Abstract: Incineration of municipal solid waste (MSW) is one of
the key scopes in the global clean energy strategy. A computational
fluid dynamics (CFD) model was established in order to reveal these
features of the combustion process in a fixed porous bed of MSW.
Transporting equations and process rate equations of the waste bed
were modeled and set up to describe the incineration process,
according to the local thermal conditions and waste property
characters. Gas phase turbulence was modeled using k-ε turbulent
model and the particle phase was modeled using the kinetic theory of
granular flow. The heterogeneous reaction rates were determined
using Arrhenius eddy dissipation and the Arrhenius-diffusion
reaction rates. The effects of primary air flow rate and temperature in
the burning process of simulated MSW are investigated
experimentally and numerically. The simulation results in bed are
accordant with experimental data well. The model provides detailed
information on burning processes in the fixed bed, which is otherwise
very difficult to obtain by conventional experimental techniques.
Abstract: The arm length, hand length, hand breadth and middle
finger length of 1540 right-handed industrial workers of Haryana
state was used to assess the relationship between the upper limb
dimensions and stature. Initially, the data were analyzed using basic
univariate analysis and independent t-tests; then simple and multiple
linear regression models were used to estimate stature using SPSS
(version 17). There was a positive correlation between upper limb
measurements (hand length, hand breadth, arm length and middle
finger length) and stature (p < 0.01), which was highest for hand
length. The accuracy of stature prediction ranged from ± 54.897 mm
to ± 58.307 mm. The use of multiple regression equations gave better
results than simple regression equations. This study provides new
forensic standards for stature estimation from the upper limb
measurements of male industrial workers of Haryana (India). The
results of this research indicate that stature can be determined using
hand dimensions with accuracy, when only upper limb is available
due to any reasons likewise explosions, train/plane crashes, mutilated
bodies, etc. The regression formula derived in this study will be
useful for anatomists, archaeologists, anthropologists, design
engineers and forensic scientists for fairly prediction of stature using
regression equations.
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: 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: 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: Improved resource efficiency of production is a key
requirement for sustainable growth, worldwide. In this regards, by
considering the energy and tourism as the extra inputs to the classical
Coub-Douglas production function, this study aims at investigating
the efficiency changes in the North African countries. To this end, the
study uses panel data for the period 1995-2010 and adopts the
Malmquist index based on the data envelopment analysis. Results
show that tourism increases technical and scale efficiencies, while it
decreases technological and total factor productivity changes. On the
other hand, when the production function is augmented by the energy
input; technical efficiency change decreases, while the technological
change, scale efficiency change and total factor productivity change
increase. Thus, in order to satisfy the needs for sustainable growth,
North African governments should take some measures for increasing
the contribution that the tourism makes to economic growth and some
others for efficient use of resources in the energy sector.
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: Groundwater inflow to the tunnels is one of the most
important problems in tunneling operation. The objective of this
study is the investigation of model dimension effects on tunnel inflow
assessment in discontinuous rock masses using numerical modeling.
In the numerical simulation, the model dimension has an important
role in prediction of water inflow rate. When the model dimension is
very small, due to low distance to the tunnel border, the model
boundary conditions affect the estimated amount of groundwater flow
into the tunnel and results show a very high inflow to tunnel. Hence,
in this study, the two-dimensional universal distinct element code
(UDEC) used and the impact of different model parameters, such as
tunnel radius, joint spacing, horizontal and vertical model domain
extent has been evaluated. Results show that the model domain extent
is a function of the most significant parameters, which are tunnel
radius and joint spacing.
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: Corrosion of concrete sewer pipes induced by sulfuric
acid is an acknowledged problem and a ticking time-bomb to sewer
operators. Whilst the chemical reaction of the corrosion process is
well-understood, the indirect roles of other parameters in the
corrosion process which are found in sewer environment are not
highly reflected on. This paper reports on a field studies undertaken
in Austria and United Kingdom, where the parameters of
temperature, pH, H2S and CO2 were monitored over a period of time.
The study establishes that (i) effluent temperature and pH have
similar daily pattern and peak times, when examined in minutes
scale; (ii) H2S and CO2 have an identical hourly pattern; (iii) H2S
instant or shifted relation to effluent temperature is governed by the
root mean square value of CO2.
Abstract: Recently, the competition between websites becomes
intense. How to make users “adopt” their websites is an issue of urgent
importance for online communities companies. Social procedures
(such as social influence) can possibly explain how and why users’
technologies usage behaviors affect other people to use the
technologies. This study proposes two types of social influences on the
initial usage of Facebook Check In-friends and group members.
Besides, this study combines social influences theory and social
network theory to explore the factors influencing initial usage of
Facebook Check In. This study indicates that Facebook friends’
previous usage of Facebook Check In and Facebook group members’
previous usage of Facebook Check In will positively influence focal
actors’ Facebook Check In adoption intention, and network centrality
will moderate the relationships among Facebook friends’ previous
usage of Facebook Check In, Facebook group members’ previous
usage of Facebook Check In and focal actors’ Facebook Check In
adoption intention. The article concludes with contributions to
academic research and practice.
Abstract: In recent years parasitic antenna play major role in
MIMO systems because of their gain and spectral efficiency. In this
paper, single RF chain MIMO transmitter is designed using
reconfigurable parasitic antenna. The Spatial Modulation (SM) is a
recently proposed scheme in MIMO scenario which activates only
one antenna at a time. The SM entirely avoids ICI and IAS, and only
requires a single RF chain at the transmitter. This would switch ON a
single transmit-antenna for data transmission while all the other
antennas are kept silent. The purpose of the parasitic elements is to
change the radiation pattern of the radio waves which is emitted from
the driven element and directing them in one direction and hence
introduces transmit diversity. Diode is connect between the patch and
ground by changing its state (ON and OFF) the parasitic element act
as reflector and director and also capable of steering azimuth and
elevation angle. This can be achieved by changing the input
impedance of each parasitic element through single RF chain. The
switching of diode would select the single parasitic antenna for
spatial modulation. This antenna is expected to achieve maximum
gain with desired efficiency.
Abstract: We have been grouping and developing various kinds
of practical, promising sensing applied systems concerning
agricultural advancement and technical tradition (guidance). These
include advanced devices to secure real-time data related to worker
motion, and we analyze by methods of various advanced statistics and
human dynamics (e.g. primary component analysis, Ward system
based cluster analysis, and mapping). What is more, we have been
considering worker daily health and safety issues. Targeted fields are
mainly common farms, meadows, and gardens. After then, we
observed and discussed time-line style, changing data. And, we made
some suggestions. The entire plan makes it possible to improve both
the aforementioned applied systems and farms.
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: Stratified double extreme ranked set sampling
(SDERSS) method is introduced and considered for estimating the
population mean. The SDERSS is compared with the simple random
sampling (SRS), stratified ranked set sampling (SRSS) and stratified
simple set sampling (SSRS). It is shown that the SDERSS estimator
is an unbiased of the population mean and more efficient than the
estimators using SRS, SRSS and SSRS when the underlying
distribution of the variable of interest is symmetric or asymmetric.
Abstract: Recently, the green architecture becomes a
significant way to a sustainable future. Green building designs
involve finding the balance between comfortable homebuilding and
sustainable environment. Moreover, the utilization of the new
technologies such as artificial intelligence techniques are used to
complement current practices in creating greener structures to keep
the built environment more sustainable. The most common objectives
in green buildings should be designed to minimize the overall impact
of the built environment that effect on ecosystems in general and in
particularly human health and natural environment. This will lead to
protecting occupant health, improving employee productivity,
reducing pollution and sustaining the environmental. In green
building design, multiple parameters which may be interrelated,
contradicting, vague and of qualitative/quantitative nature are
broaden to use. This paper presents a comprehensive critical state- ofart-
review of current practices based on fuzzy and its combination
techniques. Also, presented how green architecture/building can be
improved using the technologies that been used for analysis to seek
optimal green solutions strategies and models to assist in making the
best possible decision out of different alternatives.
Abstract: Paraffinic oils were submitted to microbial action. The
microorganisms consisted of bacteria of the genera Pseudomonas sp.
and Bacillus lincheniforms. The alterations in interfacial tension were
determined using a tensometer and applying the hanging drop
technique at room temperature (299 K ±275 K). The alteration in the
constitution of the paraffins was evaluated by means of gas
chromatography. The microbial activity was observed to reduce
interfacial tension by 54 to 78%, as well as consuming the paraffins
C19 to C29 and producing paraffins C36 to C44. The LIFirr technique
made it possible to determine the microbial action quickly.
Abstract: If teamwork is the key to organizational learning,
productivity and growth, then, why do some teams succeed in
achieving these, while others falter at different stages? Building
teams in higher education institutions has been a challenge and an
open-ended constructivist approach was considered on an
experimental basis for this study to address this challenge. For this
research, teams of students from the MBA program were chosen to
study the effect of teamwork in learning, the motivation levels among
student team members, and the effect of collaboration in achieving
team goals. The teams were built on shared vision and goals,
cohesion was ensured, positive induction in the form of faculty
mentoring was provided for each participating team and the results
have been presented with conclusions and suggestions.
Abstract: Data mining idea is mounting rapidly in admiration
and also in their popularity. The foremost aspire of data mining
method is to extract data from a huge data set into several forms that
could be comprehended for additional use. The data mining is a
technology that contains with rich potential resources which could be
supportive for industries and businesses that pay attention to collect
the necessary information of the data to discover their customer’s
performances. For extracting data there are several methods are
available such as Classification, Clustering, Association,
Discovering, and Visualization… etc., which has its individual and
diverse algorithms towards the effort to fit an appropriate model to
the data. STATISTICA mostly deals with excessive groups of data
that imposes vast rigorous computational constraints. These results
trials challenge cause the emergence of powerful STATISTICA Data
Mining technologies. In this survey an overview of the STATISTICA
software is illustrated along with their significant features.
Abstract: This paper argues nation-building theories that
prioritize democratic governance best explain the successful postindependence
development of Botswana. Three main competing
schools of thought exist regarding the sequencing of policies that
should occur to re-build weakened or failed states. The first posits
that economic development should receive foremost attention, while
democratization and a binding sense of nationalism can wait. A
second group of experts identified constructing a sense of nationalism
among a populace is necessary first, so that the state receives popular
legitimacy and obedience that are prerequisites for development.
Botswana, though, transitioned into a multi-party democracy and
prosperous open economy due to the utilization of traditional
democratic structures, enlightened and accountable leadership, and an
educated technocratic civil service. With these political foundations
already in place when the discovery of diamonds occurred, the
resulting revenues were spent wisely on projects that grew the
economy, improved basic living standards, and attracted foreign
investment. Thus democratization preceded, and therefore provided
an accountable basis for, economic development that might otherwise
have been squandered by greedy and isolated elites to the detriment
of the greater population. Botswana was one of the poorest nations in
the world at the time of its independence in 1966, with little
infrastructure, a dependence on apartheid South Africa for trade, and
a largely subsistence economy. Over the next thirty years, though, its
economy grew the fastest of any nation in the world. The transparent
and judicious use of diamond returns is only a partial explanation, as
the government also pursued economic diversification, mass
education, and rural development in response to public needs.
As nation-building has become a project undertaken by nations
and multilateral agencies such as the United Nations and the North
Atlantic Treaty Organization, Botswana may provide best practices
that others should follow in attempting to reconstruct economically
and politically unstable states.