Abstract: The task of strategic information technology
management is to focus on adapting technology to ensure
competitiveness. A key factor for success in this sector is awareness
and readiness to deploy new technologies and exploit the services
they offer. Recently, the need for more flexible and dynamic user
interfaces (UIs) has been recognized, especially in mobile
applications. An ongoing research project (MOP), initiated by TUT
in Finland, is looking at how mobile device UIs can be adapted for
different needs and contexts. It focuses on examining the possibilities
to develop adapter software for solving the challenges related to the
UI and its flexibility in mobile devices. This approach has great
potential for enhancing information transfer in mobile devices, and
consequently for improving information management. The
technology presented here could be one of the key emerging
technologies in the information technology sector in relation to
mobile devices and telecommunications.
Abstract: Durian husk (DH), a fruit waste, was studied for its ability to remove Basic blue 3 (BB3) from aqueous solutions. Batch kinetic studies were carried out to study the sorption characteristics under various experimental conditions. The optimum pH for the dye removal occurred in the pH range of 3-10. Sorption was found to be concentration and agitation dependent. The kinetics of dye sorption fitted a pseudo-second order rate expression. Both Langmuir and Freundlich models appeared to provide reasonable fittings for the sorption data of BB3 on durian husk. Maximum sorption capacity calculated from the Langmuir model is 49.50 mg g-1.
Abstract: Variable channel conditions in underwater networks,
and variable distances between sensors due to water current, leads to
variable bit error rate (BER). This variability in BER has great
effects on energy efficiency of error correction techniques used. In
this paper an efficient energy adaptive hybrid error correction
technique (AHECT) is proposed. AHECT adaptively changes error
technique from pure retransmission (ARQ) in a low BER case to a
hybrid technique with variable encoding rates (ARQ & FEC) in a
high BER cases. An adaptation algorithm depends on a precalculated
packet acceptance rate (PAR) look-up table, current BER,
packet size and error correction technique used is proposed. Based
on this adaptation algorithm a periodically 3-bit feedback is added to
the acknowledgment packet to state which error correction technique
is suitable for the current channel conditions and distance.
Comparative studies were done between this technique and other
techniques, and the results show that AHECT is more energy
efficient and has high probability of success than all those
techniques.
Abstract: The Iranian bentonite was first characterized by
Scanning Electron Microscopy (SEM), Inductively Coupled Plasma
mass spectrometry (ICP-MS), X-ray fluorescence (XRF), X-ray
Diffraction (XRD) and BET. The bentonite was then treated
thermally between 150°C-250°C at 15min, 45min and 90min and
also was activated chemically with different concentration of
sulphuric acid (3N, 5N and 10N). Although the results of thermal
activated-bentonite didn-t show any considerable changes in specific
surface area and Cation Exchange Capacity (CEC), but the results of
chemical treated bentonite demonstrated that such properties have
been improved by acid activation process.
Abstract: This paper explores the issues that influence online retailing in Saudi Arabia. Retailers in Saudi Arabia have been reserved in their adoption of electronically delivered aspects of their business. Despite the fact that Saudi Arabia has the largest and fastest growth of ICT marketplaces in the Arab region, e-commerce activities are not progressing at the same speed. Only very few Saudi companies, mostly medium and large companies from the manufacturing sector, are involved in e-commerce implementation. Based on qualitative data collected by conducting interviews with 16 retailers and 16 potential customers in Saudi Arabia, several factors influencing online retailing diffusion in Saudi Arabia are identified. However, government support comes the highest and most influencing factor for online retailing growth as identified by both parties; retailers and potential customers in Saudi Arabia.
Abstract: This paper describes the development, modeling, and
testing of skyhook and MiniMax control strategies of semi-active
suspension. The control performances are investigated using
Matlab/Simulink [1], with a two-degree-of-freedom quarter car semiactive
suspension system model. The comparison and evaluation of
control result are made using software-in-the-loop simulation (SILS)
method. This paper also outlines the development of a hardware-inthe-
loop simulation (HILS) system. The simulation results show that
skyhook strategy can significantly reduce the resonant peak of body
and provide improvement in vehicle ride comfort. Otherwise,
MiniMax strategy can be employed to effectively improve drive
safety of vehicle by influencing wheel load. The two strategies can
be switched to control semi-active suspension system to fulfill
different requirement of vehicle in different stages.
Abstract: This paper introduces two decoders for binary linear
codes based on Metaheuristics. The first one uses a genetic algorithm
and the second is based on a combination genetic algorithm with
a feed forward neural network. The decoder based on the genetic
algorithms (DAG) applied to BCH and convolutional codes give good
performances compared to Chase-2 and Viterbi algorithm respectively
and reach the performances of the OSD-3 for some Residue
Quadratic (RQ) codes. This algorithm is less complex for linear
block codes of large block length; furthermore their performances
can be improved by tuning the decoder-s parameters, in particular the
number of individuals by population and the number of generations.
In the second algorithm, the search space, in contrast to DAG which
was limited to the code word space, now covers the whole binary
vector space. It tries to elude a great number of coding operations
by using a neural network. This reduces greatly the complexity of
the decoder while maintaining comparable performances.
Abstract: We apply a particle tracking technique to track the motion of individual pathogenic Leptospira. We observe and capture images of motile Leptospira by means of CCD and darkfield microscope. Image processing, statistical theories and simulations are used for data analysis. Based on trajectory patterns, mean square displacement, and power spectral density characteristics, we found that the motion modes are most likely to be directed motion mode (70%) and the rest are either normal diffusion or unidentified mode. Our findings may support the fact that why leptospires are very well efficient toward targeting internal tissues as a result of increase in virulence factor.
Abstract: A two-dimensional numerical simulation of crossflow
around four cylinders in an in-line rectangular configuration is
studied by using the lattice Boltzmann method (LBM). Special
attention is paid to the effect of the spacing between the cylinders.
The Reynolds number ( Re ) is chosen to be e 100 R = and the
spacing ratio L / D is set at 0.5, 1.5, 2.5, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0
and 10.0. Results show that, as in the case of four cylinders in an inline
rectangular configuration , flow fields show four different
features depending on the spacing (single square cylinder, stable
shielding flow, wiggling shielding flow and a vortex shedding flow)
are observed in this study. The effects of spacing ratio on physical
quantities such as mean drag coefficient, Strouhal number and rootmean-
square value of the drag and lift coefficients are also presented.
There is more than one shedding frequency at small spacing ratios.
The mean drag coefficients for downstream cylinders are less than
that of the single cylinder for all spacing ratios. The present results
using the LBM are compared with some existing experimental data
and numerical studies. The comparison shows that the LBM can
capture the characteristics of the bluff body flow reasonably well and
is a good tool for bluff body flow studies.
Abstract: It has often been said that the strength of any country
resides in the strength of its industrial sector, and Progress in
industrial society has been accomplished by the creation of new
technologies. Developments have been facilitated by the increasing
availability of advanced manufacturing technology (AMT), in
addition the implementation of advanced manufacturing technology
(AMT) requires careful planning at all levels of the organization to
ensure that the implementation will achieve the intended goals.
Justification and implementation of advanced manufacturing
technology (AMT) involves decisions that are crucial for the
practitioners regarding the survival of business in the present days of
uncertain manufacturing world. This paper assists the industrial
managers to consider all the important criteria for success AMT
implementation, when purchasing new technology. Concurrently,
this paper classifies the tangible benefits of a technology that are
evaluated by addressing both cost and time dimensions, and the
intangible benefits are evaluated by addressing technological,
strategic, social and human issues to identify and create awareness of
the essential elements in the AMT implementation process and
identify the necessary actions before implementing AMT.
Abstract: The interactions between input/output variables are a very common phenomenon encountered in the design of multi-loop controllers for interacting multivariable processes, which can be a serious obstacle for achieving a good overall performance of multiloop control system. To overcome this impediment, the decomposed dynamic interaction analysis is proposed by decomposing the multiloop control system into a set of n independent SISO systems with the corresponding effective open-loop transfer function (EOTF) within the dynamic interactions embedded explicitly. For each EOTF, the reduced model is independently formulated by using the proposed reduction design strategy, and then the paired multi-loop proportional-integral-derivative (PID) controller is derived quite simply and straightforwardly by using internal model control (IMC) theory. This design method can easily be implemented for various industrial processes because of its effectiveness. Several case studies are considered to demonstrate the superior of the proposed method.
Abstract: Data mining can be called as a technique to extract
information from data. It is the process of obtaining hidden
information and then turning it into qualified knowledge by statistical
and artificial intelligence technique. One of its application areas is
medical area to form decision support systems for diagnosis just by
inventing meaningful information from given medical data. In this
study a decision support system for diagnosis of illness that make use
of data mining and three different artificial intelligence classifier
algorithms namely Multilayer Perceptron, Naive Bayes Classifier and
J.48. Pima Indian dataset of UCI Machine Learning Repository was
used. This dataset includes urinary and blood test results of 768
patients. These test results consist of 8 different feature vectors.
Obtained classifying results were compared with the previous studies.
The suggestions for future studies were presented.
Abstract: Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.
Abstract: Macrophomina phaseolina is a devastating soil-borne
fungal plant pathogen that causes charcoal rot disease in many
economically important crops worldwide. So far, no registered
fungicide is available against this plant pathogen. This study was
planned to examine the antifungal activity of an allelopathic grass
Cenchrus pennisetiformis (Hochst. & Steud.) Wipff. for the
management of M. phaseolina isolated from cowpea [Vigna
unguiculata (L.) Walp.] plants suffering from charcoal rot disease.
Different parts of the plants viz. inflorescence, shoot and root were
extracted in methanol. Laboratory bioassays were carried out using
different concentrations (0, 0.5, 1.0, …, 3.0 g mL-1) of methanolic
extracts of the test allelopathic grass species to assess the antifungal
activity against the pathogen. In general, extracts of all parts of the
grass exhibited antifungal activity. All the concentrations of
methanolic extracts of shoot and root significantly reduced fungal
biomass by 20–73% and 40–80%, respectively. Methanolic shoot
extract was fractionated using n-hexane, chloroform, ethyl acetate
and n-butanol. Different concentrations of these fractions (3.125,
6.25, …, 200 mg mL-1) were analyzed for their antifungal activity.
All the concentrations of n-hexane fraction significantly reduced
fungal biomass by 15–96% over corresponding control treatments.
Higher concentrations (12.5–200 mg mL-1) of chloroform, ethyl
acetate and n-butanol also reduced the fungal biomass significantly
by 29–100%, 46–100% and 24–100%, respectively.
Abstract: management of medical devices in hospitals includes
the planning of medical equipment acquisition and maintenance. The
presence of critical and non-critical areas together with technological
proliferation render the management of medical devices very
complex. This study creates an easy and objective methodology for
the analysis of medical equipment maintenance, that makes the
management of medical devices more feasible. The study has been
carried out at Florence Hospital Careggi and it aims to help the
clinical engineering department to manage medical equipment by
clarifying the hospital situation through a characterization of the
different areas, technologies and fault typologies.
Abstract: Photo-crosslinked rice starch-based biodegradable
films were prepared by casting film-solution on leveled trays and
ultra violet (UV) irradiation was applied for 10 minute. The effect of
the content (3%, 6% and 9 wt. %)of photosensitiser (sodium
benzoate) on mechanical properties, water vapor permeability (WVP)
and structural properties of rice starch films were investigated. The
tensile strength increased while elongation at break and water
resistance properties of rice starch films decreased with addition and
increasing content of photosensitiser. The % crystallinity of rice
starch films were decreased when the content of photosensitiser
increased and UV were applied. The results showed that the
carboxylate group band of sodium benzoate was found in the FTIR
spectrum of rice starch films and found that incorporation of 6% of
photosensitiser into the films showed a higher absorption band of
resulted films. This result pointed out the highest interaction between
starch molecules was occurred.
Abstract: The gases generated in oil filled transformers can be
used for qualitative determination of incipient faults. The Dissolved
Gas Analysis has been widely used by utilities throughout the world
as the primarily diagnostic tool for transformer maintenance. In this
paper, various Artificial Intelligence Techniques that have been used
by the researchers in the past have been reviewed, some conclusions
have been drawn and a sequential hybrid system has been proposed.
The synergy of ANN and FIS can be a good solution for reliable
results for predicting faults because one should not rely on a single
technology when dealing with real–life applications.
Abstract: Overall cost is a significant consideration in any
decision-making process. Although many studies were carried out on
overall cost in construction, little has treated the uncertainties of real
life cycle development. On the basis of several case studies, a
feedback process was performed on the historical data of studied
buildings. This process enabled to identify some factors causing
uncertainty during the operational period. As a result, the research
proposes a new method for assessing the overall cost during a part of
the building-s life cycle taking account of the building actual value,
its end-of-life value and the influence of the identified life cycle
uncertainty factors. The findings are a step towards a higher level of
reliability in overall cost evaluation taking account of some usually
unexpected uncertainty factors.
Abstract: Wireless sensor networks are consisted of hundreds or
thousands of small sensors that have limited resources.
Energy-efficient techniques are the main issue of wireless sensor
networks. This paper proposes an energy efficient agent-based
framework in wireless sensor networks. We adopt biologically
inspired approaches for wireless sensor networks. Agent operates
automatically with their behavior policies as a gene. Agent aggregates
other agents to reduce communication and gives high priority to nodes
that have enough energy to communicate. Agent behavior policies are
optimized by genetic operation at the base station. Simulation results
show that our proposed framework increases the lifetime of each node.
Each agent selects a next-hop node with neighbor information and
behavior policies. Our proposed framework provides self-healing,
self-configuration, self-optimization properties to sensor nodes.
Abstract: The construction of a civil structure inside a urban
area inevitably modifies the outdoor microclimate at the building
site. Wind speed, wind direction, air pollution, driving rain, radiation
and daylight are some of the main physical aspects that are subjected
to the major changes. The quantitative amount of these modifications
depends on the shape, size and orientation of the building and on its
interaction with the surrounding environment.The flow field over a
flat roof model building has been numerically investigated in order to
determine two-dimensional CFD guidelines for the calculation of the
turbulent flow over a structure immersed in an atmospheric boundary
layer. To this purpose, a complete validation campaign has been
performed through a systematic comparison of numerical simulations
with wind tunnel experimental data.Several turbulence models and
spatial node distributions have been tested for five different vertical
positions, respectively from the upstream leading edge to the
downstream bottom edge of the analyzed model. Flow field
characteristics in the neighborhood of the building model have been
numerically investigated, allowing a quantification of the capabilities
of the CFD code to predict the flow separation and the extension of
the recirculation regions.The proposed calculations have allowed the
development of a preliminary procedure to be used as a guidance in
selecting the appropriate grid configuration and corresponding
turbulence model for the prediction of the flow field over a twodimensional
roof architecture dominated by flow separation.