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: EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.
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 goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
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: In this paper a new approach for transmission pricing
is presented. The main idea is voltage angle allocation, i.e.
determining the contribution of each contract on the voltage angle of
each bus. DC power flow is used to compute a primary solution for
angle decomposition. To consider the impacts of system non-linearity
on angle decomposition, the primary solution is corrected in different
iterations of decoupled Newton-Raphson power flow. Then, the
contribution of each contract on power flow of each transmission line
is computed based on angle decomposition. Contract-related flows
are used as a measure for “extent of use" of transmission network
capacity and consequently transmission pricing. The presented
approach is applied to a 4-bus test system and IEEE 30-bus test
system.
Abstract: In this paper a class of analog algorithms based on the
concept of Cellular Neural Network (CNN) is applied in some
processing operations of some important medical images, namely
retina images, for detecting various symptoms connected with
diabetic retinopathy. Some specific processing tasks like
morphological operations, linear filtering and thresholding are
proposed, the corresponding template values are given and
simulations on real retina images are provided.
Abstract: In the first part of this paper [6], a method to
determine Frenet apparatus of the space-like curves in Minkowski
space-time is presented. In this work, the mentioned method is
developed for the time-like curves in Minkowski space-time.
Additionally, an example of presented method is illustrated.
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: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: Background noise is particularly damaging to speech
intelligibility for people with hearing loss especially for sensorineural
loss patients. Several investigations on speech intelligibility have
demonstrated sensorineural loss patients need 5-15 dB higher SNR
than the normal hearing subjects. This paper describes Discrete
Cosine Transform Power Normalized Least Mean Square algorithm
to improve the SNR and to reduce the convergence rate of the LMS
for Sensory neural loss patients. Since it requires only real arithmetic,
it establishes the faster convergence rate as compare to time domain
LMS and also this transformation improves the eigenvalue
distribution of the input autocorrelation matrix of the LMS filter.
The DCT has good ortho-normal, separable, and energy compaction
property. Although the DCT does not separate frequencies, it is a
powerful signal decorrelator. It is a real valued function and thus
can be effectively used in real-time operation. The advantages of
DCT-LMS as compared to standard LMS algorithm are shown via
SNR and eigenvalue ratio computations. . Exploiting the symmetry
of the basis functions, the DCT transform matrix [AN] can be
factored into a series of ±1 butterflies and rotation angles. This
factorization results in one of the fastest DCT implementation. There
are different ways to obtain factorizations. This work uses the fast
factored DCT algorithm developed by Chen and company. The
computer simulations results show superior convergence
characteristics of the proposed algorithm by improving the SNR at
least 10 dB for input SNR less than and equal to 0 dB, faster
convergence speed and better time and frequency characteristics.
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 this paper, we have developed an explicit analytical
drain current model comprising surface channel potential and
threshold voltage in order to explain the advantages of the proposed
Gate Stack Double Diffusion (GSDD) MOSFET design over the
conventional MOSFET with the same geometric specifications that
allow us to use the benefits of the incorporation of the high-k layer
between the oxide layer and gate metal aspect on the immunity of the
proposed design against the self-heating effects. In order to show the
efficiency of our proposed structure, we propose the simulation of the
power chopper circuit. The use of the proposed structure to design a
power chopper circuit has showed that the (GSDD) MOSFET can
improve the working of the circuit in terms of power dissipation and
self-heating effect immunity. The results so obtained are in close
proximity with the 2D simulated results thus confirming the validity
of the proposed model.
Abstract: The purpose of this paper is to conceptualize a futureoriented
human work environment and organizational activity in
deep mines that entails a vision of good and safe workplace. Futureoriented
technological challenges and mental images required for
modern work organization design were appraised. It is argued that an
intelligent-deep-mine covering the entire value chain, including
environmental issues and with work organization that supports good
working and social conditions towards increased human productivity
could be designed. With such intelligent system and work
organization in place, the mining industry could be seen as a place
where cooperation, skills development and gender equality are key
components. By this perspective, both the youth and women might
view mining activity as an attractive job and the work environment
as a safe, and this could go a long way in breaking the unequal
gender balance that exists in most mines today.
Abstract: This study presents a hybrid neural network and Gravitational Search Algorithm (HNGSA) method to solve well known Wessinger's equation. To aim this purpose, gravitational search algorithm (GSA) technique is applied to train a multi-layer perceptron neural network, which is used as approximation solution of the Wessinger's equation. A trial solution of the differential equation is written as sum of two parts. The first part satisfies the initial/ boundary conditions and does not contain any adjustable parameters and the second part which is constructed so as not to affect the initial/boundary conditions. The second part involves adjustable parameters (the weights and biases) for a multi-layer perceptron neural network. In order to demonstrate the presented method, the obtained results of the proposed method are compared with some known numerical methods. The given results show that presented method can introduce a closer form to the analytic solution than other numerical methods. Present method can be easily extended to solve a wide range of problems.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.
Abstract: Climate change is one of the greatest environmental,
economic, and social challenges of our time. Urban transportation has
had a major negative impact on our environment—most of our air
pollution comes from transport.
This paper explores ways to move toward a more sustainable
transport system by focusing on creating a more efficient and livable
city and improving the environmental efficiency of transport activity.
The analytical study covers some international examples of applying
sustainable transportation and uses them to suggest a frame work to
develop the transportation system in Egypt to be sustainable and more
intelligent.
Abstract: The objective of this work is to present a expertise on
flooding hazard analysis and how to reduce the risk. The analysis
concerns the disaster induced by the flood on November 10/11, 2001
in the Bab El Oued district of the city of Algiers.The study begins by
an expertise of damages in related with the urban environment and
the history of the urban growth of the site. After this phase, the work
is focalized on the identification of the existing correlations between
the development of the town and its vulnerability. The final step
consists to elaborate the interpretations on the interactions between
the urban growth, the sewerage network and the vulnerability of the
urban system.In conclusion, several recommendations are formulated
permitting the mitigation of the risk in the future. The principal
recommendations concern the new urban operations and the existing
urbanized sites.