Abstract: An attempt was made for availability of wastewater reuse/reclamation for irrigation purposes using phytoremediation “the low cost and less technology", using six local aquatic macrophytes “e.g. T. angustifolia, B. maritimus, Ph. australis, A. donax, A. plantago-aquatica and M. longifolia (Linn)" as biological waste purifiers. Outdoor experiments/designs were conducted from May 03, 2007 till October 15, 2008, close to one of the main sewage channels of Sulaimani City/Iraq*. All processes were mainly based on conventional wastewater treatment processes, besides two further modifications were tested, the first was sand filtration pots, implanted by individual species of experimental macrophytes and the second was constructed wetlands implanted by experimental macrophytes all together. Untreated and treated wastewater samples were analyzed for their key physico-chemical properties (only heavy metals Fe, Mn, Zn and Cu with particular reference to removal efficiency by experimental macrophytes are highlighted in this paper). On the other hand, vertical contents of heavy metals were also evaluated from both pots and the cells of constructed wetland. After 135 days, macrophytes were harvested and heavy metals were analyzed in their biomass (roots/shoots) for removal efficiency assessment (i.e. uptake/ bioaccumulation rate). Results showed that; removal efficiency of all studied heavy metals was much higher in T. angustifolia followed by Ph. Australis, B. maritimus and A. donax in triple experiment sand pots. Constructed wetland experiments have revealed that; the more replicated constructed wetland cells the highest heavy metal removal efficiency was indicated.
Abstract: Higher education institutions are increasingly opting to outsourcing methods in order to sustain themselves and this creates a gap of literature in terms of how they perceive the relationship. This research paper attempts to identify the behavioral and psychological factors that exist in the engagement thus providing valuable information to practicing and potential clients, and vendors. The determinants were gathered from previous literatures and analyzed to formulate the factors. This study adopts the case study and survey approaches in which interviews and questionnaires are deployed on employees of IT-related department in a Malaysian higher education institution.
Abstract: Numerical studies have been carried out using a
validated two-dimensional RNG k-epsilon turbulence model for the
design optimization of a thrust vector control system using shock
induced supersonic secondary jet. Parametric analytical studies have
been carried out with various secondary jets at different divergent
locations, jet interaction angles, jet pressures. The results from the
parametric studies of the case on hand reveal that the primary nozzle
with a small divergence angle, downstream injections with a distance
of 2.5 times the primary nozzle throat diameter from the primary
nozzle throat location warrant higher efficiency over a certain range
of jet pressures and jet angles. We observed that the supersonic
secondary jet opposing the core flow with jets interaction angle of
40o to the axis far downstream of the nozzle throat facilitates better
thrust vectoring than the secondary jet with same direction as that of
core flow with various interaction angles. We concluded that fixing
of the supersonic secondary jet nozzle pointing towards the throat
direction with suitable angle at a distance 2 to 4 times of the primary
nozzle throat diameter, as the case may be, from the primary nozzle
throat location could facilitate better thrust vectoring for the
supersonic aerospace vehicles.
Abstract: In the territories where high-intensity
earthquakes are frequent is paid attention to the solving of the
seismic problems. In the paper are described two
computational model variants based on finite element method
of the construction with different subsoil simulation (rigid or
elastic subsoil) is used. For simulation and calculations
program system based on method final elements ANSYS was
used. Seismic responses calculations of residential building
structure were effected on loading characterized by
accelerogram for comparing with the responses spectra
method.
Abstract: Selective harmonic elimination-pulse width modulation techniques offer a tight control of the harmonic spectrum of a given voltage waveform generated by a power electronic converter along with a low number of switching transitions. Traditional optimization methods suffer from various drawbacks, such as prolonged and tedious computational steps and convergence to local optima; thus, the more the number of harmonics to be eliminated, the larger the computational complexity and time. This paper presents a novel method for output voltage harmonic elimination and voltage control of PWM AC/AC voltage converters using the principle of hybrid Real-Coded Genetic Algorithm-Pattern Search (RGA-PS) method. RGA is the primary optimizer exploiting its global search capabilities, PS is then employed to fine tune the best solution provided by RGA in each evolution. The proposed method enables linear control of the fundamental component of the output voltage and complete elimination of its harmonic contents up to a specified order. Theoretical studies have been carried out to show the effectiveness and robustness of the proposed method of selective harmonic elimination. Theoretical results are validated through simulation studies using PSIM software package.
Abstract: Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.
Abstract: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: This paper introduces a technique of distortion
estimation in image watermarking using Genetic Programming (GP).
The distortion is estimated by considering the problem of obtaining a
distorted watermarked signal from the original watermarked signal as
a function regression problem. This function regression problem is
solved using GP, where the original watermarked signal is
considered as an independent variable. GP-based distortion
estimation scheme is checked for Gaussian attack and Jpeg
compression attack. We have used Gaussian attacks of different
strengths by changing the standard deviation. JPEG compression
attack is also varied by adding various distortions. Experimental
results demonstrate that the proposed technique is able to detect the
watermark even in the case of strong distortions and is more robust
against attacks.
Abstract: Green propellants used for satellite-level propulsion
system become attractive in recent years because the non-toxicity and
lower requirements of safety protection. One of the green propellants,
high-concentration hydrogen peroxide H2O2 solution (≥70% w/w,
weight concentration percentage), often known as high-test peroxide
(HTP), is considered because it is ITAR-free, easy to manufacture and
the operating temperature is lower than traditional monopropellant
propulsion. To establish satellite propulsion technology, the National
Space Organization (NSPO) in Taiwan has initialized a long-term
cooperation project with the National Cheng Kung University to
develop compatible tank and thruster. An experimental propulsion
payload has been allocated for the future self-reliant satellite to
perform orbit transfer and maintenance operations. In the present
research, an 1-Newton thruster prototype is designed and the thrusting
force is measured by a pendulum-type platform. The preliminary
hot-firing test at ambient environment showed the generated thrust and
the specific impulse are about 0.7 Newton and 102 seconds,
respectively.
Abstract: Flood zoning studies have become more efficient in
recent years because of the availability of advanced computational
facilities and use of Geographic Information Systems (GIS). In the
present study, flood inundated areas were mapped using GIS for the
Dikrong river basin of Arunachal Pradesh, India, corresponding to
different return periods (2, 5, 25, 50, and 100 years). Further, the developed inundation maps corresponding to 25, 50, and 100 year return period floods were compared to corresponding maps
developed by conventional methods as reported in the Brahmaputra Board Master Plan for Dikrong basin. It was found that, the average
deviation of modelled flood inundation areas from reported map
inundation areas is below 5% (4.52%). Therefore, it can be said that
the modelled flood inundation areas matched satisfactorily with
reported map inundation areas. Hence, GIS techniques were proved to be successful in extracting the flood inundation extent in a time and cost effective manner for the remotely located hilly basin of Dikrong, where conducting conventional surveys is very difficult.
Abstract: Performance appraisal of employee is important in
managing the human resource of an organization. With the change
towards knowledge-based capitalism, maintaining talented
knowledge workers is critical. However, management classification
of “outstanding", “poor" and “average" performance may not be an
easy decision. Besides that, superior might also tend to judge the
work performance of their subordinates informally and arbitrarily
especially without the existence of a system of appraisal. In this
paper, we propose a performance appraisal system using
multifactorial evaluation model in dealing with appraisal grades
which are often express vaguely in linguistic terms. The proposed
model is for evaluating staff performance based on specific
performance appraisal criteria. The project was collaboration with
one of the Information and Communication Technology company in
Malaysia with reference to its performance appraisal process.
Abstract: In a BFWA (Broadband Fixed Wireless Access Network) the evolved SINR (Signal to Interference plus Noise Ratio) is relevant influenced by the applied duplex method. The TDD (Time Division Duplex), especially adaptive TDD method has some advantage contrary to FDD (Frequency Division Duplex), for example the spectrum efficiency and flexibility. However these methods are suffering several new interference situations that can-t occur in a FDD system. This leads to reduced SINR in the covered area what could cause some connection outages. Therefore, countermeasure techniques against interference are necessary to apply in TDD systems. Synchronization is one way to handling the interference. In this paper the TDD systems – applying different system synchronization degree - will be compared by the evolved SINR at different locations of the BFWA service area and the percentage of the covered area by the system.
Abstract: The main problems of data centric and open source
project are large number of developers and changes of core
framework. Model-View-Control (MVC) design pattern significantly
improved the development and adjustments of complex projects.
Entity framework as a Model layer in MVC architecture has
simplified communication with the database. How often are the new
technologies used and whether they have potentials for designing
more efficient Enterprise Resource Planning (ERP) system that will
be more suited to accountants?
Abstract: The right information at the right time influences the
enterprise and technical success. Sharing knowledge among members
of a big organization may be a complex activity. And as long as the
knowledge is not shared, can not be exploited by the organization.
There are some mechanisms which can originate knowledge sharing.
It is intended, in this paper, to trigger these mechanisms by using
semantic nets. Moreover, the intersection and overlapping of terms
and sub-terms, as well as their relationships will be described through
the mereology science for the whole knowledge sharing system. It is
proposed a knowledge system to supply to operators with the right
information about a specific process and possible risks, e.g. at the
assembly process, at the right time in an automated manufacturing
environment, such as at the automotive industry.
Abstract: This paper presents the research agenda that has been proposed to develop an integrated model to explain technology adoption of SMEs in Malaysia. SMEs form over 90% of all business entities in Malaysia and they have been contributing to the development of the nation. Technology adoption has been a thorn issue among SMEs as they require big outlay which might not be available to the SMEs. Although resource has been an issue among SMEs they cannot lie low and ignore the technological advancements that are taking place at a rapid pace. With that in mind this paper proposes a model to explain the technology adoption issue among SMEs.
Abstract: In this article we present a change point detection algorithm based on the continuous wavelet transform. At the beginning of the article we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that we describe a probabilistic algorithm which can be used to find changes using our transformed signal. It is shown that our algorithm works well with the presence of some noise and abnormal random bursts.
Abstract: The main goal in this paper is to quantify the quality of
different techniques for radiation treatment plans, a back-propagation
artificial neural network (ANN) combined with biomedicine theory
was used to model thirteen dosimetric parameters and to calculate
two dosimetric indices. The correlations between dosimetric indices
and quality of life were extracted as the features and used in the ANN
model to make decisions in the clinic. The simulation results show
that a trained multilayer back-propagation neural network model can
help a doctor accept or reject a plan efficiently. In addition, the
models are flexible and whenever a new treatment technique enters
the market, the feature variables simply need to be imported and the
model re-trained for it to be ready for use.
Abstract: Data Structures and Algorithms is a module in most
Computer Science or Information Technology curricula. It is one of
the modules most students identify as being difficult. This paper
demonstrates how programming a solution for Sudoku can make
abstract concepts more concrete. The paper relates concepts of a
typical Data Structures and Algorithms module to a step by step
solution for Sudoku in a human type as opposed to a computer
oriented solution.
Abstract: Stirred tanks have applications in many chemical
processes where mixing is important for the overall performance of
the system. In present work 5%v of the tank is filled by solid particles
with diameter of 700 m that Rushton Turbine and Propeller impeller
is used for stirring. An Eulerian-Eulerian Multi Fluid Model coupled
and for modeling rotating of impeller, moving reference frame
(MRF) technique was used and standard-k- model was selected for
turbulency. Flow field, radial velocity and axial distribution of solid
for both of impellers was investigation and comparison. Comparisons
of simulation results between Rushton Turbine and propeller impeller
shows that final quality of solid-liquid slurry in different rotating
speed for propeller impeller is better than the Rushton Turbine.
Abstract: In the era of great competition, understanding and satisfying
customers- requirements are the critical tasks for a company
to make a profits. Customer relationship management (CRM) thus
becomes an important business issue at present. With the help of
the data mining techniques, the manager can explore and analyze
from a large quantity of data to discover meaningful patterns and
rules. Among all methods, well-known association rule is most
commonly seen. This paper is based on Apriori algorithm and uses
genetic algorithms combining a data mining method to discover fuzzy
classification rules. The mined results can be applied in CRM to
help decision marker make correct business decisions for marketing
strategies.