Abstract: The paper focuses on the enhanced stiffness modeling
of robotic manipulators by taking into account influence of the external force/torque acting upon the end point. It implements the
virtual joint technique that describes the compliance of manipulator elements by a set of localized six-dimensional springs separated by
rigid links and perfect joints. In contrast to the conventional
formulation, which is valid for the unloaded mode and small
displacements, the proposed approach implicitly assumes that the loading leads to the non-negligible changes of the manipulator posture and corresponding amendment of the Jacobian. The
developed numerical technique allows computing the static
equilibrium and relevant force/torque reaction of the manipulator for
any given displacement of the end-effector. This enables designer
detecting essentially nonlinear effects in elastic behavior of
manipulator, similar to the buckling of beam elements. It is also proposed the linearization procedure that is based on the inversion of
the dedicated matrix composed of the stiffness parameters of the
virtual springs and the Jacobians/Hessians of the active and passive
joints. The developed technique is illustrated by an application example that deals with the stiffness analysis of a parallel
manipulator of the Orthoglide family
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: Detection of incipient abnormal events is important to
improve safety and reliability of machine operations and reduce losses
caused by failures. Improper set-ups or aligning of parts often leads to
severe problems in many machines. The construction of prediction
models for predicting faulty conditions is quite essential in making
decisions on when to perform machine maintenance. This paper
presents a multivariate calibration monitoring approach based on the
statistical analysis of machine measurement data. The calibration
model is used to predict two faulty conditions from historical reference
data. This approach utilizes genetic algorithms (GA) based variable
selection, and we evaluate the predictive performance of several
prediction methods using real data. The results shows that the
calibration model based on supervised probabilistic principal
component analysis (SPPCA) yielded best performance in this work.
By adopting a proper variable selection scheme in calibration models,
the prediction performance can be improved by excluding
non-informative variables from their model building steps.
Abstract: In this paper, we are interested in attitude control of a satellite, which using wheels of reaction, by state feedback. First, we develop a method allowing us to put the control and its integral in the state-feedback form. Then, by using the theorem of Gronwall- Bellman, we put the sufficient conditions so that the nonlinear system modeling the satellite is stabilisable and observed by state feedback.
Abstract: This article proposes an Ant Colony Optimization
(ACO) metaheuristic to minimize total makespan for scheduling a set
of jobs and assign workers for uniformly related parallel machines.
An algorithm based on ACO has been developed and coded on a
computer program Matlab®, to solve this problem. The paper
explains various steps to apply Ant Colony approach to the problem
of minimizing makespan for the worker assignment & jobs
scheduling problem in a parallel machine model and is aimed at
evaluating the strength of ACO as compared to other conventional
approaches. One data set containing 100 problems (12 Jobs, 03
machines and 10 workers) which is available on internet, has been
taken and solved through this ACO algorithm. The results of our
ACO based algorithm has shown drastically improved results,
especially, in terms of negligible computational effort of CPU, to
reach the optimal solution. In our case, the time taken to solve all 100
problems is even lesser than the average time taken to solve one
problem in the data set by other conventional approaches like GA
algorithm and SPT-A/LMC heuristics.
Abstract: The objective of this paper is to analyze the
performance of a double-sided axial flux permanent magnet
brushless DC (AFPM BLDC) motor with two-phase winding.
To study the motor operation, a mathematical dynamic model
has been proposed for motor, which became the basis for
simulations that were performed using MATLAB/SIMULINK
software package. The results of simulations were presented
in form of the waveforms of selected quantities and the
electromechanical characteristics performed by the motor. The
calculation results show that the two-phase motor version
develops smooth torque and reaches high efficiency. The twophase
motor can be applied where more smooth torque is
required. Finally a study on the influence of switching angle
on motor performance shows that when advance switching
technique is used, the motor operates with the highest
efficiency.
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: Single biometric modality recognition is not able to meet the high performance supplies in most cases with its application become more and more broadly. Multimodal biometrics identification represents an emerging trend recently. This paper investigates a novel algorithm based on fusion of both fingerprint and fingervein biometrics. For both biometric recognition, we employ the Monogenic Local Binary Pattern (MonoLBP). This operator integrate the orginal LBP (Local Binary Pattern ) with both other rotation invariant measures: local phase and local surface type. Experimental results confirm that a weighted sum based proposed fusion achieves excellent identification performances opposite unimodal biometric systems. The AUC of proposed approach based on combining the two modalities has very close to unity (0.93).
Abstract: The Siemens Healthcare Sector is one of the world's
largest suppliers to the healthcare industry and a trendsetter in
medical imaging and therapy, laboratory diagnostics, medical
information technology, and hearing aids.
Siemens offers its customers products and solutions for the entire
range of patient care from a single source – from prevention and
early detection to diagnosis, and on to treatment and aftercare. By
optimizing clinical workflows for the most common diseases,
Siemens also makes healthcare faster, better, and more cost effective.
The optimization of clinical workflows requires a
multidisciplinary focus and a collaborative approach of e.g. medical
advisors, researchers and scientists as well as healthcare economists.
This new form of collaboration brings together experts with deep
technical experience, physicians with specialized medical knowledge
as well as people with comprehensive knowledge about health
economics.
As Charles Darwin is often quoted as saying, “It is neither the
strongest of the species that survive, nor the most intelligent, but the
one most responsive to change," We believe that those who can
successfully manage this change will emerge as winners, with
valuable competitive advantage.
Current medical information and knowledge are some of the core
assets in the healthcare industry. The main issue is to connect
knowledge holders and knowledge recipients from various
disciplines efficiently in order to spread and distribute knowledge.
Abstract: Combined experimental and computational analysis of
hygrothermal performance of an interior thermal insulation system
applied on a brick wall is presented in the paper. In the experimental
part, the functionality of the insulation system is tested at simulated
difference climate conditions using a semi-scale device. The
measured temperature and relative humidity profiles are used for the
calibration of computer code HEMOT that is finally applied for a
long-term hygrothermal analysis of the investigated structure.
Abstract: Human Computer Interaction (HCI) has been an
emerging field that draws in the experts from various fields to
enhance the application of computer programs and the ease of
computer users. HCI has much to do with learning and cognition and
an emerging approach to learning and problem-solving is problembased
learning (PBL). The processes of PBL involve important
cognitive functions in the various stages. This paper will illustrate
how closely related fields to HCI, PBL and cognitive psychology can
benefit from informing each other through analysing various
cognitive functions. Several cognitive functions from cognitive
function disc (CFD) would be presented and discussed in relation to
human-computer interface. This paper concludes with the
implications of bridging the gaps amongst these disciplines.
Abstract: This research’s objective is to select the model with
most accurate value by using Neural Network Technique as a way to
filter potential students who enroll in IT course by Electronic learning
at Suan Suanadha Rajabhat University. It is designed to help students
selecting the appropriate courses by themselves. The result showed
that the most accurate model was 100 Folds Cross-validation which
had 73.58% points of accuracy.
Abstract: Coal will continue to be the predominant source of
global energy for coming several decades. The huge generation of fly
ash (FA) from combustion of coal in thermal power plants (TPPs) is
apprehended to pose the concerns of its disposal and utilization. FA
application based on its typical characteristics as soil ameliorant for
agriculture and forestry is the potential area, and hence the global
attempt. The inferences drawn suffer from the variations of ash
characteristics, soil types, and agro-climatic conditions; thereby
correlating the effects of ash between various plant species and soil
types is difficult. Indian FAs have low bulk density, high water
holding capacity and porosity, rich silt-sized particles, alkaline
nature, negligible solubility, and reasonable plant nutrients. Findings
of the demonstrations trials for more than two decades from lab/pot
to field scale long-term experiments are developed as FA soil
amendment technology (FASAT) by Central Institute of Mining and
Fuel Research (CIMFR), Dhanbad. Performance of different crops
and plant species in cultivable and problematic soils, are
encouraging, eco-friendly, and being adopted by the farmers. FA
application includes ash alone and in combination with
inorganic/organic amendments; combination treatments including
bio-solids perform better than FA alone. Optimum dose being up to
100 t/ha for cultivable land and up to/ or above 200 t/ha of FA for
waste/degraded land/mine refuse, depending on the characteristics of
ash and soil. The elemental toxicity in Indian FA is usually not of
much concern owing to alkaline ashes, oxide forms of elements, and
elemental concentration within the threshold limits for soil
application. Combating toxicity, if any, is possible through
combination treatments with organic materials and phytoremediation.
Government initiatives through extension programme
involving farmers and ash generating organizations need to be
accelerated
Abstract: Fabrication and efficiency enhancement of non-mercury, high efficiency and green field emission lamps using carbon nano-materials such as carbon nanotubes as cathode field emitters was studied. Phosphor was coated on the ITO glass or metal substrates as the anode. The luminescence efficiency enhancement was carried out by upgrading the uniform of the emitters, improving electron and thermal conductivity of the phosphor and the optimization of the design of different cathode/anode configurations. After evaluation of the aforementioned parameters, the luminescence efficiency of the field emission lamps was raised.
Abstract: This paper presents performance comparison of three estimation techniques used for peak load forecasting in power systems. The three optimum estimation techniques are, genetic algorithms (GA), least error squares (LS) and, least absolute value filtering (LAVF). The problem is formulated as an estimation problem. Different forecasting models are considered. Actual recorded data is used to perform the study. The performance of the above three optimal estimation techniques is examined. Advantages of each algorithms are reported and discussed.
Abstract: This paper examines many mathematical methods for
molding the hourly price forward curve (HPFC); the model will be
constructed by numerous regression methods, like polynomial
regression, radial basic function neural networks & a furrier series.
Examination the models goodness of fit will be done by means of
statistical & graphical tools. The criteria for choosing the model will
depend on minimize the Root Mean Squared Error (RMSE), using the
correlation analysis approach for the regression analysis the optimal
model will be distinct, which are robust against model
misspecification. Learning & supervision technique employed to
determine the form of the optimal parameters corresponding to each
measure of overall loss. By using all the numerical methods that
mentioned previously; the explicit expressions for the optimal model
derived and the optimal designs will be implemented.
Abstract: This paper analyses the performance of a genetic algorithm using a new concept, namely a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. The experiments reveal superior results in terms of speed and convergence to achieve a solution.
Abstract: Falls are the primary cause of accidents in people over
the age of 65, and frequently lead to serious injuries. Since the early
detection of falls is an important step to alert and protect the aging
population, a variety of research on detecting falls was carried out
including the use of accelerators, gyroscopes and tilt sensors. In
exiting studies, falls were detected using an accelerometer with
errors. In this study, the proposed method for detecting falls was to
use two accelerometers to reject wrong falls detection. As falls are
accompanied by the acceleration of gravity and rotational motion, the
falls in this study were detected by using the z-axial acceleration
differences between two sites. The falls were detected by calculating
the difference between the analyses of accelerometers placed on two
different positions on the chest of the subject. The parameters of the
maximum difference of accelerations (diff_Z) and the integration of
accelerations in a defined region (Sum_diff_Z) were used to form the
fall detection algorithm. The falls and the activities of daily living
(ADL) could be distinguished by using the proposed parameters
without errors in spite of the impact and the change in the positions
of the accelerometers. By comparing each of the axial accelerations,
the directions of falls and the condition of the subject afterwards
could be determined.In this study, by using two accelerometers
without errors attached to two sites to detect falls, the usefulness of
the proposed fall detection algorithm parameters, diff_Z and
Sum_diff_Z, were confirmed.
Abstract: Jacobs, A.B. (1993) stated that "When I think of a city,
the first thing that comes to mind is the street. If the street is
interesting, the rest of the city is interesting. If the street is mundane,
the city is also mundane." In this statement, he expresses the
importance of the streetscape and the street environment. The
objective of this paper is to analyze the spatial relationships of the
streetscape that affect the general public's preference of the cityscape.
Furthermore, this research focuses on the important role that
streetscape plays in public perception of the city by the pedestrians
who experience it daily. The subject of this paper is eight of the
"Design Seoul Street."The analysis and survey results show the
preference criteria that affect the streetscape and ultimately the
cityscape. This research endeavor shows that differences in physical
form, shape, size, color, locations, and context are important.
Abstract: Solidification cracking and hydrogen cracking are some defects generated in the fusion welding of ultrahigh carbon steels. However, friction stir welding (FSW) of such steels, being a solid-state technique, has been demonstrated to alleviate such problems encountered in traditional welding. FSW include different process parameters that must be carefully defined prior processing. These parameters included but not restricted to: tool feed, tool RPM, tool geometry, tool tilt angle. These parameters form a key factor behind avoiding warm holes and voids behind the tool and in achieving a defect-free weld. More importantly, these parameters directly affect the microstructure of the weld and hence the final mechanical properties of weld. For that, 3D finite element (FE) thermo-mechanical model was developed using DEFORM 3D to simulate FSW of carbon steel. At points of interest in the joint, tracking is done for history of critical state variables such as temperature, stresses, and strain rates. Typical results found include the ability to simulate different weld zones. Simulations predictions were successfully compared to experimental FSW tests. It is believed that such a numerical model can be used to optimize FSW processing parameters to favor desirable defect free weld with better mechanical properties.