Abstract: Graduate attributes have received increasing attention
over recent years as universities incorporate these attributes into the
curriculum. Graduates who have adequate technical knowledge only
are not sufficiently equipped to compete effectively in the work
place; they also need non disciplinary skills ie, graduate attributes.
The purpose of this paper is to investigate the impact of an eportfolio
in a technical communication course to enhance engineering
students- graduate attributes: namely, learning of communication,
critical thinking and problem solving and teamwork skills. Two
questionnaires were used to elicit information from the students: one
on their preferred and the other on the actual learning process. In
addition, student perceptions of the use of eportfolio as a learning
tool were investigated. Preliminary findings showed that most of the
students- expectations have been met with their actual learning. This
indicated that eportfolio has the potential as a tool to enhance
students- graduate attributes.
Abstract: The environmental factors such as temperature and
relative humidity are very contribute to the effect of comfort, health,
performance and worker productivity. To ensure an ergonomics work
environment, it is possible to require a specific attention especially in
industries. The aim of this study is to show the effect of temperature
and relative humidity on worker productivity in automotive industry
by taking a workstation in an automotive plant as the location to
conduct the study. From the analysis of the data, there were
relationship between temperature and relative humidity on worker
productivity. Mathematical equation to represent the relationship
between temperatures and relative humidity on the production rate is
modelled. From the equation model, the production rate for the
workstation can be predicted base on the value of temperature and
relative humidity.
Abstract: The usual method of river flow diversion involves construction of tunnels and cofferdams. Given the fact that the cost of diversion works could be as high as 10-20% of the total dam construction cost, due attention should be paid to optimum design of the diversion works. The cost of diversion works depends, on factors, such as: the tunnel dimensions and the intended tunneling support measures during and after excavation; quality and characterizes of the rock through which the tunnel should be excavated; the dimensions of the upstream (and downstream) cofferdams; and the magnitude of river flood the system is designed to divert. In this paper by use of the cost of unit prices for tunnel excavation, tunnel lining, tunnel support (rock bolt + shotcrete) and cofferdam fill the cost function was determined. The function is then minimized by the aid of PSO Algorithm (particle swarm optimization). It is found that the optimum diameter and the total diversion cost are directly related to the river flood discharge (Q). It has also shown that in addition to optimum diameter design discharge (Q), river length, tunnel length, is mainly a function of the ratios (not the absolute values) of the unit prices and does not depend on the overall price levels in the respective country. The results of optimization use in some of the case study lead us to significant changes in the cost.
Abstract: Social, mobility and information aggregation inside
business environment need to converge to reach the next step of
collaboration to enhance interaction and innovation. The following
article is based on the “Assemblage" concept seen as a framework to
formalize new user interfaces and applications. The area of research
is the Energy Social Business Environment, especially the Energy
Smart Grids, which are considered as functional and technical
foundations of the revolution of the Energy Sector of tomorrow. The
assemblages are modelized by means of mereology and simplicial
complexes. Its objective is to offer new central attention and
decision-making tools to end-users.
Abstract: The study concerns an experimental investigation in
the laboratory of the water erosion using a rainfall simulator. We
have focused our attention on the influence of rainfall intensity on
some hydraulic characteristics. The results obtained allow us to
conclude that there is a significant correlation between rainfall
intensity and hydraulic characteristics of runoff (Reynolds number,
Froude number) and sediment concentration.
Abstract: This paper deals with automatic sentence modality
recognition in French. In this work, only prosodic features are
considered. The sentences are recognized according to the three
following modalities: declarative, interrogative and exclamatory
sentences. This information will be used to animate a talking head for
deaf and hearing-impaired children. We first statistically study a real
radio corpus in order to assess the feasibility of the automatic
modeling of sentence types. Then, we test two sets of prosodic
features as well as two different classifiers and their combination. We
further focus our attention on questions recognition, as this modality
is certainly the most important one for the target application.
Abstract: Distributed Power generation has gained a lot of
attention in recent times due to constraints associated with
conventional power generation and new advancements in DG
technologies .The need to operate the power system economically
and with optimum levels of reliability has further led to an increase
in interest in Distributed Generation. However it is important to place
Distributed Generator on an optimum location so that the purpose of
loss minimization and voltage regulation is dully served on the
feeder. This paper investigates the impact of DG units installation on
electric losses, reliability and voltage profile of distribution networks.
In this paper, our aim would be to find optimal distributed
generation allocation for loss reduction subjected to constraint of
voltage regulation in distribution network. The system is further
analyzed for increased levels of Reliability. Distributed Generator
offers the additional advantage of increase in reliability levels as
suggested by the improvements in various reliability indices such as
SAIDI, CAIDI and AENS. Comparative studies are performed and
related results are addressed. An analytical technique is used in order
to find the optimal location of Distributed Generator. The suggested
technique is programmed under MATLAB software. The results
clearly indicate that DG can reduce the electrical line loss while
simultaneously improving the reliability of the system.
Abstract: Natural gas is the most popular fossil fuel in the
current era and future as well. Natural gas is existed in underground
reservoirs so it may contain many of non-hydrocarbon components
for instance, hydrogen sulfide, nitrogen and water vapor. These
impurities are undesirable compounds and cause several technical
problems for example, corrosion and environment pollution.
Therefore, these impurities should be reduce or removed from natural
gas stream. Khurmala dome is located in southwest Erbil-Kurdistan
region. The Kurdistan region government has paid great attention for
this dome to provide the fuel for Kurdistan region. However, the
Khurmala associated natural gas is currently flaring at the field.
Moreover, nowadays there is a plan to recover and trade this gas and
to use it either as feedstock to power station or to sell it in global
market. However, the laboratory analysis has showed that the
Khurmala sour gas has huge quantities of H2S about (5.3%) and CO2
about (4.4%). Indeed, Khurmala gas sweetening process has been
removed in previous study by using Aspen HYSYS. However,
Khurmala sweet gas still contents some quintets of water about 23
ppm in sweet gas stream. This amount of water should be removed or
reduced. Indeed, water content in natural gas cause several technical
problems such as hydrates and corrosion. Therefore, this study aims
to simulate the prospective Khurmala gas dehydration process by
using Aspen HYSYS V. 7.3 program. Moreover, the simulation
process succeeded in reducing the water content to less than 0.1ppm.
In addition, the simulation work is also achieved process
optimization by using several desiccant types for example, TEG and
DEG and it also study the relationship between absorbents type and
its circulation rate with HCs losses from glycol regenerator tower.
Abstract: Feature and model selection are in the center of
attention of many researches because of their impact on classifiers-
performance. Both selections are usually performed separately but
recent developments suggest using a combined GA-SVM approach to
perform them simultaneously. This approach improves the
performance of the classifier identifying the best subset of variables
and the optimal parameters- values. Although GA-SVM is an
effective method it is computationally expensive, thus a rough
method can be considered. The paper investigates a joined approach
of Genetic Algorithm and kernel matrix criteria to perform
simultaneously feature and model selection for SVM classification
problem. The purpose of this research is to improve the classification
performance of SVM through an efficient approach, the Kernel
Matrix Genetic Algorithm method (KMGA).
Abstract: The production of activated carbon from low or zero cost of agricultural by-products or wastes has received great attention from academics and practitioners due to its economic and environmental benefits. In the production of bamboo furniture, a significant amount of bamboo waste is inevitably generated. Therefore, this research aimed to prepare activated carbons from bamboo furniture waste by chemical (KOH) activation and determine their properties and adsorption capacities for water treatment. The influence of carbonization time on the properties and adsorption capacities of activated carbons was also investigated. The finding showed that the bamboo-derived activated carbons had microporous characteristics. They exhibited high tendency for the reduction of impurities present in effluent water. Their adsorption capacities were comparable to the adsorption capacity of a commercial activated carbon regarding to the reduction in COD, TDS and turbidity of the effluent water.
Abstract: Unlike this study focused extensively on trading
behavior of option market, those researches were just taken their
attention to model-driven option pricing. For example, Black-Scholes
(B-S) model is one of the most famous option pricing models.
However, the arguments of B-S model are previously mentioned by
some pricing models reviewing. This paper following suggests the
importance of the dynamic character for option pricing, which is also
the reason why using the genetic algorithm (GA). Because of its
natural selection and species evolution, this study proposed a hybrid
model, the Genetic-BS model which combining GA and B-S to
estimate the price more accurate. As for the final experiments, the
result shows that the output estimated price with lower MAE value
than the calculated price by either B-S model or its enhanced one,
Gram-Charlier garch (G-C garch) model. Finally, this work would
conclude that the Genetic-BS pricing model is exactly practical.
Abstract: Operational risk has become one of the most discussed topics in the financial industry in the recent years. The reasons for this attention can be attributed to higher investments in information systems and technology, the increasing wave of mergers and acquisitions and emergence of new financial instruments. In addition, the New Basel Capital Accord (known as Basel II) demands a capital requirement for operational risk and further motivates financial institutions to more precisely measure and manage this type of risk. The aim of this paper is to shed light on main characteristics of operational risk management and common applied methods: scenario analysis, key risk indicators, risk control self assessment and loss distribution approach.
Abstract: ORC (Organic Rankine Cycle) has potential of
reducing consumption of fossil fuels and has many favorable
characteristics to exploit low-temperature heat sources. In this work
thermodynamic performance of ORC with regeneration is
comparatively assessed for various working fluids. Special attention is
paid to the effects of system parameters such as the turbine inlet
pressure on the characteristics of the system such as net work
production, heat input, volumetric flow rate per 1 MW of net work and
quality of the working fluid at turbine exit as well as thermal
efficiency. Results show that for a given source the thermal efficiency
generally increases with increasing of the turbine inlet pressure
however has optimal condition for working fluids of low critical
pressure such as iso-pentane or n-pentane.
Abstract: Nanomaterials have attracted considerable attention
during the last two decades, due to their unusual electrical, mechanical
and other physical properties as compared with their bulky
counterparts. The mechanical properties of nanostructured materials
show strong size dependency, which has been explained within the
framework of continuum mechanics by including the effects of surface
stress. The size-dependent deformations of two-dimensional
nanosized structures with surface effects are investigated in the paper
by the finite element method. Truss element is used to evaluate the
contribution of surface stress to the total potential energy and the
Gurtin and Murdoch surface stress model is implemented with
ANSYS through its user programmable features. The proposed
approach is used to investigate size-dependent stress concentration
around a nanosized circular hole and the size-dependent effective
moduli of nanoporous materials. Numerical results are compared with
available analytical results to validate the proposed modeling
approach.
Abstract: Intuitionistic fuzzy sets as proposed by Atanassov,
have gained much attention from past and latter researchers for
applications in various fields. Similarity measures between
intuitionistic fuzzy sets were developed afterwards. However, it does
not cater the conflicting behavior of each element evaluated. We
therefore made some modification to the similarity measure of IFS
by considering conflicting concept to the model. In this paper, we
concentrate on Zhang and Fu-s similarity measures for IFSs and
some examples are given to validate these similarity measures. A
simple modification to Zhang and Fu-s similarity measures of IFSs
was proposed to find the best result according to the use of degree of
indeterminacy. Finally, we mark up with the application to real
decision making problems.
Abstract: PPG is a potential tool in clinical applications. Among such, the relationship between respiration and PPG signal has attracted attention in past decades. In this research, a bivariate AR spectral estimation method was utilized for the coherence analysis between these two signals. Ten healthy subjects participated in this research with signals measured at different respiratory rates. The results demonstrate that high coherence exists between respiration and PPG signal, whereas the coherence disappears in breath-holding experiments. These results imply that PPG signal reveals the respiratory information. The utilized method may provide an attractive alternative approach for the related researches.
Abstract: The migration-environment nexus has gained increased interest from the social research field over the last years. While straightly connected to human security issues, this theme has pervaded through the media to the public sphere. Therefore, it is important to observe how did the discussions over environmentally induced migrations develop from the scientific basis to the media attention, passing through some political voices, and in which ways might these messages be interpreted within the broader public discourses. To achieve this purpose, the analysis of the press entries between 2004 and 2010 in three of the main Portuguese newspapers shall be presented, specially reflecting upon the events, protagonists, topics, geographical attributions and terms/expressions used to define those who migrate due to environmental degradation or disasters.
Abstract: This study discusses the effect of uncertainty on
production levels of a petrochemical complex. Uncertainly or
variations in some model parameters, such as prices, supply and
demand of materials, can affect the optimality or the efficiency of any
chemical process. For any petrochemical complex with many plants,
there are many sources of uncertainty and frequent variations which
require more attention. Many optimization approaches are proposed
in the literature to incorporate uncertainty within the model in order
to obtain a robust solution. In this work, a stability analysis approach
is applied to a deterministic LP model of a petrochemical complex
consists of ten plants to investigate the effect of such variations on
the obtained optimal production levels. The proposed approach can
determinate the allowable variation ranges of some parameters,
mainly objective or RHS coefficients, before the system lose its
optimality. Parameters with relatively narrow range of variations, i.e.
stability limits, are classified as sensitive parameters or constraints
that need accurate estimate or intensive monitoring. These stability
limits offer easy-to-use information to the decision maker and help in
understanding the interaction between some model parameters and
deciding when the system need to be re-optimize. The study shows
that maximum production of ethylene and the prices of intermediate
products are the most sensitive factors that affect the stability of the
optimum solution
Abstract: Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.
Abstract: Bionanotechnology deals with nanoscopic interactions between nanostructured materials and biological systems. Polymer nanocomposites with optimized biological activity have attracted great attention. Nanoclay is considered as reinforcing nanofiller in manufacturing of high performance nanocomposites. In current study, organomodified-nanoclay with negatively charged silicate layers was incorporated into biomedical grade silicone rubber. Nanoparticle loading has been tailored to enhance cell behavior. Addition of nanoparticles led to improved mechanical properties of substrate with enhanced strength and stiffness while no toxic effects was observed. Results indicated improved viability and proliferation of cells by addition of nanofillers. The improved mechanical properties of the matrix result in proper cell response through adjustment and arrangement of cytoskeletal fibers. Results can be applied in tissue engineering when enhanced substrates are required for improvement of cell behavior for in vivo applications.