Abstract: Human Resource (HR) applications can be used to
provide fair and consistent decisions, and to improve the
effectiveness of decision making processes. Besides that, among
the challenge for HR professionals is to manage organization
talents, especially to ensure the right person for the right job at the
right time. For that reason, in this article, we attempt to describe
the potential to implement one of the talent management tasks i.e.
identifying existing talent by predicting their performance as one of
HR application for talent management. This study suggests the
potential HR system architecture for talent forecasting by using
past experience knowledge known as Knowledge Discovery in
Database (KDD) or Data Mining. This article consists of three
main parts; the first part deals with the overview of HR
applications, the prediction techniques and application, the general
view of Data mining and the basic concept of talent management
in HRM. The second part is to understand the use of Data Mining
technique in order to solve one of the talent management tasks, and
the third part is to propose the potential HR system architecture for
talent forecasting.
Abstract: SIP (Session Initiation Protocol), using HTML based
call control messaging which is quite simple and efficient, is being
replaced for VoIP networks recently. As for authentication and
authorization purposes there are many approaches and considerations
for securing SIP to eliminate forgery on the integrity of SIP
messages. On the other hand Elliptic Curve Cryptography has
significant advantages like smaller key sizes, faster computations on
behalf of other Public Key Cryptography (PKC) systems that obtain
data transmission more secure and efficient. In this work a new
approach is proposed for secure SIP authentication by using a public
key exchange mechanism using ECC. Total execution times and
memory requirements of proposed scheme have been improved in
comparison with non-elliptic approaches by adopting elliptic-based
key exchange mechanism.
Abstract: Wireless Sensor Networks can be used to monitor the
physical phenomenon in such areas where human approach is nearly
impossible. Hence the limited power supply is the major constraint of
the WSNs due to the use of non-rechargeable batteries in sensor
nodes. A lot of researches are going on to reduce the energy
consumption of sensor nodes. Energy map can be used with
clustering, data dissemination and routing techniques to reduce the
power consumption of WSNs. Energy map can also be used to know
which part of the network is going to fail in near future. In this paper,
Energy map is constructed using the prediction based approach.
Adaptive alpha GM(1,1) model is used as the prediction model.
GM(1,1) is being used worldwide in many applications for predicting
future values of time series using some past values due to its high
computational efficiency and accuracy.
Abstract: The main purpose of this paper is to investigate a discrete time three–species food chain system with ratio dependence. By employing coincidence degree theory and analysis techniques, sufficient conditions for existence of periodic solutions are established.
Abstract: In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..
Abstract: Mixed-traffic (e.g., pedestrians, bicycles, and vehicles)
data at an intersection is one of the essential factors for intersection
design and traffic control. However, some data such as pedestrian
volume cannot be directly collected by common detectors (e.g.
inductive loop, sonar and microwave sensors). In this paper, a video
based detection algorithm is proposed for mixed-traffic data collection
at intersections using surveillance cameras. The algorithm is derived
from Gaussian Mixture Model (GMM), and uses a mergence time
adjustment scheme to improve the traditional algorithm. Real-world
video data were selected to test the algorithm. The results show that
the proposed algorithm has the faster processing speed and more
accuracy than the traditional algorithm. This indicates that the
improved algorithm can be applied to detect mixed-traffic at
signalized intersection, even when conflicts occur.
Abstract: Despite extensive study on wireless sensor network
security, defending internal attacks and finding abnormal behaviour
of the sensor are still difficult and unsolved task. The conventional
cryptographic technique does not give the robust security or detection
process to save the network from internal attacker that cause by
abnormal behavior. The insider attacker or abnormally behaved
sensor identificationand location detection framework using false
massage detection and Time difference of Arrival (TDoA) is
presented in this paper. It has been shown that the new framework
can efficiently identify and detect the insider attacker location so that
the attacker can be reprogrammed or subside from the network to
save from internal attack.
Abstract: The paper shows some ability to manage two-phase
flows arising from the use of unsteady effects. In one case, we
consider the condition of fragmentation of the interface between the
two components leads to the intensification of mixing. The problem
is solved when the temporal and linear scale are small for the
appearance of the developed mixing layer. Showing that exist such
conditions for unsteady flow velocity at the surface of the channel,
which will lead to the creation and fragmentation of vortices at Re
numbers of order unity. Also showing that the Re is not a criterion of
similarity for this type of flows, but we can introduce a criterion that
depends on both the Re, and the frequency splitting of the vortices. It
turned out that feature of this situation is that streamlines behave
stable, and if we analyze the behavior of the interface between the
components it satisfies all the properties of unstable flows. The other
problem we consider the behavior of solid impurities in the extensive
system of channels. Simulated unsteady periodic flow modeled
breaths. Consider the behavior of the particles along the trajectories.
It is shown that, depending on the mass and diameter of the particles,
they can be collected in a caustic on the channel walls, stop in a
certain place or fly back. Of interest is the distribution of particle
velocity in frequency. It turned out that by choosing a behavior of the
velocity field of the carrier gas can affect the trajectory of individual
particles including force them to fly back.
Abstract: Service innovations are central concerns in fast
changing environment. Due to the fitness in customer demands and
advances in information technologies (IT) in service management, an
expanded conceptualization of e-service innovation is required.
Specially, innovation practices have become increasingly more
challenging, driving managers to employ a different open innovation
model to maintain competitive advantages. At the same time, firms
need to interact with external and internal customers in innovative
environments, like the open innovation networks, to co-create values.
Based on these issues, an important conceptual framework of e-service
innovation is developed. This paper aims to examine the contributing
factors on e-service innovation and firm performance, including
financial and non-financial aspects. The study concludes by showing
how e-service innovation will play a significant role in growing the
overall values of the firm. The discussion and conclusion will lead to a
stronger understanding of e-service innovation and co-creating values
with customers within open innovation networks.
Abstract: When binary decision diagrams are formed from
uniformly distributed Monte Carlo data for a large number of
variables, the complexity of the decision diagrams exhibits a
predictable relationship to the number of variables and minterms. In
the present work, a neural network model has been used to analyze the
pattern of shortest path length for larger number of Monte Carlo data
points. The neural model shows a strong descriptive power for the
ISCAS benchmark data with an RMS error of 0.102 for the shortest
path length complexity. Therefore, the model can be considered as a
method of predicting path length complexities; this is expected to lead
to minimum time complexity of very large-scale integrated circuitries
and related computer-aided design tools that use binary decision
diagrams.
Abstract: This paper discusses E-government, in particular the
challenges that face adoption in Saudi Arabia. E-government can be
defined based on an existing set of requirements. In this research we
define E-government as a matrix of stakeholders: governments to
governments, governments to business and governments to citizens,
using information and communications technology to deliver and
consume services. E-government has been implemented for a
considerable time in developed countries. However, E-government
services still face many challenges in their implementation and
general adoption in many countries including Saudi Arabia. It has
been noted that the introduction of E-government is a major
challenge facing the government of Saudi Arabia, due to possible
concerns raised by its citizens. In addition, the literature review and
the discussion identify the influential factors that affect the citizens’
intention to adopt E-government services in Saudi Arabia.
Consequently, these factors have been defined and categorized
followed by an exploratory study to examine the importance of these
factors. Therefore, this research has identified factors that determine
if the citizen will adopt E-government services and thereby aiding
governments in accessing what is required to increase adoption.
Abstract: This paper discusses the causal explanation capability
of QRIOM, a tool aimed at supporting learning of organic chemistry
reactions. The development of the tool is based on the hybrid use of
Qualitative Reasoning (QR) technique and Qualitative Process
Theory (QPT) ontology. Our simulation combines symbolic,
qualitative description of relations with quantity analysis to generate
causal graphs. The pedagogy embedded in the simulator is to both
simulate and explain organic reactions. Qualitative reasoning through
a causal chain will be presented to explain the overall changes made
on the substrate; from initial substrate until the production of final
outputs. Several uses of the QPT modeling constructs in supporting
behavioral and causal explanation during run-time will also be
demonstrated. Explaining organic reactions through causal graph
trace can help improve the reasoning ability of learners in that their
conceptual understanding of the subject is nurtured.
Abstract: In this paper, algorithm estimating the blood pressure
was proposed using the pulse transit time (PTT) as a more convenient
method of measuring the blood pressure. After measuring ECG and
pressure pulse, and photoplethysmography, the PTT was calculated
from the acquired signals. Thereafter, the system to indirectly measure
the systolic pressure and the diastolic pressure was composed using
the statistic method. In comparison between the blood pressure
indirectly measured by proposed algorithm estimating the blood
pressure and real blood pressure measured by conventional
sphygmomanometer, the systolic pressure indicates the mean error of
±3.24mmHg and the standard deviation of 2.53mmHg, while the
diastolic pressure indicates the satisfactory result, that is, the mean
error of ±1.80mmHg and the standard deviation of 1.39mmHg. These
results are satisfied with the regulation of ANSI/AAMI for
certification of sphygmomanometer that real measurement error value
should be within the mean error of ±5mmHg and the standard
deviation of 8mmHg. These results are suggest the possibility of
applying to portable and long time blood pressure monitoring system
hereafter.
Abstract: From food consumption surveys has been found that potato consumption comparing to other European countries is one of the highest. Hence acrylamide (AA) intake coming from fried potatoes in population might be high as well. The aim of the research was to determine acrylamide content and estimate intake of acrylamide from roasted potatoes bred and cultivated in Latvia. Five common Latvian potato varieties were selected: Lenora, Brasla, Imanta, Zile, and Madara. A two-year research was conducted during two periods: just after harvesting and after six months of storage. Time and temperature (210 ± 5°C) was recorded during frying. AA was extracted from potatoes by solid phase extraction and AA content was determined by LC-MS/MS. estimated intake of acrylamide ranges from 0.012 to 0.496μgkg-1 BW per day.
Abstract: The use of neural networks is popular in various
building applications such as prediction of heating load, ventilation
rate and indoor temperature. Significant is, that only few papers deal
with indoor carbon dioxide (CO2) prediction which is a very good
indicator of indoor air quality (IAQ). In this study, a data-driven
modelling method based on multilayer perceptron network for indoor
air carbon dioxide in an apartment building is developed.
Temperature and humidity measurements are used as input variables
to the network. Motivation for this study derives from the following
issues. First, measuring carbon dioxide is expensive and sensors
power consumptions is high and secondly, this leads to short
operating times of battery-powered sensors. The results show that
predicting CO2 concentration based on relative humidity and
temperature measurements, is difficult. Therefore, more additional
information is needed.
Abstract: The problem of frequent itemset mining is considered in this paper. One new technique proposed to generate frequent patterns in large databases without time-consuming candidate generation. This technique is based on focusing on transaction instead of concentrating on itemset. This algorithm based on take intersection between one transaction and others transaction and the maximum shared items between transactions computed instead of creating itemset and computing their frequency. With applying real life transactions and some consumption is taken from real life data, the significant efficiency acquire from databases in generation association rules mining.
Abstract: Nowadays, quick technological changes force companies
to develop innovative products in an increasingly competitive
environment. Therefore, how to enhance the time of new product
development is very important. This design problem often lacks
the exact formula for getting it, and highly depends upon human
designers- past experiences. For these reasons, in this work, a Casebased
reasoning (CBR) system to assist in new product development
is proposed. When a case is recovered from the case base, the system
will take into account not only the attribute-s specific value and
how important it is. It will also take into account if the attribute
has a positive influence over the product development. Hence the
manufacturing time will be improved. This information will be
introduced as a new concept called “adaptability". An application to
this method for hearing instrument new design illustrates the proposed
approach.
Abstract: To comply with the international human right
legislation concerning the freedom of movement, transport systems
are required to be made accessible in order that all citizens, regardless
of their physical condition, have equal possibilities to use them. In
Hungary, apparently there is a considerable default in the
improvement of accessible public transport. This study is aiming to
overview the current Hungarian situation and to reveal the reasons of
the deficiency. The result shows that in spite of the relatively
favourable juridical background linked to the accessibility needs and
to the rights of persons with disabilities there is a strong delay in
putting all in practice in the field of public transport. Its main reason
is the lack of financial resource and referring to this the lack of
creating mandatory regulations. In addition to this the proprietary
rights related to public transport are also variable, which also limits
the improvement possibilities. Consequently, first of all an accurate
and detailed regulatory procedure is expected to change the present
unfavourable situation and to create the conditions of the fast
realization, which is already behind time.
Abstract: Optical flow is a research topic of interest for many
years. It has, until recently, been largely inapplicable to real-time
applications due to its computationally expensive nature. This paper
presents a new reliable flow technique which is combined with a
motion detection algorithm, from stationary camera image streams,
to allow flow-based analyses of moving entities, such as rigidity, in
real-time. The combination of the optical flow analysis with motion
detection technique greatly reduces the expensive computation of
flow vectors as compared with standard approaches, rendering the
method to be applicable in real-time implementation. This paper
describes also the hardware implementation of a proposed pipelined
system to estimate the flow vectors from image sequences in real
time. This design can process 768 x 576 images at a very high frame
rate that reaches to 156 fps in a single low cost FPGA chip, which is
adequate for most real-time vision applications.
Abstract: The frequency dependence of the phase field
model(PFM) is studied. A simple PFM is proposed, and is tested in a
laminar boundary layer. The Blasius-s laminar boundary layer
solution on a flat plate is used for the flow pattern, and several
frequencies are imposed on the PFM, and the decay times of the
interfaces are obtained. The computations were conducted for three
cases: 1) no-flow, and 2) a half ball on the laminar boundary layer, 3) a
line of mass sources in the laminar boundary layer. The computations
show the decay time becomes shorter as the frequency goes larger, and
also show that it is sensitive to both background disturbances and
surface tension parameters. It is concluded that the proposed simple
PFM can describe the properties of decay process, and could give the
fundamentals for the decay of the interface in turbulent flows.