Abstract: Even it has been recognized that Shape Memory
Alloys (SMA) have a significant potential for deployment actuators,
the number of applications of SMA-based actuators to the present
day is still quite small, due to the need of deep understanding of the
thermo-mechanical behavior of SMA, causing an important need for
a mathematical model able to describe all thermo-mechanical
properties of SMA by relatively simple final set of constitutive
equations. SMAs offer attractive potentials such as: reversible strains
of several percent, generation of high recovery stresses and high
power / weight ratios. The paper tries to provide an overview of the
shape memory functions and a presentation of the designed and
developed temperature control system used for a gripper actuated by
two pairs of differential SMA active springs. An experimental setup
was established, using electrical energy for actuator-s springs heating
process. As for holding the temperature of the SMA springs at certain
level for a long time was developed a control system in order to
avoid the active elements overheating.
Abstract: The main objective of this paper is to provide an efficient tool for delineating brain tumors in three-dimensional magnetic resonance images and set up compression-transmit schemes to distribute result to the remote doctor. To achieve this goal, we use basically a level-sets approach to delineating brain tumors in threedimensional. Then introduce a new compression and transmission plan of 3D brain structures based for the meshes simplification, adapted for time to the specific needs of the telemedicine and to the capacities restricted by wireless network communication. We present here the main stages of our system, and preliminary results which are very encouraging for clinical practice.
Abstract: Because of the global warming and the rising sea level, residents living in southwestern coastland, Taiwan are faced with the submerged land and may move to higher elevation area. It is desirable to discuss the key consideration factor for selecting the migration location under five dimensions of ಯ security”, “health”, “convenience”, “comfort” and “socio-economic” based on the document reviews. This paper uses the Structural Equation Modeling (SEM) and the questionnaire survey. The analysis results show that the convenience is the most key factor for residents in Taiwan.
Abstract: Almost all Libyan industries (both private and public) have struggled with many difficulties during the past three decades due to many problems. These problems have created a strongly negative impact on the productivity and utilization of many companies within Libya. This paper studies the current awareness and implementation levels of Just-In-Time (JIT) within the Libyan Textile private industry. A survey has been applied in this study using an intensive detailed questionnaire. Based on the analysis of the survey responses, the results show that the management body within the surveyed companies has a modest strategy towards most of the areas that are considered as being very crucial in any successful implementation of JIT. The results also show a variation within the implementation levels of the JIT elements as these varies between Low and Acceptable levels. The paper has also identified limitations within the investigated areas within this industry, and has pointed to areas where senior managers within the Libyan textile industry should take immediate actions in order to achieve effective implementation of JIT within their companies.
Abstract: The paper considers the effect of feed plate location
on the interactions in a seven plate binary distillation column. The
mathematical model of the distillation column is deduced based on
the equations of mass and energy balances for each stage, detailed
model for both reboiler and condenser, and heat transfer equations.
The Dynamic Relative Magnitude Criterion, DRMC is used to assess
the interactions in different feed plate locations for a seven plate
(Benzene-Toluene) binary distillation column ( the feed plate is
originally at stage 4). The results show that whenever we go far from
the optimum feed plate position, the level of interaction augments.
Abstract: Food borne illnesses have been reported to be a global
health challenge. Annual incidences of food–related diseases involve
76 million cases, of which only 14 million can be traced to known
pathogens. Poor hygienic practices have contributed greatly to this. It
has been reported that in the year 2000 about 2.1 million people died
from diarrheal diseases, hence, there is a need to ensure food safety at
all level. This study focused on the sterility examination and
inhibitory effect of honey samples on selected gram negative and
gram positive food borne pathogen from South West Nigeria. The
laboratory examinations revealed the presence of some bacterial and
fungal contaminations of honey samples and that inhibitory activity
of the honey sample was more pronounced on the gram negative
bacteria than the gram positive bacterial isolates. Antibiotic
sensitivity test conducted on the different bacterial isolates also
showed that honey was able to inhibit the proliferation of the tested
bacteria than the employed antibiotics.
Abstract: We proposed a technique to identify road traffic
congestion levels from velocity of mobile sensors with high accuracy
and consistent with motorists- judgments. The data collection utilized
a GPS device, a webcam, and an opinion survey. Human perceptions
were used to rate the traffic congestion levels into three levels: light,
heavy, and jam. Then the ratings and velocity were fed into a
decision tree learning model (J48). We successfully extracted vehicle
movement patterns to feed into the learning model using a sliding
windows technique. The parameters capturing the vehicle moving
patterns and the windows size were heuristically optimized. The
model achieved accuracy as high as 99.68%. By implementing the
model on the existing traffic report systems, the reports will cover
comprehensive areas. The proposed method can be applied to any
parts of the world.
Abstract: Quality control charts are very effective in detecting
out of control signals but when a control chart signals an out of
control condition of the process mean, searching for a special cause
in the vicinity of the signal time would not always lead to prompt
identification of the source(s) of the out of control condition as the
change point in the process parameter(s) is usually different from the
signal time. It is very important to manufacturer to determine at what
point and which parameters in the past caused the signal. Early
warning of process change would expedite the search for the special
causes and enhance quality at lower cost. In this paper the quality
variables under investigation are assumed to follow a multivariate
normal distribution with known means and variance-covariance
matrix and the process means after one step change remain at the new
level until the special cause is being identified and removed, also it is
supposed that only one variable could be changed at the same time.
This research applies artificial neural network (ANN) to identify the
time the change occurred and the parameter which caused the change
or shift. The performance of the approach was assessed through a
computer simulation experiment. The results show that neural
network performs effectively and equally well for the whole shift
magnitude which has been considered.
Abstract: Clean air in subway station is important to passengers. The Platform Screen Doors (PSDs) can improve indoor air quality in the subway station; however the air quality in the subway tunnel is degraded. The subway tunnel has high CO2 concentration and indoor particulate matter (PM) value. The Indoor Air Quality (IAQ) level in subway environment degrades by increasing the frequency of the train operation and the number of the train. The ventilation systems of the subway tunnel need improvements to have better air-quality. Numerical analyses might be effective tools to analyze the performance of subway twin-track tunnel ventilation systems. An existing subway twin-track tunnel in the metropolitan Seoul subway system is chosen for the numerical simulations. The ANSYS CFX software is used for unsteady computations of the airflow inside the twin-track tunnel when the train moves. The airflow inside the tunnel is simulated when one train runs and two trains run at the same time in the tunnel. The piston-effect inside the tunnel is analyzed when all shafts function as the natural ventilation shaft. The supplied air through the shafts is mixed with the pollutant air in the tunnel. The pollutant air is exhausted by the mechanical ventilation shafts. The supplied and discharged airs are balanced when only one train runs in the twin-track tunnel. The pollutant air in the tunnel is high when two trains run simultaneously in opposite direction and all shafts functioned as the natural shaft cases when there are no electrical power supplies in the shafts. The remained pollutant air inside the tunnel enters into the station platform when the doors are opened.
Abstract: Airport capacity has always been perceived in the
traditional sense as the number of aircraft operations during a
specified time corresponding to a tolerable level of average delay and
it mostly depends on the airside characteristics, on the fleet mix
variability and on the ATM. The adoption of the Directive
2002/30/EC in the EU countries drives the stakeholders to conceive
airport capacity in a different way though. Airport capacity in this
sense is fundamentally driven by environmental criteria, and since
acoustical externalities represent the most important factors, those are
the ones that could pose a serious threat to the growth of airports and
to aviation market itself in the short-medium term. The importance of
the regional airports in the deregulated market grew fast during the
last decade since they represent spokes for network carriers and a
preferential destination for low-fares carriers. Not only regional
airports have witnessed a fast and unexpected growth in traffic but
also a fast growth in the complaints for the nuisance by the people
living near those airports. In this paper the results of a study
conducted in cooperation with the airport of Bologna G. Marconi are
presented in order to investigate airport acoustical capacity as a defacto
constraint of airport growth.
Abstract: Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.
Abstract: The paradigm of mobile agent provides a promising technology for the development of distributed and open applications. However, one of the main obstacles to widespread adoption of the mobile agent paradigm seems to be security. This paper treats the security of the mobile agent against malicious host attacks. It describes generic mobile agent protection architecture. The proposed approach is based on the dynamic adaptability and adopts the reflexivity as a model of conception and implantation. In order to protect it against behaviour analysis attempts, the suggested approach supplies the mobile agent with a flexibility faculty allowing it to present an unexpected behaviour. Furthermore, some classical protective mechanisms are used to reinforce the level of security.
Abstract: In this paper, to optimize the “Characteristic Straight Line Method" which is used in the soil displacement analysis, a “best estimate" of the geodetic leveling observations has been achieved by taking in account the concept of 'Height systems'. This concept has been discussed in detail and consequently the concept of “height". In landslides dynamic analysis, the soil is considered as a mosaic of rigid blocks. The soil displacement has been monitored and analyzed by using the “Characteristic Straight Line Method". Its characteristic components have been defined constructed from a “best estimate" of the topometric observations. In the measurement of elevation differences, we have used the most modern leveling equipment available. Observational procedures have also been designed to provide the most effective method to acquire data. In addition systematic errors which cannot be sufficiently controlled by instrumentation or observational techniques are minimized by applying appropriate corrections to the observed data: the level collimation correction minimizes the error caused by nonhorizontality of the leveling instrument's line of sight for unequal sight lengths, the refraction correction is modeled to minimize the refraction error caused by temperature (density) variation of air strata, the rod temperature correction accounts for variation in the length of the leveling rod' s Invar/LO-VAR® strip which results from temperature changes, the rod scale correction ensures a uniform scale which conforms to the international length standard and the introduction of the concept of the 'Height systems' where all types of height (orthometric, dynamic, normal, gravity correction, and equipotential surface) have been investigated. The “Characteristic Straight Line Method" is slightly more convenient than the “Characteristic Circle Method". It permits to evaluate a displacement of very small magnitude even when the displacement is of an infinitesimal quantity. The inclination of the landslide is given by the inverse of the distance reference point O to the “Characteristic Straight Line". Its direction is given by the bearing of the normal directed from point O to the Characteristic Straight Line (Fig..6). A “best estimate" of the topometric observations was used to measure the elevation of points carefully selected, before and after the deformation. Gross errors have been eliminated by statistical analyses and by comparing the heights within local neighborhoods. The results of a test using an area where very interesting land surface deformation occurs are reported. Monitoring with different options and qualitative comparison of results based on a sufficient number of check points are presented.
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: This paper presents a useful sub-pixel image
registration method using line segments and a sub-pixel edge detector.
In this approach, straight line segments are first extracted from gray
images at the pixel level before applying the sub-pixel edge detector.
Next, all sub-pixel line edges are mapped onto the orientation-distance
parameter space to solve for line correspondence between images.
Finally, the registration parameters with sub-pixel accuracy are
analytically solved via two linear least-square problems. The present
approach can be applied to various fields where fast registration with
sub-pixel accuracy is required. To illustrate, the present approach is
applied to the inspection of printed circuits on a flat panel. Numerical
example shows that the present approach is effective and accurate
when target images contain a sufficient number of line segments,
which is true in many industrial problems.
Abstract: Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Abstract: Moisture is an important consideration in many
aspects ranging from irrigation, soil chemistry, golf course, corrosion
and erosion, road conditions, weather predictions, livestock feed
moisture levels, water seepage etc. Vegetation and crops always
depend more on the moisture available at the root level than on
precipitation occurrence. In this paper, design of an instrument is
discussed which tells about the variation in the moisture contents of
soil. This is done by measuring the amount of water content in soil by
finding the variation in capacitance of soil with the help of a
capacitive sensor. The greatest advantage of soil moisture sensor is
reduced water consumption. The sensor is also be used to set lower
and upper threshold to maintain optimum soil moisture saturation and
minimize water wilting, contributes to deeper plant root growth
,reduced soil run off /leaching and less favorable condition for insects
and fungal diseases. Capacitance method is preferred because, it
provides absolute amount of water content and also measures water
content at any depth.
Abstract: Recently, Cassava has been the driving force of many
developing countries- economic progress. To attain this level,
prerequisites were put in place enabling cassava sector to become an
industrial and a highly competitive crop. Cameroon can achieve the
same results. Moreover, it can upgrade the living conditions of both
rural and urban dwellers and stimulate the development of the whole
economy. Achieving this outcome calls for agricultural policy
reforms. The adoption and implementation of adequate policies go
along with efficient strategies. To choose effective strategies, an indepth
investigation of the sector-s problems is highly recommended.
This paper uses gap analysis method to evaluate cassava sector in
Cameroon. It studies the present situation (where it is now),
interrogates the future (where it should be) and finally proposes
solutions to fill the gap.
Abstract: Failure in mastery of motor skills proficiency during
childhood has been seen as a detrimental factor for children to be
physically active. Lack of motor skills proficiency tends to reduce
children’s competency and confidence level to participate in physical
activity. As a consequence of less participation in physical activity,
children will turn to be overweight and obese. It has been suggested
that children who master motor skill proficiency will be more
involved in physical activity thus preventing them from being
overweight. Obesity has become a serious childhood health issues
worldwide. Previous studies have found that children who were
overweight and obese were generally less active however these
studies focused on one gender. This study aims to compare motor
skill proficiency of underweight, normal-weight, overweight and
obese young boys as well as to determine the relationship between
motor skills proficiency and body composition. 112 boys aged
between 8 to 10 years old participated in this study. Participants were
assigned to four groups; underweight, normal-weight, overweight and
obese using BMI-age percentile chart for children. Bruininks-
Oseretsky Test Second Edition-Short Form was administered to
assess their motor skill proficiency. Meanwhile, body composition
was determined by the skinfold thickness measurement. Result
indicated that underweight and normal children were superior in
motor skills proficiency compared to overweight and obese children
(p < 0.05). A significant strong inverse correlation between motor
skills proficiency and body composition (r = -0.849) is noted. The
findings of this study could be explained by non-contributory mass
that carried by overweight and obese children leads to biomechanical
movement inefficiency which will become detrimental to motor skills
proficiency. It can be concluded that motor skills proficiency is
inversely correlated with body composition.
Abstract: Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.