Abstract: The Niger Delta Region of Nigeria is home to about
20 million people and 40 different ethnic groups. The region has an
area of seventy thousand square kilometers (70,000 KM2) of
wetlands, formed primarily by sediments deposition and makes up
7.5 percent of Nigeria's total landmass. The notable ecological zones
in this region includes: coastal barrier islands; mangrove swamp
forests; fresh water swamps; and lowland rainforests. This incredibly
naturally-endowed ecosystem region, which contains one of the
highest concentrations of biodiversity on the planet, in addition to
supporting abundant flora and fauna, is threatened by the inhuman act
known as gas flaring. Gas flaring is the combustion of natural gas
that is associated with crude oil when it is pumped up from the
ground. In petroleum-producing areas such as the Niger Delta region
of Nigeria where insufficient investment was made in infrastructure
to utilize natural gas, flaring is employed to dispose of this associated
gas. This practice has impoverished the communities where it is
practiced, with attendant environmental, economic and health
challenges. This paper discusses the adverse environmental and
health implication associated with the practice, the role of
Government, Policy makers, Oil companies and the Local
communities aimed at bring this inhuman practice to a prompt end.
Abstract: In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems.
Abstract: Proposal for a secure stream cipher based on Linear Feedback Shift Registers (LFSR) is presented here. In this method, shift register structure used for polynomial modular division is combined with LFSR keystream generator to yield a new keystream generator with much higher periodicity. Security is brought into this structure by using the Boolean function to combine state bits of the LFSR keystream generator and taking the output through the Boolean function. This introduces non-linearity and security into the structure in a way similar to the Non-linear filter generator. The security and throughput of the suggested stream cipher is found to be much greater than the known LFSR based structures for the same key length.
Abstract: DNA shuffling is a powerful method used for in vitro
evolute molecules with specific functions and has application in areas
such as, for example, pharmaceutical, medical and agricultural
research. The success of such experiments is dependent on a variety
of parameters and conditions that, sometimes, can not be properly
pre-established. Here, two computational models predicting DNA
shuffling results is presented and their use and results are evaluated
against an empirical experiment. The in silico and in vitro results
show agreement indicating the importance of these two models and
motivating the study and development of new models.
Abstract: Wireless Sensor Networks (WSNs) are wireless
networks consisting of number of tiny, low cost and low power
sensor nodes to monitor various physical phenomena like
temperature, pressure, vibration, landslide detection, presence of any
object, etc. The major limitation in these networks is the use of nonrechargeable
battery having limited power supply. The main cause of
energy consumption WSN is communication subsystem. This paper
presents an efficient grid formation/clustering strategy known as Grid
based level Clustering and Aggregation of Data (GCAD). The
proposed clustering strategy is simple and scalable that uses low duty
cycle approach to keep non-CH nodes into sleep mode thus reducing
energy consumption. Simulation results demonstrate that our
proposed GCAD protocol performs better in various performance
metrics.
Abstract: Particle Swarm Optimization (PSO) with elite PSO
parameters has been developed for power flow analysis under
practical constrained situations. Multiple solutions of the power flow
problem are useful in voltage stability assessment of power system.
A method of determination of multiple power flow solutions is
presented using a hybrid of Particle Swarm Optimization (PSO) and
local search technique. The unique and innovative learning factors of
the PSO algorithm are formulated depending upon the node power
mismatch values to be highly adaptive with the power flow problems.
The local search is applied on the pbest solution obtained by the PSO
algorithm in each iteration. The proposed algorithm performs reliably
and provides multiple solutions when applied on standard and illconditioned
systems. The test results show that the performances of
the proposed algorithm under critical conditions are better than the
conventional methods.
Abstract: In this research it is aimed that the effect of some demographic factors on Turkish Adolescents' subjective well being is investigated. 432 adolescents who are 247 girls and 185 boys are participated in this study. They are ages 15-17, and also are high school students. The Positive and Negative Affect Scale and Life Satisfaction Scale are used for measuring adolescents' subjective well being. The ANOVA method is used in order to examine the effect of ages. For gender differences, independent t-test method is used, and finally the Pearson Correlation method is used so as to examine the effect of socio economic statues of adolescents' parents. According to results, there is no gender difference on adolescents' subjective well being. On the other hand, SES and age are effect significantly lover level on adolescents' subjective well being.
Abstract: An optimal power flow (OPF) based on particle swarm
optimization (PSO) was developed with more realistic generator
security constraint using the capability curve instead of only Pmin/Pmax
and Qmin/Qmax. Neural network (NN) was used in designing digital
capability curve and the security check algorithm. The algorithm is
very simple and flexible especially for representing non linear
generation operation limit near steady state stability limit and under
excitation operation area. In effort to avoid local optimal power flow
solution, the particle swarm optimization was implemented with
enough widespread initial population. The objective function used in
the optimization process is electric production cost which is
dominated by fuel cost. The proposed method was implemented at
Java Bali 500 kV power systems contain of 7 generators and 20
buses. The simulation result shows that the combination of generator
power output resulted from the proposed method was more economic
compared with the result using conventional constraint but operated
at more marginal operating point.
Abstract: Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robot has three degree of freedoms and the robot was implemented for drilling a printed circuit board. The artificial neural network architecture used for modeling is a multilayer perceptron networks with steepest descent backpropagation training algorithm. The designed artificial neural network has 2 inputs, 2 outputs and varies in number of hidden layer. Experiments were done in variation of number of hidden layer and learning rate. Experimental results show that the best architecture of artificial neural network used for modeling inverse kinematics of is multilayer perceptron with 1 hidden layer and 38 neurons per hidden layer. This network resulted a RMSE value of 0.01474.
Abstract: This paper features the modeling and design of a Fast
Output Sampling (FOS) Feedback control technique for the Active
Vibration Control (AVC) of a smart flexible aluminium cantilever
beam for a Single Input Single Output (SISO) case. Controllers are
designed for the beam by bonding patches of piezoelectric layer as
sensor / actuator to the master structure at different locations along
the length of the beam by retaining the first 2 dominant vibratory
modes. The entire structure is modeled in state space form using the
concept of piezoelectric theory, Euler-Bernoulli beam theory, Finite
Element Method (FEM) and the state space techniques by dividing
the structure into 3, 4, 5 finite elements, thus giving rise to three
types of systems, viz., system 1 (beam divided into 3 finite
elements), system 2 (4 finite elements), system 3 (5 finite elements).
The effect of placing the sensor / actuator at various locations along
the length of the beam for all the 3 types of systems considered is
observed and the conclusions are drawn for the best performance and
for the smallest magnitude of the control input required to control the
vibrations of the beam. Simulations are performed in MATLAB. The
open loop responses, closed loop responses and the tip displacements
with and without the controller are obtained and the performance of
the proposed smart system is evaluated for vibration control.
Abstract: There is a acute water problem especially in the dry
season in and around Perundurai (Erode district, Tamil Nadu, India)
where there are more number of tannery units. Hence an attempt was
made to use the waste water from tannery industry for construction
purpose. The mechanical properties such as compressive strength,
tensile strength, flexural strength etc were studied by casting various
concrete specimens in form of cube, cylinders and beams etc and
were found to be satisfactory. Hence some special properties such as
chloride attack, sulphate attack and chemical attack are considered
and comparatively studied with the conventional potable water. In
this experimental study the results of specimens prepared by using
treated and untreated tannery effluent were compared with the
concrete specimens prepared by using potable water. It was observed
that the concrete had some reduction in strength while subjected to
chloride attack, sulphate attack and chemical attack. So admixtures
were selected and optimized in suitable proportion to counter act the
adverse effects and the results were found to be satisfactory.
Abstract: The join dependency provides the basis for obtaining
lossless join decomposition in a classical relational schema. The
existence of Join dependency shows that that the tables always
represent the correct data after being joined. Since the classical
relational databases cannot handle imprecise data, they were
extended to fuzzy relational databases so that uncertain, ambiguous,
imprecise and partially known information can also be stored in
databases in a formal way. However like classical databases, the
fuzzy relational databases also undergoes decomposition during
normalization, the issue of joining the decomposed fuzzy relations
remains intact. Our effort in the present paper is to emphasize on this
issue. In this paper we define fuzzy join dependency in the
framework of type-1 fuzzy relational databases & type-2 fuzzy
relational databases using the concept of fuzzy equality which is
defined using fuzzy functions. We use the fuzzy equi-join operator
for computing the fuzzy equality of two attribute values. We also
discuss the dependency preservation property on execution of this
fuzzy equi- join and derive the necessary condition for the fuzzy
functional dependencies to be preserved on joining the decomposed
fuzzy relations. We also derive the conditions for fuzzy join
dependency to exist in context of both type-1 and type-2 fuzzy
relational databases. We find that unlike the classical relational
databases even the existence of a trivial join dependency does not
ensure lossless join decomposition in type-2 fuzzy relational
databases. Finally we derive the conditions for the fuzzy equality to
be non zero and the qualification of an attribute for fuzzy key.
Abstract: The use of renewable energy sources becomes more
necessary and interesting. As wider applications of renewable energy
devices at domestic, commercial and industrial levels has not only
resulted in greater awareness, but also significantly installed
capacities. In addition, biomass principally is in the form of woods,
which is a form of energy by humans for a long time. Gasification is
a process of conversion of solid carbonaceous fuel into combustible
gas by partial combustion. Many gasifier models have various
operating conditions; the parameters kept in each model are different.
This study applied experimental data, which has three inputs, which
are; biomass consumption, temperature at combustion zone and ash
discharge rate. One output is gas flow rate. For this paper, neural
network was used to identify the gasifier system suitable for the
experimental data. In the result,neural networkis usable to attain the
answer.
Abstract: This paper presents the experimental results on
artificial ageing test of 22 kV XLPE cable for distribution system
application in Thailand. XLPE insulating material of 22 kV cable
was sliced to 60-70 μm in thick and was subjected to ac high voltage
at 23
Ôùª
C, 60
Ôùª
C and 75
Ôùª
C. Testing voltage was constantly applied to
the specimen until breakdown. Breakdown voltage and time to
breakdown were used to evaluate life time of insulating material.
Furthermore, the physical model by J. P. Crine for predicts life time
of XLPE insulating material was adopted as life time model and was
calculated in order to compare the experimental results. Acceptable
life time results were obtained from Crine-s model comparing with
the experimental result. In addition, fourier transform infrared
spectroscopy (FTIR) for chemical analysis and scanning electron
microscope (SEM) for physical analysis were conducted on tested
specimens.
Abstract: The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1).
Abstract: The ever increasing use of World Wide Web in the
existing network, results in poor performance. Several techniques
have been developed for reducing web traffic by compressing the size
of the file, saving the web pages at the client side, changing the burst
nature of traffic into constant rate etc. No single method was
adequate enough to access the document instantly through the
Internet. In this paper, adaptive hybrid algorithms are developed for
reducing web traffic. Intelligent agents are used for monitoring the
web traffic. Depending upon the bandwidth usage, user-s preferences,
server and browser capabilities, intelligent agents use the best
techniques to achieve maximum traffic reduction. Web caching,
compression, filtering, optimization of HTML tags, and traffic
dispersion are incorporated into this adaptive selection. Using this
new hybrid technique, latency is reduced to 20 – 60 % and cache hit
ratio is increased 40 – 82 %.
Abstract: In July 2012, an indoor/outdoor monitoring
programme was undertaken in two university sports facilities: a
fronton and a gymnasium. Comfort parameters (temperature, relative
humidity, CO and CO2) and total volatile organic compounds
(VOCs) were continuously monitored. Concentrations of NO2,
carbonyl compounds and individual VOCs were obtained. Low
volume samplers were used to collect particulate matter (PM10). The
minimum ventilation rates stipulated for acceptable indoor air quality
were observed in both sports facilities. It was found that cleaning
activities may have a large influence on the VOC levels. Acrolein
was one of the most abundant carbonyl compounds, showing
concentrations above the recommended limit. Formaldehyde was
detected at levels lower than those commonly reported for other
indoor environments. The PM10 concentrations obtained during the
occupancy periods ranged between 38 and 43μgm-3 in the fronton and
from 154 to 198μgm-3 in the gymnasium.
Abstract: In this research paper we have presented control
architecture for robotic arm movement and trajectory planning using
Fuzzy Logic (FL) and Genetic Algorithms (GAs). This architecture is
used to compensate the uncertainties like; movement, friction and
settling time in robotic arm movement. The genetic algorithms and
fuzzy logic is used to meet the objective of optimal control
movement of robotic arm. This proposed technique represents a
general model for redundant structures and may extend to other
structures. Results show optimal angular movement of joints as result
of evolutionary process. This technique has edge over the other
techniques as minimum mathematics complexity used.
Abstract: A scalable QoS aware multicast deployment in
DiffServ networks has become an important research dimension in
recent years. Although multicasting and differentiated services are
two complementary technologies, the integration of the two
technologies is a non-trivial task due to architectural conflicts
between them. A popular solution proposed is to extend the
functionality of the DiffServ components to support multicasting. In
this paper, we propose an algorithm to construct an efficient QoSdriven
multicast tree, taking into account the available bandwidth per
service class. We also present an efficient way to provision the
limited available bandwidth for supporting heterogeneous users. The
proposed mechanism is evaluated using simulated tests. The
simulated result reveals that our algorithm can effectively minimize
the bandwidth use and transmission cost
Abstract: The purpose of this study is to identify ideal urban
design elements of waterfronts and to analyze the differences in users-
cognition among these elements. This study follows three steps as
following: first is identifying the urban design elements of waterfronts
from literature review and second is evaluating intended users-
cognition of urban design elements in urban waterfronts. Lastly, third
is analyzing the users- cognition differences. As the result, evaluations
of waterfront areas by users show similar features that non-waterfront
urban design elements contain the highest degree of importance. This
indicates the difference of users- cognition has dimensions of
frequency and distance, and demonstrates differences in the aspect of
importance than of satisfaction. Multi-Dimensional Scaling Method
verifies differences among their cognition. This study provides
elements to increase satisfaction of users from differences of their
cognition on design elements for waterfronts. It also suggests
implications on elements when waterfronts are built.