Abstract: In this paper, a joint source-channel coding (JSCC) scheme for time-varying channels is presented. The proposed scheme uses hierarchical framework for both source encoder and transmission via QAM modulation. Hierarchical joint source channel codes with hierarchical QAM constellations are designed to track the channel variations which yields to a higher throughput by adapting certain parameters of the receiver to the channel variation. We consider the problem of still image transmission over time-varying channels with channel state information (CSI) available at 1) receiver only and 2) both transmitter and receiver being informed about the state of the channel. We describe an algorithm that optimizes hierarchical source codebooks by minimizing the distortion due to source quantizer and channel impairments. Simulation results, based on image representation, show that, the proposed hierarchical system outperforms the conventional schemes based on a single-modulator and channel optimized source coding.
Abstract: The operating control parameters of injection
flushing type of electrical discharge machining process on stainless
steel 304 workpiece with copper tools are being optimized
according to its individual machining characteristic i.e. material
removal rate (MRR). Lower MRR during EDM machining process
may decrease its- machining productivity. Hence, the quality
characteristic for MRR is set to higher-the-better to achieve the
optimum machining productivity. Taguchi method has been used
for the construction, layout and analysis of the experiment for each
of the machining characteristic for the MRR. The use of Taguchi
method in the experiment saves a lot of time and cost of preparing
and machining the experiment samples. Therefore, an L18
Orthogonal array which was the fundamental component in the
statistical design of experiments has been used to plan the
experiments and Analysis of Variance (ANOVA) is used to
determine the optimum machining parameters for this machining
characteristic. The control parameters selected for this
optimization experiments are polarity, pulse on duration, discharge
current, discharge voltage, machining depth, machining diameter
and dielectric liquid pressure. The result had shown that the higher
the discharge voltage, the higher will be the MRR.
Abstract: This paper explores the issues that influence online retailing in Saudi Arabia. Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. Only very few Saudi companies, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data collected by conducting interviews with 16 retailers and 16 potential customers in Saudi Arabia, several factors influencing online retailing diffusion in Saudi Arabia are identified. However, government support comes the highest and most influencing factor for online retailing growth as identified by both parties; retailers and potential customers in Saudi Arabia.
Abstract: Aspheric optical components are an alternative to the use of conventional lenses in the implementation of imaging systems for the visible range. Spherical lenses are capable of producing aberrations. Therefore, they are not able to focus all the light into a single point. Instead, aspherical lenses correct aberrations and provide better resolution even with compact lenses incorporating a small number of lenses.
Metrology of these components is very difficult especially when the resolution requirements increase and insufficient or complexity of conventional tools requires the development of specific approaches to characterization.
This work is part of the problem existed because the objectives are the study and comparison of different methods used to measure surface rays hybrid aspherical lenses.
Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: Developing techniques for mobile robot navigation constitutes one of the major trends in the current
research on mobile robotics. This paper develops a local
model network (LMN) for mobile robot navigation. The
LMN represents the mobile robot by a set of locally valid
submodels that are Multi-Layer Perceptrons (MLPs).
Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular
region. The submodels then are combined in a unified
structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This
proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the
proposed LMN reflect the soundness of the proposed
scheme.
Abstract: Titanium nitride (TiN) has been synthesized using the
sheet plasma negative ion source (SPNIS). The parameters used for
its effective synthesis has been determined from previous
experiments and studies. In this study, further enhancement of the
deposition rate of TiN synthesis and advancement of the SPNIS
operation is presented. This is primarily achieved by the addition of
Sm-Co permanent magnets and a modification of the configuration in
the TiN deposition process. The magnetic enhancement is aimed at
optimizing the sputtering rate and the sputtering yield of the process.
The Sm-Co permanent magnets are placed below the Ti target for
better sputtering by argon. The Ti target is biased from –250V to –
350V and is sputtered by Ar plasma produced at discharge current of
2.5–4A and discharge potential of 60–90V. Steel substrates of
dimensions 20x20x0.5mm3 were prepared with N2:Ar volumetric
ratios of 1:3, 1:5 and 1:10. Ocular inspection of samples exhibit
bright gold color associated with TiN. XRD characterization
confirmed the effective TiN synthesis as all samples exhibit the (200)
and (311) peaks of TiN and the non-stoichiometric Ti2N (220) facet.
Cross-sectional SEM results showed increase in the TiN deposition
rate of up to 0.35μm/min. This doubles what was previously obtained
[1]. Scanning electron micrograph results give a comparative
morphological picture of the samples. Vickers hardness results gave
the largest hardness value of 21.094GPa.
Abstract: In this article, we expose our research work in
Human-machine Interaction. The research consists in manipulating
the workspace by eyes. We present some of our results, in particular
the detection of eyes and the mouse actions recognition. Indeed, the
handicaped user becomes able to interact with the machine in a more
intuitive way in diverse applications and contexts. To test our
application we have chooses to work in real time on videos captured
by a camera placed in front of the user.
Abstract: Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.
Abstract: In this paper, we investigate the study of techniques
for scheduling users for resource allocation in the case of multiple
input and multiple output (MIMO) packet transmission systems. In
these systems, transmit antennas are assigned to one user or
dynamically to different users using spatial multiplexing. The
allocation of all transmit antennas to one user cannot take full
advantages of multi-user diversity. Therefore, we developed the case
when resources are allocated dynamically. At each time slot users
have to feed back their channel information on an uplink feedback
channel. Channel information considered available in the schedulers
is the zero forcing (ZF) post detection signal to interference plus
noise ratio. Our analysis study concerns the round robin and the
opportunistic schemes.
In this paper, we present an overview and a complete capacity
analysis of these schemes. The main results in our study are to give
an analytical form of system capacity using the ZF receiver at the
user terminal. Simulations have been carried out to validate all
proposed analytical solutions and to compare the performance of
these schemes.
Abstract: In [4], Kipnis and Shamir have cryptanalised
a version of HFE of degree 2. In this paper, we describe the
generalization of this attack of HFE of degree more than 2.
We are based on Fourier Transformation to acheive partially
this attack.
Abstract: The operating control parameters of injection
flushing type of electrical discharge machining process on stainless
steel 304 workpiece using copper tools are being optimized
according to its individual machining characteristic i.e. Electrode
Wear Ratio (EWR). Higher EWR would give bad dimensional
precision for the EDM machined workpiece because of high
electrode wear. Hence, the quality characteristic for EWR is set to
lower-the-better to achieve the optimum dimensional precision for
the machined workpiece. Taguchi method has been used for the
construction, layout and analysis of the experiment for EWR
machining characteristic. The use of Taguchi method in the
experiment saves a lot of time and cost of preparing and machining
the experiment samples. Therefore, an L18 Orthogonal array
which was the fundamental component in the statistical design of
experiments has been used to plan the experiments and Analysis of
Variance (ANOVA) is used to determine the optimum machining
parameters for this machining characteristic. The control
parameters selected for this optimization experiments are polarity,
pulse on duration, discharge current, discharge voltage, machining
depth, machining diameter and dielectric liquid pressure. The
result had shown that negative polarity machining parameter
setting will decreases EWR.
Abstract: In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.