Abstract: Intelligent Video-Surveillance (IVS) systems are
being more and more popular in security applications. The analysis
and recognition of abnormal behaviours in a video sequence has
gradually drawn the attention in the field of IVS, since it allows
filtering out a large number of useless information, which guarantees
the high efficiency in the security protection, and save a lot of human
and material resources. We present in this paper ADABeV, an
intelligent video-surveillance framework for event recognition in
crowded scene to detect the abnormal human behaviour. This
framework is attended to be able to achieve real-time alarming,
reducing the lags in traditional monitoring systems. This architecture
proposal addresses four main challenges: behaviour understanding in
crowded scenes, hard lighting conditions, multiple input kinds of
sensors and contextual-based adaptability to recognize the active
context of the scene.
Abstract: A time-domain numerical model within the
framework of transmission line modeling (TLM) is developed to
simulate electromagnetic pulse propagation inside multiple
microcavities forming photonic crystal (PhC) structures. The model
developed is quite general and is capable of simulating complex
electromagnetic problems accurately. The field quantities can be
mapped onto a passive electrical circuit equivalent what ensures that
TLM is provably stable and conservative at a local level.
Furthermore, the circuit representation allows a high level of
hybridization of TLM with other techniques and lumped circuit
models of components and devices. A photonic crystal structure
formed by rods (or blocks) of high-permittivity dieletric material
embedded in a low-dielectric background medium is simulated as an
example. The model developed gives vital spatio-temporal
information about the signal, and also gives spectral information over
a wide frequency range in a single run. The model has wide
applications in microwave communication systems, optical
waveguides and electromagnetic materials simulations.
Abstract: Estimation time and cost of work completion in a
project and follow up them during execution are contributors to
success or fail of a project, and is very important for project
management team. Delivering on time and within budgeted cost
needs to well managing and controlling the projects. To dealing with
complex task of controlling and modifying the baseline project
schedule during execution, earned value management systems have
been set up and widely used to measure and communicate the real
physical progress of a project. But it often fails to predict the total
duration of the project. In this paper data mining techniques is used
predicting the total project duration in term of Time Estimate At
Completion-EAC (t). For this purpose, we have used a project with
90 activities, it has updated day by day. Then, it is used regular
indexes in literature and applied Earned Duration Method to
calculate time estimate at completion and set these as input data for
prediction and specifying the major parameters among them using
Clem software. By using data mining, the effective parameters on
EAC and the relationship between them could be extracted and it is
very useful to manage a project with minimum delay risks. As we
state, this could be a simple, safe and applicable method in prediction
the completion time of a project during execution.
Abstract: In this paper, we study the oscillation of a class of second-order nonlinear neutral damped variable delay dynamic equations on time scales. By using a generalized Riccati transformation technique, we obtain some sufficient conditions for the oscillation of the equations. The results of this paper improve and extend some known results. We also illustrate our main results with some examples.
Abstract: Sustainable development is one of the most debated
issues, recently. In terms of providing more livable Earth continuity,
while Production activities are going on, on the other hand protecting
the environment has importance. As a strategy for sustainable
development, eco-innovation is the application of innovations to
reduce environmental burdens. Endeavors to understand ecoinnovation
processes have been affected from environmental
economics and innovation economics from neoclassical economics,
and evolutionary economics other than neoclassical economics. In
the light of case study analyses, this study aims to display activities
in this field through case studies after explaining the theoretical
framework of eco-innovations. This study consists of five sections
including introduction and conclusion. In the second part of the study
identifications of the concepts related with eco-innovation are
described and eco-innovations are classified. Third section considers
neoclassical and evolutionary approaches from neoclassical
economics and evolutionary economics, respectively. Fourth section
gives the case studies of successful eco-innovations. Last section is
the conclusion part and offers suggestions for future eco-innovation
research according to the theoretical framework and the case studies.
Abstract: In this paper, we propose a new algorithm for joint time-delay and direction-of-arrival (DOA) estimation, here called two-dimensional code acquisition, in an asynchronous directsequence code-division multiple-access (DS-CDMA) array system. This algorithm depends on eigenvector-eigenvalue decomposition of sample correlation matrix, and requires to know desired user-s training sequence. The performance of the algorithm is analyzed both analytically and numerically in uncorrelated and coherent multipath environment. Numerical examples show that the algorithm is robust with unknown number of coherent signals.
Abstract: For stricter drinking water regulations in the future, reducing the humic acid and disinfection byproducts in raw water, namely, trihalomethanes (THMs) and haloacetic acids (HAAs) is worthy for research. To investigate the removal of waterborne organic material using a lab-scale of bio-activated carbon filter under different EBCT, the concentrations of humic acid prepared were 0.01, 0.03, 0.06, 0.12, 0.17, 0.23, and 0.29 mg/L. Then we conducted experiments using a pilot plant with in-field of the serially connected bio-activated carbon filters and hollow fiber membrane processes employed in traditional water purification plants. Results showed under low TOC conditions of humic acid in influent (0.69 to 1.03 mg TOC/L) with an EBCT of 30 min, 40 min, and 50 min, TOC removal rates increases with greater EBCT, attaining about 39 % removal rate. The removal rate of THMs and HAAs by BACF was 54.8 % and 89.0 %, respectively.
Abstract: Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.
Abstract: Segmentation and quantification of stenosis is an
important task in assessing coronary artery disease. One of the main
challenges is measuring the real diameter of curved vessels.
Moreover, uncertainty in segmentation of different tissues in the
narrow vessel is an important issue that affects accuracy. This paper
proposes an algorithm to extract coronary arteries and measure the
degree of stenosis. Markovian fuzzy clustering method is applied to
model uncertainty arises from partial volume effect problem. The
algorithm employs: segmentation, centreline extraction, estimation of
orthogonal plane to centreline, measurement of the degree of
stenosis. To evaluate the accuracy and reproducibility, the approach
has been applied to a vascular phantom and the results are compared
with real diameter. The results of 10 patient datasets have been
visually judged by a qualified radiologist. The results reveal the
superiority of the proposed method compared to the Conventional
thresholding Method (CTM) on both datasets.
Abstract: This study examines the relationships between foreign
aid, levels of schooling and democracy for Pakistan using the ARDL
cointegration approach. The results of study provide strong evidence
for fairly robust long run as well as short run relationships among
these variables for the period 1973-2008. The results state that
foreign aid and primary school enrollments have negative impact on
democracy index and high school enrollments have positive impact
on democracy index in Pakistan. The study suggests for promotion of
education levels and relies on local resources instead of foreign aid
for a good quality of political institutions in Pakistan.
Abstract: An attempt was made for availability of wastewater reuse/reclamation for irrigation purposes using phytoremediation “the low cost and less technology", using six local aquatic macrophytes “e.g. T. angustifolia, B. maritimus, Ph. australis, A. donax, A. plantago-aquatica and M. longifolia (Linn)" as biological waste purifiers. Outdoor experiments/designs were conducted from May 03, 2007 till October 15, 2008, close to one of the main sewage channels of Sulaimani City/Iraq*. All processes were mainly based on conventional wastewater treatment processes, besides two further modifications were tested, the first was sand filtration pots, implanted by individual species of experimental macrophytes and the second was constructed wetlands implanted by experimental macrophytes all together. Untreated and treated wastewater samples were analyzed for their key physico-chemical properties (only heavy metals Fe, Mn, Zn and Cu with particular reference to removal efficiency by experimental macrophytes are highlighted in this paper). On the other hand, vertical contents of heavy metals were also evaluated from both pots and the cells of constructed wetland. After 135 days, macrophytes were harvested and heavy metals were analyzed in their biomass (roots/shoots) for removal efficiency assessment (i.e. uptake/ bioaccumulation rate). Results showed that; removal efficiency of all studied heavy metals was much higher in T. angustifolia followed by Ph. Australis, B. maritimus and A. donax in triple experiment sand pots. Constructed wetland experiments have revealed that; the more replicated constructed wetland cells the highest heavy metal removal efficiency was indicated.
Abstract: Quality evaluation of an image is an important task in image processing applications. In case of image compression, quality of decompressed image is also the criterion for evaluation of given coding scheme. In the process of compression -decompression various artifacts such as blocking artifacts, blur artifact, ringing or edge artifact are observed. However quantification of these artifacts is a difficult task. We propose here novel method to quantify blur and ringing artifact in an image.
Abstract: Higher education institutions are increasingly opting to outsourcing methods in order to sustain themselves and this creates a gap of literature in terms of how they perceive the relationship. This research paper attempts to identify the behavioral and psychological factors that exist in the engagement thus providing valuable information to practicing and potential clients, and vendors. The determinants were gathered from previous literatures and analyzed to formulate the factors. This study adopts the case study and survey approaches in which interviews and questionnaires are deployed on employees of IT-related department in a Malaysian higher education institution.
Abstract: Numerical studies have been carried out using a
validated two-dimensional RNG k-epsilon turbulence model for the
design optimization of a thrust vector control system using shock
induced supersonic secondary jet. Parametric analytical studies have
been carried out with various secondary jets at different divergent
locations, jet interaction angles, jet pressures. The results from the
parametric studies of the case on hand reveal that the primary nozzle
with a small divergence angle, downstream injections with a distance
of 2.5 times the primary nozzle throat diameter from the primary
nozzle throat location warrant higher efficiency over a certain range
of jet pressures and jet angles. We observed that the supersonic
secondary jet opposing the core flow with jets interaction angle of
40o to the axis far downstream of the nozzle throat facilitates better
thrust vectoring than the secondary jet with same direction as that of
core flow with various interaction angles. We concluded that fixing
of the supersonic secondary jet nozzle pointing towards the throat
direction with suitable angle at a distance 2 to 4 times of the primary
nozzle throat diameter, as the case may be, from the primary nozzle
throat location could facilitate better thrust vectoring for the
supersonic aerospace vehicles.
Abstract: Since hyaluronic acid (HA) receptor such as CD44 is
over-expressed at sites of cancer cells, HA can be used as a targeting
vehicles for anti-cancer drugs. The aim of this study is to synthesize
block copolymer composed of hyaluronic acid and
poly(ε-caprolactone) (HAPCL) and to fabricate polymeric micelles for
anticancer drug targeting against CD44 receptor of tumor cells.
Chemical composition of HAPCL was confirmed using 1H NMR
spectroscopy. Doxorubicin (DOX) was incorporated into polymeric
micelles of HAPCL. The diameters of HAPHS polymeric micelles
were changed around 80nm and have spherical shapes. Targeting
potential was investigated using CD44-overexpressing. When
DOX-incorporated polymeric micelles was added to KB cells, they
revealed strong red fluorescence color while blocking of CD44
receptor by pretreatment of free HA resulted in reduced intensity,
indicating that HAPCL polymeric micelles have targetability against
CD44 receptor.
Abstract: Mobile Ad hoc networks (MANETs) are collections
of wireless mobile nodes dynamically reconfiguring and collectively
forming a temporary network. These types of networks assume
existence of no fixed infrastructure and are often useful in battle-field
tactical operations or emergency search-and-rescue type of
operations where fixed infrastructure is neither feasible nor practical.
They also find use in ad hoc conferences, campus networks and
commercial recreational applications carrying multimedia traffic. All
of the above applications of MANETs require guaranteed levels of
performance as experienced by the end-user. This paper focuses on
key challenges in provisioning predetermined levels of such Quality
of Service (QoS). It also identifies functional areas where QoS
models are currently defined and used. Evolving functional areas
where performance and QoS provisioning may be applied are also
identified and some suggestions are provided for further research in
this area. Although each of the above functional areas have been
discussed separately in recent research studies, since these QoS
functional areas are highly correlated and interdependent, a
comprehensive and comparative analysis of these areas and their
interrelationships is desired. In this paper we have attempted to
provide such an overview.
Abstract: A new approach for the improvement of coding gain
in channel coding using Advanced Encryption Standard (AES) and
Maximum A Posteriori (MAP) algorithm is proposed. This new
approach uses the avalanche effect of block cipher algorithm AES
and soft output values of MAP decoding algorithm. The performance
of proposed approach is evaluated in the presence of Additive White
Gaussian Noise (AWGN). For the verification of proposed approach,
computer simulation results are included.
Abstract: Transition prediction of boundary layers has always
been an important problem in fluid mechanics both theoretically and
practically, yet notwithstanding the great effort made by many
investigators, there is no satisfactory answer to this problem. The most
popular method available is so-called e-N method which is heavily
dependent on experiments and experience. The author has proposed
improvements to the e-N method, so to reduce its dependence on
experiments and experience to a certain extent. One of the key
assumptions is that transition would occur whenever the velocity
amplitude of disturbance reaches 1-2% of the free stream velocity.
However, the reliability of this assumption needs to be verified. In this
paper, transition prediction on a flat plate is investigated by using both
the improved e-N method and the parabolized stability equations (PSE)
methods. The results show that the transition locations predicted by
both methods agree reasonably well with each other, under the above
assumption. For the supersonic case, the critical velocity amplitude in
the improved e-N method should be taken as 0.013, whereas in the
subsonic case, it should be 0.018, both are within the range 1-2%.
Abstract: Nowadays, HPC, Grid and Cloud systems are evolving
very rapidly. However, the development of infrastructure solutions
related to HPC is lagging behind. While the existing infrastructure is
sufficient for simple cases, many computational problems have more
complex requirements.Such computational experiments use different
resources simultaneously to start a large number of computational
jobs.These resources are heterogeneous. They have different
purposes, architectures, performance and used software.Users need a
convenient tool that allows to describe and to run complex
computational experiments under conditions of HPC environment.
This paper introduces a modularworkflow system called SEGL
which makes it possible to run complex computational experiments
under conditions of a real HPC organization. The system can be used
in a great number of organizations, which provide HPC power.
Significant requirements to this system are high efficiency and
interoperability with the existing HPC infrastructure of the
organization without any changes.
Abstract: The excellent suitability of the externally excited synchronous
machine (EESM) in automotive traction drive applications
is justified by its high efficiency over the whole operation range and
the high availability of materials. Usually, maximum efficiency is
obtained by modelling each single loss and minimizing the sum of all
losses. As a result, the quality of the optimization highly depends on
the precision of the model. Moreover, it requires accurate knowledge
of the saturation dependent machine inductances. Therefore, the
present contribution proposes a method to minimize the overall losses
of a salient pole EESM and its inverter in steady state operation based
on measurement data only. Since this method does not require any
manufacturer data, it is well suited for an automated measurement
data evaluation and inverter parametrization. The field oriented control
(FOC) of an EESM provides three current components resp. three
degrees of freedom (DOF). An analytic minimization of the copper
losses in the stator and the rotor (assuming constant inductances) is
performed and serves as a first approximation of how to choose the
optimal current reference values. After a numeric offline minimization
of the overall losses based on measurement data the results are
compared to a control strategy that satisfies cos (ϕ) = 1.