Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: In this paper, we design an integration security system
that provides authentication service, authorization service, and
management service of security data and a unified interface for the
management service. The interface is originated from XKMS protocol
and is used to manage security data such as XACML policies, SAML
assertions and other authentication security data including public keys.
The system includes security services such as authentication,
authorization and delegation of authentication by employing SAML
and XACML based on security data such as authentication data,
attributes information, assertions and polices managed with the
interface in the system. It also has SAML producer that issues
assertions related on the result of the authentication and the
authorization services.
Abstract: Given a simple connected unweighted undirected graph G = (V (G), E(G)) with |V (G)| = n and |E(G)| = m, we present a new algorithm for the all-pairs shortest-path (APSP) problem. The running time of our algorithm is in O(n2 log n). This bound is an improvement over previous best known O(n2.376) time bound of Raimund Seidel (1995) for general graphs. The algorithm presented does not rely on fast matrix multiplication. Our algorithm with slight modifications, enables us to compute the APSP problem for unweighted directed graph in time O(n2 log n), improving a previous best known O(n2.575) time bound of Uri Zwick (2002).
Abstract: This paper shows a traceability framework for supply risk monitoring, beginning with the identification, analysis, and evaluation of the supply chain risk and focusing on the supply operations of the Health Care Institutions with oncology services in Bogota, Colombia. It includes a brief presentation of the state of the art of the Supply Chain Risk Management and traceability systems in logistics operations, and it concludes with the methodology to integrate the SCRM model with the traceability system.
Abstract: With previous studies that examined the importance
of functional store image and CSR, this study is aimed at examining
their effects in the self-congruity model in influencing store loyalty.
In particular, this study developed and tested a structural model in the
context of retailing industry on the self-congruity theory. Whilst
much of the self-congruity studies have incorporated functional store
image, there has been lack of studies that examined social
responsibility image of retail stores in the self-congruity studies.
Findings indicate that self-congruity influence on store loyalty was
mediated by both functional store image and social responsibility
image. In influencing store loyalty, the findings have shown that
social responsibility image has a stronger influence on store loyalty
than functional store image. This study offers important findings and
implications for future research as it presents a new framework on
the importance of social responsibility image.
Abstract: At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.
Abstract: In this paper two models using a functional network
were employed to solving classification problem. Functional networks
are generalized neural networks, which permit the specification of
their initial topology using knowledge about the problem at hand. In
this case, and after analyzing the available data and their relations, we
systematically discuss a numerical analysis method used for
functional network, and apply two functional network models to
solving XOR problem. The XOR problem that cannot be solved with
two-layered neural network can be solved by two-layered functional
network, which reveals a potent computational power of functional
networks, and the performance of the proposed model was validated
using classification problems.
Abstract: This paper proposes the analysis and design of robust
fuzzy control to Stochastic Parametrics Uncertaint Linear systems.
This system type to be controlled is partitioned into several linear
sub-models, in terms of transfer function, forming a convex polytope,
similar to LPV (Linear Parameters Varying) system. Once defined the
linear sub-models of the plant, these are organized into fuzzy Takagi-
Sugeno (TS) structure. From the Parallel Distributed Compensation
(PDC) strategy, a mathematical formulation is defined in the frequency
domain, based on the gain and phase margins specifications,
to obtain robust PI sub-controllers in accordance to the Takagi-
Sugeno fuzzy model of the plant. The main results of the paper are
based on the robust stability conditions with the proposal of one
Axiom and two Theorems.
Abstract: Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.
Abstract: This work concerns the evolution and the maintenance
of an ontological resource in relation with the evolution of the corpus
of texts from which it had been built.
The knowledge forming a text corpus, especially in dynamic domains,
is in continuous evolution. When a change in the corpus occurs, the
domain ontology must evolve accordingly. Most methods manage
ontology evolution independently from the corpus from which it is
built; in addition, they treat evolution just as a process of knowledge
addition, not considering other knowledge changes. We propose a
methodology for managing an evolving ontology from a text corpus
that evolves over time, while preserving the consistency and the
persistence of this ontology.
Our methodology is based on the changes made on the corpus to
reflect the evolution of the considered domain - augmented surgery
in our case. In this context, the results of text mining techniques,
as well as the ARCHONTE method slightly modified, are used to
support the evolution process.
Abstract: Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.
Abstract: Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.
Abstract: This paper presents a numerical approach for the static
and dynamic analysis of hydrodynamic radial journal bearings. In the
first part, the effect of shaft and housing deformability on pressure
distribution within oil film is investigated. An iterative algorithm that
couples Reynolds equation with a plane finite elements (FE)
structural model is solved. Viscosity-to-pressure dependency (Vogel-
Barus equation) is also included. The deformed lubrication gap and
the overall stress state are obtained. Numerical results are presented
with reference to a typical journal bearing configuration at two
different inlet oil temperatures. Obtained results show the great
influence of bearing components structural deformation on oil
pressure distribution, compared with results for ideally rigid
components. In the second part, a numerical approach based on
perturbation method is used to compute stiffness and damping
matrices, which characterize the journal bearing dynamic behavior.
Abstract: In this paper, a study on the applications of the
optimization and regression techniques for optimal calculation of
partial ratios of helical gearboxes with second-step double gear-sets
for minimal cross section dimension is introduced. From the condition
of the moment equilibrium of a mechanic system including three gear
units and their regular resistance condition, models for calculation of
the partial ratios of helical gearboxes with second-step double
gear-sets were given. Especially, by regression analysis, explicit
models for calculation of the partial ratios are introduced. These
models allow determining the partial ratios accurately and simply.
Abstract: Bacterial cellulose, a biopolysaccharide, is produced by the bacterium, Gluconacetobacter xylinus. Static batch fermentation for bacterial cellulose production was studied in sucrose and date syrup solutions (Bx. 10%) at 28 °C using G. xylinus (PTCC, 1734). Results showed that the maximum yields of bacterial cellulose (BC) were 4.35 and 1.69 g/l00 ml for date syrup and sucrose medium after 336 hours fermentation period, respectively. Comparison of FTIR spectrum of cellulose with BC indicated appropriate coincidence which proved that the component produced by G. xylinus was cellulose. Determination of the area under X-ray diffractometry patterns demonstrated that the crystallinity amount of cellulose (83.61%) was more than that for the BC (60.73%). The scanning electron microscopy imaging of BC and cellulose were carried out in two magnifications of 1 and 6K. Results showed that the diameter ratio of BC to cellulose was approximately 1/30 which indicated more delicacy of BC fibers relative to cellulose.
Abstract: Generally flow behavior in centrifugal fan is observed
to be in a state of instability with flow separation zones on suction
surface as well as near the front shroud. Overall performance of the
diffusion process in a centrifugal fan could be enhanced by
judiciously introducing the boundary layer suction slots. With easy
accessibility of CFD as an analytical tool, an extensive numerical
whole field analysis of the effect of boundary layer suction slots in
discrete regions of suspected separation points is possible. This paper
attempts to explore the effect of boundary layer suction slots
corresponding to various geometrical locations on the impeller with
converging configurations for the slots. The analysis shows that the
converging suction slots located on the impeller blade about 25%
from the trailing edge, significantly improves the static pressure
recovery across the fan. Also it is found that Slots provided at a
radial distance of about 12% from the leading and trailing edges
marginally improve the static pressure recovery across the fan.
Abstract: In this paper three different approaches for person
verification and identification, i.e. by means of fingerprints, face and
voice recognition, are studied. Face recognition uses parts-based
representation methods and a manifold learning approach. The
assessment criterion is recognition accuracy. The techniques under
investigation are: a) Local Non-negative Matrix Factorization
(LNMF); b) Independent Components Analysis (ICA); c) NMF with
sparse constraints (NMFsc); d) Locality Preserving Projections
(Laplacianfaces). Fingerprint detection was approached by classical
minutiae (small graphical patterns) matching through image
segmentation by using a structural approach and a neural network as
decision block. As to voice / speaker recognition, melodic cepstral
and delta delta mel cepstral analysis were used as main methods, in
order to construct a supervised speaker-dependent voice recognition
system. The final decision (e.g. “accept-reject" for a verification
task) is taken by using a majority voting technique applied to the
three biometrics. The preliminary results, obtained for medium
databases of fingerprints, faces and voice recordings, indicate the
feasibility of our study and an overall recognition precision (about
92%) permitting the utilization of our system for a future complex
biometric card.
Abstract: The study of the interaction between humans and
computers has been emerging during the last few years. This
interaction will be more powerful if computers are able to perceive
and respond to human nonverbal communication such as emotions. In
this study, we present the image-based approach to emotion
classification through lower facial expression. We employ a set of
feature points in the lower face image according to the particular face
model used and consider their motion across each emotive expression
of images. The vector of displacements of all feature points input to
the Adaptive Support Vector Machines (A-SVMs) classifier that
classify it into seven basic emotions scheme, namely neutral, angry,
disgust, fear, happy, sad and surprise. The system was tested on the
Japanese Female Facial Expression (JAFFE) dataset of frontal view
facial expressions [7]. Our experiments on emotion classification
through lower facial expressions demonstrate the robustness of
Adaptive SVM classifier and verify the high efficiency of our
approach.
Abstract: Wireless Sensor Networks (WSNs) have attracted the attention of many researchers. This has resulted in their rapid integration in very different areas such as precision agriculture,environmental monitoring, object and event detection and military surveillance. Due to the current WSN characteristics this technology is specifically useful in industrial areas where security, reliability and autonomy are basic, such as nuclear power plants, chemical plants, and others. In this paper we present a system based on WSNs to monitor environmental conditions around and inside a nuclear power plant, specifically, radiation levels. Sensor nodes, equipped with radiation sensors, are deployed in fixed positions throughout the plant. In addition, plant staff are also equipped with mobile devices with higher capabilities than sensors such as for example PDAs able to monitor radiation levels and other conditions around them. The system enables communication between PDAs, which form a Mobile Ad-hoc Wireless Network (MANET), and allows workers to monitor remote conditions in the plant. It is particularly useful during stoppage periods for inspection or in the event of an accident to prevent risk situations.
Abstract: This paper proposes the novel model order
formulation scheme to design a discrete PID controller for higher
order linear time invariant discrete systems. Modified PSO (MPSO)
based model order formulation technique has used to obtain the
successful formulated second order system. PID controller is tuned to
meet the desired performance specification by using pole-zero
cancellation and proposed design procedures. Proposed PID
controller is attached with both higher order system and formulated
second order system. System specifications are tabulated and closed
loop response is observed for stabilization process. The proposed
method is illustrated through numerical examples from literature.