Abstract: Compacted clay liners (CCLs) are the main materials
used in waste disposal landfills due to their low permeability. In this
study, the effect on the shear resistant of clays with inorganic salt
solutions as permeate fluid was experimentally investigated. For this
purpose, NaCl inorganic salt solution at concentrations of 2, 5, 10%
and deionized water were used. Laboratory direct shear and Vane
shear tests were conducted on three compacted clays with low,
medium and high plasticity. Results indicated that the solutions type
and its concentration affect the shear properties of the mixture. In the
light of this study, the influence magnitude of these inorganic salts in
varies concentrations in different clays were determined and more
suitable compacted clay with the compare of plasticity were found.
Abstract: This paper is a survey of current component-based
software technologies and the description of promotion and
inhibition factors in CBSE. The features that software components
inherit are also discussed. Quality Assurance issues in componentbased
software are also catered to. The feat research on the quality
model of component based system starts with the study of what the
components are, CBSE, its development life cycle and the pro &
cons of CBSE. Various attributes are studied and compared keeping
in view the study of various existing models for general systems and
CBS. When illustrating the quality of a software component an apt
set of quality attributes for the description of the system (or
components) should be selected. Finally, the research issues that can
be extended are tabularized.
Abstract: A novel sponge submerged membrane bioreactor
(SSMBR) was developed to effectively remove organics and
nutrients from wastewater. Sponge is introduced within the SSMBR
as a medium for the attached growth of biomass. This paper evaluates
the effects of new and acclimatized sponges for dissolved organic
carbon (DOC) removal from wastewater at different mixed liquor
suspended solids- (MLSS) concentration of the sludge. It was
observed in a series of experimental studies that the acclimatized
sponge performed better than the new sponge whilst the optimum
DOC removal could be achieved at 10g/L of MLSS with the
acclimatized sponge. Moreover, the paper analyses the relationships
between the MLSSsponge/MLSSsludge and the DOC removal efficiency
of SSMBR. The results showed a non-linear relationship between the
biomass parameters of the sponge and the sludge, and the DOC
removal efficiency of SSMBR. A second-order polynomial function
could reasonably represent these relationships.
Abstract: Validation of an automation system is an important issue. The goal is to check if the system under investigation, modeled by a Petri net, never enters the undesired states. Usually, tools dedicated to Petri nets such as DESIGN/CPN are used to make reachability analysis. The biggest problem with this approach is that it is impossible to generate the full occurence graph of the system because it is too large. In this paper, we show how computational methods such as temporal logic model checking and Groebner bases can be used to verify the correctness of the design of an automation system. We report our experimental results with two automation systems: the Automated Guided Vehicle (AGV) system and the traffic light system. Validation of these two systems ranged from 10 to 30 seconds on a PC depending on the optimizing parameters.
Abstract: In this paper we study a system composed by carbon
nanotube (CNT) and bundle of carbon nanotube (BuCNT) interacting
with a specific fatty acid as molecular probe. Full system is
represented by open nanotube (or nanotubes) and the linoleic acid
(LA) relaxing due the interaction with CNT and BuCNT. The LA has
in his form an asymmetric shape with COOH termination provoking
a close BuCNT interaction mainly by van der Waals force field. The
simulations were performed by classical molecular dynamics with
standard parameterizations.
Our results show that these BuCNT and CNT are dynamically
stable and it shows a preferential interaction position with LA
resulting in three features: (i) when the LA is interacting with CNT
and BuCNT (including both termination, CH2 or COOH), the LA is
repelled; (ii) when the LA terminated with CH2 is closer to open
extremity of BuCNT, the LA is also repelled by the interaction
between them; and (iii) when the LA terminated with COOH is
closer to open extremity of BuCNT, the LA is encapsulated by the
BuCNT. These simulations are part of a more extensive work on
searching efficient selective molecular devices and could be useful to
reach this goal.
Abstract: Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.
Abstract: In this paper, we present a novel approach to location
system under indoor environment. The key idea of our work is
accurate distance estimation with cricket-based location system using
A* algorithm. We also use magnetic sensor for detecting obstacles in
indoor environment. Finally, we suggest how this system can be used
in various applications such as asset tracking and monitoring.
Abstract: There is increasing evidence that earthquakes produce electromagnetic signals observable at the surface in the extremely low to very low freqency (ELF - VLF) range often in advance to the main event. These precursors are candidates for prediction purposes. Laboratory experiments con´¼ürm that material under load emits an electromagnetic signature, the detailed generation mechanisms how- ever are not well understood yet.
Abstract: The development of the signal compression
algorithms is having compressive progress. These algorithms are
continuously improved by new tools and aim to reduce, an average,
the number of bits necessary to the signal representation by means of
minimizing the reconstruction error. The following article proposes
the compression of Arabic speech signal by a hybrid method
combining the wavelet transform and the linear prediction. The
adopted approach rests, on one hand, on the original signal
decomposition by ways of analysis filters, which is followed by the
compression stage, and on the other hand, on the application of the
order 5, as well as, the compression signal coefficients. The aim of
this approach is the estimation of the predicted error, which will be
coded and transmitted. The decoding operation is then used to
reconstitute the original signal. Thus, the adequate choice of the
bench of filters is useful to the transform in necessary to increase the
compression rate and induce an impercevable distortion from an
auditive point of view.
Abstract: Rural tourism has many economical, environmental, and socio-cultural benefits. However, the development of rural tourism compared to urban tourism is also faced with several challenges added to the disadvantages of rural tourism. The aim of this study is to design a model of the factors affecting the motivations of rural tourists, in an attempt to improve the understanding of rural tourism motivation for the development of that form of tourism. The proposed model is based on a sound theoretical framework. It was designed following a literature review of tourism motivation theoretical frameworks and of rural tourism motivation factors. The tourism motivation theoretical framework that fitted to the best all rural tourism motivation factors was then chosen as the basis for the proposed model. This study hence found that the push and pull tourism motivation framework and the inner and outer directed values theory are the most adequate theoretical frameworks for the modeling of rural tourism motivation.
Abstract: In this research, we propose to use the discrete cosine
transform to approximate the cumulative distributions of data cube
cells- values. The cosine transform is known to have a good energy
compaction property and thus can approximate data distribution
functions easily with small number of coefficients. The derived
estimator is accurate and easy to update. We perform experiments to
compare its performance with a well-known technique - the (Haar)
wavelet. The experimental results show that the cosine transform
performs much better than the wavelet in estimation accuracy, speed,
space efficiency, and update easiness.
Abstract: Internet today has a huge impact on all aspects of life,
and also in the area of the broader context of democracy, politics and
politicians. If democracy is freedom of choice, there are a number of
conditions that can ensure in practice the freedom to be achieved and
realized. These preconditions must be achieved regardless of the
manner of voting. The key contribution of ICT to achieve freedom of
choice is that technology enables the correlation of the citizens and
elected representatives on the better way than it was possible without
the Internet. In this sense, we can say that the Internet and ICT are
changing significantly, and potentially improving the environment in
which democratic processes are taking place. This paper aims to
describe trends in use of ICT in democratic processes, and analyzes
the challenges for implementation of e-Democracy in Montenegro
Abstract: Natural resources management including water resources requires reliable estimations of time variant environmental parameters. Small improvements in the estimation of environmental parameters would result in grate effects on managing decisions. Noise reduction using wavelet techniques is an effective approach for preprocessing of practical data sets. Predictability enhancement of the river flow time series are assessed using fractal approaches before and after applying wavelet based preprocessing. Time series correlation and persistency, the minimum sufficient length for training the predicting model and the maximum valid length of predictions were also investigated through a fractal assessment.
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: Being creative in an educational environment, such as in the university, has many times been downplayed by bureaucracy, human inadequacy and physical hindrance. These factors control, stifle and subsequently condemn this natural phenomenon which is normally exuded by the tertiary community. If taken in a positive light, creativity has always led to many new discoveries and inventions. These creations are then gradually developed for the university reputation and achievements, in all fields of studies from the sciences to the humanities. This paper attempts to explore, through more than twenty years of observation, issues that stifle the university citizenry – academicians and students- – creativity. It also scrutinizes how enhancement of such creativity can be further supported by bureaucracy simplicity, encouraging and developing human potential and constructing uncompromising physical infrastructure and administrative support. These ideals – all of which can help to promote creativity, increases the productivity of the university community in aspects of teaching, research, publication, innovation and commercialization; be it at national as well as at international arena for the good of human and societal growth and development. This discursive presentation hopes to address another issue on promoting university community creativity through several deliverables which require cooperation from every quarter of the institution so that being creative continues to be promoted for sustainable human capital growth and development of the country, if not, the global community.
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: Web usage mining algorithms have been widely
utilized for modeling user web navigation behavior. In this study we
advance a model for mining of user-s navigation pattern. The model
makes user model based on expectation-maximization (EM)
algorithm.An EM algorithm is used in statistics for finding maximum
likelihood estimates of parameters in probabilistic models, where the
model depends on unobserved latent variables. The experimental
results represent that by decreasing the number of clusters, the log
likelihood converges toward lower values and probability of the
largest cluster will be decreased while the number of the clusters
increases in each treatment.
Abstract: This paper proposes a new decision making approch
based on quantitative possibilistic influence diagrams which are
extension of standard influence diagrams in the possibilistic framework.
We will in particular treat the case where several expert
opinions relative to value nodes are available. An initial expert assigns
confidence degrees to other experts and fixes a similarity threshold
that provided possibility distributions should respect. To illustrate our
approach an evaluation algorithm for these multi-source possibilistic
influence diagrams will also be proposed.
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.