Abstract: The production of ethyl tert-butyl ether (ETBE) was
simulated through Aspen Plus. The objective of this work was to use
the simulation results to be an alternative platform for ETBE
production from naphtha cracking wastes for the industry to develop.
ETBE is produced from isobutylene which is one of the wastes in
naphtha cracking process. The content of isobutylene in the waste is
less than 30% weight. The main part of this work was to propose a
process to save the environment and to increase the product value by
converting a great majority of the wastes into ETBE. Various
processes were considered to determine the optimal production of
ETBE. The proposed process increased ETBE production yield by
100% from conventional process with the purity of 96% weight. The
results showed a great promise for developing this proposed process
in an industrial scale.
Abstract: This paper describes a novel projection algorithm, the Projection Onto Span Algorithm (POSA) for wavelet-based superresolution and removing speckle (in wavelet domain) of unknown variance from Synthetic Aperture Radar (SAR) images. Although the POSA is good as a new superresolution algorithm for image enhancement, image metrology and biometric identification, here one will use it like a tool of despeckling, being the first time that an algorithm of super-resolution is used for despeckling of SAR images. Specifically, the speckled SAR image is decomposed into wavelet subbands; POSA is applied to the high subbands, and reconstruct a SAR image from the modified detail coefficients. Experimental results demonstrate that the new method compares favorably to several other despeckling methods on test SAR images.
Abstract: Snake bite cases in Malaysia most often involve the
species Naja-naja and Calloselasma rhodostoma. In keeping with the
need for a rapid snake venom detection kit in a clinical setting, plate
and dot-ELISA test for the venoms of Naja-naja sumatrana,
Calloselasma rhodostoma and the cobra venom fraction V antigen
was developed. Polyclonal antibodies were raised and further used to
prepare the reagents for the dot-ELISA test kit which was tested in
mice, rabbit and virtual human models. The newly developed dot-
ELISA kit was able to detect a minimum venom concentration of
244ng/ml with cross reactivity of one antibody type. The dot-ELISA
system was sensitive and specific for all three snake venom types in
all tested animal models. The lowest minimum venom concentration
detectable was in the rabbit model, 244ng/ml of the cobra venom
fraction V antigen. The highest minimum venom concentration was
in mice, 1953ng/ml against a multitude of venoms. The developed
dot-ELISA system for the detection of three snake venom types was
successful with a sensitivity of 95.8% and specificity of 97.9%.
Abstract: The objective of the presented work is to implement the Kalman Filter into an application that reduces the influence of the environmental changes over the robot expected to navigate over a terrain of varying friction properties. The Discrete Kalman Filter is used to estimate the robot position, project the estimated current state ahead at time through time update and adjust the projected estimated state by an actual measurement at that time via the measurement update using the data coming from the infrared sensors, ultrasonic sensors and the visual sensor respectively. The navigation test has been performed in a real world environment and has been found to be robust.
Abstract: The prevalence of non organic constipation differs
from country to country and the reliability of the estimate rates is
uncertain. Moreover, the clinical relevance of subdividing the
heterogeneous functional constipation disorders into pre-defined
subgroups is largely unknown.. Aim: to estimate the prevalence of
constipation in a population-based sample and determine whether
clinical subgroups can be identified. An age and gender stratified
sample population from 5 Italian cities was evaluated using a
previously validated questionnaire. Data mining by cluster analysis
was used to determine constipation subgroups. Results: 1,500
complete interviews were obtained from 2,083 contacted households
(72%). Self-reported constipation correlated poorly with symptombased
constipation found in 496 subjects (33.1%). Cluster analysis
identified four constipation subgroups which correlated to subgroups
identified according to pre-defined symptom criteria. Significant
differences in socio-demographics and lifestyle were observed
among subgroups.
Abstract: TUSAT is a prospective Turkish
Communication Satellite designed for providing mainly data
communication and broadcasting services through Ku-Band
and C-Band channels. Thermal control is a vital issue in
satellite design process. Therefore, all satellite subsystems and
equipments should be maintained in the desired temperature
range from launch to end of maneuvering life. The main
function of the thermal control is to keep the equipments and
the satellite structures in a given temperature range for various
phases and operating modes of spacecraft during its lifetime.
This paper describes the thermal control design which uses
passive and active thermal control concepts. The active
thermal control is based on heaters regulated by software via
thermistors. Alternatively passive thermal control composes of
heat pipes, multilayer insulation (MLI) blankets, radiators,
paints and surface finishes maintaining temperature level of
the overall carrier components within an acceptable value.
Thermal control design is supported by thermal analysis using
thermal mathematical models (TMM).
Abstract: Least Significant Bit (LSB) technique is the earliest
developed technique in watermarking and it is also the most simple,
direct and common technique. It essentially involves embedding the
watermark by replacing the least significant bit of the image data with
a bit of the watermark data. The disadvantage of LSB is that it is not
robust against attacks. In this study intermediate significant bit (ISB)
has been used in order to improve the robustness of the watermarking
system. The aim of this model is to replace the watermarked image
pixels by new pixels that can protect the watermark data against
attacks and at the same time keeping the new pixels very close to the
original pixels in order to protect the quality of watermarked image.
The technique is based on testing the value of the watermark pixel
according to the range of each bit-plane.
Abstract: In the present work, we propose a new technique to
enhance the learning capabilities and reduce the computation
intensity of a competitive learning multi-layered neural network
using the K-means clustering algorithm. The proposed model use
multi-layered network architecture with a back propagation learning
mechanism. The K-means algorithm is first applied to the training
dataset to reduce the amount of samples to be presented to the neural
network, by automatically selecting an optimal set of samples. The
obtained results demonstrate that the proposed technique performs
exceptionally in terms of both accuracy and computation time when
applied to the KDD99 dataset compared to a standard learning
schema that use the full dataset.
Abstract: Decrease in hardware costs and advances in computer
networking technologies have led to increased interest in the use of
large-scale parallel and distributed computing systems. One of the
biggest issues in such systems is the development of effective
techniques/algorithms for the distribution of the processes/load of a
parallel program on multiple hosts to achieve goal(s) such as
minimizing execution time, minimizing communication delays,
maximizing resource utilization and maximizing throughput.
Substantive research using queuing analysis and assuming job
arrivals following a Poisson pattern, have shown that in a multi-host
system the probability of one of the hosts being idle while other host
has multiple jobs queued up can be very high. Such imbalances in
system load suggest that performance can be improved by either
transferring jobs from the currently heavily loaded hosts to the lightly
loaded ones or distributing load evenly/fairly among the hosts .The
algorithms known as load balancing algorithms, helps to achieve the
above said goal(s). These algorithms come into two basic categories -
static and dynamic. Whereas static load balancing algorithms (SLB)
take decisions regarding assignment of tasks to processors based on
the average estimated values of process execution times and
communication delays at compile time, Dynamic load balancing
algorithms (DLB) are adaptive to changing situations and take
decisions at run time.
The objective of this paper work is to identify qualitative
parameters for the comparison of above said algorithms. In future this
work can be extended to develop an experimental environment to
study these Load balancing algorithms based on comparative
parameters quantitatively.
Abstract: The element of justice or al-‘adl in the context of
Islamic critical thinking deals with the notion of justice in a thinking
process which critically rationalizes the truth in a fair and objective
manner with no irrelevant interference that can jeopardize a sound
judgment. This Islamic axiological element is vital in technological
decision making as it addresses the issues of religious values and
ethics that are primarily set to fulfill the purpose of human life on
earth. The main objective of this study was to examine and analyze
the perception of Muslim engineering students in Malaysian higher
education institutions towards the concept of al-‘adl as an essential
element of Islamic critical thinking. The study employed mixed
methods approach that comprises data collection from the
questionnaire survey and the interview responses. A total of 557
Muslim engineering undergraduates from six Malaysian universities
participated in the study. The study generally indicated that Muslim
engineering undergraduates in the higher institutions have rather
good comprehension and consciousness for al-‘adl with a slight
awareness on the importance of objective thinking. Nonetheless there
were a few items on the concept that have implied a comparatively
low perception on the rational justice in Islam as the means to grasp
the ultimate truth.
Abstract: In this paper, a simple active contour based visual
tracking algorithm is presented for outdoor AGV application which is
currently under development at the USM robotic research group
(URRG) lab. The presented algorithm is computationally low cost
and able to track road boundaries in an image sequence and can
easily be implemented on available low cost hardware. The proposed
algorithm used an active shape modeling using the B-spline
deformable template and recursive curve fitting method to track the
current orientation of the road.
Abstract: This paper attempts to explore the phenomenon of metaphorization in English newspaper headlines from the perspective of pragmatic investigation. With relevance theory as the guideline, this paper makes an explanation of the processing of metaphor with a pragmatic approach and points that metaphor is the stimulus adopted by journalists to achieve optimal relevance in this ostensive communication, as well as the strategy to fulfill their writing purpose.
Abstract: In very narrow pathways, the speed of sound propagation and the phase of sound waves change due to the air viscosity. We have developed a new finite element method (FEM) that includes the effects of air viscosity for modeling a narrow sound pathway. This method is developed as an extension of the existing FEM for porous sound-absorbing materials. The numerical calculation results for several three-dimensional slit models using the proposed FEM are validated against existing calculation methods.
Abstract: The knowledge base of welding defect recognition is
essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is
concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set
model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups
of the representative multiple compound defects have been chosen
from the defect library and then classified correctly to form the
decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to
the right quality level. Compared with the ordinary ones, this method
has higher accuracy and better robustness.
Abstract: Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.
Abstract: This work deals with unsupervised image deblurring.
We present a new deblurring procedure on images provided by lowresolution
synthetic aperture radar (SAR) or simply by multimedia in
presence of multiplicative (speckle) or additive noise, respectively.
The method we propose is defined as a two-step process. First, we
use an original technique for noise reduction in wavelet domain.
Then, the learning of a Kohonen self-organizing map (SOM) is
performed directly on the denoised image to take out it the blur. This
technique has been successfully applied to real SAR images, and the
simulation results are presented to demonstrate the effectiveness of
the proposed algorithms.
Abstract: Wind farms (WFs) with high level of penetration are
being established in power systems worldwide more rapidly than
other renewable resources. The Independent System Operator (ISO),
as a policy maker, should propose appropriate places for WF
installation in order to maximize the benefits for the investors. There
is also a possibility of congestion relief using the new installation of
WFs which should be taken into account by the ISO when proposing
the locations for WF installation. In this context, efficient wind farm
(WF) placement method is proposed in order to reduce burdens on
congested lines. Since the wind speed is a random variable and load
forecasts also contain uncertainties, probabilistic approaches are used
for this type of study. AC probabilistic optimal power flow (P-OPF)
is formulated and solved using Monte Carlo Simulations (MCS). In
order to reduce computation time, point estimate methods (PEM) are
introduced as efficient alternative for time-demanding MCS.
Subsequently, WF optimal placement is determined using generation
shift distribution factors (GSDF) considering a new parameter
entitled, wind availability factor (WAF). In order to obtain more
realistic results, N-1 contingency analysis is employed to find the
optimal size of WF, by means of line outage distribution factors
(LODF). The IEEE 30-bus test system is used to show and compare
the accuracy of proposed methodology.
Abstract: Diagnosis can be achieved by building a model of a
certain organ under surveillance and comparing it with the real time
physiological measurements taken from the patient. This paper deals
with the presentation of the benefits of using Data Mining techniques
in the computer-aided diagnosis (CAD), focusing on the cancer
detection, in order to help doctors to make optimal decisions quickly
and accurately. In the field of the noninvasive diagnosis techniques,
the endoscopic ultrasound elastography (EUSE) is a recent elasticity
imaging technique, allowing characterizing the difference between
malignant and benign tumors. Digitalizing and summarizing the main
EUSE sample movies features in a vector form concern with the use
of the exploratory data analysis (EDA). Neural networks are then
trained on the corresponding EUSE sample movies vector input in
such a way that these intelligent systems are able to offer a very
precise and objective diagnosis, discriminating between benign and
malignant tumors. A concrete application of these Data Mining
techniques illustrates the suitability and the reliability of this
methodology in CAD.
Abstract: The need in cognitive radio system for a simple, fast, and independent technique to sense the spectrum occupancy has led to the energy detection approach. Energy detector is known by its dependency on noise variation in the system which is one of its major drawbacks. In this paper, we are aiming to improve its performance by utilizing a weighted collaborative spectrum sensing, it is similar to the collaborative spectrum sensing methods introduced previously in the literature. These weighting methods give more improvement for collaborative spectrum sensing as compared to no weighting case. There is two method proposed in this paper: the first one depends on the channel status between each sensor and the primary user while the second depends on the value of the energy measured in each sensor.
Abstract: Tourism and coastal lines are the business sectors
since centuries especially in the European Nations and Albania is one
such spots. However, in recent decades tourism is experienced as
vulnerability of the surrounding ecological conditions of air, soil,
water, land and the communities that are dependant and sharing the
ecosystem among flora and fauna. Experts opine that apart from the
maintenance of near-originality of ecological biodiversity the tourism
rather known as ecotourism an indigenous socio-cultural
maintenance of indigenous/traditional knowledge of the local people
must be well cared in order to sustain on sustainable grounds. As a
general tendency, growth of tourism has been affected by the deterioration in the economic conditions on one aspect and unsustainable ecological areas affected since human interventions
earlier to this has negative impact on futuristic tourist spots. However, tourism in Albania as of now is 11% of GDP and coastal regions accounting to 2-4%. An amicable Mediterranean
climate with 300 sunny days similar parameters of Greece and Spain
throws up sustainable ecotourism in future decades provided public services namely, transportation, road safety, lodging, food
availability, recreational regiments, banking accessibility are as per
the World Tourism Organizations- protocols. Thus as of Albanian
situation, classification of ecotourism activities to safe-guard the localities with its maintenance of ecological land, water and climate
has become a paramount importance with a wanting and satisfactory options through harnessing human energy for profit and fitness of
ecological flora and fauna. A check on anthropogenic wastes and
their safer utilizations inclusive of agricultural and industrial
operations in line with Lalzi Bay Coastal Line are of utmost importance for the reason that the Adriatic Sea Coast is the one long
stretch of Albanian Lifeline. The present work is based on the methodology of the sustainable management of the same issue.