Abstract: In this study, a computational fluid dynamics (CFD)
model has been developed for studying the effect of surface
roughness profile on the EHL problem. The cylinders contact
geometry, meshing and calculation of the conservation of mass and
momentum equations are carried out using the commercial software
packages ICEMCFD and ANSYS Fluent. The user defined functions
(UDFs) for density, viscosity and elastic deformation of the cylinders
as the functions of pressure and temperature are defined for the CFD
model. Three different surface roughness profiles are created and
incorporated into the CFD model. It is found that the developed CFD
model can predict the characteristics of fluid flow and heat transfer in
the EHL problem, including the main parameters such as pressure
distribution, minimal film thickness, viscosity, and density changes.
The results obtained show that the pressure profile at the center of the
contact area directly relates to the roughness amplitude. A rough
surface with kurtosis value of more than 3 has greater influence over
the fluctuated shape of pressure distribution than in other cases.
Abstract: Nature is the immense gifted source for solving
complex problems. It always helps to find the optimal solution to
solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide
research area of networks which has set of independent nodes. The
characteristics involved in MANET’s are Dynamic, does not depend
on any fixed infrastructure or centralized networks, High mobility.
The Bio-Inspired algorithms are mimics the nature for solving
optimization problems opening a new era in MANET. The typical
Swarm Intelligence (SI) algorithms are Ant Colony Optimization
(ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization
(PSO), Modified Termite Algorithm, Bat Algorithm (BA), Wolf
Search Algorithm (WSA) and so on. This work mainly concentrated
on nature of MANET and behavior of nodes. Also it analyses various
performance metrics such as throughput, QoS and End-to-End delay
etc.
Abstract: Catalytic combustion of methane is imperative due to
stability of methane at low temperature. Methane (CH4), therefore,
remains unconverted in vehicle exhausts thereby causing greenhouse
gas GHG emission problem. In this study, heterogeneous catalysts of
palladium with bio-char (2 wt% Pd/Bc) and Al2O3 (2wt% Pd/ Al2O3)
supports were prepared by incipient wetness impregnation and then
subsequently tested for catalytic combustion of CH4. Support-porous
heterogeneous catalytic combustion (HCC) material were selected
based on factors such as surface area, porosity, thermal stability,
thermal conductivity, reactivity with reactants or products, chemical
stability, catalytic activity, and catalyst life. Sustainable and
renewable support-material of bio-mass char derived from palm shell
waste material was compared with those from the conventional
support-porous materials. Kinetic rate of reaction was determined for
combustion of methane on Palladium (Pd) based catalyst with Al2O3
support and bio-char (Bc). Material characterization was done using
TGA, SEM, and BET surface area. The performance test was
accomplished using tubular quartz reactor with gas mixture ratio of
3% methane and 97% air. The methane porous-HCC conversion was
carried out using online gas analyzer connected to the reactor that
performed porous-HCC. BET surface area for prepared 2 wt% Pd/Bc
is smaller than prepared 2wt% Pd/ Al2O3 due to its low porosity
between particles. The order of catalyst activity based on kinetic rate
on reaction of catalysts in low temperature was 2wt%
Pd/Bc>calcined 2wt% Pd/ Al2O3> 2wt% Pd/ Al2O3>calcined 2wt%
Pd/Bc. Hence agro waste material can successfully be utilized as an
inexpensive catalyst support material for enhanced CH4 catalytic
combustion.
Abstract: Planning of infrastructure and processes in logistic
center within the frame of various kinds of logistic hubs and
technological activities in them represent quite complex problem.
The main goal is to design appropriate layout, which enables to
realize expected operation on the desired levels. The simulation
software represents progressive contemporary experimental
technique, which can support complex processes of infrastructure
planning and all of activities on it. It means that simulation
experiments, reflecting various planned infrastructure variants,
investigate and verify their eligibilities in relation with corresponding
expected operation. The inducted approach enables to make qualified
decisions about infrastructure investments or measures, which derive
benefit from simulation-based verifications. The paper represents
simulation software for simulation infrastructural layout and
technological activities in marshalling yard, intermodal terminal,
warehouse and combination between them as the parts of logistic
center.
Abstract: In this paper, we consider the vehicle routing problem
with mixed fleet of conventional and heterogenous electric vehicles
and time dependent charging costs, denoted VRP-HFCC, in which
a set of geographically scattered customers have to be served by a
mixed fleet of vehicles composed of a heterogenous fleet of Electric
Vehicles (EVs), having different battery capacities and operating
costs, and Conventional Vehicles (CVs). We include the possibility
of charging EVs in the available charging stations during the routes
in order to serve all customers. Each charging station offers charging
service with a known technology of chargers and time dependent
charging costs. Charging stations are also subject to operating time
windows constraints. EVs are not necessarily compatible with all
available charging technologies and a partial charging is allowed.
Intermittent charging at the depot is also allowed provided that
constraints related to the electricity grid are satisfied.
The objective is to minimize the number of employed vehicles and
then minimize the total travel and charging costs.
In this study, we present a Mixed Integer Programming Model and
develop a Charging Routing Heuristic and a Local Search Heuristic
based on the Inject-Eject routine with different insertion methods. All
heuristics are tested on real data instances.
Abstract: Load modeling is one of the central functions in
power systems operations. Electricity cannot be stored, which means
that for electric utility, the estimate of the future demand is necessary
in managing the production and purchasing in an economically
reasonable way. A majority of the recently reported approaches are
based on neural network. The attraction of the methods lies in the
assumption that neural networks are able to learn properties of the
load. However, the development of the methods is not finished, and
the lack of comparative results on different model variations is a
problem. This paper presents a new approach in order to predict the
Tunisia daily peak load. The proposed method employs a
computational intelligence scheme based on the Fuzzy neural
network (FNN) and support vector regression (SVR). Experimental
results obtained indicate that our proposed FNN-SVR technique gives
significantly good prediction accuracy compared to some classical
techniques.
Abstract: In this paper we consider the rule reduct generation
problem. Rule Reduct Generation (RG) and Modified Rule
Generation (MRG) algorithms, that are used to solve this problem,
are well-known. Alternative to these algorithms, we develop Pruning
Rule Generation (PRG) algorithm. We compare the PRG algorithm
with RG and MRG.
Abstract: There exists some time lag between the consumption of
inputs and the production of outputs. This time lag effect should be
considered in calculating efficiency of decision making units (DMU).
Recently, a couple of DEA models were developed for considering
time lag effect in efficiency evaluation of research activities. However,
these models can’t discriminate efficient DMUs because of the nature
of basic DEA model in which efficiency scores are limited to ‘1’. This
problem can be resolved a super-efficiency model. However, a super
efficiency model sometimes causes infeasibility problem. This paper
suggests an output oriented super-efficiency model for efficiency
evaluation under the consideration of time lag effect. A case example
using a long term research project is given to compare the suggested
model with the MpO model.
Abstract: Securing the confidential data transferred via wireless
network remains a challenging problem. It is paramount to ensure
that data are accessible only by the legitimate users rather than by the
attackers. One of the most serious threats to organization is jamming,
which disrupts the communication between any two pairs of nodes.
Therefore, designing an attack-defending scheme without any packet
loss in data transmission is an important challenge. In this paper,
Dependence based Malicious Route Defending DMRD Scheme has
been proposed in multi path routing environment to prevent jamming
attack. The key idea is to defend the malicious route to ensure
perspicuous transmission. This scheme develops a two layered
architecture and it operates in two different steps. In the first step,
possible routes are captured and their agent dependence values are
marked using triple agents. In the second step, the dependence values
are compared by performing comparator filtering to detect malicious
route as well as to identify a reliable route for secured data
transmission. By simulation studies, it is observed that the proposed
scheme significantly identifies malicious route by attaining lower
delay time and route discovery time; it also achieves higher
throughput.
Abstract: The star network is one of the promising
interconnection networks for future high speed parallel computers, it
is expected to be one of the future-generation networks. The star
network is both edge and vertex symmetry, it was shown to have
many gorgeous topological proprieties also it is owns hierarchical
structure framework. Although much of the research work has been
done on this promising network in literature, it still suffers from
having enough algorithms for load balancing problem. In this paper
we try to work on this issue by investigating and proposing an
efficient algorithm for load balancing problem for the star network.
The proposed algorithm is called Star Clustered Dimension Exchange
Method SCDEM to be implemented on the star network. The
proposed algorithm is based on the Clustered Dimension Exchange
Method (CDEM). The SCDEM algorithm is shown to be efficient in
redistributing the load balancing as evenly as possible among all
nodes of different factor networks.
Abstract: In regards to the energy sector in the modern period,
two points were raised. First is a vast and growing energy demand, and
second is an environmental impact associated with it. The enormous
consumption of fossil fuel to the mobile unit is leading to its rapid
depletion. Nuclear power is not the only problem. A modal shift that
utilizes personal transporters and independent power, in order to
realize a sustainable society, is very effective. The author proposes that
the world will continue to work on this. Energy of the future society,
innovation in battery technology and the use of natural energy is a big
key. And it is also necessary in order to save on energy consumption.
Abstract: Distributed Generation (DG) can help in reducing the
cost of electricity to the costumer, relieve network congestion and
provide environmentally friendly energy close to load centers. Its
capacity is also scalable and it provides voltage support at distribution
level. Hence, DG placement and penetration level is an important
problem for both the utility and DG owner. DG allocation and capacity
determination is a nonlinear optimization problem. The objective
function of this problem is the minimization of the total loss of the
distribution system. Also high levels of penetration of DG are a new
challenge for traditional electric power systems. This paper presents a
new methodology for the optimal placement of DG and penetration
level of DG in distribution system based on General Algebraic
Modeling System (GAMS) and Genetic Algorithm (GA).
Abstract: Electricity is recognized as fundamental to
industrialization and improving the quality of life of the people.
Harnessing the immense untapped hydropower potential in Tripura
region opens avenues for growth and provides an opportunity to
improve the well-being of the people of the region, while making
substantial contribution to the national economy. Gumti hydro power
plant generates power to mitigate the crisis of power in Tripura,
India. The first unit of hydro power plant (5MW) was commissioned
in June 1976 & another two units of 5 MW was commissioned
simultaneously. But out of 15MW capacity at present only 8MW-
9MW power is produced from Gumti hydro power plant during rainy
season. But during lean season the production reduces to 0.5MW due
to shortage of water. Now, it is essential to implement some
mitigation measures so that the further atrocities can be prevented
and originality will be possible to restore. The decision making
ability of the Analytic Hierarchy Process (AHP) and Concordance
Analysis Techniques (CAT) are utilized to identify the better decision
or solution to the present problem. Some related attributes are
identified by the method of surveying within the experts and the
available reports and literatures. Similar criteria are removed and
ultimately seven relevant ones are identified. All the attributes are
compared with each other and rated accordingly to their importance
over the other with the help of Pair wise Comparison Matrix. In the
present investigation different mitigation measures are identified and
compared to find the best suitable alternative which can solve the
present uncertainties involving the existence of the Gumti Hydro
Power Plant.
Abstract: In this paper, we introduce a generalized Chebyshev
collocation method (GCCM) based on the generalized Chebyshev
polynomials for solving stiff systems. For employing a technique
of the embedded Runge-Kutta method used in explicit schemes, the
property of the generalized Chebyshev polynomials is used, in which
the nodes for the higher degree polynomial are overlapped with those
for the lower degree polynomial. The constructed algorithm controls
both the error and the time step size simultaneously and further
the errors at each integration step are embedded in the algorithm
itself, which provides the efficiency of the computational cost. For
the assessment of the effectiveness, numerical results obtained by the
proposed method and the Radau IIA are presented and compared.
Abstract: The reachable set bounding estimation for distributed
delay systems with disturbances is a new problem. In this paper,we
consider this problem subject to not only time varying delay and
polytopic uncertainties but also distributed delay systems which is
not studied fully untill now. we can obtain improved non-ellipsoidal
reachable set estimation for neural networks with time-varying delay
by the maximal Lyapunov-Krasovskii fuctional which is constructed
as the pointwise maximum of a family of Lyapunov-Krasovskii
fuctionals corresponds to vertexes of uncertain polytope.On the other
hand,matrix inequalities containing only one scalar and Matlabs
LMI Toolbox is utilized to give a non-ellipsoidal description of the
reachable set.finally,numerical examples are given to illustrate the
existing results.
Abstract: Students’ achievement and motivation in learning
English in Malaysia is a worrying trend as it is lagging behind several
other countries in Asia. Thus, necessary actions have to be taken by
the parties concerned to overcome this problem. The purpose of this
research was to study the effects of drill and practice courseware on
students’ achievement and motivation in learning English language.
A multimedia courseware was developed for this purpose. The
independent variable was the drill and practice courseware while the
dependent variables were the students’ achievement and motivation.
Their achievement was measured using pre-test and post-test scores,
while motivation was measured using a questionnaire. A total of 60
students from three vernacular primary schools in a northern state in
Malaysia were randomly selected in this study. The findings indicate:
(1) a significant difference between the students’ pre-test and posttest
scores after using the courseware, (2) no significant difference in
the achievement score between male and female students after using
the courseware, (3) a significant difference in motivation score
between the female and the male students, and (4) while the female
students scored significantly higher than the male students in the
aspects of relevance, confidence and satisfaction, no significant
difference in terms of attention was observed between them. Overall,
the findings clearly indicate that although the female students are
significantly more motivated than their male students, they are
equally good in terms of achievement after learning from the
courseware. Through this study, the drill and practice courseware is
proven to influence the students’ learning and motivation.
Abstract: Recently, an increasing number of researchers have
been focusing on working out realistic solutions to sustainability
problems. As sustainability issues gain higher importance for
organisations, the management of such decisions becomes critical.
Knowledge representation is a fundamental issue of complex
knowledge based systems. Many types of sustainability problems
would benefit from models based on experts’ knowledge. Cognitive
maps have been used for analyzing and aiding decision making. A
cognitive map can be made of almost any system or problem. A
fuzzy cognitive map (FCM) can successfully represent knowledge
and human experience, introducing concepts to represent the essential
elements and the cause and effect relationships among the concepts to
model the behaviour of any system. Integrated waste management
systems (IWMS) are complex systems that can be decomposed to
non-related and related subsystems and elements, where many factors
have to be taken into consideration that may be complementary,
contradictory, and competitive; these factors influence each other and
determine the overall decision process of the system. The goal of the
present paper is to construct an efficient IWMS which considers
various factors. The authors’ intention is to propose an expert based
system design approach for implementing expert decision support in
the area of IWMSs and introduces an appropriate methodology for
the development and analysis of group FCM. A framework for such a
methodology consisting of the development and application phases is
presented.
Abstract: Economic Dispatch (ED) is one of the most
challenging problems of power system since it is difficult to determine
the optimum generation scheduling to meet the particular load demand
with the minimum fuel costs while all constraints are satisfied. The
objective of the Economic Dispatch Problems (EDPs) of electric
power generation is to schedule the committed generating units
outputs so as to meet the required load demand at minimum operating
cost while satisfying all units and system equality and inequality
constraints. In this paper, an efficient and practical steady-state genetic
algorithm (SSGAs) has been proposed for solving the economic
dispatch problem. The objective is to minimize the total generation
fuel cost and keep the power flows within the security limits. To
achieve that, the present work is developed to determine the optimal
location and size of capacitors in transmission power system where,
the Participation Factor Algorithm and the Steady State Genetic
Algorithm are proposed to select the best locations for the capacitors
and determine the optimal size for them.
Abstract: This paper presents general results on the Java source
code snippet detection problem. We propose the tool which uses
graph and subgraph isomorphism detection. A number of solutions
for all of these tasks have been proposed in the literature. However,
although that all these solutions are really fast, they compare just the
constant static trees. Our solution offers to enter an input sample
dynamically with the Scripthon language while preserving an
acceptable speed. We used several optimizations to achieve very low
number of comparisons during the matching algorithm.
Abstract: Audio-lingual Method (ALM) is a teaching approach
that is claimed that ineffective for teaching second/foreign languages.
Because some linguists and second/foreign language teachers believe
that ALM is a rote learning style. However, this study is done on a
belief that ALM will be able to solve Thais’ English speaking
problem. This paper aims to report the findings on teaching English
speaking to adult learners with an “adapted ALM”, one distinction of
which is to use Thai as the medium language of instruction.
The participants are consisted of 9 adult learners. They were
allowed to speak English more freely using both the materials
presented in the class and their background knowledge of English. At
the end of the course, they spoke English more fluently, more
confidently, to the extent that they applied what they learnt both in
and outside the class.