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: 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: 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: 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: 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: 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: Ontology is a terminology which is used in artificial
intelligence with different meanings. Ontology researching has an
important role in computer science and practical applications,
especially distributed knowledge systems. In this paper we present an
ontology which is called Computational Object Knowledge Base
Ontology. It has been used in designing some knowledge base
systems for solving problems such as the system that supports
studying knowledge and solving analytic geometry problems, the
program for studying and solving problems in Plane Geometry, the
knowledge system in linear algebra.
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: 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.