Abstract: This paper presents circuit models to analyze the
conducted susceptibility of multiconductor shielded cables in
frequency domains using Branin’s method, which is referred to as the
method of characteristics. These models, which can be used directly
in the time and frequency domains, take into account the presence of
both the transfer impedance and admittance. The conducted
susceptibility is studied by using an injection current on the cable
shield as the source. Two examples are studied; a coaxial shielded
cable and shielded cables with two parallel wires (i.e., twinax cables).
This shield has an asymmetry (one slot on the side). Results obtained
by these models are in good agreement with those obtained by other
methods.
Abstract: Despite the highly touted benefits, emerging
technologies have unleashed pervasive concerns regarding unintended
and unforeseen social impacts. Thus, those wishing to create safe and
socially acceptable products need to identify such side effects and
mitigate them prior to the market proliferation. Various methodologies
in the field of technology assessment (TA), namely Delphi, impact
assessment, and scenario planning, have been widely incorporated in
such a circumstance. However, literatures face a major limitation in
terms of sole reliance on participatory workshop activities. They
unfortunately missed out the availability of a massive untapped data
source of futuristic information flooding through the Internet. This
research thus seeks to gain insights into utilization of futuristic data,
future-oriented documents from the Internet, as a supplementary
method to generate social impact scenarios whilst capturing
perspectives of experts from a wide variety of disciplines. To this end,
network analysis is conducted based on the social keywords extracted
from the futuristic documents by text mining, which is then used as a
guide to produce a comprehensive set of detailed scenarios. Our
proposed approach facilitates harmonized depictions of possible
hazardous consequences of emerging technologies and thereby makes
decision makers more aware of, and responsive to, broad qualitative
uncertainties.
Abstract: The detection of moving objects from a video image
sequences is very important for object tracking, activity recognition,
and behavior understanding in video surveillance.
The most used approach for moving objects detection / tracking is
background subtraction algorithms. Many approaches have been
suggested for background subtraction. But, these are illumination
change sensitive and the solutions proposed to bypass this problem
are time consuming.
In this paper, we propose a robust yet computationally efficient
background subtraction approach and, mainly, focus on the ability to
detect moving objects on dynamic scenes, for possible applications in
complex and restricted access areas monitoring, where moving and
motionless persons must be reliably detected. It consists of three
main phases, establishing illumination changes invariance,
background/foreground modeling and morphological analysis for
noise removing.
We handle illumination changes using Contrast Limited Histogram
Equalization (CLAHE), which limits the intensity of each pixel to
user determined maximum. Thus, it mitigates the degradation due to
scene illumination changes and improves the visibility of the video
signal. Initially, the background and foreground images are extracted
from the video sequence. Then, the background and foreground
images are separately enhanced by applying CLAHE.
In order to form multi-modal backgrounds we model each channel
of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture
Model (GMM). Finally, we post process the resulting binary
foreground mask using morphological erosion and dilation
transformations to remove possible noise.
For experimental test, we used a standard dataset to challenge the
efficiency and accuracy of the proposed method on a diverse set of
dynamic scenes.
Abstract: Electroencephalogram (EEG) is a noninvasive
technique that registers signals originating from the firing of neurons
in the brain. The Emotiv EEG Neuroheadset is a consumer product
comprised of 14 EEG channels and was used to record the reactions
of the neurons within the brain to two forms of stimuli in 10
participants. These stimuli consisted of auditory and visual formats
that provided directions of ‘right’ or ‘left.’ Participants were
instructed to raise their right or left arm in accordance with the
instruction given. A scenario in OpenViBE was generated to both
stimulate the participants while recording their data. In OpenViBE,
the Graz Motor BCI Stimulator algorithm was configured to govern
the duration and number of visual stimuli. Utilizing EEGLAB under
the cross platform MATLAB®, the electrodes most stimulated during
the study were defined. Data outputs from EEGLAB were analyzed
using IBM SPSS Statistics® Version 20. This aided in determining
the electrodes to use in the development of a brain-machine interface
(BMI) using real-time EEG signals from the Emotiv EEG
Neuroheadset. Signal processing and feature extraction were
accomplished via the Simulink® signal processing toolbox. An
Arduino™ Duemilanove microcontroller was used to link the Emotiv
EEG Neuroheadset and the right and left Mecha TE™ Hands.
Abstract: Future mobile networks following 5th generation will
be characterized by one thousand times higher gains in capacity;
connections for at least one hundred billion devices; user experience
capable of extremely low latency and response times. To be close to
the capacity requirements and higher reliability, advanced
technologies have been studied, such as multiple connectivity, small
cell enhancement, heterogeneous networking, and advanced
interference and mobility management. This paper is focused on the
multiple connectivity in heterogeneous cellular networks. We
investigate the performance of coverage and user throughput in several
deployment scenarios. Using the stochastic geometry approach, the
SINR distributions and the coverage probabilities are derived in case
of dual connection. Also, to compare the user throughput enhancement
among the deployment scenarios, we calculate the spectral efficiency
and discuss our results.
Abstract: Anxiety is a common psychological problem and also
implicated as a contributor to many chronic diseases which decreased
quality of life even with pharmacological treatment. At the present
time several yogic practices- meditation, pranayama, and mantra,
etcetera are playing important role in treating physiological and
psychological problems. Hence, the present investigation is aimed to
see the effect of Trataka on the level of anxiety among adolescents.
For the present study, a sample of 30 adolescents belonging to the
age range 20-30 years was selected from Devsanskriti Vishwa
Vidyalaya Haridwar through random sampling. In this investigation,
Sinha’s Comprehensive anxiety test has been used to measure the
level of anxiety. Statistical analysis has been done by using t-test.
Findings of this study reveal that Trataka significantly decreases the
level of anxiety among adolescents.
Abstract: This experimental study evaluates the effect of using
Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-
Concept Model (MSCM) in a drug prevention programme to increase
resiliency and reduce aggression among at-risk youth in Malaysia. A
number of 60 (N=60) university students who were at-risk of taking
drugs were involved in this study. Participants were identified with
self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and
Aggression Questionnaire. Based on the mean score of these
instruments, the participants were divided into the treatment group,
and the control group. Data were analyzed using t-test. The finding
showed that the mean score of resiliency was increased in the
treatment group compared to the control group. It also shows that the
mean score of aggression was reduced in the treatment group
compared to the control group. Drug Prevention Programme was
found to help in enhancing resiliency and reducing aggression among
participants in the treatment group compared to the controlled group.
Implications were given regarding the preventive actions on drug
abuse among youth in Malaysia.
Abstract: The ultrasound imaging is very popular to diagnosis
the disease because of its non-invasive nature. The ultrasound
imaging slowly produces low quality images due to the presence of
spackle noise and wave interferences. There are several algorithms to
be proposed for the segmentation of ultrasound carotid artery images
but it requires a certain limit of user interaction. The pixel in an
image is highly correlated so the spatial information of surrounding
pixels may be considered in the process of image segmentation which
improves the results further. When data is highly correlated, one pixel
may belong to more than one cluster with different degree of
membership. There is an important step to computerize the evaluation
of arterial disease severity using segmentation of carotid artery lumen
in 2D and 3D ultrasonography and in finding vulnerable
atherosclerotic plaques susceptible to rupture which can cause stroke.
Abstract: It is likely that robots will cross the boundaries of
industry into households over the next decades. With demographic
challenges worldwide, the future ageing populations will require the
introduction of assistive technologies capable of providing, care,
human dignity and quality of life through the aging process. Robotics
technology has a high potential for being used in the areas of social
and healthcare by promoting a wide range of activities such as
entertainment, companionship, supervision or cognitive and physical
assistance. However such close Human Robotics Interaction (HRI)
encompass a rich set of ethical scenarios that need to be addressed
before Socially Assistive Robots (SARs) reach the global markets.
Such interactions with robots may seem a worthy goal for many
technical/financial reasons but inevitably require close attention to
the ethical dimensions of such interactions. This article investigates
the current HRI benchmark of social success. It revises it according
to the ethical principles of beneficence, non-maleficence and justice
aligned with social care ethos. An extension of such benchmark is
proposed based on an empirical study of HRIs conducted with elderly
groups.
Abstract: ESPRIT-TLS method appears a good choice for high
resolution fault detection in induction machines. It has a very high
effectiveness in the frequency and amplitude identification.
Contrariwise, it presents a high computation complexity which
affects its implementation in real time fault diagnosis. To avoid this
problem, a Fast-ESPRIT algorithm that combined the IIR band-pass
filtering technique, the decimation technique and the original
ESPRIT-TLS method was employed to enhance extracting accurately
frequencies and their magnitudes from the wind stator current with
less computation cost. The proposed algorithm has been applied to
verify the wind turbine machine need in the implementation of an online,
fast, and proactive condition monitoring. This type of remote
and periodic maintenance provides an acceptable machine lifetime,
minimize its downtimes and maximize its productivity. The
developed technique has evaluated by computer simulations under
many fault scenarios. Study results prove the performance of Fast-
ESPRIT offering rapid and high resolution harmonics recognizing
with minimum computation time and less memory cost.
Abstract: This paper presents an efficient fusion algorithm for
iris images to generate stable feature for recognition in unconstrained
environment. Recently, iris recognition systems are focused on real
scenarios in our daily life without the subject’s cooperation. Under
large variation in the environment, the objective of this paper is to
combine information from multiple images of the same iris. The
result of image fusion is a new image which is more stable for further
iris recognition than each original noise iris image. A wavelet-based
approach for multi-resolution image fusion is applied in the fusion
process. The detection of the iris image is based on Adaboost
algorithm and then local binary pattern (LBP) histogram is then
applied to texture classification with the weighting scheme.
Experiment showed that the generated features from the proposed
fusion algorithm can improve the performance for verification system
through iris recognition.
Abstract: An investigation into Cahn-Hilliard equation was
carried out through numerical simulation to identify a possible phase
separation for one and two dimensional domains. It was observed that
this equation can reproduce important mass fluxes necessary for
phase separation within the miscibility gap and for coalescence of
particles.
Abstract: Recently, universities are increasingly consuming
energy to support various activities. A large population of staff and
students in Malaysian universities has led to excessive energy
consumption which directly gives an impact to the environment. The
key question then ascended “How well is an energy management
(EM) been practiced in universities without taking the Critical
Success Factors (CSFs) into consideration to ensure the management
of university achieves the goals in reducing energy consumption.
Review on past literature is carried out to establish CSFs for EM best
practices. Thus, this paper highlighted the CSFs which have to be
focused on by management of university to successfully measure the
EM implementation and its performance. At the end of this paper, a
theoretical framework is developed for EM success factors towards
sustainable university.
Abstract: A knowledge-based expert system with the acronym
RASPE is developed as an application tool to help decision makers in
construction companies make informed decisions about managing
risks in pipeline construction projects. Choosing to use expert
systems from all available artificial intelligence techniques is due to
the fact that an expert system is more suited to representing a
domain’s knowledge and the reasoning behind domain-specific
decisions. The knowledge-based expert system can capture the
knowledge in the form of conditional rules which represent various
project scenarios and potential risk mitigation/response actions. The
built knowledge in RASPE is utilized through the underlying
inference engine that allows the firing of rules relevant to a project
scenario into consideration. Paper provides an overview of the
knowledge acquisition process and goes about describing the
knowledge structure which is divided up into four major modules.
The paper shows one module in full detail for illustration purposes
and concludes with insightful remarks.
Abstract: In this letter, we explore exact solutions for the
Horava-Lifshitz gravity. We use of an extension of this theory with
first order dynamical lapse function. The equations of motion have
been derived in a fully consistent scenario. We assume that there
are some spherically symmetric families of exact solutions of this
extended theory of gravity. We obtain exact solutions and investigate
the singularity structures of these solutions. Specially, an exact
solution with the regular horizon is found.
Abstract: The tombolo of Giens is located in the town of Hyères
(France). We recall the history of coastal erosion, and prominent
factors affecting the evolution of the western tombolo. We then
discuss the possibility of stabilizing the western tombolo. Our
argumentation relies on a coupled model integrating swells, currents,
water levels and sediment transport. We present the conclusions of
the simulations of various scenarios, including pre-existing
propositions from coastal engineering offices. We conclude that
beach replenishment seems to be necessary but not sufficient for the
stabilization of the beach. Breakwaters reveal effective particularly in
the most exposed northern area. Some solutions fulfill conditions so
as to be elected as satisfactory. We give a comparative analysis of the
efficiency of 14 alternatives for the protection of the tombolo.
Abstract: A collection of thirty cultivars/clones of a red pitaya
was used to investigate flowering response to lighting
supplementation in the winter season of 2013-2014 in southern
Taiwan. The night-breaking treatment was conducted during the
period of 10 Oct. 2013 to 5 Mar. 2014 with 4-continuous hours
(22.00 – 02.00 hrs) of additional lighting daily using incandescent
bulbs (100W). Among cultivars and clones tested, twenty-three
genotypes, most belonging to the red-magenta flesh type, were found
to have positively flowering response to the lighting treatment. The
duration of night-breaking treatment for successful flowering
initiation varied from 33- 48 days. The lighting-sensitive genotypes
bore 1-2 flowering flushes. Floral and fruiting stages took 21-26 and
46-59 days, respectively. Among sixteen fruiting genotypes, the
highest fruit set rates were found in Damao 9, D4, D13, Chaozou
large, Chaozhou 5, Small Nick and F22. Five cultivars and clones
(Orejona, D4, Chaozhou large, Chaozhou 5 and Small Nick) produced
fruits with an average weight of more than 300 g per fruit which were
higher than those of the fruits formed in the summer of 2013. Fruits
produced during off-season containing total soluble solids (TSS)
from 17.5 to 20.7oBrix, which were higher than those produced inseason.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: The continuous decline of petroleum and natural gas
reserves and non linear rise of oil price has brought about a
realisation of the need for a change in our perpetual dependence on
the fossil fuel. A day to day increased consumption of crude and
petroleum products has made a considerable impact on our foreign
exchange reserves. Hence, an alternate resource for the conversion of
energy (both liquid and gas) is essential for the substitution of
conventional fuels. Biomass is the alternate solution for the present
scenario. Biomass can be converted into both liquid as well as
gaseous fuels and other feedstocks for the industries.
Abstract: Many issues about the relationship between auditors in
auditing practices with its stakeholders often heard. It appears in
perspectives of bringing out the variety of phenomena affecting from
the audit practice of greed and not appreciating from the
independency of the audit profession and professional code of ethics.
It becomes a logical consequence in practicing of capitalism in
accounting. The main purpose of this article would like to uncover
the existing auditing practices in Indonesia, especially in Java that
associated with a strong influence of Javanese culture with reluctant
/”shy", politely, "legowo (gratefully accepted)", "ngemong"
(friendly), "not mentholo" (lenient), "tepo seliro" (tolerance),
"ngajeni" (respectful), "acquiescent" and also reveals its relationships
with Non Javanese culture in facing the conflict of interest in
practical of auditing world. The method used by interpretive
approach that emphasizes the role of language, interpret and
understand and see social reality as something other than a label,
name or concept. Global practices in auditing of each country have
particular cultures that affect the standard set by those regulatory
standards results the adaptation of IAS. The majority of parties in
Indonesia is dominated by Javanese racial regulators, so Java culture
is embedded in every audit practices and those conditions in Java
leads auditors in having similar behaviour, sometimes interfere with
standard Java code of conduct must be executed by an auditor.
Auditors who live in Java have the characters of Javanese culture that
is hard to avoid in the audit practice. However, practically, the
auditors still are relevant in their profession.