Abstract: Process control and energy conservation are the two
primary reasons for using an adjustable speed drive. However,
voltage sags are the most important power quality problems facing
many commercial and industrial customers. The development of
boost converters has raised much excitement and speculation
throughout the electric industry. Now utilities are looking to these
devices for performance improvement and reliability in a variety of
areas. Examples of these include sags, spikes, or transients in supply
voltage as well as unbalanced voltages, poor electrical system
grounding, and harmonics. In this paper, simulations results are
presented for the verification of the proposed boost converter
topology. Boost converter provides ride through capability during
sag and swell. Further, input currents are near sinusoidal. This
eliminates the need of braking resistor also.
Abstract: Present wireless communication demands compact and intelligent devices with multitasking capabilities at affordable cost. The focus in the presented paper is on a dual band antenna for wireless communication with the capability of operating at two frequency bands with same structure. Two resonance frequencies are observed with the second operation band at 4.2GHz approximately three times the first resonance frequency at 1.5GHz. Structure is simple loop of microstrip line with characteristic impedance 50 ohms. The proposed antenna is designed using defective ground structure (DGS) and shows the nearly one third reductions in size as compared to without DGS. This antenna was simulated on electromagnetic (EM) simulation software and fabricated using microwave integrated circuit technique on RT-Duroid dielectric substrate (εr= 2.22) of thickness (H=15 mils). The designed antenna was tested on automatic network analyzer and shows the good agreement with simulated results. The proposed structure is modeled into an equivalent electrical circuit and simulated on circuit simulator. Subsequently, theoretical analysis was carried out and simulated. The simulated, measured, equivalent circuit response, and theoretical results shows good resemblance. The bands of operation draw many potential applications in today’s wireless communication.
Abstract: Robustness is one of the primary performance criteria for an Intelligent Video Surveillance (IVS) system. One of the key factors in enhancing the robustness of dynamic video analysis is,providing accurate and reliable means for shadow detection. If left undetected, shadow pixels may result in incorrect object tracking and classification, as it tends to distort localization and measurement information. Most of the algorithms proposed in literature are computationally expensive; some to the extent of equalling computational requirement of motion detection. In this paper, the homogeneity property of shadows is explored in a novel way for shadow detection. An adaptive division image (which highlights homogeneity property of shadows) analysis followed by a relatively simpler projection histogram analysis for penumbra suppression is the key novelty in our approach.
Abstract: Misalignment and unbalance are the major concerns
in rotating machinery. When the power supply to any rotating system
is cutoff, the system begins to lose the momentum gained during
sustained operation and finally comes to rest. The exact time period
from when the power is cutoff until the rotor comes to rest is called
Coast Down Time. The CDTs for different shaft cutoff speeds were
recorded at various misalignment and unbalance conditions. The
CDT reduction percentages were calculated for each fault and there
is a specific correlation between the CDT reduction percentage and
the severity of the fault. In this paper, radial basis network, a new
generation of artificial neural networks, has been successfully
incorporated for the prediction of CDT for misalignment and
unbalance conditions. Radial basis network has been found to be
successful in the prediction of CDT for mechanical faults in rotating
machinery.
Abstract: Through 1980s, management accounting researchers
described the increasing irrelevance of traditional control and
performance measurement systems. The Balanced Scorecard (BSC)
is a critical business tool for a lot of organizations. It is a
performance measurement system which translates mission and
strategy into objectives. Strategy map approach is a development
variant of BSC in which some necessary causal relations must be
established. To recognize these relations, experts usually use
experience. It is also possible to utilize regression for the same
purpose. Structural Equation Modeling (SEM), which is one of the
most powerful methods of multivariate data analysis, obtains more
appropriate results than traditional methods such as regression. In the
present paper, we propose SEM for the first time to identify the
relations between objectives in the strategy map, and a test to
measure the importance of relations. In SEM, factor analysis and test
of hypotheses are done in the same analysis. SEM is known to be
better than other techniques at supporting analysis and reporting. Our
approach provides a framework which permits the experts to design
the strategy map by applying a comprehensive and scientific method
together with their experience. Therefore this scheme is a more
reliable method in comparison with the previously established
methods.
Abstract: The study of non-equilibrium systems has attracted
increasing interest in recent years, mainly due to the lack of
theoretical frameworks, unlike their equilibrium counterparts.
Studying the steady state and/or simple systems is thus one of the
main interests. Hence in this work we have focused our attention on
the driven lattice gas model (DLG model) consisting of interacting
particles subject to an external field E. The dynamics of the system
are given by hopping of particles to nearby empty sites with rates
biased for jumps in the direction of E. Having used small two
dimensional systems of DLG model, the stochastic properties at nonequilibrium
steady state were analytically studied. To understand the
non-equilibrium phenomena, we have applied the analytic approach
via master equation to calculate probability function and analyze
violation of detailed balance in term of the fluctuation-dissipation
theorem. Monte Carlo simulations have been performed to validate
the analytic results.
Abstract: The main purpose of this paper is to investigate thelong-run equilibrium and short-run dynamics of international housing prices when macroeconomic variables change. We apply the Pedroni’s, panel cointegration, using the unbalanced panel data analysis of 33 countries over the period from 1980Q1 to 2013Q1, to examine the relationships among house prices and macroeconomic variables. Our empirical results of panel data cointegration tests support the existence of a cointegration among these macroeconomic variables and house prices. Besides, the empirical results of panel DOLS further present that a 1% increase in economic activity, long-term interest rates, and construction costs cause house prices to respectively change 2.16%, -0.04%, and 0.22% in the long run.Furthermore, the increasing economic activity and the construction cost would cause strongerimpacts on the house prices for lower income countries than higher income countries.The results lead to the conclusion that policy of house prices growth can be regarded as economic growth for lower income countries. Finally, in America region, the coefficient of economic activity is the highest, which displays that increasing economic activity causes a faster rise in house prices there than in other regions. There are some special cases whereby the coefficients of interest rates are significantly positive in America and Asia regions.
Abstract: The aim of this study was to evaluate the sensitivity
of a range of EEG indices to time-on-task effects and to a workload
manipulation (cueing), during performance of a resource-limited
vigilance task. Effects of task period and cueing on performance and
subjective state response were consistent with previous vigilance
studies and with resource theory. Two EEG indices – the Task Load
Index (TLI) and global lower frequency (LF) alpha power – showed
effects of task period and cueing similar to those seen with correct
detections. Across four successive task periods, the TLI declined and
LF alpha power increased. Cueing increased TLI and decreased LF
alpha. Other indices – the Engagement Index (EI), frontal theta and
upper frequency (UF) alpha failed to show these effects. However, EI
and frontal theta were sensitive to interactive effects of task period
and cueing, which may correspond to a stronger anxiety response to
the uncued task.
Abstract: This paper focuses on reducing the power consumption
of wireless sensor networks. Therefore, a communication protocol
named LEACH (Low-Energy Adaptive Clustering Hierarchy) is modified.
We extend LEACHs stochastic cluster-head selection algorithm
by a modifying the probability of each node to become cluster-head
based on its required energy to transmit to the sink. We present
an efficient energy aware routing algorithm for the wireless sensor
networks. Our contribution consists in rotation selection of clusterheads
considering the remoteness of the nodes to the sink, and then,
the network nodes residual energy. This choice allows a best distribution
of the transmission energy in the network. The cluster-heads
selection algorithm is completely decentralized. Simulation results
show that the energy is significantly reduced compared with the
previous clustering based routing algorithm for the sensor networks.
Abstract: This paper analyses the non linear properties
exhibited by a drill string system under various un balanced mass
conditions. The drill string is affected by continuous friction in the
form of drill bit and well bore hole interactions. This paper proves
the origin of limit cycling and increase of non linearity with increase
in speed of the drilling in the presence of friction. The spectrum of
the frequency response is also studied to detect the presence of
vibration abnormalities arising during the drilling process.
Abstract: Wireless Sensor Networks (WSNs) have attracted the attention of many researchers. This has resulted in their rapid integration in very different areas such as precision agriculture,environmental monitoring, object and event detection and military surveillance. Due to the current WSN characteristics this technology is specifically useful in industrial areas where security, reliability and autonomy are basic, such as nuclear power plants, chemical plants, and others. In this paper we present a system based on WSNs to monitor environmental conditions around and inside a nuclear power plant, specifically, radiation levels. Sensor nodes, equipped with radiation sensors, are deployed in fixed positions throughout the plant. In addition, plant staff are also equipped with mobile devices with higher capabilities than sensors such as for example PDAs able to monitor radiation levels and other conditions around them. The system enables communication between PDAs, which form a Mobile Ad-hoc Wireless Network (MANET), and allows workers to monitor remote conditions in the plant. It is particularly useful during stoppage periods for inspection or in the event of an accident to prevent risk situations.
Abstract: In this paper we propose a Multiple Description Image Coding(MDIC) scheme to generate two compressed and balanced rates descriptions in the wavelet domain (Daubechies biorthogonal (9, 7) wavelet) using pairwise correlating transform optimal and application method for Generalized Multiple Description Coding (GMDC) to image coding in the wavelet domain. The GMDC produces statistically correlated streams such that lost streams can be estimated from the received data. Our performance test shown that the proposed method gives more improvement and good quality of the reconstructed image when the wavelet coefficients are normalized by Gaussian Scale Mixture (GSM) model then the Gaussian one ,.
Abstract: This paper presents modeling and analysis of 12-phase distribution static compensator (DSTATCOM), which is capable of balancing the source currents in spite of unbalanced loading and phase outages. In addition to balance the supply current, the power factor can be set to a desired value. The theory of instantaneous symmetrical components is used to generate the twelve-phase reference currents. These reference currents are then tracked using current controlled voltage source inverter, operated in a hysteresis band control scheme. An ideal compensator in place of physical realization of the compensator is used. The performance of the proposed DTATCOM is validated through MATLAB simulation and detailed simulation results are given.
Abstract: The increasing demand for sufficient and clean
energy forces industrial and service companies to align their strategies towards efficient consumption. This trend refers also to the
residential building sector. There, large amounts of energy consumption are caused by house and facility heating. Many of the
operated hot water heating systems lack hydraulic balanced working
conditions for heat distribution and –transmission and lead to
inefficient heating. Through hydraulic balancing of heating systems,
significant energy savings for primary and secondary energy can be
achieved. This paper addresses the use of KNX-technology (Smart
Buildings) in residential buildings to ensure a dynamic adaption of
hydraulic system's performance, in order to increase the heating
system's efficiency. In this paper, the procedure of heating system
segmentation into hydraulically independent units (meshes) is
presented. Within these meshes, the heating valve are addressed and
controlled by a central facility server. Feasibility criteria towards
such drivers will be named. The dynamic hydraulic balance is
achieved by positioning these valves according to heating loads, that
are generated from the temperature settings in the corresponding
rooms. The energetic advantages of single room heating control
procedures, based on the application FacilityManager, is presented.
Abstract: The human head representations usually are based on
the morphological – structural components of a real model. Over the
time became more and more necessary to achieve full virtual models
that comply very rigorous with the specifications of the human
anatomy. Still, making and using a model perfectly fitted with the
real anatomy is a difficult task, because it requires large hardware
resources and significant times for processing. That is why it is
necessary to choose the best compromise solution, which keeps the
right balance between the details perfection and the resources
consumption, in order to obtain facial animations with real-time
rendering. We will present here the way in which we achieved such a
3D system that we intend to use as a base point in order to create
facial animations with real-time rendering, used in medicine to find
and to identify different types of pathologies.
Abstract: This study examined the effects of neuromuscular
training (NT) on limits of stability (LOS) in female individuals.
Twenty female basketball amateurs were assigned into NT
experimental group or control group by volunteer. All the players were
underwent regular basketball practice, 90 minutes, 3 times per week
for 6 weeks, but the NT experimental group underwent extra NT with
plyometric and core training, 50 minutes, 3 times per week for 6 weeks
during this period. Limits of stability (LOS) were evaluated by the
Biodex Balance System. One factor ANCOVA was used to examine
the differences between groups after training. The significant level for
statistic was set at p
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: In this paper, a neural tree (NT) classifier having a
simple perceptron at each node is considered. A new concept for
making a balanced tree is applied in the learning algorithm of the
tree. At each node, if the perceptron classification is not accurate and
unbalanced, then it is replaced by a new perceptron. This separates
the training set in such a way that almost the equal number of patterns
fall into each of the classes. Moreover, each perceptron is trained only
for the classes which are present at respective node and ignore other
classes. Splitting nodes are employed into the neural tree architecture
to divide the training set when the current perceptron node repeats
the same classification of the parent node. A new error function based
on the depth of the tree is introduced to reduce the computational
time for the training of a perceptron. Experiments are performed to
check the efficiency and encouraging results are obtained in terms of
accuracy and computational costs.
Abstract: To minimize power losses, it is important to
determine the location and size of local generators to be placed in
unbalanced power distribution systems. On account of some inherent
features of unbalanced distribution systems, such as radial structure,
large number of nodes, a wide range of X/R ratios, the conventional
techniques developed for the transmission systems generally fail on
the determination of optimum size and location of distributed
generators (DGs). This paper presents a simple method for
investigating the problem of contemporaneously choosing best
location and size of DG in three-phase unbalanced radial distribution
system (URDS) for power loss minimization and to improve the
voltage profile of the system. Best location of the DG is determined
by using voltage index analysis and size of DG is computed by
variational technique algorithm according to available standard size
of DGs. This paper presents the results of simulations for 25-bus and
IEEE 37- bus Unbalanced Radial Distribution system.
Abstract: The wireless link can be unreliable in realistic wireless
sensor networks (WSNs). Energy efficient and reliable data
forwarding is important because each node has limited resources.
Therefore, we must suggest an optimal solution that considers using
the information of the node-s characteristics. Previous routing
protocols were unsuited to realistic asymmetric WSNs. In this paper,
we propose a Protocol that considers Both sides of Link-quality and
Energy (PBLE), an optimal routing protocol that balances modified
link-quality, distance and energy. Additionally, we propose a node
scheduling method. PBLE achieves a longer lifetime than previous
routing protocols and is more energy-efficient. PBLE uses energy,
local information and both sides of PRR in a 1-hop distance. We
explain how to send data packets to the destination node using the
node's information. Simulation shows PBLE improves delivery rate
and network lifetime compared to previous schemes. Moreover, we
show the improvement in various WSN environments.