Abstract: Border Gateway Protocol (BGP) is the standard routing protocol between various autonomous systems (AS) in the internet. In the event of failure, a considerable delay in the BGP convergence has been shown by empirical measurements. During the convergence time the BGP will repeatedly advertise new routes to some destination and withdraw old ones until it reach a stable state. It has been found that the KEEPALIVE message timer and the HOLD time are tow parameters affecting the convergence speed. This paper aims to find the optimum value for the KEEPALIVE timer and the HOLD time that maximally reduces the convergence time without increasing the traffic. The KEEPALIVE message timer optimal value founded by this paper is 30 second instead of 60 seconds, and the optimal value for the HOLD time is 90 seconds instead of 180 seconds.
Abstract: Retrieval image by shape similarity, given a template
shape is particularly challenging, owning to the difficulty to derive a
similarity measurement that closely conforms to the common
perception of similarity by humans. In this paper, a new method for the
representation and comparison of shapes is present which is based on
the shape matrix and snake model. It is scaling, rotation, translation
invariant. And it can retrieve the shape images with some missing or
occluded parts. In the method, the deformation spent by the template
to match the shape images and the matching degree is used to evaluate
the similarity between them.
Abstract: This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.
Abstract: Avalanche velocity (from start to track zone) has been estimated in the present model for an avalanche which is triggered artificially by an explosive devise. The initial development of the model has been from the concept of micro-continuum theories [1], underwater explosions [2] and from fracture mechanics [3] with appropriate changes to the present model. The model has been computed for different slab depth R, slope angle θ, snow density ¤ü, viscosity μ, eddy viscosity η*and couple stress parameter η. The applicability of the present model in the avalanche forecasting has been highlighted.
Abstract: Interpretation of aerial images is an important task in
various applications. Image segmentation can be viewed as the essential
step for extracting information from aerial images. Among many
developed segmentation methods, the technique of clustering has been
extensively investigated and used. However, determining the number
of clusters in an image is inherently a difficult problem, especially
when a priori information on the aerial image is unavailable. This
study proposes a support vector machine approach for clustering
aerial images. Three cluster validity indices, distance-based index,
Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative
measures of the quality of clustering results. Comparisons on the
effectiveness of these indices and various parameters settings on the
proposed methods are conducted. Experimental results are provided
to illustrate the feasibility of the proposed approach.
Abstract: The number of features required to represent an image
can be very huge. Using all available features to recognize objects
can suffer from curse dimensionality. Feature selection and
extraction is the pre-processing step of image mining. Main issues in
analyzing images is the effective identification of features and
another one is extracting them. The mining problem that has been
focused is the grouping of features for different shapes. Experiments
have been conducted by using shape outline as the features. Shape
outline readings are put through normalization and dimensionality
reduction process using an eigenvector based method to produce a
new set of readings. After this pre-processing step data will be
grouped through their shapes. Through statistical analysis, these
readings together with peak measures a robust classification and
recognition process is achieved. Tests showed that the suggested
methods are able to automatically recognize objects through their
shapes. Finally, experiments also demonstrate the system invariance
to rotation, translation, scale, reflection and to a small degree of
distortion.
Abstract: There are three approaches to complete Bayesian
Network (BN) model construction: total expert-centred, total datacentred,
and semi data-centred. These three approaches constitute the
basis of the empirical investigation undertaken and reported in this
paper. The objective is to determine, amongst these three
approaches, which is the optimal approach for the construction of a
BN-based model for the performance assessment of students-
laboratory work in a virtual electronic laboratory environment. BN
models were constructed using all three approaches, with respect to
the focus domain, and compared using a set of optimality criteria. In
addition, the impact of the size and source of the training, on the
performance of total data-centred and semi data-centred models was
investigated. The results of the investigation provide additional
insight for BN model constructors and contribute to literature
providing supportive evidence for the conceptual feasibility and
efficiency of structure and parameter learning from data. In addition,
the results highlight other interesting themes.
Abstract: Smart Dust particles, are small smart materials used for generating weather maps. We investigate question of the optimal number of Smart Dust particles necessary for generating precise, computationally feasible and cost effective 3–D weather maps. We also give an optimal matching algorithm for the generalized scenario, when there are N Smart Dust particles and M ground receivers.
Abstract: The Comparison analysis of the Wald-s and Bayestype sequential methods for testing hypotheses is offered. The merits of the new sequential test are: universality which consists in optimality (with given criteria) and uniformity of decision-making regions for any number of hypotheses; simplicity, convenience and uniformity of the algorithms of their realization; reliability of the obtained results and an opportunity of providing the errors probabilities of desirable values. There are given the Computation results of concrete examples which confirm the above-stated characteristics of the new method and characterize the considered methods in regard to each other.
Abstract: This paper presents the convergence analysis
of a prediction based blind equalizer for IIR channels.
Predictor parameters are estimated by using the recursive
least squares algorithm. It is shown that the prediction
error converges almost surely (a.s.) toward a scalar
multiple of the unknown input symbol sequence. It is
also proved that the convergence rate of the parameter
estimation error is of the same order as that in the iterated
logarithm law.
Abstract: In many buildings we rely on large footings to offer
structural stability. Designers often compensate for the lack of
knowledge available with regard to foundation-soil interaction by
furnishing structures with overly large footings. This may lead to a
significant increase in building expenditures if many large
foundations are present. This paper describes the interface material
law that governs the behavior along the contact surface of adjacent
materials, and the behavior of a large foundation under ultimate limit
loading. A case study is chosen that represents a common
foundation-soil system frequently used in general practice and
therefore relevant to other structures. Investigations include
compressing versus uplifting wind forces, alterations to the
foundation size and subgrade compositions, the role of the slab
stiffness and presence and the effect of commonly used structural
joints and connections. These investigations aim to provide the
reader with an objective design approach, efficiently preventing
structural instability.
Abstract: The purpose of this study was to evaluate the tissue
composition and carcass muscularity of 32 legs of Ile de France
lambs fed with diets containing sunflower seeds and vitamin E, with
mean body weight of 15 kg, lodged in individual pens at 15 kg and
slaughtered at 32 kg of body weight. The treatments influenced
(P0,05) by the treatments. The
interaction of the sunflower and vitamin E was positive for bone total
weights and intermuscular fat.
Abstract: Not only is municipal pattern the institution basement of urban management, but it also determines the forms of the management results. There-s a considerable possibility of bankruptcy for China-s current municipal pattern as it-s an overdraft of land deal in fact. Based on the analysis of China-s current municipal pattern, the passage proposed an assumption of a new pattern verified legitimacy by conceptual as well as econometric models. Conclusion is: the added supernumerary value of investment in public goods was not included in China-s current municipal pattern, but hidden in the rising housing prices; we should set housing tax or municipal tax to optimize the municipal pattern, to correct the behavior of local governments and to ensure the regular development of China-s urbanization.
Abstract: A model of vortex wake is suggested to determine the
induced power during animal hovering flight. The wake is modeled
by a series of equi-spaced rigid rectangular vortex plates, positioned
horizontally and moving vertically downwards with identical speeds;
each plate is generated during powering of the functionally wing
stroke. The vortex representation of the wake considered in the
current theory allows a considerable loss of momentum to occur. The
current approach accords well with the nature of the wingbeat since it
considers the unsteadiness in the wake as an important fluid
dynamical characteristic. Induced power in hovering is calculated as
the aerodynamic power required to generate the vortex wake system.
Specific mean induced power to mean wing tip velocity ratio is
determined by solely the normal spacing parameter (f) for a given
wing stroke amplitude. The current theory gives much higher specific
induced power estimate than anticipated by classical methods.
Abstract: The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.
Abstract: In this paper, we seek to determine one reasonable
local hub port and optimal routes for a containership fleet,
performing pick-ups and deliveries, between the hub and spoke ports
in a same region. The relationship between a hub port, and traffic in
feeder lines is analyzed. A new network planning method is proposed,
an integrated hub port location and route design, a capacitated vehicle
routing problem with pick-ups, deliveries and time deadlines are
formulated and solved using an improved genetic algorithm for
positioning the hub port and establishing routes for a containership
fleet. Results on the performance of the algorithm and the feasibility
of the approach show that a relatively small fleet of containerships
could provide efficient services within deadlines.
Abstract: The study was conducted to investigate the profile of
hepatitis in Kingdom of Saudi Arabia, and to determine which age
group hepatitis viruses most commonly infect. The epidemiology of
viral hepatitis in Saudi Arabia has undergone major changes,
concurrent with major socioeconomic developments over the last two
to three decades. This disease represents a major public health
problem in Saudi Arabia resulting in the need for considerable
healthcare resources. A retrospective cross sectional analysis of the
reported cases of viral hepatitis was conducted based on the reports
of The Ministry of Health in Saudi Arabia about Hepatitis A, B and C
infections in all regions from the period of January 2006 to December
2010. The study demonstrated that incidence of viral Hepatitis is
decreasing, except for Hepatitis B that showed minimal increase. Of
hepatitis A, B, and C, Hepatitis B virus (HBV) was the most
predominant type, accounting for (53%) of the cases, followed by
Hepatitis C virus (HCV) (30%) and HAV (17%). HAV infection
predominates in children (5–14 years) with 60% of viral hepatitis
cases, HBV in young adults (15–44 years) with 69% of viral hepatitis
cases, and HCV in older adults (>45 years) with 59% of viral
hepatitis cases. Despite significant changes in the prevalence of viral
hepatitis A, B and C, it remains a major public health problem in
Saudi Arabia; however, it showed a significant decline in the last two
decades that could be attributed to the vaccination programs and the
improved health facilities. Further researches are needed to identify
the risk factors making a specific age group or a specific region in
Saudi Arabia targeted for a specific type of hepatitis viruses.
Abstract: Fourier transform infrared (FT-IR) spectroscopic imaging
is an emerging technique that provides both chemically and
spatially resolved information. The rich chemical content of data
may be utilized for computer-aided determinations of structure and
pathologic state (cancer diagnosis) in histological tissue sections for
prostate cancer. FT-IR spectroscopic imaging of prostate tissue has
shown that tissue type (histological) classification can be performed to
a high degree of accuracy [1] and cancer diagnosis can be performed
with an accuracy of about 80% [2] on a microscopic (≈ 6μm)
length scale. In performing these analyses, it has been observed
that there is large variability (more than 60%) between spectra from
different points on tissue that is expected to consist of the same
essential chemical constituents. Spectra at the edges of tissues are
characteristically and consistently different from chemically similar
tissue in the middle of the same sample. Here, we explain these
differences using a rigorous electromagnetic model for light-sample
interaction. Spectra from FT-IR spectroscopic imaging of chemically
heterogeneous samples are different from bulk spectra of individual
chemical constituents of the sample. This is because spectra not
only depend on chemistry, but also on the shape of the sample.
Using coupled wave analysis, we characterize and quantify the nature
of spectral distortions at the edges of tissues. Furthermore, we
present a method of performing histological classification of tissue
samples. Since the mid-infrared spectrum is typically assumed to
be a quantitative measure of chemical composition, classification
results can vary widely due to spectral distortions. However, we
demonstrate that the selection of localized metrics based on chemical
information can make our data robust to the spectral distortions
caused by scattering at the tissue boundary.
Abstract: Rapid urbanization, industrialization and population
growth have led to an increase in number of automobiles that cause
air pollution. It is estimated that road traffic contributes 60% of air
pollution in urban areas. A case by case assessment is required to
predict the air quality in urban situations, so as to evolve certain
traffic management measures to maintain the air quality levels with
in the tolerable limits. Calicut city in the state of Kerala, India has
been chosen as the study area. Carbon Monoxide (CO) concentration
was monitored at 15 links in Calicut city and air quality performance
was evaluated over each link. The CO pollutant concentration values
were compared with the National Ambient Air Quality Standards
(NAAQS), and the CO values were predicted by using CALINE4 and
IITLS and Linear regression models. The study has revealed that
linear regression model performs better than the CALINE4 and
IITLS models. The possible association between CO pollutant
concentration and traffic parameters like traffic flow, type of vehicle,
and traffic stream speed was also evaluated.
Abstract: In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.