Abstract: The aim of the present study was to investigate the
chemical and biological properties of local cowpea seed protein
cultivated in Gizan region. The results showed that the cowpea and
its products contain high level of protein (22.9-77.6%), high
carbohydrates (9.4-64.3%) and low fats (0.1-0.3%). The trypsin and
chymotrypsin activities were found to be 32.2 and 15.2 units,
respectively. These activities were not affected in both defatted and
protein concentrate whereas they were significantly reduced in
isolated protein and cooked samples. The phytate content of cooked
and concentrated cowpea samples varied from 0.25% -0.32%,
respectively. Tannin content was found to be 0.4% and 0.23% for
cooked and raw samples, respectively. The in vitro protein
digestibility was very high in cowpea seeds (75.04-78.76%). The
biological evaluation using rats showed that the group fed with
animal feed containing casein gain more weight than those fed with
that containing cowpea. However, the group fed with cooked cowpea
gain more weight than those fed with uncooked cowpea. On the
other hand, in vivo digestion showed high value (98.33%) among the
group consumed casein compared to other groups those consumed
cowpea contains feed. This could be attributed to low antinutritional
factors in casein contains feed compared to those of cowpea contains
feed because cooking significantly increased the digestion rate
(80.8% to 83.5%) of cowpea contains feed. Furthermore, the
biological evaluation was high (91.67%) of casein containing feed
compared to that of cowpea containing feed (80.83%-87.5%). The
net protein utilization (NPU) was higher (89.67%) in the group fed
with casein containing feed than that of cowpea containing feed
(56.33%-69.67%).
Abstract: The State of Rio de Janeiro, Brazil, will hold two important events in the nearby future. In 2014 it will have the final game of the Football World Cup, and in 2016 it will be holding the Olympic Games. Therefore, the public transportation system (mainly buses) is of a major concern to the Rio de Janeiro State authorities-. The main objective of this work is to compare the quality of service of the bus companies operating in the cities of ItaperunaandCampos, both cities situated in the state of Rio de Janeiro, Brazil. The outcome of thiscomparison, based on the opinion of the bus users, has shownthemdispleased with the quality of the service provided by the bus companies operating in both cities. It is urgent the need to find possible practical alternatives to minimize the consequences of the main problems detected in this work. With these practical alternatives available, we will be able to offer to the Rio de Janeiro State authorities- suggestions about possible solutions to the main problems identified in this survey, as well as the time of implantation and costs of these solutions.
Abstract: The flow field over a flat roof model building has been numerically investigated in order to determine threedimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data. Wind tunnel measurements and numerical predictions have been compared for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions. The proposed calculations have allowed the development of a preliminary procedure to be used as guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a three-dimensional roof architecture dominated by flow separation.
Abstract: Two Amphiphilic catalysts, iron (III) dodecylbenzene
sulfonate and nickel (II) dodecylbenzene sulfonate, were synthesized
and used in the catalytic aquathermolysis of heavy crude oil to reduce
its viscosity. The prepared catalysts exhibited good performance in
the aquathermolysis and the viscosity is reduced by ~ 78.9 % for
Egyptian heavy crude oil. The chemical and physical properties of
heavy oil both before and after reaction were investigated by FT-IR,
dynamic viscosity, molecular weight and SARA analysis. The results
indicated that the content of resin, asphaltene, average molecular
weight and sulfur content of heavy oil is reduced after the catalytic
aquathermolysis.
Abstract: The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.
Abstract: Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.
Abstract: Time interleaved sigma-delta (TIΣΔ) architecture is a
potential candidate for high bandwidth analog to digital converters
(ADC) which remains a bottleneck for software and cognitive radio
receivers. However, the performance of the TIΣΔ architecture is
limited by the unavoidable gain and offset mismatches resulting
from the manufacturing process. This paper presents a novel digital
calibration method to compensate the gain and offset mismatch
effect. The proposed method takes advantage of the reconstruction
digital signal processing on each channel and requires only few logic
components for implementation. The run time calibration is estimated
to 10 and 15 clock cycles for offset cancellation and gain mismatch
calibration respectively.
Abstract: In this paper, we study the formation control problem
for car-like mobile robots. A team of nonholonomic mobile robots navigate in a terrain with obstacles, while maintaining a desired
formation, using a leader-following strategy. A set of artificial potential field functions is proposed using the direct Lyapunov
method for the avoidance of obstacles and attraction to their designated targets. The effectiveness of the proposed control laws to verify the feasibility of the model is demonstrated through computer simulations
Abstract: Small-scale RC models of both piles and tunnel ducts
were produced as mockups of reality and loaded under soil
confinement conditionsto investigate the damage evolution of
structural RC interacting with soil. Experimental verifications usinga
3D nonlinear FE analysis program called COM3D, which was
developed at the University of Tokyo, are introduced. This analysis
has been used in practice for seismic performance assessment of
underground ducts and in-ground LNG storage tanks in consideration
of soil-structure interactionunder static and dynamic loading. Varying
modes of failure of RCpilessubjected to different magnitudes of soil
confinement were successfully reproduced in the proposed small-scale
experiments and numerically simulated as well. Analytical simulation
was applied to RC tunnel mockups under a wide variety of depth and
soil confinement conditions, and reasonable matching was confirmed.
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: A simple but effective digital watermarking scheme
utilizing a context adaptive variable length coding (CAVLC) method
is presented for wireless communication system. In the proposed
approach, the watermark bits are embedded in the final non-zero
quantized coefficient of each DCT block, thereby yielding a potential
reduction in the length of the coded block. As a result, the
watermarking scheme not only provides the means to check the
authenticity and integrity of the video stream, but also improves the
compression ratio and therefore reduces both the transmission time
and the storage space requirements of the coded video sequence. The
results confirm that the proposed scheme enables the detection of
malicious tampering attacks and reduces the size of the coded H.264
file. Therefore, the current study is feasible to apply in the video
applications of wireless communication such as 3G system
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: 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: 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.
Abstract: Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20) and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specificity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%.
Abstract: Formulation of biological profile is one of the modern roles of forensic anthropologist. The present study was conducted to estimate height using foot and shoeprint length of Malaysian population. The present work can be very useful information in the process of identification of individual in forensic cases based on shoeprint evidence. It can help to narrow down suspects and ease the police investigation. Besides, stature is important parameters in determining the partial identify of unidentified and mutilated bodies. Thus, this study can help the problem encountered in cases of mass disaster, massacre, explosions and assault cases. This is because it is very hard to identify parts of bodies in these cases where people are dismembered and become unrecognizable. Samples in this research were collected from 200 Malaysian adults (100 males and 100 females) with age ranging from 20 to 45 years old. In this research, shoeprint length were measured based on the print of the shoes made from the flat shoes. Other information like gender, foot length and height of subject were also recorded. The data was analyzed using IBM® SPSS Statistics 19 software. Results indicated that, foot length has a strong correlation with stature than shoeprint length for both sides of the feet. However, in the unknown, where the gender was undetermined have shown a better correlation in foot length and shoeprint length parameter compared to males and females analyzed separately. In addition, prediction equations are developed to estimate the stature using linear regression analysis of foot length and shoeprint length. However, foot lengths give better prediction than shoeprint length.
Abstract: Aircraft propulsion systems often use Y-shaped
subsonic diffusing ducts as twin air-intakes to supply the ambient air
into the engine compressor for thrust generation. Due to space
constraint, the diffusers need to be curved, which causes severe flow
non-uniformity at the engine face. The present study attempt to
control flow in a mild-curved Y-duct diffuser using trapezoidalshaped
vortex generators (VG) attached on either both the sidewalls
or top and bottom walls of the diffuser at the inflexion plane. A
commercial computational fluid dynamics (CFD) code is modified
and is used to simulate the effects of SVG in flow of a Y-duct
diffuser. A few experiments are conducted for CFD code validation,
while the rest are done computationally. The best combination of Yduct
diffuser is found with VG-2 arranged in co-rotating sequence
and attached to both the sidewalls, which ensures highest static
pressure recovery, lowest total pressure loss, minimum flow
distortion and less flow separation in Y-duct diffuser. The decrease in
VG height while attached to top and bottom walls further improves
axial flow uniformity at the diffuser outlet by a great margin as
compared to the bare duct.
Abstract: This paper suggests a calibration method to reduce
errors occurring due to mobile robot sliding during location estimation
using the Dead-reckoning. Due to sliding of the mobile robot caused
between its wheels and the road surface while on free run, location
estimation can be erroneous. Sliding especially occurs during
cornering of mobile robot. Therefore, in order to reduce these frequent
sliding errors in cornering, we calibrated the mobile robot-s heading
values using a vision camera and templates of the ceiling.
Abstract: Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.