Abstract: This paper presents development results of the method
of seismoacoustic activity monitoring based on usage vibrosensitive
properties of optical fibers. Analysis of Rayleigh backscattering
radiation parameters changes, which take place due to microscopic
seismoacoustic impacts on the optical fiber, allows to determine
seismoacoustic emission sources positions and to identify their types.
Results of using this approach are successful for complex monitoring
of railways.
Abstract: Traditional document representation for classification
follows Bag of Words (BoW) approach to represent the term weights.
The conventional method uses the Vector Space Model (VSM) to
exploit the statistical information of terms in the documents and they
fail to address the semantic information as well as order of the terms
present in the documents. Although, the phrase based approach
follows the order of the terms present in the documents rather than
semantics behind the word. Therefore, a semantic concept based
approach is used in this paper for enhancing the semantics by
incorporating the ontology information. In this paper a novel method
is proposed to forecast the intraday stock market price directional
movement based on the sentiments from Twitter and money control
news articles. The stock market forecasting is a very difficult and
highly complicated task because it is affected by many factors such
as economic conditions, political events and investor’s sentiment etc.
The stock market series are generally dynamic, nonparametric, noisy
and chaotic by nature. The sentiment analysis along with wisdom of
crowds can automatically compute the collective intelligence of
future performance in many areas like stock market, box office sales
and election outcomes. The proposed method utilizes collective
sentiments for stock market to predict the stock price directional
movements. The collective sentiments in the above social media have
powerful prediction on the stock price directional movements as
up/down by using Granger Causality test.
Abstract: These days customer satisfaction plays vital role in
any business. When customer searches for a product, significantly a
junk of irrelevant information is what is given, leading to customer
dissatisfaction. To provide exactly relevant information on the
searched product, we are proposing a model of KaaS (Knowledge as
a Service), which pre-processes the information using decision
making paradigm using Multi-agents.
Information obtained from various sources is taken to derive
knowledge and they are linked to Cloud to capture new idea. The
main focus of this work is to acquire relevant information
(knowledge) related to product, then convert this knowledge into a
service for customer satisfaction and deploy on cloud.
For achieving these objectives we are have opted to use multi
agents. They are communicating and interacting with each other,
manipulate information, provide knowledge, to take decisions. The
paper discusses about KaaS as an intelligent approach for Knowledge
acquisition.
Abstract: An artificial neural network is a mathematical model
inspired by biological neural networks. There are several kinds of
neural networks and they are widely used in many areas, such as:
prediction, detection, and classification. Meanwhile, in day to day life,
people always have to make many difficult decisions. For example,
the coach of a soccer club has to decide which offensive player
to be selected to play in a certain game. This work describes a
novel Neural Network using a combination of the General Regression
Neural Network and the Probabilistic Neural Networks to help a
soccer coach make an informed decision.
Abstract: Parabolic solar trough systems have seen limited
deployments in cold northern climates as they are more suitable for
electricity production in southern latitudes. A numerical dynamic
model is developed to simulate troughs installed in cold climates and
validated using a parabolic solar trough facility in Winnipeg. The
model is developed in Simulink and will be utilized to simulate a trigeneration
system for heating, cooling and electricity generation in
remote northern communities. The main objective of this simulation
is to obtain operational data of solar troughs in cold climates and use
the model to determine ways to improve the economics and address
cold weather issues.
In this paper the validated Simulink model is applied to simulate a
solar assisted absorption cooling system along with electricity
generation using Organic Rankine Cycle (ORC) and thermal storage.
A control strategy is employed to distribute the heated oil from solar
collectors among the above three systems considering the
temperature requirements. This modelling provides dynamic
performance results using measured meteorological data recorded
every minute at the solar facility location. The purpose of this
modeling approach is to accurately predict system performance at
each time step considering the solar radiation fluctuations due to
passing clouds. Optimization of the controller in cold temperatures is
another goal of the simulation to for example minimize heat losses in
winter when energy demand is high and solar resources are low.
The solar absorption cooling is modeled to use the generated heat
from the solar trough system and provide cooling in summer for a
greenhouse which is located next to the solar field.
The results of the simulation are presented for a summer day in
Winnipeg which includes comparison of performance parameters of
the absorption cooling and ORC systems at different heat transfer
fluid (HTF) temperatures.
Abstract: In this paper, the exergy analysis of vapor absorption
refrigeration system using LiBr-H2O as working fluid is carried out
with the modified Gouy-Stodola approach rather than the classical
Gouy-Stodola equation and effect of varying input parameters is also
studied on the performance of the system. As the modified approach
uses the concept of effective temperature, the mathematical
expressions for effective temperature have been formulated and
calculated for each component of the system. Various constraints and
equations are used to develop program in EES to solve these
equations. The main aim of this analysis is to determine the
performance of the system and the components having major
irreversible loss. Results show that exergy destruction rate is
considerable in absorber and generator followed by evaporator and
condenser. There is an increase in exergy destruction in generator,
absorber and condenser and decrease in the evaporator by the
modified approach as compared to the conventional approach. The
value of exergy determined by the modified Gouy-Stodola equation
deviates maximum i.e. 26% in the generator as compared to the
exergy calculated by the classical Gouy-Stodola method.
Abstract: This study analyzes the innovative orientation of the
Croatian entrepreneurs. Innovative orientation is represented by the
perceived extent to which an entrepreneur’s product or service or
technology is new, and no other businesses offer the same product.
The sample is extracted from the GEM Croatia Adult Population
Survey dataset for the years 2003-2013. We apply descriptive
statistics, t-test, Chi-square test and logistic regression. Findings
indicate that innovative orientations vary with personal, firm, meso
and macro level variables, and between different stages in
entrepreneurship process. Significant predictors are occupation of the
entrepreneurs, size of the firm and export aspiration for both early
stage and established entrepreneurs. In addition, fear of failure,
expecting to start a new business and seeing an entrepreneurial career
as a desirable choice are predictors of innovative orientation among
early stage entrepreneurs.
Abstract: This paper introduces an original method for
guaranteed estimation of the accuracy for an ensemble of Lipschitz
classifiers. The solution was obtained as a finite closed set of
alternative hypotheses, which contains an object of classification with
probability of not less than the specified value. Thus, the
classification is represented by a set of hypothetical classes. In this
case, the smaller the cardinality of the discrete set of hypothetical
classes is, the higher is the classification accuracy. Experiments have
shown that if cardinality of the classifiers ensemble is increased then
the cardinality of this set of hypothetical classes is reduced. The
problem of the guaranteed estimation of the accuracy for an ensemble
of Lipschitz classifiers is relevant in multichannel classification of
target events in C-OTDR monitoring systems. Results of suggested
approach practical usage to accuracy control in C-OTDR monitoring
systems are present.
Abstract: Cloud computing is a new technology in industry and
academia. The technology has grown and matured in last half decade
and proven their significant role in changing environment of IT
infrastructure where cloud services and resources are offered over the
network. Cloud technology enables users to use services and
resources without being concerned about the technical implications of
technology. There are substantial research work has been performed
for the usage of cloud computing in educational institutes and
majority of them provides cloud services over high-end blade servers
or other high-end CPUs. However, this paper proposes a new stack
called “CiCKAStack” which provide cloud services over unutilized
computing resources, named as commodity computers.
“CiCKAStack” provides IaaS and PaaS using underlying commodity
computers. This will not only increasing the utilization of existing
computing resources but also provide organize file system, on
demand computing resource and design and development
environment.
Abstract: International and domestic environmental law has
evolved quite rapidly in the last few decades. At the international
level the Stockholm and Rio Declarations paved the way for a broad
based consensus of the international community on environmental
issues and principles. At the Domestic level also many states have
incorporated environmental protection in their constitutions and even
more states are doing the same at least in their domestic legislations.
In this process of evolution environmental law has unleashed a
number of novel principles such as; the participatory principle, the
polluter pays principle, the precautionary principle, the intergenerational
and intra-generational principles, the prevention
principle, the sustainable development principle and so on.
Abstract: Flash Floods, together with landslides, are a common
natural threat for people living in mountainous regions and foothills.
One way to deal with this constant menace is the use of Early
Warning Systems, which have become a very important mitigation
strategy for natural disasters.
In this work we present our proposal for a pilot Flash Flood Early
Warning System for Santiago, Chile, the first stage of a more
ambitious project that in a future stage shall also include early
warning of landslides.
To give a context for our approach, we first analyze three existing
Flash Flood Early Warning Systems, focusing on their general
architectures. We then present our proposed system, with main focus
on the decision support system, a system that integrates empirical
models and fuzzy expert systems to achieve reliable risk estimations.
Abstract: Nanofibers are effective materials which have
frequently been investigated to produce high quality air filters. As an
environmental approach our aim is to achieve nanofibers by melting.
In spun-bond systems extruder, spin-pump, nozzle package and
attenuator are used. Molten polymer which flows from extruder is
made steady by spin-pump. Regular melt passes through nozzle holes
and forms fibers under high pressure. The fibers pulled from nozzle
are shrunk to micron size by an attenuator; after solidification, they
are collected on a conveyor. In this research different designs of
attenuator system have been studied; and also CFD analysis has been
done on these different designs. Afterwards, one of these designs
tested and finally some optimizations have been done to reduce
pressure loss and increase air velocity.
Abstract: In this paper we propose a discrete tracking control of
nonholonomic mobile robots with two degrees of freedom. The
electromechanical model of a mobile robot moving on a horizontal
surface without slipping, with two rear wheels controlled by two
independent DC electric, and one front roal wheel is considered. We
present backstepping design based on the Euler approximate discretetime
model of a continuous-time plant. Theoretical considerations are
verified by numerical simulation.
Abstract: An innovative concept called “Flexy-Energy” is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energy sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel Diesel generators and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel Diesel generators. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand.This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.
Abstract: The aim of this paper is to understand emerging
learning conditions, when a visual analytics is implemented and used
in K 12 (education). To date, little attention has been paid to the role
visual analytics (digital media and technology that highlight visual
data communication in order to support analytical tasks) can play in
education, and to the extent to which these tools can process
actionable data for young students. This study was conducted in three
public K 12 schools, in four social science classes with students aged
10 to 13 years, over a period of two to four weeks at each school.
Empirical data were generated using video observations and analyzed
with help of metaphors within Actor-network theory (ANT). The
learning conditions are found to be distinguished by broad
complexity, characterized by four dimensions. These emerge from
the actors’ deeply intertwined relations in the activities. The paper
argues in relation to the found dimensions that novel approaches to
teaching and learning could benefit students’ knowledge building as
they work with visual analytics, analyzing visualized data.
Abstract: This paper aims to investigate the influence of quality
of education and quality of research, provided by local educational
institutions, on the adoption of Information and Communication
Technology (ICT) in managing business operations for companies in
Saudi market. A model was developed and tested using data collected
from 138 Chief Executive Officers (CEOs) of foreign companies in
diverse business sectors. The data is analyzed and managed using
multivariate approaches through standard statistical packages. The
results showed that educational quality has little contribution to the
ICT adoption while research quality seems to play a more prominent
role. These results are analyzed in terms of business environment and
market constraints and further extended to the perceived effectiveness
of applied pedagogical approaches in schools and universities.
Abstract: Modeling and forecasting dynamics of rainfall
occurrences constitute one of the major topics, which have been
largely treated by statisticians, hydrologists, climatologists and many
other groups of scientists. In the same issue, we propose, in the
present paper, a new hybrid method, which combines Extreme
Values and fractal theories. We illustrate the use of our methodology
for transformed Emberger Index series, constructed basing on data
recorded in Oujda (Morocco).
The index is treated at first by Peaks Over Threshold (POT)
approach, to identify excess observations over an optimal threshold u.
In the second step, we consider the resulting excess as a fractal object
included in one dimensional space of time. We identify fractal
dimension by the box counting. We discuss the prospect descriptions
of rainfall data sets under Generalized Pareto Distribution, assured by
Extreme Values Theory (EVT). We show that, despite of the
appropriateness of return periods given by POT approach, the
introduction of fractal dimension provides accurate interpretation
results, which can ameliorate apprehension of rainfall occurrences.
Abstract: This paper is a report on the findings of a study
conducted at the Institute of Public Administration (IPA) in Saudi
Arabia. The paper applied both qualitative and quantitative
approaches to assess the levels of basic computer applications’ skills
among students enrolled in the preparatory programs of the
institution. Qualitative data have been collected from semi-structured
interviews with the instructors who have previously been assigned to
teach Introduction to information technology courses. Quantitative
data were collected by executing a self-report questionnaire and a
written statistical test. Three hundred eighty enrolled students
responded to the questionnaire and one hundred forty two
accomplished the statistical test. The results indicate the lack of
necessary skills to deal with computer applications among most of
the students who are enrolled in the IPA’s preparatory programs.
Abstract: Teaching art by digital means is a big challenge for
the majority of teachers of art and design in primary schools, yet it
allows relationships between art, technology and creativity to be
clearly identified. The aim of this article is to present a modern way
of teaching art, using digital tools in the art classroom to improve
creative ability in pupils aged between nine and eleven years. It also
presents a conceptual model for creativity based on digital art. The
model could be useful for pupils interested in learning to draw by
using an e-drawing package, and for teachers who are interested in
teaching modern digital art in order to improve children’s creativity.
By illustrating the strategy of teaching art through technology, this
model may also help education providers to make suitable choices
about which technological approaches are most effective in
enhancing students’ creative ability, and which digital art tools can
benefit children by developing their technical skills. It is also
expected that use of this model will help to develop skills of social
interaction, which may in turn improve intellectual ability.
Abstract: Beta-glucosidase, chitinase, leucine-aminopeptidase, acid phosphomonoesterase and acetate-esterase enzyme activities in
the soils under the impact of metallurgical industrial activity in Lori
marz (district) were investigated. The results of the study showed that
the activities of the investigated enzymes in the soils decreased with increasing distance from the Shamlugh copper mine, the Chochkan
tailings storage facility and the ore transportation road. Statistical
analysis revealed that the activities of the enzymes were positively
correlated (significant) to each other according to the observation
sites which indicated that enzyme activities were affected by the
same anthropogenic factor. The investigations showed that the soils
were polluted with heavy metals (Cu, Pb, As, Co, Ni, Zn) due to
copper mining activity in this territory. The results of Pearson
correlation analysis revealed a significant negative correlation
between heavy metal pollution degree (Nemerow integrated pollution
index) and soil enzyme activity. All of this indicated that copper
mining activity in this territory causing the heavy metal pollution of
the soils resulted in the inhabitation of the activities of the enzymes
which are considered as biological catalysts to decompose organic
materials and facilitate the cycling of nutrients.