Abstract: Buoyancy driven heat transfer of nanofluids in a
cylindrical enclosure used as a control unit in the subsea hydrocarbon
injection wells is investigated in this study. The governing equations
obtained with the Boussinesq approximation are solved using Comsol
Multiphysics finite element analysis and simulation software. The
base fluid is water and CuO is used as nanoparticles. Solution is
obtained for nanoparticle solid volume fraction of 8% and for
Rayleigh number in the range of 105-107. The results show that
nanoparticle usage in the cylindrical electronic control unit has a
significant effect on the flow and heat transfer.
Abstract: In this paper we use the property of co-occurrence
matrix in finding parallel lines in binary pictures for fingerprint
identification. In our proposed algorithm, we reduce the noise by
filtering the fingerprint images and then transfer the fingerprint
images to binary images using a proper threshold. Next, we divide
the binary images into some regions having parallel lines in the same
direction. The lines in each region have a specific angle that can be
used for comparison. This method is simple, performs the
comparison step quickly and has a good resistance in the presence of
the noise.
Abstract: Calcium [Ca2+] is an important second messenger
which plays an important role in signal transduction. There are
several parameters that affect its concentration profile like buffer
source etc. The effect of stationary immobile buffer on Ca2+
concentration has been incorporated which is a very important
parameter needed to be taken into account in order to make the
model more realistic. Interdependence of all the important parameters
like diffusion coefficient and influx over [Ca2+] profile has been
studied. Model is developed in the form of advection diffusion
equation together with buffer concentration. A program has been
developed using finite volume method for the entire problem and
simulated on an AMD-Turion 32-bit machine to compute the
numerical results.
Abstract: Saturated hydraulic conductivity is one of the soil
hydraulic properties which is widely used in environmental studies
especially subsurface ground water. Since, its direct measurement is
time consuming and therefore costly, indirect methods such as
pedotransfer functions have been developed based on multiple linear
regression equations and neural networks model in order to estimate
saturated hydraulic conductivity from readily available soil
properties e.g. sand, silt, and clay contents, bulk density, and organic
matter. The objective of this study was to develop neural networks
(NNs) model to estimate saturated hydraulic conductivity from
available parameters such as sand and clay contents, bulk density,
van Genuchten retention model parameters (i.e. r
θ , α , and n) as well
as effective porosity. We used two methods to calculate effective
porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s
θ is
saturated water content, FC θ is water content retained at -33 kPa
matric potential, and inf θ is water content at the inflection point.
Total of 311 soil samples from the UNSODA database was divided
into three groups as 187 for the training, 62 for the validation (to
avoid over training), and 62 for the test of NNs model. A commercial
neural network toolbox of MATLAB software with a multi-layer
perceptron model and back propagation algorithm were used for the
training procedure. The statistical parameters such as correlation
coefficient (R2), and mean square error (MSE) were also used to
evaluate the developed NNs model. The best number of neurons in
the middle layer of NNs model for methods (1) and (2) were
calculated 44 and 6, respectively. The R2 and MSE values of the test
phase were determined for method (1), 0.94 and 0.0016, and for
method (2), 0.98 and 0.00065, respectively, which shows that method
(2) estimates saturated hydraulic conductivity better than method (1).
Abstract: Many multimedia communication applications require a
source to transmit messages to multiple destinations subject to quality
of service (QoS) delay constraint. To support delay constrained
multicast communications, computer networks need to guarantee an
upper bound end-to-end delay from the source node to each of
the destination nodes. This is known as multicast delay problem.
On the other hand, if the same message fails to arrive at each
destination node at the same time, there may arise inconsistency and
unfairness problem among users. This is related to multicast delayvariation
problem. The problem to find a minimum cost multicast
tree with delay and delay-variation constraints has been proven to
be NP-Complete. In this paper, we propose an efficient heuristic
algorithm, namely, Economic Delay and Delay-Variation Bounded
Multicast (EDVBM) algorithm, based on a novel heuristic function,
to construct an economic delay and delay-variation bounded multicast
tree. A noteworthy feature of this algorithm is that it has very high
probability of finding the optimal solution in polynomial time with
low computational complexity.
Abstract: Waste problem is becoming a future problem all over the world. Magnesium wastes which can be used in recycling processes are produced by many industrial activities. Magnesium borates which have useful properties such as; high heat resistance, corrosion resistance, supermechanical strength, superinsulation, light weight, high coefficient of elasticity and so on. Addition, magnesium borates have great potential in the development of ceramic and detergents industry, whisker-reinforced composites, antiwear, and reducing friction additives.
In this study, using the starting materials of waste magnesium and H3BO3 the hydrothermal method was applied at a moderate temperature of 70oC with different reaction times. Several reaction times of waste magnesium to H3BO3 were selected as; 30, 60, 120, 240 minutes. After the synthesis, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR) techniques were applied to products. As a result, the forms of Admontite [MgO(B2O3)3.7(H2O)] and Mcallisterite [Mg2(B6O7(OH)6)2.9(H2O)] were synthesized.
Abstract: In this paper we investigate the watermarking authentication when applied to medical imagery field. We first give an overview of watermarking technology by paying attention to fragile watermarking since it is the usual scheme for authentication.We then analyze the requirements for image authentication and integrity in medical imagery, and we show finally that invertible schemes are the best suited for this particular field. A well known authentication method is studied. This technique is then adapted here for interleaving patient information and message authentication code with medical images in a reversible manner, that is using lossless compression. The resulting scheme enables on a side the exact recovery of the original image that can be unambiguously authenticated, and on the other side, the patient information to be saved or transmitted in a confidential way. To ensure greater security the patient information is encrypted before being embedded into images.
Abstract: The general purpose processors that are used in
embedded systems must support constraints like execution time,
power consumption, code size and so on. On the other hand an
Application Specific Instruction-set Processor (ASIP) has advantages
in terms of power consumption, performance and flexibility. In this
paper, a 16-bit Application Specific Instruction-set processor for the
sensor data transfer is proposed. The designed processor architecture
consists of on-chip transmitter and receiver modules along with the
processing and controlling units to enable the data transmission and
reception on a single die. The data transfer is accomplished with less
number of instructions as compared with the general purpose
processor. The ASIP core operates at a maximum clock frequency of
1.132GHz with a delay of 0.883ns and consumes 569.63mW power
at an operating voltage of 1.2V. The ASIP is implemented in Verilog
HDL using the Xilinx platform on Virtex4.
Abstract: Thermoplastic starch, polylactic acid glycerol and
maleic anhydride (MA) were compounded with natural
montmorillonite (MMT) through a twin screw extruder to investigate
the effects of different loading of MMT on structure, thermal and
absorption behavior of the nanocomposites. X-ray diffraction analysis
(XRD) showed that sample with MMT loading 4phr exhibited
exfoliated structure while sample that contained MMT 8 phr
exhibited intercalated structure. FESEM images showed big lump
when MMT loading was at 8 phr. The thermal properties were
characterized by using differential scanning calorimeter (DSC). The
results showed that MMT increased melting temperature and
crystallization temperature of matrix but reduction in glass transition
temperature was observed Meanwhile the addition of MMT has
improved the water barrier property. The nanosize MMT particle is
also able to block a tortuous pathway for water to enter the starch
chain, thus reducing the water uptake and improved the physical
barrier of nanocomposite.
Abstract: Land shortage for burials is one of many issues that emerge out of accelerated urban growth in most developing Asian cities, including Kuala Lumpur. Despite actions taken by the federal government and local authorities in addressing this issue, there is no strategic solution being formulated. Apart from making provisions for land to be developed as new cemeteries, the future plan is merely to allocate reserve land to accommodate the increasing demands of burial grounds around the city. This paper examines problems that arise from the traditional practices of Malay funerary as well as an insight to current urban practices in managing Muslim burial spaces around Kuala Lumpur metropolitan region. This paper will also provide some solutions through design approach that can be applied to counter the existing issues.
Abstract: In the past, there were more researches of recommendation system in applied electronic commerce. However, because all circles promote information technology integrative instruction actively, the quantity of instruction resources website is more and more increasing on the Internet. But there are less website including recommendation service, especially for teachers. This study established an instruction resource recommendation website that analyzed teaching style of teachers, then provided appropriate instruction resources for teachers immediately. We used the questionnaire survey to realize teacher-s suggestions and satisfactions with the instruction resource contents and recommendation results. The study shows: (1)The website used “Transactional Ability Inventory" that realized teacher-s style and provided appropriate instruction resources for teachers in a short time, it reduced the step of data filter. (2)According to the content satisfaction of questionnaire survey, four styles teachers were almost satisfied with the contents of the instruction resources that the website recommended, thus, the conception of developing instruction resources with different teaching style is accepted. (3) According to the recommendation satisfaction of questionnaire survey, four styles teachers were almost satisfied with the recommendation service of the website, thus, the recommendation strategy that provide different results for teachers in different teaching styles is accepted.
Abstract: This paper presents a design of source encoding
calculator software which applies the two famous algorithms in the
field of information theory- the Shannon-Fano and the Huffman
schemes. This design helps to easily realize the algorithms without
going into a cumbersome, tedious and prone to error manual
mechanism of encoding the signals during the transmission. The
work describes the design of the software, how it works, comparison
with related works, its efficiency, its usefulness in the field of
information technology studies and the future prospects of the
software to engineers, students, technicians and alike. The designed
“Encodia" software has been developed, tested and found to meet the
intended requirements. It is expected that this application will help
students and teaching staff in their daily doing of information theory
related tasks. The process is ongoing to modify this tool so that it can
also be more intensely useful in research activities on source coding.
Abstract: For about two decades scientists have been
developing techniques for enhancing the quality of medical images
using Fourier transform, DWT (Discrete wavelet transform),PDE
model etc., Gabor wavelet on hexagonal sampled grid of the images
is proposed in this work. This method has optimal approximation
theoretic performances, for a good quality image. The computational
cost is considerably low when compared to similar processing in the
rectangular domain. As X-ray images contain light scattered pixels,
instead of unique sigma, the parameter sigma of 0.5 to 3 is found to
satisfy most of the image interpolation requirements in terms of high
Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error
(MSE) and better image quality by adopting windowing technique.
Abstract: A multilayer self organizing neural neural network
(MLSONN) architecture for binary object extraction, guided by a beta
activation function and characterized by backpropagation of errors
estimated from the linear indices of fuzziness of the network output
states, is discussed. Since the MLSONN architecture is designed to
operate in a single point fixed/uniform thresholding scenario, it does
not take into cognizance the heterogeneity of image information in
the extraction process. The performance of the MLSONN architecture
with representative values of the threshold parameters of the beta
activation function employed is also studied. A three layer bidirectional
self organizing neural network (BDSONN) architecture
comprising fully connected neurons, for the extraction of objects from
a noisy background and capable of incorporating the underlying image
context heterogeneity through variable and adaptive thresholding,
is proposed in this article. The input layer of the network architecture
represents the fuzzy membership information of the image scene to
be extracted. The second layer (the intermediate layer) and the final
layer (the output layer) of the network architecture deal with the self
supervised object extraction task by bi-directional propagation of the
network states. Each layer except the output layer is connected to the
next layer following a neighborhood based topology. The output layer
neurons are in turn, connected to the intermediate layer following
similar topology, thus forming a counter-propagating architecture
with the intermediate layer. The novelty of the proposed architecture
is that the assignment/updating of the inter-layer connection weights
are done using the relative fuzzy membership values at the constituent
neurons in the different network layers. Another interesting feature
of the network lies in the fact that the processing capabilities of
the intermediate and the output layer neurons are guided by a beta
activation function, which uses image context sensitive adaptive
thresholding arising out of the fuzzy cardinality estimates of the
different network neighborhood fuzzy subsets, rather than resorting to
fixed and single point thresholding. An application of the proposed
architecture for object extraction is demonstrated using a synthetic
and a real life image. The extraction efficiency of the proposed
network architecture is evaluated by a proposed system transfer index
characteristic of the network.
Abstract: Multimedia security is an incredibly significant area of concern. The paper aims to discuss a robust image watermarking scheme, which can withstand geometric attacks. The source image is initially moment normalized in order to make it withstand geometric attacks. The moment normalized image is wavelet transformed. The first level wavelet transformed image is segmented into blocks if size 8x8. The product of mean and standard and standard deviation of each block is computed. The second level wavelet transformed image is divided into 8x8 blocks. The product of block mean and the standard deviation are computed. The difference between products in the two levels forms the watermark. The watermark is inserted by modulating the coefficients of the mid frequencies. The modulated image is inverse wavelet transformed and inverse moment normalized to generate the watermarked image. The watermarked image is now ready for transmission. The proposed scheme can be used to validate identification cards and financial instruments. The performance of this scheme has been evaluated using a set of parameters. Experimental results show the effectiveness of this scheme.
Abstract: The goal of steganography is to avoid drawing
suspicion to the transmission of a hidden message. If suspicion is
raised, steganography may fail. The success of steganography
depends on the secrecy of the action. If steganography is detected,
the system will fail but data security depends on the robustness of the
applied algorithm. In this paper, we propose a novel plausible
deniability scheme in steganography by using a diversionary message
and encrypt it with a DES-based algorithm. Then, we compress the
secret message and encrypt it by the receiver-s public key along with
the stego key and embed both messages in a carrier using an
embedding algorithm. It will be demonstrated how this method can
support plausible deniability and is robust against steganalysis.
Abstract: This paper reviews the greenhouse gas emissions of prefabrication elements for residential development in Hong Kong. Prefabrication becomes a common practice in residential development in Hong Kong and is considered as a green approach. In Hong Kong, prefabrication took place at factories in Pearl River Delta. Although prefabrication reduces construction wastage, it might generate more greenhouse gas emission from transportation and manufacturing processes. This study attempts to measure the “cradle to site" greenhouse gas emission from prefabrication elements for a public housing development in Kai Tak area. The findings could help further reduction of greenhouse gas emissions through process improvement.
Abstract: This study deals with a multi-criteria optimization
problem which has been transformed into a single objective
optimization problem using Response Surface Methodology (RSM),
Artificial Neural Network (ANN) and Grey Relational Analyses
(GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques
which can be used for solving multi-criteria optimization problem.
There have been two main purposes of this research as follows.
1. To determine optimum and robust fiber dyeing process
conditions by using RSM and ANN based on GRA,
2. To obtain the best suitable model by comparing models
developed by different methodologies.
The design variables for fiber dyeing process in textile are
temperature, time, softener, anti-static, material quantity, pH,
retarder, and dispergator. The quality characteristics to be evaluated
are nominal color consistency of fiber, maximum strength of fiber,
minimum color of dyeing solution. GRA-RSM with exact level
value, GRA-RSM with interval level value and GRA-ANN models
were compared based on GRA output value and MSE (Mean Square
Error) performance measurement of outputs with each other. As a
result, GRA-ANN with interval value model seems to be suitable
reducing the variation of dyeing process for GRA output value of the
model.
Abstract: In a transcutanious inductive coupling of a biomedical
implant, a new formula is given for the study of the Radio Frequency
power attenuation by the biological tissue. The loss of the signal
power is related to its interaction with the biological tissue and the
composition of this one. A confrontation with the practical
measurements done with a synthetic muscle into a Faraday cage,
allowed a checking of the obtained theoretical results. The
supply/data transfer systems used in the case of biomedical implants,
can be well dimensioned by taking in account this type of power
attenuation.
Abstract: Ambient Intelligence (AmI) environments bring
significant potential to exploit sophisticated computer technology in
everyday life. In particular, the educational domain could be
significantly enhanced through AmI, as personalized and adapted
learning could be transformed from paper concepts and prototypes to
real-life scenarios. In this paper, an integrated framework is
presented, named ClassMATE, supporting ubiquitous computing and
communication in a school classroom. The main objective of
ClassMATE is to enable pervasive interaction and context aware
education in the technologically augmented classroom of the future.