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: 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model is used to predict two faulty conditions from historical reference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: Cooperative communication scheme can be substituted
for multiple-input multiple-output (MIMO) technique when it may
not be able to support multiple antennas due to size, cost or
hardware limitations. In other words, cooperative communication
scheme is an efficient method to achieve spatial diversity without
multiple antennas. For satisfaction of rising QoS, we propose a
reliable cooperative communication scheme with M-QAM based Dual
Carrier Modulation (M-DCM), which can increase diversity gain.
Although our proposed scheme is very simple method, it gives us
frequency and spatial diversity. Simulation result shows our proposed
scheme obtains diversity gain more than the conventional cooperative
communication scheme.
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: In this paper, novel techniques in increasing the accuracy
and speed of convergence of a Feed forward Back propagation
Artificial Neural Network (FFBPNN) with polynomial activation
function reported in literature is presented. These technique was
subsequently used to determine the coefficients of Autoregressive
Moving Average (ARMA) and Autoregressive (AR) system. The
results obtained by introducing sequential and batch method of weight
initialization, batch method of weight and coefficient update, adaptive
momentum and learning rate technique gives more accurate result
and significant reduction in convergence time when compared t the
traditional method of back propagation algorithm, thereby making
FFBPNN an appropriate technique for online ARMA coefficient
determination.
Abstract: Water has always been a very precious resource.
However, many of us do not fully understand or appreciate water-s
value until there will be a shortage. We intended to analyze the water
consumption into the Spanish households to understand their
behavior according to the habitants of the house. In this research was
carried out a survey of users, asking for water consumption of their
households. The aim of this paper is get a reference value of
consumers in Spanish households to help to check their bill and
realize if their consumption is excessive, including some tips to
decrease it.
Abstract: Modeling of Panel Zone (PZ) seismic behavior,
because of its role in overall ductility and lateral stiffness of steel
moment frames, has been considered a challenge for years. There are
some studies regarding the effects of different doubler plates
thicknesses and geometric properties of PZ on its seismic behavior.
However, there is not much investigation on the effects of number of
provided continuity plates in case of presence of one triangular
haunch, two triangular haunches and rectangular haunch (T shape
haunches) for exterior columns. In this research first detailed finite
element models of 12tested connection of SAC joint venture were
created and analyzed then obtained cyclic behavior backbone curves
of these models besides other FE models for similar tests were used
for neural network training. Then seismic behavior of these data is
categorized according to continuity plate-s arrangements and
differences in type of haunches. PZ with one-sided haunches have
little plastic rotation. As the number of continuity plates increases
due to presence of two triangular haunches (four continuity plate),
there will be no plastic rotation, in other words PZ behaves in its
elastic range. In the case of rectangular haunch, PZ show more plastic
rotation in comparison with one-sided triangular haunch and
especially double-sided triangular haunches. Moreover, the models
that will be presented in case of triangular one-sided and double-
sided haunches and rectangular haunches as a result of this study
seem to have a proper estimation of PZ seismic behavior.
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: 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: 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: The structural stability of the model of a nonelectroneutral current sheath is investigated. The stationary model of a current sheath represents the system of four connected nonlinear differential first-order equations and thus they should manifest structural instability property, i.e. sensitivity to the infinitesimal changes of parameters and starting conditions. Domains of existence of the solutions of current sheath type are found. Those solutions of the current sheath type are realized only in some regions of sevendimensional space of parameters of the problem. The phase volume of those regions is small in comparison with the whole phase volume of the definition range of those parameters. It is shown that the offered model of a nonelectroneutral current sheath is applicable for theoretical interpretation of the bifurcational current sheaths observed in the magnetosphere.
Abstract: It is sometimes difficult to differentiate between
innocent murmurs and pathological murmurs during auscultation. In
these difficult cases, an intelligent stethoscope with decision support
abilities would be of great value. In this study, using a dog model,
phonocardiographic recordings were obtained from 27 boxer dogs
with various degrees of aortic stenosis (AS) severity. As a reference
for severity assessment, continuous wave Doppler was used. The data
were analyzed with recurrence quantification analysis (RQA) with
the aim to find features able to distinguish innocent murmurs from
murmurs caused by AS. Four out of eight investigated RQA features
showed significant differences between innocent murmurs and
pathological murmurs. Using a plain linear discriminant analysis
classifier, the best pair of features (recurrence rate and entropy)
resulted in a sensitivity of 90% and a specificity of 88%. In
conclusion, RQA provide valid features which can be used for
differentiation between innocent murmurs and murmurs caused by
AS.
Abstract: An experiment was implemented in a filed in the south of Morocco to evaluate the effects of domestic treated wastewater use for irrigation of amaranth crop under semi-arid conditions. Three varieties (A0020, A0057 & A211) were tested and irrigated using domestic treated wastewater EC1 (0,92 dS/m) as control, EC3 (3dS/m) and EC6 (6dS/m) obtained by adding sea water. In term of growth, an increase of the EC level of applied irrigation water reduced significantly the plant-s height, leaf area, fresh and dry weight measured at vegetative, flowering and maturity stage for all varieties. Even with the application of the EC6, yields were relatively higher in comparison with the once obtained in normal cultivation conditions. A significant accumulation of nitrate, chloride and sodium in soil layers during the crop cycle was noted. The use of treated waste water for its irrigation is proved to be possible. The variety A211 had showed to be less sensitive to salinity stress and it could be more promising its introduction to study area.
Abstract: In this paper, an authentication system using keystroke dynamics is presented. We introduced pressure sensing for the improvement of the accuracy of measurement and durability against intrusion using key-logger, and so on, however additional instrument is needed. As the result, it has been found that the pressure sensing is also effective for estimation of real moment of keystroke.
Abstract: Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.