Abstract: The interaction between wakes of bluff body and
airfoil have profound influences on system performance in many
industrial applications, e.g., turbo-machinery and cooling fan. The
present work investigates the effect of configuration include; airfoil-s
angle of attack, transverse and inline spacing of the models, on
frequency behavior of the cylinder-s near-wake. The experiments
carried on under subcritical flow regime, using the hot-wire
anemometry (HWA). The relationship between the Strouhal numbers
and arrangements provide an insight into the global physical
processes of wake interaction and vortex shedding.
Abstract: Poly-β-hydroxybutyrate (PHB) is one of the most
famous biopolymers that has various applications in production of
biodegradable carriers. The most important strategy for enhancing
efficiency in production process and reducing the price of PHB, is the
accurate expression of kinetic model of products formation and
parameters that are effective on it, such as Dry Cell Weight (DCW)
and substrate consumption. Considering the high capabilities of
artificial neural networks in modeling and simulation of non-linear
systems such as biological and chemical industries that mainly are
multivariable systems, kinetic modeling of microbial production of
PHB that is a complex and non-linear biological process, the three
layers perceptron neural network model was used in this study.
Artificial neural network educates itself and finds the hidden laws
behind the data with mapping based on experimental data, of dry cell
weight, substrate concentration as input and PHB concentration as
output. For training the network, a series of experimental data for
PHB production from Hydrogenophaga Pseudoflava by glucose
carbon source was used. After training the network, two other
experimental data sets that have not intervened in the network
education, including dry cell concentration and substrate
concentration were applied as inputs to the network, and PHB
concentration was predicted by the network. Comparison of predicted
data by network and experimental data, indicated a high precision
predicted for both fructose and whey carbon sources. Also in present
study for better understanding of the ability of neural network in
modeling of biological processes, microbial production kinetic of
PHB by Leudeking-Piret experimental equation was modeled. The
Observed result indicated an accurate prediction of PHB
concentration by artificial neural network higher than Leudeking-
Piret model.
Abstract: Developers need to evaluate software's performance to make software efficient. This paper suggests a performance evaluation system for embedded software. The suggested system consists of code analyzer, testing agents, data analyzer, and report viewer. The code analyzer inserts additional code dependent on target system into source code and compiles the source code. The testing agents execute performance test. The data analyzer translates raw-level results data to class-level APIs for reporting viewer. The report viewer offers users graphical report views by using the APIs. We hope that the suggested tool will be useful for embedded-related software development,because developers can easily and intuitively analyze software's performance and resource utilization.
Abstract: In this paper we propose a method for modeling the
correlation between the received signals by two or more antennas
operating in a multipath environment. Considering the maximum
excess delay in the channel being modeled, an elliptical region
surrounding both transmitter and receiver antennas is produced. A
number of scatterers are randomly distributed in this region and
scatter the incoming waves. The amplitude and phase of incoming
waves are computed and used to obtain statistical properties of the
received signals. This model has the distinguishable advantage of
being applicable for any configuration of antennas. Furthermore the
common PDF (Probability Distribution Function) of received wave
amplitudes for any pair of antennas can be calculated and used to
produce statistical parameters of received signals.
Abstract: This paper explores the opportunity of using tri-axial
wireless accelerometers for supervised monitoring of sports
movements. A motion analysis system for the upper extremities of
lawn bowlers in particular is developed. Accelerometers are placed
on parts of human body such as the chest to represent the shoulder
movements, the back to capture the trunk motion, back of the hand,
the wrist and one above the elbow, to capture arm movements. These
sensors placement are carefully designed in order to avoid restricting
bowler-s movements. Data is acquired from these sensors in soft-real
time using virtual instrumentation; the acquired data is then
conditioned and converted into required parameters for motion
regeneration. A user interface was also created to facilitate in the
acquisition of data, and broadcasting of commands to the wireless
accelerometers. All motion regeneration in this paper deals with the
motion of the human body segment in the X and Y direction, looking
into the motion of the anterior/ posterior and lateral directions
respectively.
Abstract: In this paper, we present a novel approach to accurately
detect text regions including shop name in signboard images with
complex background for mobile system applications. The proposed
method is based on the combination of text detection using edge
profile and region segmentation using fuzzy c-means method. In the
first step, we perform an elaborate canny edge operator to extract all
possible object edges. Then, edge profile analysis with vertical and
horizontal direction is performed on these edge pixels to detect
potential text region existing shop name in a signboard. The edge
profile and geometrical characteristics of each object contour are
carefully examined to construct candidate text regions and classify the
main text region from background. Finally, the fuzzy c-means
algorithm is performed to segment and detected binarize text region.
Experimental results show that our proposed method is robust in text
detection with respect to different character size and color and can
provide reliable text binarization result.
Abstract: The evaluation of the contribution of professional
baseball starting pitchers is a complex decision-making problem that
includes several quantitative attributes. It is considered a type of
multi-attribute or multi-criteria decision making (MADM/MCDM)
problem. This study proposes a model using the Grey Relational
Analysis (GRA) to evaluate the starting pitcher contribution for teams
of the Chinese Professional Baseball League. The GRA calculates the
individual grey relational degree of each alternative to the positive
ideal alternative. An empirical analysis was conducted to show the use
of the model for the starting pitcher contribution problem. The results
demonstrate the effectiveness and feasibility of the proposed model.
Abstract: Phytases are enzymes used as an important component
in monogastric animals feeds in order to improve phosphorous
availability, since it is not readily assimilated by these animals in the
form of the phytate presented in plants and grains. As these enzymes
are used in industrial activities, they must retain its catalytic activities
during a certain storage period. This study presents information about
the stability of 4 different phytases, produced by four macromycetes
fungi through solid-state fermentation (SSF). There is a lack of data
in literature concerning phytase from macromycetes shelf-life in
storage conditions at room, cooling and freezing temperatures. The 4
phytases from macromycetes still had enzymatic activities around
100 days of storage at room temperature. At cooling temperature in
146 days of studies, the phytase from G. stipitatum was the most
stable with 44% of the initial activity, in U.gds (units per gram of
dried fermented substrate). The freezing temperature was the best
condition storage for phytases from G. stipitatum and T. versicolor.
Each condition provided a study for each mushroom phytase,
totalizing 12 studies. The phytases showed to be stable for a long
period without the addition of additives.
Abstract: In this work a software simulation model has been
proposed for two driven wheels mobile robot path planning; that can
navigate in dynamic environment with static distributed obstacles.
The work involves utilizing Bezier curve method in a proposed N
order matrix form; for engineering the mobile robot path. The Bezier
curve drawbacks in this field have been diagnosed. Two directions:
Up and Right function has been proposed; Probability Recursive
Function (PRF) to overcome those drawbacks.
PRF functionality has been developed through a proposed;
obstacle detection function, optimization function which has the
capability of prediction the optimum path without comparison
between all feasible paths, and N order Bezier curve function that
ensures the drawing of the obtained path.
The simulation results that have been taken showed; the mobile
robot travels successfully from starting point and reaching its goal
point. All obstacles that are located in its way have been avoided.
This navigation is being done successfully using the proposed PRF
techniques.
Abstract: We report a novel fusion tag for expressing
recombinant proteins in E. coli. The fusion tag is the C-terminus part
of the human GMCSF gene comprising 45 amino acids, which aid in
over expression of otherwise non expressible genes. Expression of
hIFN a2b with this fusion tag also escapes the requirement of rare
codons for expression. This is also a first report of a small fusion tag
of human origin having affinity to heparin sepharose column
facilitating the purification of fusion protein.
Abstract: A new dynamic clustering approach (DCPSO), based
on Particle Swarm Optimization, is proposed. This approach is
applied to unsupervised image classification. The proposed approach
automatically determines the "optimum" number of clusters and
simultaneously clusters the data set with minimal user interference.
The algorithm starts by partitioning the data set into a relatively large
number of clusters to reduce the effects of initial conditions. Using
binary particle swarm optimization the "best" number of clusters is
selected. The centers of the chosen clusters is then refined via the Kmeans
clustering algorithm. The experiments conducted show that
the proposed approach generally found the "optimum" number of
clusters on the tested images.
Abstract: Road authorities have confronted problems to
maintaining the serviceability of road infrastructure systems by using
various traditional methods of contracting. As a solution to these
problems, many road authorities have started contracting out road
maintenance works to the private sector based on performance
measures. This contracting method is named Performance-Based
Maintenance Contracting (PBMC). It is considered more costeffective
than other traditional methods of contracting. It has a
substantial success records in many developed and developing
countries over the last two decades. This paper discusses and
analyses the potential issues to be considered before the introduction
of PBMC in a country.
Abstract: Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR), Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing (LAR1).Our evaluation is based on energy consumption in mobile ad hoc networks. The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.
Abstract: This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.
Abstract: In this paper, an efficient technique is proposed to manage the cache memory. The proposed technique introduces some modifications on the well-known set associative mapping technique. This modification requires a little alteration in the structure of the cache memory and on the way by which it can be referenced. The proposed alteration leads to increase the set size virtually and consequently to improve the performance and the utilization of the cache memory. The current mapping techniques have accomplished good results. In fact, there are still different cases in which cache memory lines are left empty and not used, whereas two or more processes overwrite the lines of each other, instead of using those empty lines. The proposed algorithm aims at finding an efficient way to deal with such problem.
Abstract: Learning is the acquisition of new mental schemata, knowledge, abilities and skills which can be used to solve problems potentially more successfully. The learning process is optimum when it is assisted and personalized. Learning is not a single activity, but should involve many possible activities to make learning become meaningful. Many e-learning applications provide facilities to support teaching and learning activities. One way to identify whether the e-learning system is being used by the learners is through the number of hits that can be obtained from the e-learning system's log data. However, we cannot rely solely to the number of hits in order to determine whether learning had occurred meaningfully. This is due to the fact that meaningful learning should engage five characteristics namely active, constructive, intentional, authentic and cooperative. This paper aims to analyze the e-learning activities that is meaningful to learning. By focusing on the meaningful learning characteristics, we match it to the corresponding Moodle e-learning activities. This analysis discovers the activities that have high impact to meaningful learning, as well as activities that are less meaningful. The high impact activities is given high weights since it become important to meaningful learning, while the low impact has less weight and said to be supportive e-learning activities. The result of this analysis helps us categorize which e-learning activities that are meaningful to learning and guide us to measure the effectiveness of e-learning usage.
Abstract: Mathematical and computational modeling of calcium
signalling in nerve cells has produced considerable insights into how
the cells contracts with other cells under the variation of biophysical
and physiological parameters. The modeling of calcium signaling in
astrocytes has become more sophisticated. The modeling effort has
provided insight to understand the cell contraction. Main objective
of this work is to study the effect of voltage gated (Operated)
calcium channel (VOC) on calcium profile in the form of advection
diffusion equation. A mathematical model is developed in the form
of advection diffusion equation for the calcium profile. The model
incorporates the important physiological parameter like diffusion
coefficient etc. Appropriate boundary conditions have been framed.
Finite volume method is employed to solve the problem. A program
has been developed using in MATLAB 7.5 for the entire problem
and simulated on an AMD-Turion 32-bite machine to compute the
numerical results.
Abstract: This paper focuses on assessment of air pollution in Umm-Alhyman, Kuwait, which is located south to oil refineries, power station, oil field, and highways. The measurements were made over a period of four days in March and July in 2001, 2004, and 2008. The measured pollutants included methanated and nonmethanated hydrocarbons (MHC, NMHC), CO, CO2, SO2, NOX, O3, and PM10. Also, meteorological parameters were measured, which includes temperature, wind speed and direction, and solar radiation. Over the study period, data analysis showed increase in measured SO2, NOX and CO by factors of 1.2, 5.5 and 2, respectively. This is explained in terms of increase in industrial activities, motor vehicle density, and power generation. Predictions of the measured data were made by the ISC-AERMOD software package and by using the ISCST3 model option. Finally, comparison was made between measured data against international standards.
Abstract: Since 2004, we have been developing an in-situ storage image sensor (ISIS) that captures more than 100 consecutive images at a frame rate of 10 Mfps with ultra-high sensitivity as well as the video camera for use with this ISIS. Currently, basic research is continuing in an attempt to increase the frame rate up to 100 Mfps and above. In order to suppress electro-magnetic noise at such high frequency, a digital-noiseless imaging transfer scheme has been developed utilizing solely sinusoidal driving voltages. This paper presents highly efficient-yet-accurate expressions to estimate attenuation as well as phase delay of driving voltages through RC networks of an ultra-high-speed image sensor. Elmore metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE data, we found a simple expression that significantly improves the accuracy of the approximation. Similarly, another simple closed-form model to estimate phase delay through fundamental RC networks is also obtained. Estimation error of both expressions is much less than previous works, only less 2% for most of the cases . The framework of this analysis can be extended to address similar issues of other VLSI structures.
Abstract: Augmented Reality (AR) shows great promises for
its usage as a tool for simulation and verification of design proposal
of new technological systems. Main advantage of augmented reality
application usage is possibility of creation and simulation of new
technological unit before its realization. This may contribute to
increasing of safety and ergonomics and decreasing of economical
aspects of new proposed unit. Virtual model of proposed workcell
could reveal hidden errors which elimination in later stage of new
workcell creation should cause great difficulties. Paper describes
process of such virtual model creation and possibilities of its
simulation and verification by augmented reality tools.