Abstract: In this paper we propose a Multiple Description Image Coding(MDIC) scheme to generate two compressed and balanced rates descriptions in the wavelet domain (Daubechies biorthogonal (9, 7) wavelet) using pairwise correlating transform optimal and application method for Generalized Multiple Description Coding (GMDC) to image coding in the wavelet domain. The GMDC produces statistically correlated streams such that lost streams can be estimated from the received data. Our performance test shown that the proposed method gives more improvement and good quality of the reconstructed image when the wavelet coefficients are normalized by Gaussian Scale Mixture (GSM) model then the Gaussian one ,.
Abstract: With the advance of information technology in the
new era the applications of Internet to access data resources has
steadily increased and huge amount of data have become accessible
in various forms. Obviously, the network providers and agencies,
look after to prevent electronic attacks that may be harmful or may
be related to terrorist applications. Thus, these have facilitated the
authorities to under take a variety of methods to protect the special
regions from harmful data. One of the most important approaches is
to use firewall in the network facilities. The main objectives of
firewalls are to stop the transfer of suspicious packets in several
ways. However because of its blind packet stopping, high process
power requirements and expensive prices some of the providers are
reluctant to use the firewall. In this paper we proposed a method to
find a discriminate function to distinguish between usual packets and
harmful ones by the statistical processing on the network router logs.
By discriminating these data, an administrator may take an approach
action against the user. This method is very fast and can be used
simply in adjacent with the Internet routers.
Abstract: Covering-based rough sets is an extension of rough
sets and it is based on a covering instead of a partition of the
universe. Therefore it is more powerful in describing some practical
problems than rough sets. However, by extending the rough sets,
covering-based rough sets can increase the roughness of each model
in recognizing objects. How to obtain better approximations from
the models of a covering-based rough sets is an important issue.
In this paper, two concepts, determinate elements and indeterminate
elements in a universe, are proposed and given precise definitions
respectively. This research makes a reasonable refinement of the
covering-element from a new viewpoint. And the refinement may
generate better approximations of covering-based rough sets models.
To prove the theory above, it is applied to eight major coveringbased
rough sets models which are adapted from other literature.
The result is, in all these models, the lower approximation increases
effectively. Correspondingly, in all models, the upper approximation
decreases with exceptions of two models in some special situations.
Therefore, the roughness of recognizing objects is reduced. This
research provides a new approach to the study and application of
covering-based rough sets.
Abstract: With the intention of screening for heavy metal
tolerance, a number of bacteria were isolated and characterized from
a pristine soil. Two Gram positive isolates were identified as
Paenibacillus sp. and Bacillus thuringeinsis. Tolerance of Cd2+, Cu2+
and Zn2+ by these bacteria was studied and found that both bacteria
were highly sensitive to Cu2+ compared to other two metals. Both
bacteria showed the same pattern of metal tolerance in the order Zn+
> Cd2+ > Cu2+. When the metal tolerance in both bacteria was
compared, Paenibacillus sp. showed the highest sensitivity to Cu2+
where as B. thuringiensis showed highest sensitivity to Cd2+ and Zn2+
.These findings revealed the potential of Paenibacillus sp. in
developing a biosensor to detect Cu2+ in environmental samples.
Abstract: To determine the length of engagement threads of a bolt installed in a tapped part in order to avoid the threads stripping remains a very current problem in the design of the thread assemblies. It does not exist a calculation method formalized for the cases where the bolt is screwed directly in a ductile material. In this article, we study the behavior of the threads stripping of a loaded assembly by using a modelling by finite elements and a rupture criterion by damage. This modelling enables us to study the different parameters likely to influence the behavior of this bolted connection. We study in particular, the influence of couple of materials constituting the connection, of the bolt-s diameter and the geometrical characteristics of the tapped part, like the external diameter and the length of engagement threads. We established an experiments design to know the most significant parameters. That enables us to propose a simple expression making possible to calculate the resistance of the threads whatever the metallic materials of the bolt and the tapped part. We carried out stripping tests in order to validate our model. The estimated results are very close to those obtained by the tests.
Abstract: Names are important in many societies, even in technologically oriented ones which use e.g. ID systems to identify individual people. Names such as surnames are the most important as they are used in many processes, such as identifying of people and genealogical research. On the other hand variation of names can be a major problem for the identification and search for people, e.g. web search or security reasons. Name matching presumes a-priori that the recorded name written in one alphabet reflects the phonetic identity of two samples or some transcription error in copying a previously recorded name. We add to this the lode that the two names imply the same person. This paper describes name variations and some basic description of various name matching algorithms developed to overcome name variation and to find reasonable variants of names which can be used to further increasing mismatches for record linkage and name search. The implementation contains algorithms for computing a range of fuzzy matching based on different types of algorithms, e.g. composite and hybrid methods and allowing us to test and measure algorithms for accuracy. NYSIIS, LIG2 and Phonex have been shown to perform well and provided sufficient flexibility to be included in the linkage/matching process for optimising name searching.
Abstract: This paper presents a hybrid association control
scheme that can maintain load balancing among access points in the
wireless LANs and can satisfy the quality of service requirements of
the multimedia traffic applications. The proposed model is
mathematically described as a linear programming model. Simulation
study and analysis were conducted in order to demonstrate the
performance of the proposed hybrid load balancing and association
control scheme. Simulation results shows that the proposed scheme
outperforms the other schemes in term of the percentage of blocking
and the quality of the data transfer rate providing to the multimedia
and real-time applications.
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Abstract: This paper reports our analysis of 163 ks observations
of PSR J0538+2817 with the Rossi X-Ray Timing Explorer
(RXTE).The pulse profiles, detected up to 60 keV, show a single
peak asin the case for radio frequency. The profile is well described
by one Gaussians function with full width at half maximum (FWHM)
0.04794. We compared the difference of arrival time between radio
and X-ray pulse profiles for the first time. It turns out that the phase
of radio emits precede the X-ray by 8.7 ± 4.5 ms. Furthermore we
obtained the pulse profiles in the energy ranges of 2.29-6.18 keV,
6.18-12.63 keV and 12.63-17.36 keV. The intensity of pulses
decreases with the increasing energy range. We discuss the emission
geometry in our work.
Abstract: Web-based cooperative learning focuses on (1) the interaction and the collaboration of community members, and (2) the sharing and the distribution of knowledge and expertise by network technology to enhance learning performance. Numerous research literatures related to web-based cooperative learning have demonstrated that cooperative scripts have a positive impact to specify, sequence, and assign cooperative learning activities. Besides, literatures have indicated that role-play in web-based cooperative learning environments enhances two or more students to work together toward the completion of a common goal. Since students generally do not know each other and they lack the face-to-face contact that is necessary for the negotiation of assigning group roles in web-based cooperative learning environments, this paper intends to further extend the application of genetic algorithm (GA) and propose a GA-based algorithm to tackle the problem of role assignment in web-based cooperative learning environments, which not only saves communication costs but also reduces conflict between group members in negotiating role assignments.
Abstract: In this paper an analysis of blackouts in electric power
transmission systems is implemented using a model and studied in
simple networks with a regular topology. The proposed model
describes load demand and network improvements evolving on a
slow timescale as well as the fast dynamics of cascading overloads
and outages.
Abstract: Nuclear matrix protein 22 (NMP22) is a FDA approved
biomarker for bladder cancer. The objective of this study is to develop
a simple NMP22 immumosensor (NMP22-IMS) for accurate
measurement of NMP22. The NMP22-IMS was constructed with
NMP22 antibody immobilized on screen-printed carbon electrodes.
The construction procedures and antibody immobilization are simple.
Results showed that the NMP22-IMS has an excellent (r2³0.95)
response range (20 – 100 ng/mL). In conclusion, a simple and reliable
NMP22-IMS was developed, capable of precisely determining urine
NMP22 level.
Abstract: In this paper, an innovative watermarking scheme for audio signal based on genetic algorithms (GA) in the discrete wavelet transforms is proposed. It is robust against watermarking attacks, which are commonly employed in literature. In addition, the watermarked image quality is also considered. We employ GA for the optimal localization and intensity of watermark. The watermark detection process can be performed without using the original audio signal. The experimental results demonstrate that watermark is inaudible and robust to many digital signal processing, such as cropping, low pass filter, additive noise.
Abstract: Chemical and physical functionalization of multiwalled
carbon nanotubes (MWCNT) has been commonly practiced to
achieve better dispersion of carbon nanotubes (CNTs) in polymer
matrix. This work describes various functionalization methods (acidtreatment,
non-ionic surfactant treatment with TritonX-100),
fabrication of MWCNT/PP nanocomposites via melt blending and
characterization of mechanical properties. Microscopy analysis
(FESEM, TEM, XPS) showed effective purification of MWCNTs
under acid treatment, and better dispersion under both chemical and
physical functionalization techniques combined, in their respective
order. Tensile tests showed increase in tensile strength for the
nanocomposites that contain MWCNTs up to 2 wt%. A decrease in
tensile strength was seen in samples that contain 4 wt% of MWCNTs
for both raw and Triton X-100 functionalized, signifying MWCNT
degradation/rebundling at composition with higher content of
MWCNTs. For the acid-treated MWCNTs, however, the tensile
results showed slight improvement even at 4wt%, indicating effective
dispersion of MWCNTs.
Abstract: For fire safety purposes, the fire resistance and the
structural behavior of reinforced concrete members are assessed to
satisfy specific fire performance criteria. The available prescribed
provisions are based on standard fire load. Under various fire
scenarios, engineers are in need of both heat transfer analysis and
structural analysis. For heat transfer analysis, the study proposed a
modified finite difference method to evaluate the temperature profile
within a cross section. The research conducted is limited to concrete
sections exposed to a fire on their one side. The method is based on
the energy conservation principle and a pre-determined power
function of the temperature profile. The power value of 2.7 is found
to be a suitable value for concrete sections. The temperature profiles
of the proposed method are only slightly deviate from those of the
experiment, the FEM and the FDM for various fire loads such as
ASTM E 119, ASTM 1529, BS EN 1991-1-2 and 550 oC. The
proposed method is useful to avoid incontinence of the large matrix
system of the typical finite difference method to solve the
temperature profile. Furthermore, design engineers can simply apply
the proposed method in regular spreadsheet software.
Abstract: Some quality control tools use non metric subjective information coming from experts, who qualify the intensity of relations existing inside processes, but without quantifying them. In this paper we have developed a quality control analytic tool, measuring the impact or strength of the relationship between process operations and product characteristics. The tool includes two models: a qualitative model, allowing relationships description and analysis; and a formal quantitative model, by means of which relationship quantification is achieved. In the first one, concepts from the Graphs Theory were applied to identify those process elements which can be sources of variation, that is, those quality characteristics or operations that have some sort of prelacy over the others and that should become control items. Also the most dependent elements can be identified, that is those elements receiving the effects of elements identified as variation sources. If controls are focused in those dependent elements, efficiency of control is compromised by the fact that we are controlling effects, not causes. The second model applied adapts the multivariate statistical technique of Covariance Structural Analysis. This approach allowed us to quantify the relationships. The computer package LISREL was used to obtain statistics and to validate the model.
Abstract: In this paper we propose an NLP-based method for
Ontology Population from texts and apply it to semi automatic
instantiate a Generic Knowledge Base (Generic Domain Ontology) in
the risk management domain. The approach is semi-automatic and
uses a domain expert intervention for validation. The proposed
approach relies on a set of Instances Recognition Rules based on
syntactic structures, and on the predicative power of verbs in the
instantiation process. It is not domain dependent since it heavily
relies on linguistic knowledge.
A description of an experiment performed on a part of the
ontology of the PRIMA1 project (supported by the European
community) is given. A first validation of the method is done by
populating this ontology with Chemical Fact Sheets from
Environmental Protection Agency2. The results of this experiment
complete the paper and support the hypothesis that relying on the
predicative power of verbs in the instantiation process improves the
performance.
Abstract: This study is concerned with the investigation of the
suitability of several empirical and semi-empirical drying models
available in the literature to define drying behavior of viscose yarn
bobbins. For this purpose, firstly, experimental drying behaviour of
viscose bobbins was determined on an experimental dryer setup
which was designed and manufactured based on hot-air bobbin
dryers used in textile industry. Afterwards, drying models considered
were fitted to the experimentally obtained moisture ratios. Drying
parameters were drying temperature and bobbin diameter. The fit
was performed by selecting the values for constants in the models in
such a way that these values make the sum of the squared differences
between the experimental and the model results for moisture ratio
minimum. Suitability of fitting was specified as comparing the
correlation coefficient, standard error and mean square deviation.
The results show that the most appropriate model in describing the
drying curves of viscose bobbins is the Page model.
Abstract: Current OCR technology does not allow to
accurately recognizing small text images, such as those found
in web images. Our goal is to investigate new approaches to
recognize very low resolution text images containing antialiased
character shapes.
This paper presents a preliminary study on the variability of
such characters and the feasibility to discriminate them by
using geometrical features. In a first stage we analyze the
distribution of these features. In a second stage we present a
study on the discriminative power for recognizing isolated
characters, using various rendering methods and font
properties. Finally we present interesting results of our
evaluation tests leading to our conclusion and future focus.
Abstract: The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.