Abstract: The distressing flood scenarios that occur in
recent years at the surrounding areas of Sarawak River have
left damages of properties and indirectly caused disruptions of
productive activities. This study is meant to reconstruct a 100-year
flood event that took place in this river basin. Sarawak River Subbasin
was chosen and modeled using the one-dimensional
hydrodynamic modeling approach using InfoWorks River Simulation
(RS), in combination with Geographical Information System (GIS).
This produces the hydraulic response of the river and its floodplains
in extreme flooding conditions. With different parameters introduced
to the model, correlations of observed and simulated data are
between 79% – 87%. Using the best calibrated model, flood
mitigation structures are imposed along the sub-basin. Analysis is
done based on the model simulation results. Result shows that the
proposed retention ponds constructed along the sub-basin provide the
most efficient reduction of flood by 34.18%.
Abstract: In this paper, we argue the security protocols of
ZigBee wireless sensor network in MAC layer. AES 128-bit
encryption algorithm in CCM* mode is secure transferred data;
however, AES-s secret key will be break within nearest future.
Efficient public key algorithm, ECC has been mixed with AES to
rescue the ZigBee wireless sensor from cipher text and replay attack.
Also, the proposed protocol can parallelize the integrity function to
increase system performance.
Abstract: Regenerative Thermal Oxidizer (RTO) is one of the
best solutions for removal of Volatile Organic Compounds (VOC)
from industrial processes. In the RTO, VOC in a raw gas are usually
decomposed at 950-1300 K and the combustion heat of VOC is
recovered by regenerative heat exchangers charged with ceramic
honeycombs. The optimization of the treatment of VOC leads to the
reduction of fuel addition to VOC decomposition, the minimization of
CO2 emission and operating cost as well.
In the present work, the thermal efficiency of the RTO was
investigated experimentally in a pilot-scale RTO unit using toluene as
a typical representative of VOC. As a result, it was recognized that the
radiative heat transfer was dominant in the preheating process of a raw
gas when the gas flow rate was relatively low. Further, it was found
that a minimum heat exchanger volume to achieve self combustion of
toluene without additional heating of the RTO by fuel combustion was
dependent on both the flow rate of a raw gas and the concentration of
toluene. The thermal efficiency calculated from fuel consumption and
the decomposed toluene ratio, was found to have a maximum value of
0.95 at a raw gas mass flow rate of 1810 kg·h-1 and honeycombs height
of 1.5m.
Abstract: This paper is a continuation of our interest in the influence of temperature on specific retention volumes and the resulting infinite dilution activity coefficients. This has a direct effect in the design of absorption and stripping columns for the abatement of volatile organic compounds. The interaction of 13 volatile organic compounds (VOCs) with polydimethylsiloxane (PDMS) at varying temperatures was studied by gas liquid chromatography (GLC). Infinite dilution activity coefficients and specific retention volumes obtained in this study were found to be in agreement with those obtained from static headspace and group contribution methods by the authors as well as literature values for similar systems. Temperature variation also allows for transport calculations for different seasons. The results of this work confirm that PDMS is well suited for the scrubbing of VOCs from waste gas streams. Plots of specific retention volumes against temperature gave linear van-t Hoff plots.
Abstract: Mobile devices, which are progressively surrounded
in our everyday life, have created a new paradigm where they
interconnect, interact and collaborate with each other. This network
can be used for flexible and secure coordinated sharing. On the other
hand Grid computing provides dependable, consistent, pervasive, and
inexpensive access to high-end computational capabilities. In this
paper, efforts are made to map the concepts of Grid on Ad-Hoc
networks because both exhibit similar kind of characteristics like
Scalability, Dynamism and Heterogeneity. In this context we
propose “Mobile Ad-Hoc Services Grid – MASGRID".
Abstract: This paper provides the design steps of a robust Linear
Matrix Inequality (LMI) based iterative multivariable PID controller
whose duty is to drive a sample power system that comprises a
synchronous generator connected to a large network via a step-up
transformer and a transmission line. The generator is equipped with
two control-loops, namely, the speed/power (governor) and voltage
(exciter). Both loops are lumped in one where the error in the
terminal voltage and output active power represent the controller
inputs and the generator-exciter voltage and governor-valve position
represent its outputs. Multivariable PID is considered here because of
its wide use in the industry, simple structure and easy
implementation. It is also preferred in plants of higher order that
cannot be reduced to lower ones. To improve its robustness to
variation in the controlled variables, H∞-norm of the system transfer
function is used. To show the effectiveness of the controller, divers
tests, namely, step/tracking in the controlled variables, and variation
in plant parameters, are applied. A comparative study between the
proposed controller and a robust H∞ LMI-based output feedback is
given by its robustness to disturbance rejection. From the simulation
results, the iterative multivariable PID shows superiority.
Abstract: The paper provides a literature review of the STEPNC
compliant research around the world. The first part of this paper
focuses on projects based on STEP compliance followed by research
and development in this area based on machining operations. Review
the literature relating to relevant STEP standards and application in
the area of turning centers. This research will review the various
research work, carried out from the evolution of STEP-NC of the
CNC manufacturing activities. The paper concludes with discussion
of the applications in this particular area.
Abstract: In this paper, a novel method for recognition of musical
instruments in a polyphonic music is presented by using an
embedded hidden Markov model (EHMM). EHMM is a doubly
embedded HMM structure where each state of the external HMM
is an independent HMM. The classification is accomplished for
two different internal HMM structures where GMMs are used as
likelihood estimators for the internal HMMs. The results are compared
to those achieved by an artificial neural network with two
hidden layers. Appropriate classification accuracies were achieved
both for solo instrument performance and instrument combinations
which demonstrates that the new approach outperforms the similar
classification methods by means of the dynamic of the signal.
Abstract: Losses reduction initiatives in distribution systems
have been activated due to the increasing cost of supplying
electricity, the shortage in fuel with ever-increasing cost to produce
more power, and the global warming concerns. These initiatives have
been introduced to the utilities in shape of incentives and penalties.
Recently, the electricity distribution companies in Oman have been
incentivized to reduce the distribution technical and non-technical
losses with an equal annual reduction rate for 6 years. In this paper,
different techniques for losses reduction in Mazoon Electricity
Company (MZEC) are addressed. In this company, high numbers of
substation and feeders were found to be non-compliant with the
Distribution System Security Standard (DSSS). Therefore, 33
projects have been suggested to bring non-complying 29 substations
and 28 feeders to meet the planed criteria and to comply with the
DSSS. The largest part of MZEC-s network (South Batinah region)
was modeled by ETAP software package. The model has been
extended to implement the proposed projects and to examine their
effects on losses reduction. Simulation results have shown that the
implementation of these projects leads to a significant improvement
in voltage profile, and reduction in the active and the reactive power
losses. Finally, the economical analysis has revealed that the
implementation of the proposed projects in MZEC leads to an annual
saving of about US$ 5 million.
Abstract: Many researchers are working on information hiding
techniques using different ideas and areas to hide their secrete data.
This paper introduces a robust technique of hiding secret data in
image based on LSB insertion and RSA encryption technique. The
key of the proposed technique is to encrypt the secret data. Then the
encrypted data will be converted into a bit stream and divided it into
number of segments. However, the cover image will also be divided
into the same number of segments. Each segment of data will be
compared with each segment of image to find the best match
segment, in order to create a new random sequence of segments to be
inserted then in a cover image. Experimental results show that the
proposed technique has a high security level and produced better
stego-image quality.
Abstract: This paper presents an approach for daily optimal operation of distribution networks considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. A genetic algorithm is used to solve the optimal operation problem. The approach is tested on an IEEE34 buses distribution feeder.
Abstract: This paper presents the feasibility study of CO2 sequestration from the sources to the sinks in the prospective of Italian Industries. CO2 produced at these sources captured, compressed to supercritical pressures, transported via pipelines and stored in underground geologic formations such as depleted oil and natural gas reservoirs, un-minable coal seams and deep saline aquifers. In this work, we present the optimized pipeline infrastructure for the CO2 with appropriate constraints to find lower cost system by the use of nonlinear optimization software LINGO 11.0. This study was conducted on CO2 transportation complex network of Italian Industries, to find minimum cost network for transporting the CO2 from sources to the sinks.
Abstract: In this paper, low end Digital Signal Processors (DSPs)
are applied to accelerate integer neural networks. The use of DSPs
to accelerate neural networks has been a topic of study for some
time, and has demonstrated significant performance improvements.
Recently, work has been done on integer only neural networks, which
greatly reduces hardware requirements, and thus allows for cheaper
hardware implementation. DSPs with Arithmetic Logic Units (ALUs)
that support floating or fixed point arithmetic are generally more
expensive than their integer only counterparts due to increased circuit
complexity. However if the need for floating or fixed point math
operation can be removed, then simpler, lower cost DSPs can be
used. To achieve this, an integer only neural network is created in
this paper, which is then accelerated by using DSP instructions to
improve performance.
Abstract: There are increasingly plagiarism offences for
students in higher education in the digital educational world. On the
other hand, various and competitive online assessment and
plagiarism detection tools are available in the market. Taking the
University of Glamorgan as a case study, this paper describes and
introduces an institutional journey on electronic plagiarism detection
to inform the initial experience of an innovative tool and method
which could be further explored in the future research. The
comparative study and system workflow for e-plagiarism detection
tool are discussed. Benefits for both academics and students are also
presented. Electronic plagiarism detection tools brought great
benefits to both academics and students in Glamorgan. On the other
hand, the debates raised in such initial experience are discussed.
Abstract: An Artificial Neural Network based modeling
technique has been used to study the influence of different
combinations of meteorological parameters on evaporation from a
reservoir. The data set used is taken from an earlier reported study.
Several input combination were tried so as to find out the importance
of different input parameters in predicting the evaporation. The
prediction accuracy of Artificial Neural Network has also been
compared with the accuracy of linear regression for predicting
evaporation. The comparison demonstrated superior performance of
Artificial Neural Network over linear regression approach. The
findings of the study also revealed the requirement of all input
parameters considered together, instead of individual parameters
taken one at a time as reported in earlier studies, in predicting the
evaporation. The highest correlation coefficient (0.960) along with
lowest root mean square error (0.865) was obtained with the input
combination of air temperature, wind speed, sunshine hours and
mean relative humidity. A graph between the actual and predicted
values of evaporation suggests that most of the values lie within a
scatter of ±15% with all input parameters. The findings of this study
suggest the usefulness of ANN technique in predicting the
evaporation losses from reservoirs.
Abstract: Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.
Abstract: In this study, a fuzzy-logic based control system was
designed to ensure that time and energy is saved during the operation
of load elevators which are used during the construction of tall
buildings. In the control system that was devised, for the load
elevators to work more efficiently, the energy interval where the
motor worked was taken as the output variable whereas the amount
of load and the building height were taken as input variables. The
most appropriate working intervals depending on the characteristics
of these variables were defined by the help of an expert. Fuzzy expert
system software was formed using Delphi programming language. In
this design, mamdani max-min inference mechanism was used and
the centroid method was employed in the clarification procedure. In
conclusion, it is observed that the system that was designed is
feasible and this is supported by statistical analyses..
Abstract: This work deals with modeling and simulation of SO2 removal in a ceramic membrane by means of FEM. A mass transfer model was developed to predict the performance of SO2 absorption in a chemical solvent. The model was based on solving conservation equations for gas component in the membrane. Computational fluid dynamics (CFD) of mass and momentum were used to solve the model equations. The simulations aimed to obtain the distribution of gas concentration in the absorption process. The effect of the operating parameters on the efficiency of the ceramic membrane was evaluated. The modeling findings showed that the gas phase velocity has significant effect on the removal of gas whereas the liquid phase does not affect the SO2 removal significantly. It is also indicated that the main mass transfer resistance is placed in the membrane and gas phase because of high tortuosity of the ceramic membrane.
Abstract: In this paper, we first consider the quality of service
problems in heterogeneous wireless networks for sending the video
data, which their problem of being real-time is pronounced. At last,
we present a method for ensuring the end-to-end quality of service at
application layer level for adaptable sending of the video data at
heterogeneous wireless networks. To do this, mechanism in different
layers has been used. We have used the stop mechanism, the
adaptation mechanism and the graceful degrade at the application
layer, the multi-level congestion feedback mechanism in the network
layer and connection cutting off decision mechanism in the link
layer. At the end, the presented method and the achieved
improvement is simulated and presented in the NS-2 software.
Abstract: Advancement in Artificial Intelligence has lead to the
developments of various “smart" devices. Character recognition
device is one of such smart devices that acquire partial human
intelligence with the ability to capture and recognize various
characters in different languages. Firstly multiscale neural training
with modifications in the input training vectors is adopted in this
paper to acquire its advantage in training higher resolution character
images. Secondly selective thresholding using minimum distance
technique is proposed to be used to increase the level of accuracy of
character recognition. A simulator program (a GUI) is designed in
such a way that the characters can be located on any spot on the
blank paper in which the characters are written. The results show that
such methods with moderate level of training epochs can produce
accuracies of at least 85% and more for handwritten upper case
English characters and numerals.