Abstract: This paper presents the design process of a high
performance 3-phase 3.7 kW 2-pole line start permanent magnet
synchronous motor for pumping system. A method was proposed to
study the starting torque characteristics considering line start with
high inertia load. A d-q model including cage was built to study the
synchronization capability. Time-stepping finite element method
analysis was utilized to accurately predict the dynamic and transient
performance, efficiency, starting current, speed curve and etc.
Considering the load torque of pumps during starting stage, the rotor
bar was designed with minimum demagnetization of permanent
magnet caused by huge starting current.
Abstract: The purpose of this article is to make an approach to
the Security Studies, exposing their theories and concepts to
understand the role that they have had in the interpretation of the
changes and continuities of the world order and their impact on
policies in facing the problems of the 21st century. The aim is to
build a bridge between the security studies as a subfield and the
meaning that has been given to the world order. The idea of epistemic
communities serves as a methodological proposal for the different
programs of research in security studies, showing their influence in
the realities of States, intergovernmental organizations and
transnational forces, moving to implement, perpetuate and project a
vision of the world order.
Abstract: In this paper, the secure BioSemantic Scheme is
presented to bridge biological/biomedical research problems and
computational solutions via semantic computing. Due to the diversity
of problems in various research fields, the semantic capability
description language (SCDL) plays and important role as a common
language and generic form for problem formalization. SCDL is
expected the essential for future semantic and logical computing in
Biosemantic field. We show several example to Biomedical problems
in this paper. Moreover, in the coming age of cloud computing, the
security problem is considered to be crucial issue and we presented a
practical scheme to cope with this problem.
Abstract: The purpose of this project is to propose a quick and
environmentally friendly alternative to measure the quality of oils
used in food industry. There is evidence that repeated and
indiscriminate use of oils in food processing cause physicochemical
changes with formation of potentially toxic compounds that can
affect the health of consumers and cause organoleptic changes. In
order to assess the quality of oils, non-destructive optical techniques
such as Interferometry offer a rapid alternative to the use of reagents,
using only the interaction of light on the oil. Through this project, we
used interferograms of samples of oil placed under different heating
conditions to establish the changes in their quality. These
interferograms were obtained by means of a Mach-Zehnder
Interferometer using a beam of light from a HeNe laser of 10mW at
632.8nm. Each interferogram was captured, analyzed and measured
full width at half-maximum (FWHM) using the software from
Amcap and ImageJ. The total of FWHMs was organized in three
groups. It was observed that the average obtained from each of the
FWHMs of group A shows a behavior that is almost linear, therefore
it is probable that the exposure time is not relevant when the oil is
kept under constant temperature. Group B exhibits a slight
exponential model when temperature raises between 373 K and 393
K. Results of the t-Student show a probability of 95% (0.05) of the
existence of variation in the molecular composition of both samples.
Furthermore, we found a correlation between the Iodine Indexes
(Physicochemical Analysis) and the Interferograms (Optical
Analysis) of group C. Based on these results, this project highlights
the importance of the quality of the oils used in food industry and
shows how Interferometry can be a useful tool for this purpose.
Abstract: In this paper, we provided a literature survey on the
artificial stock problem (ASM). The paper began by exploring the
complexity of the stock market and the needs for ASM. ASM
aims to investigate the link between individual behaviors (micro
level) and financial market dynamics (macro level). The variety of
patterns at the macro level is a function of the AFM complexity. The
financial market system is a complex system where the relationship
between the micro and macro level cannot be captured analytically.
Computational approaches, such as simulation, are expected to
comprehend this connection. Agent-based simulation is a simulation
technique commonly used to build AFMs. The paper proceeds by
discussing the components of the ASM. We consider the roles
of behavioral finance (BF) alongside the traditionally risk-averse
assumption in the construction of agent’s attributes. Also, the
influence of social networks in the developing of agents interactions is
addressed. Network topologies such as a small world, distance-based,
and scale-free networks may be utilized to outline economic
collaborations. In addition, the primary methods for developing
agents learning and adaptive abilities have been summarized.
These incorporated approach such as Genetic Algorithm, Genetic
Programming, Artificial neural network and Reinforcement Learning.
In addition, the most common statistical properties (the stylized facts)
of stock that are used for calibration and validation of ASM are
discussed. Besides, we have reviewed the major related previous
studies and categorize the utilized approaches as a part of these
studies. Finally, research directions and potential research questions
are argued. The research directions of ASM may focus on the macro
level by analyzing the market dynamic or on the micro level by
investigating the wealth distributions of the agents.
Abstract: Bloom’s Taxonomy has been changed during the
years. The idea of this writing is about the revision that has happened
in both facts and terms. It also contains case studies of using
cognitive Bloom’s taxonomy in teaching geometric solids to the
secondary school students, affective objectives in a creative
workshop for adults and psychomotor objectives in fixing a
malfunctioned refrigerator lamp. There is also pointed to the
important role of classification objectives in adult education as a way
to prevent memory loss.
Abstract: Currently there are many use of threaded reinforcing
bars in construction fields because those do not need additional screw
processing when connecting reinforcing bar by threaded coupler. In
this study, reinforced concrete bridge piers using threaded rebar
coupler system at the plastic hinge area were tested to evaluate seismic
performance. The test results showed that threads of the threaded rebar
coupler system could be loosened while under tension-compression
cyclic loading because tolerance and rib face angle of a threaded rebar
coupler system are greater than that of a conventional ribbed rebar
coupler system. As a result, cracks were concentrated just outside of
the mechanical coupler and stiffness of reinforced concrete bridge pier
decreased. Therefore, it is recommended that connection ratio of
mechanical couplers in one section shall be below 50% in order that
cracks are not concentrated just outside of the mechanical coupler.
Also, reduced stiffness of the specimen should be considered when
using the threaded rebar coupler system.
Abstract: Mobile Adhoc Networks (MANETs) are
infrastructure-less, dynamic network of collections of wireless mobile
nodes communicating with each other without any centralized
authority. A MANET is a mobile device of interconnections through
wireless links, forming a dynamic topology. Routing protocols have a
big role in data transmission across a network. Routing protocols,
two major classifications are unipath and multipath. This study
evaluates performance of an on-demand multipath routing protocol
named Adhoc On-demand Multipath Distance Vector routing
(AOMDV). This study proposes Energy Aware AOMDV (EAAOMDV)
an extension of AOMDV which decreases energy
consumed on a route.
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: Phonocardiography is important in appraisal of
congenital heart disease and pulmonary hypertension as it reflects the
duration of right ventricular systoles. The systolic murmur in patients
with intra-cardiac shunt decreases as pulmonary hypertension
develops and may eventually disappear completely as the pulmonary
pressure reaches systemic level. Phonocardiography and auscultation
are non-invasive, low-cost, and accurate methods to assess heart
disease. In this work an objective signal processing tool to extract
information from phonocardiography signal using Wavelet is
proposed to classify the murmur as normal or abnormal. Since the
feature vector is large, a Binary Particle Swarm Optimization (PSO)
with mutation for feature selection is proposed. The extracted
features improve the classification accuracy and were tested across
various classifiers including Naïve Bayes, kNN, C4.5, and SVM.
Abstract: ANDASA is a knowledge management platform for
the capitalization of knowledge and cultural assets for the artistic and
cultural sectors. It was built based on the priorities expressed by the
participating artists. Through mapping artistic activities and
specificities, it enables to highlight various aspects of the artistic
research and production. Such instrument will contribute to create
networks and partnerships, as it enables to evidentiate who does
what, in what field, using which methodology. The platform is
accessible to network participants and to the general public.
Abstract: This paper represents an experimental study of LPG
diffusion flame at elevated preheated air temperatures. The flame is
stabilized in a vertical water-cooled combustor by using air swirler. An
experimental test rig was designed to investigate the different
operating conditions. The burner head is designed so that the LPG fuel
issued centrally and surrounded by the swirling air issues from an air
swirler. There are three air swirlers having the same dimensions but
having different blade angles to give different swirl numbers of 0.5,
0.87 and 1.5. The combustion air was heated electrically before
entering the combustor up to a temperature about 500 K. Five air to
fuel mass ratios of 15, 20, 30, 40 and 50 were also studied. The effect
of preheated air temperature, swirl number and air to fuel mass ratios
on the temperature maps, visible flame length, high temperature region
(size) and exhaust species concentrations are studied. Some results
show that as the preheated air temperature increases, the volume of
high temperature region also increased but the flame length decreased.
Increasing the preheated air temperature, EINOx, EICO2 and EIO2
increased, while EICO decreased. Increasing the preheated air
temperature from 300 to 500 K, for all air swirl numbers used, the
highest increase in EINOx, EICO2 and EIO2 are 141, 4 and 65%,
respectively.
Abstract: The output error of the globoidal cam mechanism can
be considered as a relevant indicator of mechanism performance,
because it determines kinematic and dynamical behavior of
mechanical transmission. Based on the differential geometry and the
rigid body transformations, the mathematical model of surface
geometry of the globoidal cam is established. Then we present the
analytical expression of the output error (including the transmission
error and the displacement error along the output axis) by considering
different manufacture and assembly errors. The effects of the center
distance error, the perpendicular error between input and output axes
and the rotational angle error of the globoidal cam on the output error
are systematically analyzed. A globoidal cam mechanism which is
widely used in automatic tool changer of CNC machines is applied for
illustration. Our results show that the perpendicular error and the
rotational angle error have little effects on the transmission error but
have great effects on the displacement error along the output axis. This
study plays an important role in the design, manufacture and assembly
of the globoidal cam mechanism.
Abstract: Live video streaming is one of the most widely used
service among end users, yet it is a big challenge for the network
operators in terms of quality. The only way to provide excellent
Quality of Experience (QoE) to the end users is continuous
monitoring of live video streaming. For this purpose, there are several
objective algorithms available that monitor the quality of the video in
a live stream. Subjective tests play a very important role in fine
tuning the results of objective algorithms. As human perception is
considered to be the most reliable source for assessing the quality of a
video stream subjective tests are conducted in order to develop more
reliable objective algorithms. Temporal impairments in a live video
stream can have a negative impact on the end users. In this paper we
have conducted subjective evaluation tests on a set of video
sequences containing temporal impairment known as frame freezing.
Frame Freezing is considered as a transmission error as well as a
hardware error which can result in loss of video frames on the
reception side of a transmission system. In our subjective tests, we
have performed tests on videos that contain a single freezing event
and also for videos that contain multiple freezing events. We have
recorded our subjective test results for all the videos in order to give a
comparison on the available No Reference (NR) objective
algorithms. Finally, we have shown the performance of no reference
algorithms used for objective evaluation of videos and suggested the
algorithm that works better. The outcome of this study shows the
importance of QoE and its effect on human perception. The results
for the subjective evaluation can serve the purpose for validating
objective algorithms.
Abstract: Psychopathic disorders are taking an important part in
judge sentencing, especially in Canada. First, we will see how this
phenomenon can be illustrated by the high proportion of psychopath
offenders incarcerated in North American prisons. Many decisions in
Canadians courtrooms seem to point out that psychopathy is often
used as a strong argument by the judges to preserve public safety.
The fact that psychopathy is often associated with violence,
recklessness and recidivism, could explain why many judges consider
psychopathic disorders as an aggravating factor. Generally, the judge
reasoning is based on Article 753 of Canadian Criminal Code related
to dangerous offenders, which is used for individuals who show a
pattern of repetitive and persistent aggressive behaviour. Then we
will show how, with cognitive neurosciences, the psychopath’s
situation in courtrooms would probably change. Cerebral imaging
and news data provided by the neurosciences show that emotional
and volitional functions in psychopath’s brains are impaired.
Understanding these new issues could enable some judges to
recognize psychopathic disorders as a mitigating factor. Finally, two
important questions ought to be raised in this article: can exploring
psychopaths ‘brains really change the judge sentencing in Canadian
courtrooms? If yes, can judges consider psychopathy more as a
mitigating factor than an aggravating factor?
Abstract: We apply the non-parametric, unconditional,
hyperbolic order-α quantile estimator to appraise the relative
efficiency of Microfinance Institutions in Africa in terms of outreach.
Our purpose is to verify if these institutions, which must constantly
try to strike a compromise between their social role and financial
sustainability are operationally efficient.
Using data on African MFIs extracted from the Microfinance
Information eXchange (MIX) database and covering the 2004 to
2006 periods, we find that more efficient MFIs are also the most
profitable. This result is in line with the view that social performance
is not in contradiction with the pursuit of excellent financial
performance. Our results also show that large MFIs in terms of asset
and those charging the highest fees are not necessarily the most
efficient.
Abstract: In this study, nuclear magnetic resonance
spectroscopy and nuclear quadrupole resonance spectroscopy
parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen
bonding for Histidine hydrochloride monohydrate were calculated via
density functional theory. We considered a five-molecule model
system of Histidine hydrochloride monohydrate. Also we examined
the trends of environmental effect on hydrogen bonds as well as
cooperativity. The functional used in this research is M06-2X which
is a good functional and the obtained results has shown good
agreement with experimental data. This functional was applied to
calculate the NMR and NQR parameters. Some correlations among
NBO parameters, NMR and NQR parameters have been studied
which have shown the existence of strong correlations among them.
Furthermore, the geometry optimization has been performed using
M062X/6-31++G(d,p) method. In addition, in order to study
cooperativity and changes in structural parameters, along with
increase in cluster size, natural bond orbitals have been employed.
Abstract: Accurate forecasting of fresh produce demand is one
the challenges faced by Small Medium Enterprise (SME)
wholesalers. This paper is an attempt to understand the cause for the
high level of variability such as weather, holidays etc., in demand of
SME wholesalers. Therefore, understanding the significance of
unidentified factors may improve the forecasting accuracy. This
paper presents the current literature on the factors used to predict
demand and the existing forecasting techniques of short shelf life
products. It then investigates a variety of internal and external
possible factors, some of which is not used by other researchers in the
demand prediction process. The results presented in this paper are
further analysed using a number of techniques to minimize noise in
the data. For the analysis past sales data (January 2009 to May 2014)
from a UK based SME wholesaler is used and the results presented
are limited to product ‘Milk’ focused on café’s in derby. The
correlation analysis is done to check the dependencies of variability
factor on the actual demand. Further PCA analysis is done to
understand the significance of factors identified using correlation.
The PCA results suggest that the cloud cover, weather summary and
temperature are the most significant factors that can be used in
forecasting the demand. The correlation of the above three factors
increased relative to monthly and becomes more stable compared to
the weekly and daily demand.
Abstract: Optic disk segmentation plays a key role in the mass
screening of individuals with diabetic retinopathy and glaucoma
ailments. An efficient hardware-based algorithm for optic disk
localization and segmentation would aid for developing an automated
retinal image analysis system for real time applications. Herein,
TMS320C6416DSK DSP board pixel intensity based fractal analysis
algorithm for an automatic localization and segmentation of the optic
disk is reported. The experiment has been performed on color and
fluorescent angiography retinal fundus images. Initially, the images
were pre-processed to reduce the noise and enhance the quality. The
retinal vascular tree of the image was then extracted using canny
edge detection technique. Finally, a pixel intensity based fractal
analysis is performed to segment the optic disk by tracing the origin
of the vascular tree. The proposed method is examined on three
publicly available data sets of the retinal image and also with the data
set obtained from an eye clinic. The average accuracy achieved is
96.2%. To the best of the knowledge, this is the first work reporting
the use of TMS320C6416DSK DSP board and pixel intensity based
fractal analysis algorithm for an automatic localization and
segmentation of the optic disk. This will pave the way for developing
devices for detection of retinal diseases in the future.
Abstract: The present study aimed to investigate the effect of
synchronous music in Gymnastics' motor skill performance among
undergraduate female students in physical education college at Basra
University. The researcher used experimental design. 20 female
students of physical education divided equally into two groups, (10)
experimental group with music, (10) control group without music.
All participants complete 6 weeks in testing. Data analysis based on
T-test shows significant difference at (α = 0.05) in all skills level
between experimental and control groups in favor of experimental
group. Results of this study contribute to developing the role of
synchronous music in improving gymnastic skills performance.