Abstract: Wireless sensor networks is an emerging technology
that serves as environment monitors in many applications. Yet
these miniatures suffer from constrained resources in terms of
computation capabilities and energy resources. Limited energy
resource in these nodes demands an efficient consumption of that
resource either by developing the modules itself or by providing
an efficient communication protocols. This paper presents a
comprehensive summarization and a comparative study of the
available MAC protocols proposed for Wireless Sensor Networks
showing their capabilities and efficiency in terms of energy
consumption and delay guarantee.
Abstract: While computers are known to facilitate lower levels of learning, such as rote memorization of facts, measurable through electronically administered and graded multiple-choice questions, yes/no, and true/false answers, the imparting and measurement of higher-level cognitive skills is more vexing. These require more open-ended delivery and answers, and may be more problematic in an entirely virtual environment, notwithstanding the advances in technologies such as wikis, blogs, discussion boards, etc. As with the integration of all technology, merit is based more on the instructional design of the course than on the technology employed in, and of, itself. With this in mind, this study examined the perceptions of online students in an introductory Computer Information Systems course regarding the fostering of various higher-order thinking and team-building skills as a result of the activities, resources and technologies (ART) used in the course.
Abstract: In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).
Abstract: This paper examines the students’ self-concept among 16- and 17- year- old adolescents in Malaysian secondary schools. Previous studies have shown that positive self-concept played an important role in student adjustment and academic performance during schooling. This study attempts to investigate the factors influencing students’ perceptions toward their own self-concept. A total of 1168 students participated in the survey. This study utilized the CoPs (UM) instrument to measure self-concept. Principal Component Analysis (PCA) revealed three factors: academic selfconcept, physical self-concept and social self-concept. This study confirmed that students perceived certain internal context factors, and revealed that external context factor also have an impact on their self-concept.
Abstract: This paper examines long-range dependence or longmemory
of financial time series on the exchange rate data by the
fractional Brownian motion (fBm). The principle of spectral density
function in Section 2 is used to find the range of Hurst parameter (H)
of the fBm. If 0< H
Abstract: The shelf life of fish was extended using disinfection
properties of ozone. For this purpose, Trout specimens were exposed
to ozone in the aqueous media for two hours and their microbial
growth and biochemical properties were measured over time.
Microbial growth of ozone treated fish was significantly slower than
control sample, resulting in lower counts of bacteria. According to
the biochemical tests; ozone treatment had no negative effects on fat,
protein and humidity of fish. Peroxide and TVN (Total Volatile
Nitrogen) measurements showed that treatment by ozone increased
the trout shelf life from 4 days to 6 days. According to the sensory
analysis, no changes were observed in color or flavor of the ozone
treated trout.
Abstract: Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.
Abstract: For today-s and future wireless communications applications,
more and more data traffic has to be transmitted with
growing speed and quality demands. The analog front-end of any
mobile device has to cope with very hard specifications regardless
which transmission standard has to be supported. State-of-the-art
analog front-end implementations are reaching the limit of technical
feasibility. For that reason, alternative front-end architectures could
support a continuing development of mobile communications e.g.,
six-port-based front-ends [1], [2].
In this article we propose an analog front-end with high intermediate
frequency and which utilizes additive mixing instead
of multiplicative mixing. The system architecture is presented and
several spurious effects as well as their influence on the system
dimensioning are discussed. Furthermore, several issues concerning
the technical feasibility are provided and some simulation results
are discussed which show the principle functionality of the proposed
superposition heterodyne receiver.
Abstract: Design Patterns have gained more and more
acceptances since their emerging in software development world last
decade and become another de facto standard of essential knowledge
for Object-Oriented Programming developers nowadays.
Their target usage, from the beginning, was for regular computers,
so, minimizing power consumption had never been a concern.
However, in this decade, demands of more complicated software for
running on mobile devices has grown rapidly as the much higher
performance portable gadgets have been supplied to the market
continuously. To get along with time to market that is business
reason, the section of software development for power conscious,
battery, devices has shifted itself from using specific low-level
languages to higher level ones. Currently, complicated software
running on mobile devices are often developed by high level
languages those support OOP concepts. These cause the trend of
embracing Design Patterns to mobile world.
However, using Design Patterns directly in software development
for power conscious systems is not recommended because they were
not originally designed for such environment. This paper
demonstrates the adapted Design Pattern for power limitation system.
Because there are numerous original design patterns, it is not possible
to mention the whole at once. So, this paper focuses only in creating
Energy Conscious version of existing regular "Builder Pattern" to be
appropriated for developing low power consumption software.
Abstract: This survey highlights a number of important issues
which relate to the needs to counseling for distance learners studying
at the School of Distance Education in University science Malaysia
(DEUSM) according to their gender. Data were obtained by selfreport
questionnaire that had been developed by the researchers in
counseling and educational psychology and interviews were take
place. 116 voluntary respondents complete the Questionnaire and
returned it back during new student-s registration week.64% of the
respondents were female and 52% were males that means
55%ofthem were females and 45% were males. The data was
analyzed to find out the frequencies of respondents agreements of the
items. The average of the female was 18 and the average of the male
was 19.6 by using t- test there is no significant values between the
genders. The findings show that respondents have needs for
counseling. (22) Significant needs for mails (DEUSM) the highest
was their families complain about the amount of time they spend at
work. (11) Significant needs for females the highest was they
convinced themselves that they only need 4 to 5 hours of sleep per
night.
Abstract: In this paper a one-dimension Self Organizing Map
algorithm (SOM) to perform feature selection is presented. The
algorithm is based on a first classification of the input dataset on a
similarity space. From this classification for each class a set of
positive and negative features is computed. This set of features is
selected as result of the procedure. The procedure is evaluated on an
in-house dataset from a Knowledge Discovery from Text (KDT)
application and on a set of publicly available datasets used in
international feature selection competitions. These datasets come
from KDT applications, drug discovery as well as other applications.
The knowledge of the correct classification available for the training
and validation datasets is used to optimize the parameters for positive
and negative feature extractions. The process becomes feasible for
large and sparse datasets, as the ones obtained in KDT applications,
by using both compression techniques to store the similarity matrix
and speed up techniques of the Kohonen algorithm that take
advantage of the sparsity of the input matrix. These improvements
make it feasible, by using the grid, the application of the
methodology to massive datasets.
Abstract: This paper explores an application of an adaptive learning mechanism for robots based on the natural immune system. Most of the research carried out so far are based either on the innate or adaptive characteristics of the immune system, we present a combination of these to achieve behavior arbitration wherein a robot learns to detect vulnerable areas of a track and adapts to the required speed over such portions. The test bed comprises of two Lego robots deployed simultaneously on two predefined near concentric tracks with the outer robot capable of helping the inner one when it misaligns. The helper robot works in a damage-control mode by realigning itself to guide the other robot back onto its track. The panic-stricken robot records the conditions under which it was misaligned and learns to detect and adapt under similar conditions thereby making the overall system immune to such failures.
Abstract: In contrast to conventional generators, self-excited induction generators are found to be most suitable machines for wind energy conversion in remote and windy areas due to many advantages over grid connected machines. This papers presents a Self-Excited Induction Generator (SEIG) driven by wind turbine and supplying an induction motor which is coupled to a centrifugal pump. A method to describe the steady state performance based on nodal analysis is presented. Therefore the advanced knowledge of the minimum excitation capacitor value is required. The effects of variation of excitation capacitance on system and rotor speed under different loading conditions have been analyzed and considered to optimize induction motor pump performances.
Abstract: This paper presents a cold chain monitoring system which focuses on assessment of quality and dynamic pricing information about food in cold chain. Cold chain is composed of many actors and stages; however it can be seen as a single entity since a breakdown in temperature control at any stage can impact the final quality of the product. In a cold chain, the shelf life, quality, and safety of perishable food throughout the supply chain is greatly impacted by environmental factors especially temperature. In this paper, a prototype application is implemented to retrieve timetemperature history, the current quality and the dynamic price setting according to changing quality impacted by temperature fluctuations in real-time.
Abstract: School experiences, family bonding and self-concept
had always been a crucial factor in influencing all aspects of a
student-s development. The purpose of this study is to develop and to
validate a priori model of self-concept among students. The study
was tested empirically using Structural Equation Modeling (SEM)
and Confirmatory Factor Analysis (CFA) to validate the structural
model. To address these concerns, 1167 students were randomly
selected and utilized the Cognitive Psycho-Social University of
Malaya instrument (2009).Resulted demonstrated there is indirect
effect from family bonding to self-concept through school
experiences among secondary school students as a mediator. Besides
school experiences, there is a direct effect from family bonding to
self-concept and family bonding to school experiences among
students.
Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: This paper presents a new technique for detection of
human faces within color images. The approach relies on image
segmentation based on skin color, features extracted from the two-dimensional
discrete cosine transform (DCT), and self-organizing
maps (SOM). After candidate skin regions are extracted, feature
vectors are constructed using DCT coefficients computed from those
regions. A supervised SOM training session is used to cluster feature
vectors into groups, and to assign “face" or “non-face" labels to those
clusters. Evaluation was performed using a new image database of
286 images, containing 1027 faces. After training, our detection
technique achieved a detection rate of 77.94% during subsequent
tests, with a false positive rate of 5.14%. To our knowledge, the
proposed technique is the first to combine DCT-based feature
extraction with a SOM for detecting human faces within color
images. It is also one of a few attempts to combine a feature-invariant
approach, such as color-based skin segmentation, together with
appearance-based face detection. The main advantage of the new
technique is its low computational requirements, in terms of both
processing speed and memory utilization.
Abstract: This research aimed to modify pineapple leaf paper
(PALP) for using as wet media in the evaporation cooling system by
improving wet mechanical property (tensile strength) without
compromising water absorption property. Polyamideamineepichorohydrin
resin (PAE) and carboxymethylcellulose (CMC)
were used to strengthen the paper, and the PAE and CMC ratio of
80:20 showed the optimum wet and dry tensile index values, which
were higher than those of the commercial cooling pad (CCP).
Compared with CCP, PALP itself and all the PAE/CMC modified
PALP possessed better water absorption. The PAE/CMC modified
PALP had potential to become a new type of wet media.
Abstract: This paper presents the prediction of kidney
dysfunction using different neural network (NN) approaches. Self
organization Maps (SOM), Probabilistic Neural Network (PNN) and
Multi Layer Perceptron Neural Network (MLPNN) trained with Back
Propagation Algorithm (BPA) are used in this study. Six hundred and
sixty three sets of analytical laboratory tests have been collected from
one of the private clinical laboratories in Baghdad. For each subject,
Serum urea and Serum creatinin levels have been analyzed and tested
by using clinical laboratory measurements. The collected urea and
cretinine levels are then used as inputs to the three NN models in
which the training process is done by different neural approaches.
SOM which is a class of unsupervised network whereas PNN and
BPNN are considered as class of supervised networks. These
networks are used as a classifier to predict whether kidney is normal
or it will have a dysfunction. The accuracy of prediction, sensitivity
and specificity were found for each type of the proposed networks
.We conclude that PNN gives faster and more accurate prediction of
kidney dysfunction and it works as promising tool for predicting of
routine kidney dysfunction from the clinical laboratory data.
Abstract: The fractal-shaped orifices are assumed to have a
significant effect on the pressure drop downstream pipe flow due to
their edge self-similarity shape which enhances the mixing
properties. Here, we investigate the pressure drop after these fractals
using a digital micro-manometer at different stations downstream a
turbulent flow pipe then a direct comparison has been made with the
pressure drop measured from regular orifices with the same flow
area. Our results showed that the fractal-shaped orifices have a
significant effect on the pressure drop downstream the flow. Also
the pressure drop measured across the fractal-shaped orifices is
noticed to be lower that that from ordinary orifices of the same flow
areas. This result could be important in designing piping systems
from point of view of losses consideration with the same flow
control area. This is promising to use the fractal-shaped orifices as
flowmeters as they can sense the pressure drop across them
accurately with minimum losses than the regular ones.