Abstract: Anchovy (Engraulis Encrasicholus) and sardine
(Sardina Pilchardus) are blue fishes linked to our alimentary tradition
of Mediterranean. In our work, particularly, we tested for the first
time physical and enzymatic methods to verify the freshness of
species of blue fish, anchovy and sardine of Mediterranean. In
connection with to the lowering of the pH after post-mortem stage we
assisted to a increase in proteolytic activity of calpaine and catpsine.
Already after 2 h in post-mortem there was a significant increase.
Abstract: Case based reasoning (CBR) methodology presents a foundation for a new technology of building intelligent computeraided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. This paper discusses the CBR methodology, the research issues and technical aspects of implementing intelligent medical diagnoses systems. Successful applications in cancer and heart diseases developed by Medical Informatics Research Group at Ain Shams University are also discussed.
Abstract: In this paper the use of sequential machines for recognizing actions taken by the objects detected by a general tracking algorithm is proposed. The system may deal with the uncertainty inherent in medium-level vision data. For this purpose, fuzzification of input data is performed. Besides, this transformation allows to manage data independently of the tracking application selected and enables adding characteristics of the analyzed scenario. The representation of actions by means of an automaton and the generation of the input symbols for finite automaton depending on the object and action compared are described. The output of the comparison process between an object and an action is a numerical value that represents the membership of the object to the action. This value is computed depending on how similar the object and the action are. The work concludes with the application of the proposed technique to identify the behavior of vehicles in road traffic scenes.
Abstract: Reinforced Concrete (RC) structures strengthened
with fiber reinforced polymer (FRP) lack in thermal resistance under
elevated temperatures in the event of fire. This phenomenon led to
the lining of strengthened concrete with thin high performance
cementitious composites (THPCC) to protect the substrate against
elevated temperature. Elevated temperature effects on THPCC, based
on different cementitious materials have been studied in the past but
high-alumina cement (HAC)-based THPCC have not been well
characterized. This research study will focus on the THPCC based on
HAC replaced by 60%, 70%, 80% and 85% of ground granulated
blast furnace slag (GGBS). Samples were evaluated by the
measurement of their mechanical strength (28 & 56 days of curing)
after exposed to 400°C, 600°C and 28°C of room temperature for
comparison and corroborated by their microstructure study. Results
showed that among all mixtures, the mix containing only HAC
showed the highest compressive strength after exposed to 600°C as
compared to other mixtures. However, the tensile strength of THPCC
made of HAC and 60% GGBS content was comparable to the
THPCC with HAC only after exposed to 600°C. Field emission
scanning electron microscopy (FESEM) images of THPCC
accompanying Energy Dispersive X-ray (EDX) microanalysis
revealed that the microstructure deteriorated considerably after
exposure to elevated temperatures which led to the decrease in
mechanical strength.
Abstract: We investigate efficient spreading codes for transmitter based techniques of code division multiple access (CDMA) systems. The channel is considered to be known at the transmitter which is usual in a time division duplex (TDD) system where the channel is assumed to be the same on uplink and downlink. For such a TDD/CDMA system, both bitwise and blockwise multiuser transmission schemes are taken up where complexity is transferred to the transmitter side so that the receiver has minimum complexity. Different spreading codes are considered at the transmitter to spread the signal efficiently over the entire spectrum. The bit error rate (BER) curves portray the efficiency of the codes in presence of multiple access interference (MAI) as well as inter symbol interference (ISI).
Abstract: As the web continues to grow exponentially, the idea
of crawling the entire web on a regular basis becomes less and less
feasible, so the need to include information on specific domain,
domain-specific search engines was proposed. As more information
becomes available on the World Wide Web, it becomes more difficult
to provide effective search tools for information access. Today,
people access web information through two main kinds of search
interfaces: Browsers (clicking and following hyperlinks) and Query
Engines (queries in the form of a set of keywords showing the topic
of interest) [2]. Better support is needed for expressing one's
information need and returning high quality search results by web
search tools. There appears to be a need for systems that do reasoning
under uncertainty and are flexible enough to recover from the
contradictions, inconsistencies, and irregularities that such reasoning
involves. In a multi-view problem, the features of the domain can be
partitioned into disjoint subsets (views) that are sufficient to learn the
target concept. Semi-supervised, multi-view algorithms, which
reduce the amount of labeled data required for learning, rely on the
assumptions that the views are compatible and uncorrelated. This
paper describes the use of semi-structured machine learning approach
with Active learning for the “Domain Specific Search Engines". A
domain-specific search engine is “An information access system that
allows access to all the information on the web that is relevant to a
particular domain. The proposed work shows that with the help of
this approach relevant data can be extracted with the minimum
queries fired by the user. It requires small number of labeled data and
pool of unlabelled data on which the learning algorithm is applied to
extract the required data.
Abstract: We report a computational study of the spreading
dynamics of a viral infection in a complex (scale-free) network. The
final epidemic size distribution (FESD) was found to be unimodal or
bimodal depending on the value of the basic reproductive
number R0 . The FESDs occurred on time-scales long enough for
intermediate-time epidemic size distributions (IESDs) to be important
for control measures. The usefulness of R0 for deciding on the
timeliness and intensity of control measures was found to be limited
by the multimodal nature of the IESDs and by its inability to inform
on the speed at which the infection spreads through the population. A
reduction of the transmission probability at the hubs of the scale-free
network decreased the occurrence of the larger-sized epidemic events
of the multimodal distributions. For effective epidemic control, an
early reduction in transmission at the index cell and its neighbors was
essential.
Abstract: In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.
Abstract: Shadoo protein (Sho) was described in 2003 as the newest member of Prion protein superfamily [1]. Sho has similar structural motifs like prion protein (PrP) that is known for its central role in transmissible spongiform enchephalopathies. Although a great number of functions have been proposed, the exact physiological function of PrP is not known yet. Investigation of the function and localization of Sho may help us to understand the function of the Prion protein superfamily. Analyzing the subcellular localization of YFP-tagged forms of Sho, we detected the protein in the plasma membrane and in the nucleus of various cell lines. To reveal the localization of the endogenous protein we generated antibodies against Shadoo as well as employed commercially available anti-Shadoo antibodies: i) EG62 anti-mouse Shadoo antibody generated by Eurogentec Ltd.; ii) S-12 anti-human Shadoo antibody by Santa Cruz Biotechnology Inc.; iii) R-12 anti-mouse Shadoo antibody by Santa Cruz Biotechnology Inc.; iv) SPRN antibody against human Shadoo by Abgent Inc. We carried out immunocytochemistry on non-transfected HeLa, Zpl 2-1, Zw 3-5, GT1-1, GT1-7 and SHSY5Y cells as well as on YFP-Sho, Sho-YFP, and YFP-GPI transfected HeLa cells. Their specificity (in antibody-peptide competition assay) and co-localization (with the YFP signal) were assessed.
Abstract: Graph coloring is an important problem in computer
science and many algorithms are known for obtaining reasonably
good solutions in polynomial time. One method of comparing
different algorithms is to test them on a set of standard graphs where
the optimal solution is already known. This investigation analyzes a
set of 50 well known graph coloring instances according to a set of
complexity measures. These instances come from a variety of
sources some representing actual applications of graph coloring
(register allocation) and others (mycieleski and leighton graphs) that
are theoretically designed to be difficult to solve. The size of the
graphs ranged from ranged from a low of 11 variables to a high of
864 variables. The method used to solve the coloring problem was
the square of the adjacency (i.e., correlation) matrix. The results
show that the most difficult graphs to solve were the leighton and the
queen graphs. Complexity measures such as density, mobility,
deviation from uniform color class size and number of block
diagonal zeros are calculated for each graph. The results showed that
the most difficult problems have low mobility (in the range of .2-.5)
and relatively little deviation from uniform color class size.
Abstract: The paper depicts air velocity values, reproduced by laser Doppler anemometer (LDA) and ultrasonic anemometer (UA), relations with calculated ones from flow rate measurements using the gas meter which calibration uncertainty is ± (0.15 – 0.30) %. Investigation had been performed in channel installed in aerodynamical facility used as a part of national standard of air velocity. Relations defined in a research let us confirm the LDA and UA for air velocity reproduction to be the most advantageous measures. The results affirm ultrasonic anemometer to be reliable and favourable instrument for measurement of mean velocity or control of velocity stability in the velocity range of 0.05 m/s – 10 (15) m/s when the LDA used. The main aim of this research is to investigate low velocity regularities, starting from 0.05 m/s, including region of turbulent, laminar and transitional air flows. Theoretical and experimental results and brief analysis of it are given in the paper. Maximum and mean velocity relations for transitional air flow having unique distribution are represented. Transitional flow having distinctive and different from laminar and turbulent flow characteristics experimentally have not yet been analysed.
Abstract: There have been various methods created based on the regression ideas to resolve the problem of data set containing censored observations, i.e. the Buckley-James method, Miller-s method, Cox method, and Koul-Susarla-Van Ryzin estimators. Even though comparison studies show the Buckley-James method performs better than some other methods, it is still rarely used by researchers mainly because of the limited diagnostics analysis developed for the Buckley-James method thus far. Therefore, a diagnostic tool for the Buckley-James method is proposed in this paper. It is called the renovated Cook-s Distance, (RD* i ) and has been developed based on the Cook-s idea. The renovated Cook-s Distance (RD* i ) has advantages (depending on the analyst demand) over (i) the change in the fitted value for a single case, DFIT* i as it measures the influence of case i on all n fitted values Yˆ∗ (not just the fitted value for case i as DFIT* i) (ii) the change in the estimate of the coefficient when the ith case is deleted, DBETA* i since DBETA* i corresponds to the number of variables p so it is usually easier to look at a diagnostic measure such as RD* i since information from p variables can be considered simultaneously. Finally, an example using Stanford Heart Transplant data is provided to illustrate the proposed diagnostic tool.
Abstract: The study investigated the hydrophilic to hydrophobic
transition of modified polyacrylamide hydrogel with the inclusion of
N-isopropylacrylamide (NIAM). The modification was done by
mimicking micellar polymerization, which resulted in better
arrangement of NIAM chains in the polyacrylamide network. The
degree of NIAM arrangement is described by NH number. The
hydrophilic to hydrophobic transition was measured through the
partition coefficient, K, of Orange II and Methylene Blue in hydrogel
and in water. These dyes were chosen as a model for solutes with
different degree of hydrophobicity. The study showed that the
hydrogel with higher NH values resulted in better solubility of both
dyes. Moreover, in temperature above the lower critical solution
temperature (LCST) of Poly(N-isopropylacrylamide) (PNIAM)also
caused the collapse of NIPAM chains which results in a more
hydrophobic environment that increases the solubility of Methylene
Blue and decreases the solubility of Orange II in the hydrogels with
NIPAM present.
Abstract: Nanoemulsions are a class of emulsions with a droplet
size in the range of 50–500 nm and have attracted a great deal of
attention in recent years because it is unique characteristics. The
physicochemical properties of nanoemulsion suggests that it can be
successfully used to recover the residual oil which is trapped in the
fine pore of reservoir rock by capillary forces after primary and
secondary recovery. Oil-in-water nanoemulsion which can be formed
by high-energy emulsification techniques using specific surfactants
can reduce oil-water interfacial tension (IFT) by 3-4 orders of
magnitude. The present work is aimed on characterization of oil-inwater
nanoemulsion in terms of its phase behavior, morphological
studies; interfacial energy; ability to reduce the interfacial tension and
understanding the mechanisms of mobilization and displacement of
entrapped oil blobs by lowering interfacial tension both at the
macroscopic and microscopic level. In order to investigate the
efficiency of oil-water nanoemulsion in enhanced oil recovery
(EOR), experiments were performed to characterize the emulsion in
terms of their physicochemical properties and size distribution of the
dispersed oil droplet in water phase. Synthetic mineral oil and a series
of surfactants were used to prepare oil-in-water emulsions.
Characterization of emulsion shows that it follows pseudo-plastic
behaviour and drop size of dispersed oil phase follows lognormal
distribution. Flooding experiments were also carried out in a
sandpack system to evaluate the effectiveness of the nanoemulsion as
displacing fluid for enhanced oil recovery. Substantial additional
recoveries (more than 25% of original oil in place) over conventional
water flooding were obtained in the present investigation.
Abstract: Hidden Markov Model (HMM) is a stochastic method
which has been used in various signal processing and character
recognition. This study proposes to use HMM to recognize Javanese
characters from a number of different handwritings, whereby HMM
is used to optimize the number of state and feature extraction. An
85.7 % accuracy is obtained as the best result in 16-stated vertical
model using pure HMM. This initial result is satisfactory for
prompting further research.
Abstract: Gas chromatography (GC) is the most widely used
technique in analytical chemistry. However, GC has high initial cost
and requires frequent maintenance. This paper examines the
feasibility and potential of using a neural network model as an
alternative whenever GC is unvailable. It can also be part of system
verification on the performance of GC for preventive maintenance
activities. It shows the performance of MultiLayer Perceptron (MLP)
with Backpropagation structure. Results demonstrate that neural
network model when trained using this structure provides an
adequate result and is suitable for this purpose. cm.
Abstract: We propose an enhanced key management scheme
based on Key Infection, which is lightweight scheme for tiny sensors.
The basic scheme, Key Infection, is perfectly secure against node
capture and eavesdropping if initial communications after node
deployment is secure. If, however, an attacker can eavesdrop on
the initial communications, they can take the session key. We use
common neighbors for each node to generate the session key. Each
node has own secret key and shares it with its neighbor nodes. Then
each node can establish the session key using common neighbors-
secret keys and a random number. Our scheme needs only a few
communications even if it uses neighbor nodes- information. Without
losing the lightness of basic scheme, it improves the resistance against
eavesdropping on the initial communications more than 30%.
Abstract: In this paper, a study on the modes of collapse of
compress- expand members are presented. Compress- expand member
is a compact, multiple-combined cylinders, to be proposed as energy
absorbers. Previous studies on the compress- expand member have
clarified its energy absorption efficiency, proposed an approximate
equation to describe its deformation characteristics and also
highlighted the improvement that it has brought. However, for the
member to be practical, the actual range of geometrical dimension that
it can maintain its applicability must be investigated. In this study,
using a virtualized materials that comply the bilinear hardening law,
Finite element Method (FEM) analysis on the collapse modes of
compress- expand member have been conducted. Deformation maps
that plotted the member's collapse modes with regards to the member's
geometric and material parameters were then presented in order to
determine the dimensional range of each collapse modes.
Abstract: The objective of this paper is to present explicit analytical formulas for evaluating important characteristics of Double Moving Average control chart (DMA) for Poisson distribution. The most popular characteristics of a control chart are Average Run Length ( 0 ARL ) - the mean of observations that are taken before a system is signaled to be out-of control when it is actually still incontrol, and Average Delay time ( 1 ARL ) - mean delay of true alarm times. An important property required of 0 ARL is that it should be sufficiently large when the process is in-control to reduce a number of false alarms. On the other side, if the process is actually out-ofcontrol then 1 ARL should be as small as possible. In particular, the explicit analytical formulas for evaluating 0 ARL and 1 ARL be able to get a set of optimal parameters which depend on a width of the moving average ( w ) and width of control limit ( H ) for designing DMA chart with minimum of 1 ARL
Abstract: In this paper, based on a novel synthesis, a set of new simplified circuit design to implement the linguistic-hedge operations for adjusting the fuzzy membership function set is presented. The circuits work in current-mode and employ floating-gate MOS (FGMOS) transistors that operate in weak inversion region. Compared to the other proposed circuits, these circuits feature severe reduction of the elements number, low supply voltage (0.7V), low power consumption (60dB). In this paper, a set of fuzzy linguistic hedge circuits, including absolutely, very, much more, more, plus minus, more or less and slightly, has been implemented in 0.18 mm CMOS process. Simulation results by Hspice confirm the validity of the proposed design technique and show high performance of the circuits.