods, the dynamic load of the proper servomotor rotor
increases and efficiency of electronic cams strongly decreases.
Though conventional intermittent mechanisms with radial cams are
representatives of fixed automation, they have distinct advantages in
their high speed (high dynamics), positional accuracy and relatively
easy manufacture. We try to remove the disadvantage of firm
displacement diagram by reducing costs for simple design and
automated calculation that leads reliably to high-quality and
inexpensive manufacture.
Abstract: The emergence of person-centred discourse based
around notions of 'personal development planning- and 'work'life
balance' has taken hold in education and the workplace in recent
years. This paper examines this discourse with regard to recent
developments in higher education as well as the inter-related issue of
work-life balance in occupational careers. In both cases there have
been national and trans-national policy initiatives directed towards
improving both personal opportunities and competitive advantage in
a global knowledge-based economy. However, despite an increasing
concern with looking outward at this globalised educational and
employment marketplace, there is something of a paradox in
encouraging people to look inward at themselves in order to become
more self-determined. This apparent paradox is considered from a
discourse analytic perspective in terms of the ideological effects of an
increasing concern with the personal world. Specifically, it is argued
that there are tensions that emerge from a concern with an innerdirected
process of self-reflection that dissolve any engagement with
wider political issues that impact upon educational and career
development.
Abstract: Due to important issues, such as deadlock, starvation,
communication, non-deterministic behavior and synchronization,
concurrent systems are very complex, sensitive, and error-prone.
Thus ensuring reliability and accuracy of these systems is very
essential. Therefore, there has been a big interest in the formal
specification of concurrent programs in recent years. Nevertheless,
some features of concurrent systems, such as dynamic process
creation, scheduling and starvation have not been specified formally
yet. Also, some other features have been specified partially and/or
have been described using a combination of several different
formalisms and methods whose integration needs too much effort. In
other words, a comprehensive and integrated specification that could
cover all aspects of concurrent systems has not been provided yet.
Thus, this paper makes two major contributions: firstly, it provides a
comprehensive formal framework to specify all well-known features
of concurrent systems. Secondly, it provides an integrated
specification of these features by using just a single formal notation,
i.e., the Z language.
Abstract: The problem of agricultural-soil pollution is closely
linked to the production of ecologically pure foodstuffs and to human health. An important task, therefore, is to rehabilitate agricultural
soils with the help of state-of-the-art biotechnologies, based on the use of metal-accumulating plants. In this work, on the basis of
literature data and the results of prior research from this laboratory, plants were selected for which the growing technology is well
developed and which are widespread locally: sugar sorghum (Sorghum saccharatum), sudangrass (Sorghum sudanense (Piper.)
Stapf.), and sunflower (Helianthus annuus L.). I report on laboratory
experiments designed to study the influence of synthetic indole-3-
acetic acid and the extracellular indole-3-acetic acid released by the
plant-growth-promoting rhizobacterium Azospirillum brasilense Sp245 on growth of and arsenic accumulation by these plants.
Abstract: Artificial Neural Network (ANN)s are best suited for
prediction and optimization problems. Trained ANNs have found
wide spread acceptance in several antenna design systems. Four
parameters namely antenna radiation resistance, loss resistance, efficiency,
and inductance can be used to design an antenna layout though
there are several other parameters available. An ANN can be trained
to provide the best and worst case precisions of an antenna design
problem defined by these four parameters. This work describes the
use of an ANN to generate the four mentioned parameters for a loop
antenna for the specified frequency range. It also provides insights
to the prediction of best and worst-case design problems observed
in applications and thereby formulate a model for physical layout
design of a loop antenna.
Abstract: This paper presents a novel method for remaining
useful life prediction using the Elliptical Basis Function (EBF)
network and a Markov chain. The EBF structure is trained by a
modified Expectation-Maximization (EM) algorithm in order to take
into account the missing covariate set. No explicit extrapolation is
needed for internal covariates while a Markov chain is constructed to
represent the evolution of external covariates in the study. The
estimated external and the unknown internal covariates constitute an
incomplete covariate set which are then used and analyzed by the EBF
network to provide survival information of the asset. It is shown in the
case study that the method slightly underestimates the remaining
useful life of an asset which is a desirable result for early maintenance
decision and resource planning.
Abstract: As the air traffic increases at a hub airport, some
flights cannot land or depart at their preferred target time. This event
happens because the airport runways become occupied to near their
capacity. It results in extra costs for both passengers and airlines
because of the loss of connecting flights or more waiting, more fuel
consumption, rescheduling crew members, etc. Hence, devising an
appropriate scheduling method that determines a suitable runway and
time for each flight in order to efficiently use the hub capacity and
minimize the related costs is of great importance. In this paper, we
present a mixed-integer zero-one model for scheduling a set of mixed
landing and departing flights (despite of most previous studies
considered only landings). According to the fact that the flight cost is
strongly affected by the level of airline, we consider different airline
categories in our model. This model presents a single objective
minimizing the total sum of three terms, namely 1) the weighted
deviation from targets, 2) the scheduled time of the last flight (i.e.,
makespan), and 3) the unbalancing the workload on runways. We
solve 10 simulated instances of different sizes up to 30 flights and 4
runways. Optimal solutions are obtained in a reasonable time, which
are satisfactory in comparison with the traditional rule, namely First-
Come-First-Serve (FCFS) that is far apart from optimality in most
cases.
Abstract: This paper deals with the combination of OSGi and
cloud computing. Both technologies are mainly placed in the field of
distributed computing. Therefore, it is discussed how different
approaches from different institutions work. In addition, the
approaches are compared to each other.
Abstract: This paper presents the methodology from machine
learning approaches for short-term rain forecasting system. Decision
Tree, Artificial Neural Network (ANN), and Support Vector Machine
(SVM) were applied to develop classification and prediction models
for rainfall forecasts. The goals of this presentation are to
demonstrate (1) how feature selection can be used to identify the
relationships between rainfall occurrences and other weather
conditions and (2) what models can be developed and deployed for
predicting the accurate rainfall estimates to support the decisions to
launch the cloud seeding operations in the northeastern part of
Thailand. Datasets collected during 2004-2006 from the
Chalermprakiat Royal Rain Making Research Center at Hua Hin,
Prachuap Khiri khan, the Chalermprakiat Royal Rain Making
Research Center at Pimai, Nakhon Ratchasima and Thai
Meteorological Department (TMD). A total of 179 records with 57
features was merged and matched by unique date. There are three
main parts in this work. Firstly, a decision tree induction algorithm
(C4.5) was used to classify the rain status into either rain or no-rain.
The overall accuracy of classification tree achieves 94.41% with the
five-fold cross validation. The C4.5 algorithm was also used to
classify the rain amount into three classes as no-rain (0-0.1 mm.),
few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall
accuracy of classification tree achieves 62.57%. Secondly, an ANN
was applied to predict the rainfall amount and the root mean square
error (RMSE) were used to measure the training and testing errors of
the ANN. It is found that the ANN yields a lower RMSE at 0.171 for
daily rainfall estimates, when compared to next-day and next-2-day
estimation. Thirdly, the ANN and SVM techniques were also used to
classify the rain amount into three classes as no-rain, few-rain, and
moderate-rain as above. The results achieved in 68.15% and 69.10%
of overall accuracy of same-day prediction for the ANN and SVM
models, respectively. The obtained results illustrated the comparison
of the predictive power of different methods for rainfall estimation.
Abstract: The paper represents a reflection on how to select proper indicators to assess the progress of regional contexts towards a knowledge-based society. Taking the first research methodologies elaborated at an international level (World Bank, OECD, etc.) as a reference point, this work intends to identify a set of indicators of the knowledge economy suitable to adequately understand in which manner and to which extent the territorial development dynamics are correlated with the knowledge-base of the considered local society. After a critical survey of the variables utilized within other approaches adopted by international or national organizations, this paper seeks to elaborate a framework of variables, named Regional Knowledge Economy Indicators (ReKEI), necessary to describe the knowledge-based relations of subnational socio-economic contexts. The realization of this framework has a double purpose: an analytical one consisting in highlighting the regional differences in the governance of knowledge based processes, and an operative one consisting in providing some reference parameters for contributing to increasing the effectiveness of those economic policies aiming at enlarging the knowledge bases of local societies.
Abstract: A preliminary evaluation of the urban land system is
presented in the article together with the instruments of land policy in
Serbia. The main reason for the analysis is demand for
definition of reform framework for urban land management in
Serbia in the period of transition towards market-led system. It
is concluded that due to the limitations of the current regulation it
will be impossible in the future to apply market principles in the
urban land policy (supply and demand of land, land capitalization,
investment efficiency, et al.). Based on the estimation that the urban
land system and land policy are key factors of competitiveness
between regions and towns in Serbia, it is necessary to initiate
changes in this field. There are indicated on an option of privatization
of urban public land and possible establishment of leasehold land. A
comparative analysis of the possibilities of the reform urban land
system in Serbia has been carried out in relation to two approaches of
market systems: (a) with dominant private ownership of urban land
(neo/liberal approach) and (b) with dominant public ownership of
urban land (system of leasehold)whose findings can be a basis for
further study of the new system in Serbia.. The attanied results are
part of studies matter for the making of Strategy of territorial
development of Serbia.
Abstract: Although lots of research work has been done for
human pose recognition, the view-point of cameras is still critical
problem of overall recognition system. In this paper, view-point
insensitive human pose recognition is proposed. The aims of the
proposed system are view-point insensitivity and real-time processing.
Recognition system consists of feature extraction module, neural
network and real-time feed forward calculation. First, histogram-based
method is used to extract feature from silhouette image and it is
suitable for represent the shape of human pose. To reduce the
dimension of feature vector, Principle Component Analysis(PCA) is
used. Second, real-time processing is implemented by using Compute
Unified Device Architecture(CUDA) and this architecture improves
the speed of feed-forward calculation of neural network. We
demonstrate the effectiveness of our approach with experiments on
real environment.
Abstract: Tool wear and surface roughness prediction plays a
significant role in machining industry for proper planning and control
of machining parameters and optimization of cutting conditions. This
paper deals with developing an artificial neural network (ANN)
model as a function of cutting parameters in turning steel under
minimum quantity lubrication (MQL). A feed-forward
backpropagation network with twenty five hidden neurons has been
selected as the optimum network. The co-efficient of determination
(R2) between model predictions and experimental values are 0.9915,
0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra
respectively. The results imply that the model can be used easily to
forecast tool wear and surface roughness in response to cutting
parameters.
Abstract: Renewable and non-renewable resource constraints have been vast studied in theoretical fields of project scheduling problems. However, although cumulative resources are widespread in practical cases, the literature on project scheduling problems subject to these resources is scant. So in order to study this type of resources more, in this paper we use the framework of a resource constrained project scheduling problem (RCPSP) with finish-start precedence relations between activities and subject to the cumulative resources in addition to the renewable resources. We develop a branch and bound algorithm for this problem customizing precedence tree algorithm of RCPSP. We perform extensive experimental analysis on the algorithm to check its effectiveness and performance for solving different instances of the problem in question.
Abstract: In this paper, a neural network tuned fuzzy controller
is proposed for controlling Multi-Input Multi-Output (MIMO)
systems. For the convenience of analysis, the structure of MIMO
fuzzy controller is divided into single input single-output (SISO)
controllers for controlling each degree of freedom. Secondly,
according to the characteristics of the system-s dynamics coupling, an
appropriate coupling fuzzy controller is incorporated to improve the
performance. The simulation analysis on a two-level mass–spring
MIMO vibration system is carried out and results show the
effectiveness of the proposed fuzzy controller. The performance
though improved, the computational time and memory used is
comparatively higher, because it has four fuzzy reasoning blocks and
number may increase in case of other MIMO system. Then a fuzzy
neural network is designed from a set of input-output training data to
reduce the computing burden during implementation. This control
strategy can not only simplify the implementation problem of fuzzy
control, but also reduce computational time and consume less
memory.