Abstract: An organic bulk heterojunction (BHJ) was fabricated using a blended film containing Copper (II) tetrakis(4-acumylphenoxy) phthalocyanine (Tc-CuPc) along with [6,6]-Phenyl C61 butyric acid methyl ester (PCBM). Weight ratio between Tc-CuPc and PCBM was 1:1. The electrical properties of Tc-CuPc: PCBM BHJ were examined. Rectifying nature of the BHJ was displayed by current-voltage (I-V) curves, recorded in dark and at various temperatures. At low voltages, conduction was ohmic succeeded by space-charge limiting current (SCLC) conduction at higher voltages in which exponential trap distribution was dominant. Series resistance, shunt resistance, ideality factor, effective barrier height and mobility at room temperature were found to be 526 4, 482 k4, 3.7, 0.17 eV and 2×10-7 cm2V-1s-1 respectively. Temperature effect towards different BHJ parameters was observed under dark condition.
Abstract: Teaching and learning about sustainability is a pedagogical endeavour with various innate difficulties and increased demands. Higher education has a dual role to play in addressing this challenge: to identify and explore innovative approaches and tools for addressing the complex and value-laden nature of sustainability in more meaningful ways, and to help teachers to integrate these approaches into their practice through appropriate professional development programs. The study reported here was designed and carried out within the context of a Masters course in Environmental Education. Eight teachers were collaboratively engaged in reconstructing a digital game microworld which was deliberately designed by the researchers to be questioned and evoke critical discussion on the idea of ‘sustainable city’. The study was based on the design-based research method. The findings indicate that the teachers’ involvement in processes of co-constructing the microworld initiated discussion and reflection upon the concepts of sustainability and sustainable lifestyles.
Abstract: A research project dealing with the phytoremediation
of a soil polluted by some heavy metals is currently running. The
case study is represented by a mining area in Hamedan province in
the central west part of Iran. The potential of phytoextraction and
phytostabilization of plants was evaluated considering the
concentration of heavy metals in the plant tissues and also the
bioconcentration factor (BCF) and the translocation factor (TF). Also
the several established criteria were applied to define
hyperaccumulator plants in the studied area. Results showed that
none of the collected plant species were suitable for phytoextraction
of Cu, Zn, Fe and Mn, but among the plants, Euphorbia macroclada
was the most efficient in phytostabilization of Cu and Fe, while,
Ziziphora clinopodioides, Cousinia sp. and Chenopodium botrys
were the most suitable for phytostabilization of Zn and Chondrila
juncea and Stipa barbata had the potential for phytostabilization of
Mn. Using the most common criterion, Euphorbia macroclada and
Verbascum speciosum were Fe hyperaccumulator plants. Present
study showed that native plant species growing on contaminated sites
may have the potential for phytoremediation.
Abstract: Let D = 1 be a positive non-square integer and let δ = √D or 1+√D 2 be a real quadratic irrational with trace t =δ + δ and norm n = δδ. Let γ = P+δ Q be a quadratic irrational for positive integers P and Q. Given a quadratic irrational γ, there exist a quadratic ideal Iγ = [Q, δ + P] and an indefinite quadratic form Fγ(x, y) = Q(x−γy)(x−γy) of discriminant Δ = t
2−4n. In the first section, we give some preliminaries form binary quadratic forms, quadratic irrationals and quadratic ideals. In the second section, we obtain some results on γ, Iγ and Fγ for some specific values of Q and P.
Abstract: Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.
Abstract: In many data mining applications, it is a priori known
that the target function should satisfy certain constraints imposed
by, for example, economic theory or a human-decision maker. In this
paper we consider partially monotone prediction problems, where the
target variable depends monotonically on some of the input variables
but not on all. We propose a novel method to construct prediction
models, where monotone dependences with respect to some of
the input variables are preserved by virtue of construction. Our
method belongs to the class of mixture models. The basic idea is to
convolute monotone neural networks with weight (kernel) functions
to make predictions. By using simulation and real case studies,
we demonstrate the application of our method. To obtain sound
assessment for the performance of our approach, we use standard
neural networks with weight decay and partially monotone linear
models as benchmark methods for comparison. The results show that
our approach outperforms partially monotone linear models in terms
of accuracy. Furthermore, the incorporation of partial monotonicity
constraints not only leads to models that are in accordance with the
decision maker's expertise, but also reduces considerably the model
variance in comparison to standard neural networks with weight
decay.
Abstract: The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.
Abstract: Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: The composition, vapour pressure, and heat capacity
of nine biodiesel fuels from different sources were measured. The
vapour pressure of the biodiesel fuels is modeled assuming an ideal
liquid phase of the fatty acid methyl esters constituting the fuel. New
methodologies to calculate the vapour pressure and ideal gas and
liquid heat capacities of the biodiesel fuel constituents are proposed.
Two alternative optimization scenarios are evaluated: 1) vapour
pressure only; 2) vapour pressure constrained with liquid heat
capacity. Without physical constraints, significant errors in liquid
heat capacity predictions were found whereas the constrained
correlation accurately fit both vapour pressure and liquid heat
capacity.
Abstract: In this paper parametric analytical studies have been carried out to examine the intrinsic flow physics pertaining to the liftoff time of solid propellant rockets. Idealized inert simulators of solid rockets are selected for numerical studies to examining the preignition chamber dynamics. Detailed diagnostic investigations have been carried out using an unsteady two-dimensional k-omega turbulence model. We conjectured from the numerical results that the altered variations of the igniter jet impingement angle, turbulence level, time and location of the first ignition, flame spread characteristics, the overall chamber dynamics including the boundary layer growth history are having bearing on the time for nozzle flow chocking for establishing the required thrust for the rocket liftoff. We concluded that the altered flow choking time of strap-on motors with the pre-determined identical ignition time at the lift off phase will lead to the malfunctioning of the rocket. We also concluded that, in the light of the space debris, an error in predicting the liftoff time can lead to an unfavorable launch window amounts the satellite injection errors and/or the mission failures.
Abstract: One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness.
Abstract: Animation is simply defined as the sequencing of a
series of static images to generate the illusion of movement. Most
people believe that actual drawings or creation of the individual
images is the animation, when in actuality it is the arrangement of
those static images that conveys the motion. To become an animator,
it is often assumed that needed the ability to quickly design
masterpiece after masterpiece. Although some semblance of artistic
skill is a necessity for the job, the real key to becoming a great
animator is in the comprehension of timing. This paper will use a
combination of sprite animation, frame animation, and some other
techniques to cause a group of multi-colored static images to slither
around in the bounded area. In addition to slithering, the images
will also change the color of different parts of their body, much like
the real world creatures that have this amazing ability to change the
colors on their bodies do. This paper was implemented by using
Java 2 Standard Edition (J2SE).
It is both time-consuming and expensive to create animations,
regardless if they are created by hand or by using motion-capture
equipment. If the animators could reuse old animations and even
blend different animations together, a lot of work would be saved in
the process. The main objective of this paper is to examine a method
for blending several animations together in real time. This paper
presents and analyses a solution using Weighted Skeleton
Animation (WSA) resulting in limited CPU time and memory waste
as well as saving time for the animators. The idea presented is
described in detail and implemented. In this paper, text animation,
vertex animation, sprite part animation and whole sprite animation
were tested.
In this research paper, the resolution, smoothness and movement
of animated images will be carried out from the parameters, which
will be obtained from the experimental research of implementing
this paper.
Abstract: A subsea hydrocarbon production system can undergo planned and unplanned shutdowns during the life of the field. The thermal FEA is used to simulate the cool down to verify the insulation design of the subsea equipment, but it is also used to derive an acceptable insulation design for the cold spots. The driving factors of subsea analyses require fast responding and accurate models of the equipment cool down. This paper presents cool down analysis carried out by a Krylov subspace reduction method, and compares this approach to the commonly used FEA solvers. The model considered represents a typical component of a subsea production system, a closed valve on a dead leg. The results from the Krylov reduction method exhibits the least error and requires the shortest computational time to reach the solution. These findings make the Krylov model order reduction method very suitable for the above mentioned subsea applications.
Abstract: This paper examines the issues, the dangers and the
saving graces of life in a transparent global community where there is
truly “no place to hide". In recent years, social networks and online
groups have transformed issues of privacy and the ways in which we
perceive and interact with others. The idea of reputation is critical to
this dynamic. The discussion begins with a brief etymological history
of the concept of reputation and moves to an exploration of how and
why online communication changes our basic nature, our various
selves and the Bakhtin idea of the polyphonic nature of truth. The
discussion considers the damaging effects of bullying and gossip,
both of which constitute an assault on reputation and the latter of
which is not limited to the lifetime of the person. It concludes with
guidelines and specific recommendations.
Abstract: This paper deals with a novel approach of power
transformers diagnostics. This approach identifies the exact location
and the range of a fault in the transformer and helps to reduce
operation costs related to handling of the faulty transformer, its
disassembly and repair. The advantage of the approach is a
possibility to simulate healthy transformer and also all faults, which
can occur in transformer during its operation without its
disassembling, which is very expensive in practice. The approach is
based on creating frequency dependent impedance of the transformer
by sweep frequency response analysis measurements and by 3D FE
parametrical modeling of the fault in the transformer. The parameters
of the 3D FE model are the position and the range of the axial short
circuit. Then, by comparing the frequency dependent impedances of
the parametrical models with the measured ones, the location and the
range of the fault is identified. The approach was tested on a real
transformer and showed high coincidence between the real fault and
the simulated one.
Abstract: The Boundary Representation of a 3D manifold contains
FACES (connected subsets of a parametric surface S : R2 -!
R3). In many science and engineering applications it is cumbersome
and algebraically difficult to deal with the polynomial set and
constraints (LOOPs) representing the FACE. Because of this reason, a
Piecewise Linear (PL) approximation of the FACE is needed, which is
usually represented in terms of triangles (i.e. 2-simplices). Solving the
problem of FACE triangulation requires producing quality triangles
which are: (i) independent of the arguments of S, (ii) sensitive to the
local curvatures, and (iii) compliant with the boundaries of the FACE
and (iv) topologically compatible with the triangles of the neighboring
FACEs. In the existing literature there are no guarantees for the point
(iii). This article contributes to the topic of triangulations conforming
to the boundaries of the FACE by applying the concept of parameterindependent
Gabriel complex, which improves the correctness of the
triangulation regarding aspects (iii) and (iv). In addition, the article
applies the geometric concept of tangent ball to a surface at a point to
address points (i) and (ii). Additional research is needed in algorithms
that (i) take advantage of the concepts presented in the heuristic
algorithm proposed and (ii) can be proved correct.
Abstract: In this paper, a two factor scheme is proposed to
generate cryptographic keys directly from biometric data, which
unlike passwords, are strongly bound to the user. Hash value of the
reference iris code is used as a cryptographic key and its length
depends only on the hash function, being independent of any other
parameter. The entropy of such keys is 94 bits, which is much higher
than any other comparable system. The most important and distinct
feature of this scheme is that it regenerates the reference iris code by
providing a genuine iris sample and the correct user password. Since
iris codes obtained from two images of the same eye are not exactly
the same, error correcting codes (Hadamard code and Reed-Solomon
code) are used to deal with the variability. The scheme proposed here
can be used to provide keys for a cryptographic system and/or for
user authentication. The performance of this system is evaluated on
two publicly available databases for iris biometrics namely CBS and
ICE databases. The operating point of the system (values of False
Acceptance Rate (FAR) and False Rejection Rate (FRR)) can be set
by properly selecting the error correction capacity (ts) of the Reed-
Solomon codes, e.g., on the ICE database, at ts = 15, FAR is 0.096%
and FRR is 0.76%.
Abstract: Until recently, energy security and climate change
were considered separate issues to be dealt with by policymakers.
The two issues are now converging, challenging the security and
climate communities to develop a better understanding of how to deal
with both issues simultaneously. Although Egypt is not a major
contributor to the world's total GHG emissions, it is particularly
vulnerable to the potential effects of global climate change such as
rising sea levels and changed patterns of rainfall in the Nile Basin.
Climate change is a major threat to sustainable growth and
development in Egypt, and the achievement of the Millennium
Development Goals. Egypt-s capacity to respond to the challenges of
climate instability will be expanded by improving overall resilience,
integrating climate change goals into sustainable development
strategies, increasing the use of modern energy systems with reduced
carbon intensity, and strengthening international initiatives. This
study seeks to establish a framework for considering the complex and
evolving links between energy security and climate change,
applicable to Egypt.
Abstract: Analytical seismic response of multi-story building
supported on base isolation system is investigated under real
earthquake motion. The superstructure is idealized as a shear type
flexible building with lateral degree-of-freedom at each floor. The
force-deformation behaviour of the isolation system is modelled by
the bi-linear behaviour which can be effectively used to model all
isolation systems in practice. The governing equations of motion of
the isolated structural system are derived. The response of the system
is obtained numerically by step-by-method under three real recorded
earthquake motions and pulse motions associated in the near-fault
earthquake motion. The variation of the top floor acceleration, interstory
drift, base shear and bearing displacement of the isolated
building is studied under different initial stiffness of the bi-linear
isolation system. It was observed that the high initial stiffness of the
isolation system excites higher modes in base-isolated structure and
generate floor accelerations and story drift. Such behaviour of the
base-isolated building especially supported on sliding type of
isolation systems can be detrimental to sensitive equipment installed
in the building. On the other hand, the bearing displacement and base
shear found to reduce marginally with the increase of the initial
stiffness of the initial stiffness of the isolation system. Further, the
above behaviour of the base-isolated building was observed for
different parameters of the bearing (i.e. post-yield stiffness and
characteristic strength) and earthquake motions (i.e. real time history
as well as pulse type motion).