Abstract: Thepurpose of the research is to characterize the levels
of satisfaction of the students in e-learning post-graduate courses,
taking into account specific dimensions of the course which were
considered as benchmarks for the quality of this type of online
learning initiative, as well as the levels of satisfaction towards each
specific indicator identified in each dimension. It was also an aim of
this study to understand how thesedimensions relate to one another.
Using a quantitative research approach in the collection and analysis
of the data, the study involves the participation of the students who
attended on e-learning course in 2010/2011. The conclusions of this
study suggest that online students present relatively high levels of
satisfaction, which points towards a positive experience during the
course. It is possible to note that there is a correlation between the
different dimensions studied, consequently leading to different
improvement strategies. Ultimately, this investigation aims to
contribute to the promotion of quality and the success of e-learning
initiatives in Higher Education.
Abstract: This paper describes WiPoD (Wireless Position
Detector) which is a pure software based location determination and
tracking (positioning) system. It uses empirical signal strength measurements from different wireless access points for mobile user
positioning. It is designed to determine the location of users having
802.11 enabled mobile devices in an 802.11 WLAN infrastructure
and track them in real time. WiPoD is the first main module in our
LBS (Location Based Services) framework. We tested K-Nearest
Neighbor and Triangulation algorithms to estimate the position of a
mobile user. We also give the analysis results of these algorithms for
real time operations. In this paper, we propose a supportable, i.e.
understandable, maintainable, scalable and portable wireless
positioning system architecture for an LBS framework. The WiPoD
software has a multithreaded structure and was designed and implemented with paying attention to supportability features and real-time constraints and using object oriented design principles. We also describe the real-time software design issues of a wireless positioning system which will be part of an LBS framework.
Abstract: In this paper, a comparative study of application of
supervised and unsupervised learning algorithms on illumination
invariant face recognition has been carried out. The supervised
learning has been carried out with the help of using a bi-layered
artificial neural network having one input, two hidden and one output
layer. The gradient descent with momentum and adaptive learning
rate back propagation learning algorithm has been used to implement
the supervised learning in a way that both the inputs and
corresponding outputs are provided at the time of training the
network, thus here is an inherent clustering and optimized learning of
weights which provide us with efficient results.. The unsupervised
learning has been implemented with the help of a modified
Counterpropagation network. The Counterpropagation network
involves the process of clustering followed by application of Outstar
rule to obtain the recognized face. The face recognition system has
been developed for recognizing faces which have varying
illumination intensities, where the database images vary in lighting
with respect to angle of illumination with horizontal and vertical
planes. The supervised and unsupervised learning algorithms have
been implemented and have been tested exhaustively, with and
without application of histogram equalization to get efficient results.
Abstract: Complex assemblies of interacting proteins carry out
most of the interesting jobs in a cell, such as metabolism, DNA
synthesis, mitosis and cell division. These physiological properties
play out as a subtle molecular dance, choreographed by underlying
regulatory networks that control the activities of cyclin-dependent
kinases (CDK). The network can be modeled by a set of nonlinear
differential equations and its behavior predicted by numerical
simulation. In this paper, an innovative approach has been proposed
that uses genetic algorithms to mine a set of behavior data output by
a biological system in order to determine the kinetic parameters of
the system. In our approach, the machine learning method is
integrated with the framework of existent biological information in a
wiring diagram so that its findings are expressed in a form of system
dynamic behavior. By numerical simulations it has been illustrated
that the model is consistent with experiments and successfully shown
that such application of genetic algorithms will highly improve the
performance of mathematical model of the cell division cycle to
simulate such a complicated bio-system.
Abstract: The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.
Abstract: A fundamental model consisting of charged particles
moving in free space exposed to alternating and direct current (ACDC)
electromagnetic fields is analyzed. Effects of charged particles
initial position and initial velocity to cyclotron resonance frequency
are observed. Strong effects are observed revealing that effects of
electric and magnetic fields on a charged particle in free space
varies with the initial conditions. This indicates the frequency where
maximum displacement occur can be changed. At this frequency
the amplitude of oscillation of the particle displacement becomes
unbounded.
Abstract: A new numerical method for simultaneously updating mass and stiffness matrices based on incomplete modal measured data is presented. By using the Kronecker product, all the variables that are to be modified can be found out and then can be updated directly. The optimal approximation mass matrix and stiffness matrix which satisfy the required eigenvalue equation and orthogonality condition are found under the Frobenius norm sense. The physical configuration of the analytical model is preserved and the updated model will exactly reproduce the modal measured data. The numerical example seems to indicate that the method is quite accurate and efficient.
Abstract: Protective effect of ethanolic extract of polyherbal formulation (PHF) was studied on carbon tetrachloride induced liver damage on carbon tetrachloride induced liver damage. Treatment of rats with 250mg /kg body weight of ethanolic extract of PHF protected rats against carbon tetrachloride liver injury by significant lowerering 5’ nucleotidase (5’NT), Gamma Glutamyl transferase (GGT), Glutamate dehdyrogenasse (GDH) and Succinate Dehydrogenase (SDH) levels compared to control. Normalization in these enzyme levels indicates strong hepatoprotective property of PHF extract.
Abstract: Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.
Abstract: In vitro gastro-duodenal digestion model was used to investigate the changes of emulsions under digestion conditions. Oil in water emulsions stabilized by whey proteins (2%) and stabilized by whey proteins (2%) with addition of carboxymethyl cellulose (0.75%) as gelling agent of continuous phase were prepared at pH7. Both emulsions were destabilized under gastric conditions; however the protective role of carboxymethyl cellulose was indicated by recording delay of fat digestibility of this emulsion. In the presence of carboxymethyl cellulose whey proteins on the interfacial surface of droplets were more resistant to gastric degradation causing limited hydrolysis of fat due to the poor acceptability of lipids for the enzymes. Studies of emulsions using in vivo model supported results from in vitro studies. Lower content of triglycerides in blood serum and higher amount of fecal fat of rats were determined when rats were fed by diet containing emulsion made with whey proteins and carboxymethyl cellulose.
Abstract: Real world Speaker Identification (SI) application
differs from ideal or laboratory conditions causing perturbations that
leads to a mismatch between the training and testing environment
and degrade the performance drastically. Many strategies have been
adopted to cope with acoustical degradation; wavelet based Bayesian
marginal model is one of them. But Bayesian marginal models
cannot model the inter-scale statistical dependencies of different
wavelet scales. Simple nonlinear estimators for wavelet based
denoising assume that the wavelet coefficients in different scales are
independent in nature. However wavelet coefficients have significant
inter-scale dependency. This paper enhances this inter-scale
dependency property by a Circularly Symmetric Probability Density
Function (CS-PDF) related to the family of Spherically Invariant
Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain
and corresponding joint shrinkage estimator is derived by Maximum
a Posteriori (MAP) estimator. A framework is proposed based on
these to denoise speech signal for automatic speaker identification
problems. The robustness of the proposed framework is tested for
Text Independent Speaker Identification application on 100 speakers
of POLYCOST and 100 speakers of YOHO speech database in three
different noise environments. Experimental results show that the
proposed estimator yields a higher improvement in identification
accuracy compared to other estimators on popular Gaussian Mixture
Model (GMM) based speaker model and Mel-Frequency Cepstral
Coefficient (MFCC) features.
Abstract: Mutations of the telomeric copy of the survival motor neuron 1 (SMN1) gene cause spinal muscular atrophy. A deletion of the Eef1a2 gene leads to lower motor neuron degeneration in wasted mice. Indirect evidences have been shown that the eEF1A protein family may interact with SMN, and our previous study showed that abnormalities of neuromuscular junctions in wasted mice were similar to those of Smn mutant mice. To determine potential colocalization between SMN and tissue-specific translation elongation factor 1A2 (eEF1A2), an immunochemical analysis of HeLa cells transfected with the plasmid pcDNA3.1(+)C-hEEF1A2- myc and a new quantitative test of colocalization by intensity correlation analysis (ICA) was used to explore the association of SMN and eEF1A2. Here the results showed that eEF1A2 redistributed from the cytoplasm to the nucleus in response to serum and epidermal growth factor. In the cytoplasm, compelling evidence showed that staining for myc-tagged eEF1A2 varied in synchrony with that for SMN, consistent with the formation of a SMN-eEF1A2 complex in the cytoplasm of HeLa cells. These findings suggest that eEF1A2 may colocalize with SMN in the cytoplasm and may be a component of the SMN complex. However, the limitation of the ICA method is an inability to resolve colocalization in components of small organelles such as the nucleus.
Abstract: This paper presents a new and efficient approach for capacitor placement in radial distribution systems that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Plant growth Simulation Algorithm (PGSA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately, avoiding the trouble to determine the barrier factors. The proposed method is applied to 9, 34, and 85-bus radial distribution systems. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution.
Abstract: When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.
Abstract: The main emphasis of metallurgists has been to process the materials to obtain the balanced mechanical properties for the given application. One of the processing routes to alter the properties is heat treatment. Nearly 90% of the structural applications are related to the medium carbon an alloyed steels and hence are regarded as structural steels. The major requirement in the conventional steel is to improve workability, toughness, hardness and grain refinement. In this view, it is proposed to study the mechanical and tribological properties of unalloyed structural (AISI 1140) steel with different thermal (heat) treatments like annealing, normalizing, tempering and hardening and compared with as brought (cold worked) specimen. All heat treatments are carried out in atmospheric condition. Hardening treatment improves hardness of the material, a marginal decrease in hardness value with improved ductility is observed in tempering. Annealing and normalizing improve ductility of the specimen. Normalized specimen shows ultimate ductility. Hardened specimen shows highest wear resistance in the initial period of slide wear where as above 25KM of sliding distance, as brought steel dominates the hardened specimen. Both mild and severe wear regions are observed. Microstructural analysis shows the existence of pearlitic structure in normalized specimen, lath martensitic structure in hardened, pearlitic, ferritic structure in annealed specimen.
Abstract: In this paper the features of multiple material gate
silicon-on-insulator MOSFETs are presented and compared with
single material gate silicon-on-insulator MOSFET structures. The
results indicate that the multiple material gate structures reduce short
channel effects such as drain induce barrier lowering, hot electron
effect and better current characteristics in comparison with single
material structures
Abstract: This study was carried out to develop a flotation
procedure for an oxide copper ore from a Region in Central Africa
for producing an 18% copper concentrate for downstream processing
at maximum recovery from a 4% copper feed grade. The copper
recoveries achieved from the test work were less than 50% despite
changes in reagent conditions (multistage sulphidisation, use of RCA
emulsion and mixture, use of AM 2, etc). The poor recoveries were
attributed to the mineralogy of the ore from which copper silicates
accounted for approximately 70% (mass) of the copper minerals in
the ore. These can be complex and difficult to float using
conventional flotation methods. Best results were obtained using
basic sulphidisation procedures, a high flotation temperature and
extended flotation residence time.
Abstract: A new, combinatorial model for analyzing and inter-
preting an electrocardiogram (ECG) is presented. An application of
the model is QRS peak detection. This is demonstrated with an
online algorithm, which is shown to be space as well as time efficient.
Experimental results on the MIT-BIH Arrhythmia database show that
this novel approach is promising. Further uses for this approach are
discussed, such as taking advantage of its small memory requirements
and interpreting large amounts of pre-recorded ECG data.
Abstract: Fishbone of Nile Tilapia (Tilapia nilotica), waste from the frozen Nile Tilapia fillet factory, is one of calcium sources. In order to increase fish bone powder value, this study aimed to investigate the effect of Tilapia bone flour (TBF) addition (5, 10, 15% by flour weight) on cooking quality, texture and sensory attributes of noodles. The results indicated that tensile strength, color value (a*) and water absorption of noodles significantly decreased (p£0.05) as the levels of TBF increased from 0-15%. While cooking loss, cooking time and color values (L* and b*) of noodles significantly increased (p£0.05). Sensory evaluation indicated that noodles with 5% TBF received the highest overall acceptability score.
Abstract: Pyrolysis of waste tire is one of alternative technique
to produce petrochemicals, such as light olefins, mixed C4, and monoaromatics.
Noble metals supported on acid zeolite catalysts were
reported as potential catalysts to produce the high valuable products
from waste tire pyrolysis. Especially, Pd supported on HBeta gave a
high yield of olefins, mixed C4, and mono-aromatics. Due to the high
prices of noble metals, the objective of this work was to investigate
whether or not a non-noble Ni metal can be used as a substitute of a
noble metal, Pd, supported on HBeta as a catalyst for waste tire pyrolysis.
Ni metal was selected in this work because Ni has high activity
in cracking, isomerization, hydrogenation and the ring opening of
hydrocarbons Moreover, Ni is an element in the same group as Pd
noble metal, which is VIIIB group, aiming to produce high valuable
products similarly obtained from Pd. The amount of Ni was varied as
5, 10, and 20% by weight, for comparison with a fixed 1 wt% Pd,
using incipient wetness impregnation. The results showed that as a
petrochemical-producing catalyst, 10%Ni/HBeta performed better
than 1%Pd/HBeta because it did not only produce the highest yield of
olefins and cooking gases, but the yields were also higher than
1%Pd/HBeta. 5%Ni/HBeta can be used as a substitute of
1%Pd/HBeta for similar crude production because its crude contains
the similar amounts of naphtha and saturated HCs, although it gave
no concentration of light mono-aromatics (C6-C11) in the oil. Additionally,
10%Ni/HBeta that gave high olefins and cooking gases was
found to give a fairly high concentration of the light mono-aromatics
in the oil.