Abstract: The Resource-Constrained Project Scheduling
Problem (RCPSP) is concerned with single-item or small batch
production where limited resources have to be allocated to dependent
activities over time. Over the past few decades, a lot of work has
been made with the use of optimal solution procedures for this basic
problem type and its extensions. Brucker and Knust[1] discuss, how
timetabling problems can be modeled as a RCPSP. Authors discuss
high school timetabling and university course timetabling problem as
an example. We have formulated two mathematical formulations of
course timetabling problem in a new way which are the prototype of
single-mode RCPSP. Our focus is to show, how course timetabling
problem can be transformed into RCPSP. We solve this
transformation model with genetic algorithm.
Abstract: The aim of this study was to investigate ammonium
exchange capacity of natural and activated clinoptilolite from
Kwazulu-Natal Province, South Africa. X – ray fluorescence (XRF)
analysis showed that the clinoptilolite contained exchangeable ions
of sodium, potassium, calcium and magnesium. This analysis also
confirmed that the zeolite sample had a high silicon composition
compared to aluminium. Batch equilibrium studies were performed
in an orbital shaker and the data fitted the Langmuir isotherm very
well. The ammonium exchange capacity was found to increase with
pH and temperature. Clinoptilolite functionalization with
hydrochloric acid increased its ammonia uptake ability.
Abstract: Many metrics were proposed to evaluate the
characteristics of the analysis and design model of a given product
which in turn help to assess the quality of the product. Function point
metric is a measure of the 'functionality' delivery by the software.
This paper presents an analysis of a set of programs of a project
developed in Cµ through Function Points metric. Function points
are measured for a Data Flow Diagram (DFD) of the case developed
at initial stage. Lines of Codes (LOCs) and possible errors are
calculated with the help of measured Function Points (FPs). The
calculations are performed using suitable established functions.
Calculated LOCs and errors are compared with actual LOCs and
errors found at the time of analysis & design review, implementation
and testing. It has been observed that actual found errors are more
than calculated errors. On the basis of analysis and observations,
authors conclude that function point provides useful insight and helps
to analyze the drawbacks in the development process.
Abstract: Hospitals in southern Hualien teamed with the
Hypertension Joint Care Network. Working with the network, the
team provided a special designed health education to the individual
who had been identified as a hypertension patient in the outpatient
department. Some metabolism improvements achieved. This is a
retrospective study by purposively taking 106 patients from a hospital
between 2008 and 2010. Records of before and after education
intervention of the objects was collected and analyzed to see the how
the intervention affected the patients- hypertension control via clinical
parameter monitoring. The results showed that the clinical indicators,
the LDL-C, the cholesterol and the systolic blood pressure were
significantly improved. The study provides evidence for the
effectiveness of the network in controlling hypertension.
Abstract: In the modern manufacturing systems, the use of
thermal cutting techniques using oxyfuel, plasma and laser have
become indispensable for the shape forming of high quality complex
components; however, the conventional chip removal production
techniques still have its widespread space in the manufacturing
industry. Both these types of machining operations require the
positioning of end effector tool at the edge where the cutting process
commences. This repositioning of the cutting tool in every machining
operation is repeated several times and is termed as non-productive
time or airtime motion. Minimization of this non-productive
machining time plays an important role in mass production with high
speed machining. As, the tool moves from one region to the other by
rapid movement and visits a meticulous region once in the whole
operation, hence the non-productive time can be minimized by
synchronizing the tool movements. In this work, this problem is
being formulated as a general travelling salesman problem (TSP) and
a genetic algorithm approach has been applied to solve the same. For
improving the efficiency of the algorithm, the GA has been
hybridized with a noble special heuristic and simulating annealing
(SA). In the present work a novel heuristic in the combination of GA
has been developed for synchronization of toolpath movements
during repositioning of the tool. A comparative analysis of new Meta
heuristic techniques with simple genetic algorithm has been
performed. The proposed metaheuristic approach shows better
performance than simple genetic algorithm for minimization of nonproductive
toolpath length. Also, the results obtained with the help of
hybrid simulated annealing genetic algorithm (HSAGA) are also
found better than the results using simple genetic algorithm only.
Abstract: Pharmacology curriculum plays an integral role in
medical education. Learning pharmacology to choose and prescribe
drugs is a major challenge encountered by students. We developed
pharmacology applied learning activities for first year medical
students that included realistic clinical situations with escalating
complications which required the students to analyze the situation
and think critically to choose a safe drug. Tutor feedback was
provided at the end of session. Evaluation was done to assess the
students- level of interest and usefulness of the sessions in rational
selection of drugs. Majority (98 %) of the students agreed that the
session was an extremely useful learning exercise and agreed that
similar sessions would help in rational selection of drugs. Applied
learning sessions in the early years of medical program may promote
deep learning and bridge the gap between pharmacology theory and
clinical practice. Besides, it may also enhance safe prescribing skills.
Abstract: Multidrug resistant organisms have been taunting the
medical world for the last few decades. Even with new antibiotics
developed, resistant strains have emerged soon after. With the
advancement of nanotechnology, we investigated colloidal silver
nanoparticles for its antimicrobial activity against Pseudomonas
aeruginosa. This organism is a multidrug resistant which contributes
to the high morbidity and mortality in immunocompromised patients.
Five multidrug resistant strains were used in this study. The
antimicrobial effect was studied using the disc diffusion and broth
dilution techniques. An inhibition zone of 11 mm was observed with
10 μg dose of the nanoparticles. The nanoparticles exhibited MIC of
50 μg/ml when added at the lag phase and the subinhibitory
concentration was measured as 100 μg/ml. The MIC50 value showed
to be 15 μg/ml. This study suggests that silver nanoparticles can be
further developed as an antimicrobial agent, hence decreasing the
burden of the multidrug resistance phenomena.
Abstract: Computer worm detection is commonly performed by
antivirus software tools that rely on prior explicit knowledge of the
worm-s code (detection based on code signatures). We present an
approach for detection of the presence of computer worms based on
Artificial Neural Networks (ANN) using the computer's behavioral
measures. Identification of significant features, which describe the
activity of a worm within a host, is commonly acquired from security
experts. We suggest acquiring these features by applying feature
selection methods. We compare three different feature selection
techniques for the dimensionality reduction and identification of the
most prominent features to capture efficiently the computer behavior
in the context of worm activity. Additionally, we explore three
different temporal representation techniques for the most prominent
features. In order to evaluate the different techniques, several
computers were infected with five different worms and 323 different
features of the infected computers were measured. We evaluated
each technique by preprocessing the dataset according to each one
and training the ANN model with the preprocessed data. We then
evaluated the ability of the model to detect the presence of a new
computer worm, in particular, during heavy user activity on the
infected computers.
Abstract: The role of the pollen grain, with to the reproductive
process of higher plants, is to deliver the spermatic cells to the
embryo sac for egg fertilization. The aim of this project was study
the effect of electromagnetic fields on structure and pollen grains
development in Chenopodium album. Anthers of Chenopodium
album L. were collected at different stages of development from
control (without electromagnetic field) and plants grown at 10m from
the field sources. Structure and development of pollen grains were
studied and compared. The studying pollen structure by Light and
Scanning electron microscopy showed that electromagnetic fields
reduction of pollen grains number and male sterility, thus , in some
anthers, pollen grains were attached together and deformed compared
to control ones. The data presented suggest that prolonged exposures
of plants to magnetic field may cause different biological effects at
the cellular tissue and organ levels.
Abstract: Sensors possess several properties of physical
measures. Whether devices that convert a sensed signal into an
electrical signal, chemical sensors and biosensors, thus all these
sensors can be considered as an interface between the physical and
electrical equipment. The problem is the analysis of the multitudes of
saved settings as input variables. However, they do not all have the
same level of influence on the outputs. In order to identify the most
sensitive parameters, those that can guide users in gathering
information on the ground and in the process of model calibration
and sensitivity analysis for the effect of each change made.
Mathematical models used for processing become very complex.
In this paper a fuzzy rule-based system is proposed as a solution
for this problem. The system collects the available signals
information from sensors. Moreover, the system allows the study of
the influence of the various factors that take part in the decision
system. Since its inception fuzzy set theory has been regarded as a
formalism suitable to deal with the imprecision intrinsic to many
problems. At the same time, fuzzy sets allow to use symbolic models.
In this study an example was applied for resolving variety of
physiological parameters that define human health state. The
application system was done for medical diagnosis help. The inputs
are the signals expressed the cardiovascular system parameters, blood
pressure, Respiratory system paramsystem was done, it will be able
to predict the state of patient according any input values.
Abstract: The blood ducts must be occluded to avoid loss of
blood from vessels in laparoscopic surgeries. This paper presents a
locking mechanism to be used in a ligation laparoscopic procedure
(LigLAP I), as an alternative solution for a stapling procedure.
Currently, stapling devices are being used to occlude vessels. Using
these devices may result in some problems, including injury of bile
duct, taking up a great deal of space behind the vessel, and bile leak.
In this new procedure, a two-layer suture occludes a vessel. A
locking mechanism is also required to hold the suture. Since there is
a limited space at the device tip, a Shape Memory Alloy (SMA)
actuator is used in this mechanism. Suitability for cleanroom
applications, small size, and silent performance are among the
advantages of SMA actuators in biomedical applications. An
experimental study is conducted to examine the function of the
locking mechanism. To set up the experiment, a prototype of a
locking mechanism is built using nitinol, which is a nickel-titanium
shape memory alloy. The locking mechanism successfully locks a
polymer suture for all runs of the experiment. In addition, the effects
of various surface materials on the applied pulling forces are studied.
Various materials are mounted at the mechanism tip to compare the
maximum pulling forces applied to the suture for each material. The
results show that the various surface materials on the device tip
provide large differences in the applied pulling forces.
Abstract: In this study, a low temperature sensor highly selective to CO in presence of methane is fabricated by using 4 nm SnO2 quantum dots (QDs) prepared by sonication assisted precipitation. SnCl4 aqueous solution was precipitated by ammonia under sonication, which continued for 2 h. A part of the sample was then dried and calcined at 400°C for 1.5 h and characterized by XRD and BET. The average particle size and the specific surface area of the SnO2 QDs as well as their sensing properties were compared with the SnO2 nano-particles which were prepared by conventional sol-gel method. The BET surface area of sonochemically as-prepared product and the one calcined at 400°C after 1.5 hr are 257 m2/gr and 212 m2/gr respectively while the specific surface area for SnO2 nanoparticles prepared by conventional sol-gel method is about 80m2/gr. XRD spectra revealed pure crystalline phase of SnO2 is formed for both as-prepared and calcined samples of SnO2 QDs. However, for the sample prepared by sol-gel method and calcined at 400°C SnO crystals are detected along with those of SnO2. Quantum dots of SnO2 show exceedingly high sensitivity to CO with different concentrations of 100, 300 and 1000 ppm in whole range of temperature (25- 350°C). At 50°C a sensitivity of 27 was obtained for 1000 ppm CO, which increases to a maximum of 147 when the temperature rises to 225°C and then drops off while the maximum sensitivity for the SnO2 sample prepared by the sol-gel method was obtained at 300°C with the amount of 47.2. At the same time no sensitivity to methane is observed in whole range of temperatures for SnO2 QDs. The response and recovery times of the sensor sharply decreases with temperature, while the high selectivity to CO does not deteriorate.
Abstract: Recent years, adaptive pushover methods have been
developed for seismic analysis of structures. Herein, the accuracy of
the displacement-based adaptive pushover (DAP) method, which is
introduced by Antoniou and Pinho [2004], is evaluated for Irregular
buildings. The results are compared to the force-based procedure.
Both concrete and steel frame structures, asymmetric in plan and
elevation are analyzed and also torsional effects are taking into the
account. These analyses are performed using both near fault and far
fault records. In order to verify the results, the Incremental Dynamic
Analysis (IDA) is performed.
Abstract: In this paper, a Smart Home Service Robot, McBot II,
which performs mess-cleanup function etc. in house, is designed much
more optimally than other service robots. It is newly developed in
much more practical system than McBot I which we had developed
two years ago. One characteristic attribute of mobile platforms
equipped with a set of dependent wheels is their omni- directionality
and the ability to realize complex translational and rotational
trajectories for agile navigation in door. An accurate coordination of
steering angle and spinning rate of each wheel is necessary for a
consistent motion. This paper develops trajectory controller of
3-wheels omni-directional mobile robot using fuzzy azimuth estimator.
A specialized anthropomorphic robot manipulator which can be
attached to the housemaid robot McBot II, is developed in this paper.
This built-in type manipulator consists of both arms with 3 DOF
(Degree of Freedom) each and both hands with 3 DOF each. The
robotic arm is optimally designed to satisfy both the minimum
mechanical size and the maximum workspace. Minimum mass and
length are required for the built-in cooperated-arms system. But that
makes the workspace so small. This paper proposes optimal design
method to overcome the problem by using neck joint to move the arms
horizontally forward/backward and waist joint to move them
vertically up/down. The robotic hand, which has two fingers and a
thumb, is also optimally designed in task-based concept. Finally, the
good performance of the developed McBot II is confirmed through
live tests of the mess-cleanup task.
Abstract: Analysis of blood vessel mechanics in normal and
diseased conditions is essential for disease research, medical device
design and treatment planning. In this work, 3D finite element
models of normal vessel and atherosclerotic vessel with 50% plaque
deposition were developed. The developed models were meshed
using finite number of tetrahedral elements. The developed models
were simulated using actual blood pressure signals. Based on the
transient analysis performed on the developed models, the parameters
such as total displacement, strain energy density and entropy per unit
volume were obtained. Further, the obtained parameters were used to
develop artificial neural network models for analyzing normal and
atherosclerotic blood vessels. In this paper, the objectives of the
study, methodology and significant observations are presented.
Abstract: In this paper we used data mining techniques to
identify outlier patients who are using large amount of drugs over a
long period of time. Any healthcare or health insurance system
should deal with the quantities of drugs utilized by chronic diseases
patients. In Kingdom of Bahrain, about 20% of health budget is spent
on medications. For the managers of healthcare systems, there is no
enough information about the ways of drug utilization by chronic
diseases patients, is there any misuse or is there outliers patients. In
this work, which has been done in cooperation with information
department in the Bahrain Defence Force hospital; we select the data
for Cardiac patients in the period starting from 1/1/2008 to
December 31/12/2008 to be the data for the model in this paper. We
used three techniques for finding the drug utilization for cardiac
patients. First we applied a clustering technique, followed by
measuring of clustering validity, and finally we applied a decision
tree as classification algorithm. The clustering results is divided into
three clusters according to the drug utilization, for 1603 patients, who
received 15,806 prescriptions during this period can be partitioned
into three groups, where 23 patients (2.59%) who received 1316
prescriptions (8.32%) are classified to be outliers. The classification
algorithm shows that the use of average drug utilization and the age,
and the gender of the patient can be considered to be the main
predictive factors in the induced model.
Abstract: This paper proposes a method for speckle reduction in
medical ultrasound imaging while preserving the edges with the
added advantages of adaptive noise filtering and speed. A nonlinear
image diffusion method that incorporates local image parameter,
namely, scatterer density in addition to gradient, to weight the
nonlinear diffusion process, is proposed. The method was tested for
the isotropic case with a contrast detail phantom and varieties of
clinical ultrasound images, and then compared to linear and some
other diffusion enhancement methods. Different diffusion parameters
were tested and tuned to best reduce speckle noise and preserve
edges. The method showed superior performance measured both
quantitatively and qualitatively when incorporating scatterer density
into the diffusivity function. The proposed filter can be used as a
preprocessing step for ultrasound image enhancement before
applying automatic segmentation, automatic volumetric calculations,
or 3D ultrasound volume rendering.
Abstract: The incidence of oral cancer in Taiwan increased year
by year. It replaced the nasopharyngeal as the top incurrence among
head and neck cancers since 1994. Early examination and earlier
identification for earlier treatment is the most effective medical
treatment for these cancers. Although the government fully subsidized
the expenses with tremendous promotion program for oral cancer
screening, the citizen-s participation remained low. Purpose of this
study is to understand the factors affecting the citizens- behavior
intensions of taking an oral cancer screening. Based on the Theory of
Planned Behavior, this study adopted four distinctive variables in
explaining the captioned behavior intentions.700 questionnaires were
dispatched with 500 valid responses or 71.4% returned by the citizens
with an age 30 or above from the eastern counties of Taiwan. Test
results has shown that attitude toward, subjective norms of, and
perceived behavioral control over the oral cancer screening varied
from some demographic factors to another. The study proofed that
attitude toward, subjective norms of, and perceived behavioral control
over the oral cancer screening had positive impacts on the
corresponding behavior intention. The test concluded that the theory
of planned behavior was appropriate as a theoretical framework in
explaining the influencing factors of intentions of taking oral cancer
screening. This study suggested the healthcare professional should
provide high accessibility of screening services other than just
delivering knowledge on oral cancer to promote the citizens-
intentions of taking the captioned screening. This research also
provided a practical implication to the healthcare professionals when
formulating and implementing promotion instruments for lifting the
screening rate of oral cancer.
Abstract: Three reactor types were explored and successfully
used for pigment production by Monascus: shake flasks, and shaken
and stirred miniaturized reactors. Also, the use of dielectric
spectroscopy for the on-line measurement of biomass levels was
explored. Shake flasks gave good pigment yields, but scale up is
difficult, and they cannot be automated. Shaken bioreactors were less
successful with pigment production than stirred reactors.
Experiments with different impeller speeds in different volumes of
liquid in the reactor confirmed that this is most likely due oxygen
availability. The availability of oxygen appeared to affect biomass
levels less than pigment production; red pigment production in
particular needed very high oxygen levels. Dielectric spectroscopy
was effectively used to continuously measure biomass levels during
the submerged fungal fermentation in the shaken and stirred
miniaturized bioreactors, despite the presence of the solid substrate
particles. Also, the capacitance signal gave useful information about
the viability of the cells in the culture.
Abstract: Computer networks are essential part in computerbased
information systems. The performance of these networks has a
great influence on the whole information system. Measuring the
usability criteria and customers satisfaction on small computer
network is very important. In this article, an effective approach for
measuring the usability of business network in an information system
is introduced. The usability process for networking provides us with a
flexible and a cost-effective way to assess the usability of a network
and its products. In addition, the proposed approach can be used to
certify network product usability late in the development cycle.
Furthermore, it can be used to help in developing usable interfaces
very early in the cycle and to give a way to measure, track, and
improve usability. Moreover, a new approach for fast information
processing over computer networks is presented. The entire data are
collected together in a long vector and then tested as a one input
pattern. Proposed fast time delay neural networks (FTDNNs) use
cross correlation in the frequency domain between the tested data and
the input weights of neural networks. It is proved mathematically and
practically that the number of computation steps required for the
presented time delay neural networks is less than that needed by
conventional time delay neural networks (CTDNNs). Simulation
results using MATLAB confirm the theoretical computations.