Abstract: A SnO2/CdS/CdTe heterojunction was fabricated by
thermal evaporation technique. The fabricated cells were annealed at
573K for periods of 60, 120 and 180 minutes. The structural
properties of the solar cells have been studied by using X-ray
diffraction. Capacitance- voltage measurements were studied for the
as-prepared and annealed cells at a frequency of 102 Hz. The
capacitance- voltage measurements indicated that these cells are
abrupt. The capacitance decreases with increasing annealing time.
The zero bias depletion region width and the carrier concentration
increased with increasing annealing time. The carrier transport
mechanism for the CdS/CdTe heterojunction in dark is tunneling
recombination. The ideality factor is 1.56 and the reverse bias
saturation current is 9.6×10-10A. The energy band lineup for the n-
CdS/p-CdTe heterojunction was investigated using current - voltage
and capacitance - voltage characteristics.
Abstract: Geopolymer cement was evaluated as wellbore sealing material for carbon dioxide geosequestration application. Curing of cement system in saline water and strength testing in triaxial stress state condition under lateral confinement is relevant to primary cementing in CO2 geosequestration wellbore in saline aquifer. Geopolymer cement was cured in saline water (both at ambient conditions for 28 days and heated (60°C) conditions for 12 hours) and tested for triaxial strength at different levels of lateral confinement. Normal water and few other curing techniques were also studied both for geopolymer and API ‘G’ cement. Results reported were compared to evaluate the suitability of saline water for curing of geopolymer cement. Unconfined compression test results showed higher strength for curing in saline water than normal water. Besides, testing strength under lateral confinement demonstrated the material failure behavior from brittle to plastic.
Abstract: In the present work, an attempt has been made to
understand the feasibility of using UHF technique for identification
of any corona discharges/ arcing in insulating material due to water
droplets. The sensors of broadband type are useful for identification
of such discharges. It is realised that arcing initiated by liquid droplet
radiates UHF signals in the entire bandwidth up to 2 GHz. The
frequency content of the UHF signal generated due to corona/arcing
is not much varied in epoxy nanocomposites with different weight
percentage of clay content. The exfoliated/intercalated properties
were analysed through TEM studies. It is realized that corona
initiated discharges are of intermittent process. The hydrophobicity
of the material characterized through contact angle measurement. It
is realized that low Wt % of nanoclay content in epoxy resin reduces
the surface carbonization due to arcing/corona discharges. The results
of the study with gamma irradiated specimen indicates that contact
angle, discharge inception time and evaporation time of the liquid are
much lower than the virgin epoxy nanocomposite material.
Abstract: Random Access Memory (RAM) is an important
device in computer system. It can represent the snapshot on how the
computer has been used by the user. With the growth of its
importance, the computer memory has been an issue that has been
discussed in digital forensics. A number of tools have been developed
to retrieve the information from the memory. However, most of the
tools have their limitation in the ability of retrieving the important
information from the computer memory. Hence, this paper is aimed
to discuss the limitation and the setback for two main techniques such
as process signature search and process enumeration. Then, a new
hybrid approach will be presented to minimize the setback in both
individual techniques. This new approach combines both techniques
with the purpose to retrieve the information from the process block
and other objects in the computer memory. Nevertheless, the basic
theory in address translation for x86 platforms will be demonstrated
in this paper.
Abstract: In this paper back-propagation artificial neural network
(BPANN )with Levenberg–Marquardt algorithm is employed to
predict the deformation of the upsetting process. To prepare a
training set for BPANN, some finite element simulations were
carried out. The input data for the artificial neural network are a set
of parameters generated randomly (aspect ratio d/h, material
properties, temperature and coefficient of friction). The output data
are the coefficient of polynomial that fitted on barreling curves.
Neural network was trained using barreling curves generated by
finite element simulations of the upsetting and the corresponding
material parameters. This technique was tested for three different
specimens and can be successfully employed to predict the
deformation of the upsetting process
Abstract: Today, incorrect use of lands and land use changes,
excessive grazing, no suitable using of agricultural farms, plowing on
steep slopes, road construct, building construct, mine excavation etc
have been caused increasing of soil erosion and sediment yield. For
erosion and sediment estimation one can use statistical and empirical
methods. This needs to identify land unit map and the map of
effective factors. However, these empirical methods are usually time
consuming and do not give accurate estimation of erosion. In this
study, we applied GIS techniques to estimate erosion and sediment of
Menderjan watershed at upstream Zayandehrud river in center of
Iran. Erosion faces at each land unit were defined on the basis of land
use, geology and land unit map using GIS. The UTM coordinates of
each erosion type that showed more erosion amounts such as rills and
gullies were inserted in GIS using GPS data. The frequency of
erosion indicators at each land unit, land use and their sediment yield
of these indices were calculated. Also using tendency analysis of
sediment yield changes in watershed outlet (Menderjan hydrometric
gauge station), was calculated related parameters and estimation
errors. The results of this study according to implemented watershed
management projects can be used for more rapid and more accurate
estimation of erosion than traditional methods. These results can also
be used for regional erosion assessment and can be used for remote
sensing image processing.
Abstract: This paper investigates vortex shedding processes
occurring at the end of a stack of parallel plates, due to an oscillating
flow induced by an acoustic standing wave within an acoustic
resonator. Here, Particle Image Velocimetry (PIV) is used to quantify
the vortex shedding processes within an acoustic cycle
phase-by-phase, in particular during the “ejection" of the fluid out of
the stack. Standard hot-wire anemometry measurement is also applied
to detect the velocity fluctuations near the end of the stack.
Combination of these two measurement techniques allowed a detailed
analysis of the vortex shedding phenomena. The results obtained show
that, as the Reynolds number varies (by varying the plate thickness
and drive ratio), different flow patterns of vortex shedding are
observed by the PIV measurement. On the other hand, the
time-dependent hot-wire measurements allow obtaining detailed
frequency spectra of the velocity signal, used for calculating
characteristic Strouhal numbers. The impact of the plate thickness and
the Reynolds number on the vortex shedding pattern has been
discussed. Furthermore, a detailed map of the relationship between the
Strouhal number and Reynolds number has been obtained and
discussed.
Abstract: The iris recognition technology is the most accurate,
fast and less invasive one compared to other biometric techniques
using for example fingerprints, face, retina, hand geometry, voice or
signature patterns. The system developed in this study has the
potential to play a key role in areas of high-risk security and can
enable organizations with means allowing only to the authorized
personnel a fast and secure way to gain access to such areas. The
paper aim is to perform the iris region detection and iris inner and
outer boundaries localization. The system was implemented on
windows platform using Visual C# programming language. It is easy
and efficient tool for image processing to get great performance
accuracy. In particular, the system includes two main parts. The first
is to preprocess the iris images by using Canny edge detection
methods, segments the iris region from the rest of the image and
determine the location of the iris boundaries by applying Hough
transform. The proposed system tested on 756 iris images from 60
eyes of CASIA iris database images.
Abstract: Large full frequency band gaps of surface and bulk
acoustic waves in two-dimensional phononic band structures with
hollow cylinders are addressed in this paper. It is well-known that
absolute frequency band gaps are difficultly obtained in a band
structure consisted of low-acoustic-impedance cylinders in
high-acoustic-impedance host materials such as PMMA/Ni band
structures. Phononic band structures with hollow cylinders are
analyzed and discussed to obtain large full frequency band gaps not
only for bulk modes but also for surface modes. The tendency of
absolute frequency band gaps of surface and bulk acoustic waves is
also addressed by changing the inner radius of hollow cylinders in this
paper. The technique and this kind of band structure are useful for
tuning the frequency band gaps and the design of acoustic waveguides.
Abstract: Cluster analysis divides data into groups that are
meaningful, useful, or both. Analysis of biological data is creating a
new generation of epidemiologic, prognostic, diagnostic and
treatment modalities. Clustering of protein sequences is one of the
current research topics in the field of computer science. Linear
relation is valuable in rule discovery for a given data, such as if value
X goes up 1, value Y will go down 3", etc. The classical linear
regression models the linear relation of two sequences perfectly.
However, if we need to cluster a large repository of protein sequences
into groups where sequences have strong linear relationship with
each other, it is prohibitively expensive to compare sequences one by
one. In this paper, we propose a new technique named General
Regression Model Technique Clustering Algorithm (GRMTCA) to
benignly handle the problem of linear sequences clustering. GRMT
gives a measure, GR*, to tell the degree of linearity of multiple
sequences without having to compare each pair of them.
Abstract: Model mapping and transformation are important processes in high level system abstractions, and form the cornerstone of model-driven architecture (MDA) techniques. Considerable research in this field has devoted attention to static system abstraction, despite the fact that most systems are dynamic with high frequency changes in behavior. In this paper we provide an overview of work that has been done with regard to behavior model mapping and transformation, based on: (1) the completeness of the platform independent model (PIM); (2) semantics of behavioral models; (3) languages supporting behavior model transformation processes; and (4) an evaluation of model composition to effect the best approach to describing large systems with high complexity.
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: It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.
Abstract: Resource Discovery in Grids is critical for efficient
resource allocation and management. Heterogeneous nature and
dynamic availability of resources make resource discovery a
challenging task. As numbers of nodes are increasing from tens to
thousands, scalability is essentially desired. Peer-to-Peer (P2P)
techniques, on the other hand, provide effective implementation of
scalable services and applications. In this paper we propose a model
for resource discovery in Condor Middleware by using the four axis
framework defined in P2P approach. The proposed model enhances
Condor to incorporate functionality of a P2P system, thus aim to
make Condor more scalable, flexible, reliable and robust.
Abstract: Due to memory leaks, often-valuable system memory
gets wasted and denied for other processes thereby affecting the
computational performance. If an application-s memory usage
exceeds virtual memory size, it can leads to system crash. Current
memory leak detection techniques for clusters are reactive and
display the memory leak information after the execution of the
process (they detect memory leak only after it occur).
This paper presents a Dynamic Memory Monitoring Agent
(DMMA) technique. DMMA framework is a dynamic memory leak
detection, that detects the memory leak while application is in
execution phase, when memory leak in any process in the cluster is
identified by DMMA it gives information to the end users to enable
them to take corrective actions and also DMMA submit the affected
process to healthy node in the system. Thus provides reliable service
to the user. DMMA maintains information about memory
consumption of executing processes and based on this information
and critical states, DMMA can improve reliability and
efficaciousness of cluster computing.
Abstract: The Taiwan Health Literacy Scale (THLS) was developed to cope with the need of measuring heath literacy of Chinese-speaking adults in Taiwan. Although the scale was proven having good reliability and validity, it was not popularly adopted by the practitioners due to the length, and the time required completing. Based on the THLS, this research further invited healthcare professionals to review the original scale for a possible shorten work. Under the logic of THLS, the research adopted an analytic hierarchy process technique to consolidate the healthcare experts- assessments to shorten the original scale. There are fifteen items out of the original 66 items were identified having higher loadings. Confirmed by the experts and passed a pilot test with 40 undergraduate students, a short form of THLS is then introduced. This research then used 839 samples from the major cities of the Hua-lien county in the eastern part of Taiwan to test the reliability and validity of this new scale. The reliability of the scale is high and acceptable. The current scale is also highly correlated with the original, of which provide evidence for the validity of the scale.
Abstract: In this paper, we propose a robust controller design method for discrete-time systems with sector-bounded nonlinearities and time-varying delay. Based on the Lyapunov theory, delaydependent stabilization criteria are obtained in terms of linear matrix inequalities (LMIs) by constructing the new Lyapunov-Krasovskii functional and using some inequalities. A robust state feedback controller is designed by LMI framework and a reciprocally convex combination technique. The effectiveness of the proposed method is verified throughout a numerical example.
Abstract: The one of best robust search technique on large scale
search area is heuristic and meta heuristic approaches. Especially in
issue that the exploitation of combinatorial status in the large scale
search area prevents the solution of the problem via classical
calculating methods, so such problems is NP-complete. in this
research, the problem of winner determination in combinatorial
auctions have been formulated and by assessing older heuristic
functions, we solve the problem by using of genetic algorithm and
would show that this new method would result in better performance
in comparison to other heuristic function such as simulated annealing
greedy approach.
Abstract: This paper examines the forced convection flow of
incompressible, electrically conducting viscous fluid past a sharp
wedge in the presence of heat generation or absorption with an
applied magnetic field. The system of partial differential equations
governing Falkner - Skan wedge flow and heat transfer is first
transformed into a system of ordinary differential equations using
similarity transformations which is later solved using an implicit
finite - difference scheme, along with quasilinearization technique.
Numerical computations are performed for air (Pr = 0.7) and
displayed graphically to illustrate the influence of pertinent physical
parameters on local skin friction and heat transfer coefficients and,
also on, velocity and temperature fields. It is observed that the
magnetic field increases both the coefficients of skin friction and heat
transfer. The effect of heat generation or absorption is found to be
very significant on heat transfer, but its effect on the skin friction is
negligible. Indeed, the occurrence of overshoot is noticed in the
temperature profiles during heat generation process, causing the
reversal in the direction of heat transfer.
Abstract: Based on statistics released by Islamic Republic of
Iran Police (IRIP), from among the total 9555 motorcycle accidents
that happened in 2007, 857 riders died and 11219 one got injured. If
we also consider the death toll and injuries of other vehicles'
accidents resulted from traffic violation by motorcycle riders, then
paying attention to the motorcycle accidents seems to be very
necessary. Therefore, in this study we tried to investigate the traits
and issues related to production, application, and training, along with
causes of motorcycle accidents from 4 perspectives of road, human,
environment and vehicle and also based on statistical and
geographical analysis of accident-sheets prepared by Iran Road
Patrol Department (IRPD). Unfamiliarity of riders with regulations
and techniques of motorcycling, disuse of safety equipments,
inefficiency of roads and design of junctions for safe trafficking of
motorcycles and finally the lack of sufficient control of responsible
organizations are among the major causes which lead to these
accidents.