Abstract: Computer languages are usually lumped together
into broad -paradigms-, leaving us in want of a finer classification
of kinds of language. Theories distinguishing between -genuine
differences- in language has been called for, and we propose that
such differences can be observed through a notion of expressive mode.
We outline this concept, propose how it could be operationalized and
indicate a possible context for the development of a corresponding
theory. Finally we consider a possible application in connection
with evaluation of language revision. We illustrate this with a case,
investigating possible revisions of the relational algebra in order to
overcome weaknesses of the division operator in connection with
universal queries.
Abstract: In this paper we have proposed a methodology to
develop an amperometric biosensor for the analysis of glucose
concentration using a simple microcontroller based data acquisition
system. The work involves the development of Detachable
Membrane Unit (enzyme based biomembrane) with immobilized
glucose oxidase on the membrane and interfacing the same to the
signal conditioning system. The current generated by the biosensor
for different glucose concentrations was signal conditioned, then
acquired and computed by a simple AT89C51-microcontroller. The
optimum operating parameters for the better performance were found
and reported. The detailed performance evaluation of the biosensor
has been carried out. The proposed microcontroller based biosensor
system has the sensitivity of 0.04V/g/dl, with a resolution of
50mg/dl. It has exhibited very good inter day stability observed up to
30 days. Comparing to the reference method such as HPLC, the
accuracy of the proposed biosensor system is well within ± 1.5%.
The system can be used for real time analysis of glucose
concentration in the field such as, food and fermentation and clinical
(In-Vitro) applications.
Abstract: Water hyacinth has been used in aquatic systems for
wastewater purification in many years worldwide. The role of water
hyacinth (Eichhornia crassipes) species in polishing nitrate and
phosphorus concentration from municipal wastewater treatment plant
effluent by phytoremediation method was evaluated. The objective
of this project is to determine the removal efficiency of water
hyacinth in polishing nitrate and phosphorus, as well as chemical
oxygen demand (COD) and ammonia. Water hyacinth is considered
as the most efficient aquatic plant used in removing vast range of
pollutants such as organic matters, nutrients and heavy metals. Water
hyacinth, also referred as macrophytes, were cultivated in the
treatment house in a reactor tank of approximately 90(L) x 40(W) x
25(H) in dimension and built with three compartments. Three water
hyacinths were placed in each compartments and water sample in
each compartment were collected in every two days. The plant
observation was conducted by weight measurement, plant uptake and
new young shoot development. Water hyacinth effectively removed
approximately 49% of COD, 81% of ammonia, 67% of phosphorus
and 92% of nitrate. It also showed significant growth rate at starting
from day 6 with 0.33 shoot/day and they kept developing up to 0.38
shoot/day at the end of day 24. From the studies conducted, it was
proved that water hyacinth is capable of polishing the effluent of
municipal wastewater which contains undesirable amount of nitrate
and phosphorus concentration.
Abstract: As the enormous amount of on-line text grows on the
World-Wide Web, the development of methods for automatically
summarizing this text becomes more important. The primary goal of
this research is to create an efficient tool that is able to summarize
large documents automatically. We propose an Evolving
connectionist System that is adaptive, incremental learning and
knowledge representation system that evolves its structure and
functionality. In this paper, we propose a novel approach for Part of
Speech disambiguation using a recurrent neural network, a paradigm
capable of dealing with sequential data. We observed that
connectionist approach to text summarization has a natural way of
learning grammatical structures through experience. Experimental
results show that our approach achieves acceptable performance.
Abstract: The development of shape and size of a crack in a
pressure vessel under uniaxial and biaxial loadings is important in
fitness-for-service evaluations such as leak-before-break. In this
work finite element modelling was used to evaluate the mean stress
and the J-integral around a front of a surface-breaking crack. A
procedure on the basis of ductile tearing resistance curves of high and
low constrained fracture mechanics geometries was developed to
estimate the amount of ductile crack extension for surface-breaking
cracks and to show the evolution of the initial crack shape. The
results showed non-uniform constraint levels and crack driving forces
around the crack front at large deformation levels. It was also shown
that initially semi-elliptical surface cracks under biaxial load
developed higher constraint levels around the crack front than in
uniaxial tension. However similar crack shapes were observed with
more extensions associated with cracks under biaxial loading.
Abstract: The objective is to fabricate organic light emitting
diode and to study its degradation process in atmosphere condition in
which PFO as an emitting material and PEDOT:PSS as a hole
injecting material were used on ITO substrate. Thus degradation
process of the OLED was studied upon its current-voltage
characteristic. By fabricating this OLED and obtaining blue light and
analysis of current-voltage characteristic during the time after
fabrication, it was observed that the current of the OLED was
exponentially decreased. Current reduction during the initial hours of
fabrication was outstanding and after few days its reduction rate was
dropped significantly, while the diode was dying.
Abstract: This paper presents a numerical analysis of the
seismic behaviour of earth dams. Analysis is conducted for the solid
phase. It may correspond to the response of the dam before water
filling. Analysis is conducted for a simple case which concerns the
elastic response of the dam. Numerical analyses are conducted using
the FLAC3D program. The behaviour of the Shell and core of the
dam and the foundation behaviour is assumed to be elastic. Result
shows the influence of the variation of the shear modulus of the core
and shell on the seismic amplification of the dam. It can be observed
that the variation of the shearing modulus of the core leads to a
moderate increase in the dynamic amplification and the increase in
the shell shearing modulus leads to a significant increase in the
dynamic amplification.
Abstract: This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost. Our algorithm uses both colour and texture features but texture is only needed when colour is unreliable. During the training stage, texture features are learned specifically to improve the performance of a colour classifier. The algorithm learns a set of simple texture features and only the most effective features are used in the classification stage. Therefore our algorithm has a very good classification rate while is still fast enough to run on a limited computer platform. The proposed algorithm was tested with a challenging outdoor image set. Test result shows the algorithm achieves a much better trade-off between classification performance and efficiency than a typical colour classifier.
Abstract: In unsupervised segmentation context, we propose a bi-dimensional hidden Markov chain model (X,Y) that we adapt to the image segmentation problem. The bi-dimensional observed process Y = (Y 1, Y 2) is such that Y 1 represents the noisy image and Y 2 represents a noisy supplementary information on the image, for example a noisy proportion of pixels of the same type in a neighborhood of the current pixel. The proposed model can be seen as a competitive alternative to the Hilbert-Peano scan. We propose a bayesian algorithm to estimate parameters of the considered model. The performance of this algorithm is globally favorable, compared to the bi-dimensional EM algorithm through numerical and visual data.
Abstract: Aerial and satellite images are information rich. They are also complex to analyze. For GIS systems, many features require fast and reliable extraction of roads and intersections. In this paper, we study efficient and reliable automatic extraction algorithms to address some difficult issues that are commonly seen in high resolution aerial and satellite images, nonetheless not well addressed in existing solutions, such as blurring, broken or missing road boundaries, lack of road profiles, heavy shadows, and interfering surrounding objects. The new scheme is based on a new method, namely reference circle, to properly identify the pixels that belong to the same road and use this information to recover the whole road network. This feature is invariable to the shape and direction of roads and tolerates heavy noise and disturbances. Road extraction based on reference circles is much more noise tolerant and flexible than the previous edge-detection based algorithms. The scheme is able to extract roads reliably from images with complex contents and heavy obstructions, such as the high resolution aerial/satellite images available from Google maps.
Abstract: Obsessive-Compulsive Disorder (OCD) is a common
and disabling condition. Therapist-delivered treatments that use
exposure and response prevention have been found to be very
effective in treating OCD, although they are costly and associated
with high rates of attrition. Effective treatments that can be made
widely available without the need for therapist contact are urgently
needed. This case study represents the first published investigation of
a self-administered cognitive treatment for OCD in a 50-year old
female with a 20 year history of OCD. The treatment evaluation
occurred over 27 weeks, including 12 weeks of self-administration of
the Danger Ideation Reduction Therapy (DIRT) program. Decreases
of between 23% to 33% on measures from pre-treatment to follow-up
were observed. Bearing in mind the methodological limitations
associated with a case study, we conclude that the results reported
here are encouraging and indicate that further research effort
evaluating the effectiveness of self-administered DIRT is warranted.
Abstract: High-voltage power transmission lines are the back
bone of electrical power utilities. The stability and continuous
monitoring of this critical infrastructure is pivotal. Nine-Sigma
representing Eskom Holding SOC limited, South Africa has a major
problem on proactive detection of fallen power lines and real time
sagging measurement together with slipping of such conductors. The
main objective of this research is to innovate RFID technology to
solve this challenge. Various options and technologies such as GPS,
PLC, image processing, MR sensors and etc., have been reviewed
and draw backs were made. The potential of RFID to give precision
measurement will be observed and presented. The future research
will look at magnetic and electrical interference as well as corona
effect on the technology.
Abstract: Bacillus subtilis strain LB5 produced lipopeptide
antibiotic iturin A-2 in liquid medium. Crude extract
from cell-free supernatant of B. subtilis cultivated broth extracted
with n-butanol showed antifungal activity to conidial germination of
Colletotrichum gloeosporioides. The germination of conidia was
completely inhibited by crude extract. The ultrastructure of conidia
after treated with crude extract was found an accumulation of vesiclelike
material between cell wall and plasma membrane while this
accumulation was not observed in untreated and germinated conidia.
Besides, the cell wall was not affected by crude extract.
Abstract: The security of computer networks plays a strategic
role in modern computer systems. Intrusion Detection Systems (IDS)
act as the 'second line of defense' placed inside a protected
network, looking for known or potential threats in network traffic
and/or audit data recorded by hosts. We developed an Intrusion
Detection System using LAMSTAR neural network to learn patterns
of normal and intrusive activities, to classify observed system
activities and compared the performance of LAMSTAR IDS with
other classification techniques using 5 classes of KDDCup99 data.
LAMSAR IDS gives better performance at the cost of high
Computational complexity, Training time and Testing time, when
compared to other classification techniques (Binary Tree classifier,
RBF classifier, Gaussian Mixture classifier). we further reduced the
Computational Complexity of LAMSTAR IDS by reducing the
dimension of the data using principal component analysis which in
turn reduces the training and testing time with almost the same
performance.
Abstract: The theoretical investigation is carried out to describe
the effect of increase of pressure waves amplitude in clean and bubbly liquid. The goal of the work is to capture the regime of multiple magnification of acoustic and shock waves in the liquid,
which enables to get appropriate conditions to enlarge collapses of
micro-bubbles. The influence of boundary conditions and frequency
of the governing acoustic field is studied for the case of the
cylindrical acoustic resonator. It has been observed the formation of
standing waves with large amplitude at resonant frequencies. The
interaction of the compression wave with gas and vapor bubbles is
investigated for the convergent channel. It is shown theoretically that
the chemical reactions, which occur inside gas bubbles, provide additional impulse to the wave, that affect strongly on the collapses
of the vapor bubbles
Abstract: In the context of business incubation (BI) as strategic
enablers, this paper critically reviews the literature relating to the
strategic benefits of BI in the Middle East. The taxonomy of BI
benefits in the strategic elements on 1) type, 2) financial model, 3)
services, 4) objectives, 5) number of clients, 6) number of graduates,
and 7) jobs creation. Understanding the importance of BI benefits can
be significant in the economic development although most incubators
lead to diversify the economy. Thus, taxonomies of the benefits of BI
are produced from both the academic literature and published case
studies. In this way, a classification of strategic benefits elements as
they relate to incubators has been developed to provide a greater
understanding of the benefits needed to obtain a specific element.
The result of this paper is Business incubators is aimed
entrepreneurship, jobs creation, research commercialization and
profitable enterprises in Middle Eastern countries.
Abstract: Milk from differently fed cows (supplemented with carotenoids from carrots or palm oil product Carotino CAF 100) was obtained in a conventional dairy farm to assess the carotenoid potential to protect milk fat against oxidation. The extracted anhydrous milk fat (AMF) was tested by peroxide value, and Rancimat tests. Temperature, and light stimulation for reaction acceleration was used. The oxidative stability enhancement by carotenoids was detected in peroxide value test – the strongest effect was observed in palm oil, following by carrot supplemented group, compared to control group, whose feed was unchanged. Rancimat accelerated oxidation test results did not show any superiority of the oxidative stability of the AMF samples from milk of the carotenoidsupplemented cow groups. The average oxidation stability of AMF dark-stored samples was 12.59 ± 0.294 h, and it was significantly (p < 0.05) higher than that of AMF light-affected samples, i.e. 2.60 ± 0.191 h.
Abstract: Realistic 3D face model is desired in various
applications such as face recognition, games, avatars, animations, and
etc. Construction of 3D face model is composed of 1) building a face
shape model and 2) rendering the face shape model. Thus, building a
realistic 3D face shape model is an essential step for realistic 3D face
model. Recently, 3D morphable model is successfully introduced to
deal with the various human face shapes. 3D dense correspondence
problem should be precedently resolved for constructing a realistic 3D
dense morphable face shape model. Several approaches to 3D dense
correspondence problem in 3D face modeling have been proposed
previously, and among them optical flow based algorithms and TPS
(Thin Plate Spline) based algorithms are representative. Optical flow
based algorithms require texture information of faces, which is
sensitive to variation of illumination. In TPS based algorithms
proposed so far, TPS process is performed on the 2D projection
representation in cylindrical coordinates of the 3D face data, not
directly on the 3D face data and thus errors due to distortion in data
during 2D TPS process may be inevitable.
In this paper, we propose a new 3D dense correspondence algorithm
for 3D dense morphable face shape modeling. The proposed algorithm
does not need texture information and applies TPS directly on 3D face
data. Through construction procedures, it is observed that the proposed
algorithm constructs realistic 3D face morphable model reliably and
fast.
Abstract: Composite steel shear wall is a lateral load resisting system which consists of a steel plate with concrete wall attached to one or both sides to prevent it from elastic buckling. The composite behavior is ensured by utilizing high-strength bolts. This paper investigates the effect of distance between bolts, and for this purpose 14 one-story one-bay specimens with various bolts spacing were modeled by finite element code which is developed by the authors. To verify the model, numerical results were compared with a valid experiment which illustrate proper agreement. Results depict increasing the distance between bolts would improve the seismic ever, this increase must be limited, because of large distances will cause widespread buckling of the steel plate in free subpanels between bolts and would result in no improvement. By comparing the results in elastic region, it was observed initial stiffness is not affected by changing the distance.
Abstract: This paper discusses the effectiveness of the EEG signal
for human identification using four or less of channels of two different
types of EEG recordings. Studies have shown that the EEG signal
has biometric potential because signal varies from person to person
and impossible to replicate and steal. Data were collected from 10
male subjects while resting with eyes open and eyes closed in 5
separate sessions conducted over a course of two weeks. Features
were extracted using the wavelet packet decomposition and analyzed
to obtain the feature vectors. Subsequently, the neural networks
algorithm was used to classify the feature vectors. Results show that,
whether or not the subjects- eyes were open are insignificant for a 4–
channel biometrics system with a classification rate of 81%. However,
for a 2–channel system, the P4 channel should not be included if data
is acquired with the subjects- eyes open. It was observed that for 2–
channel system using only the C3 and C4 channels, a classification
rate of 71% was achieved.