Abstract: In this paper we use low frequency noise analysis to understand and map the current conduction path in a multi gate junctionless FinFET. The device used in this study behaves as a gated resistor and shows excellent short channel effect suppression due to its multi gate structure. Generally for a bulk conduction device like the junctionless device studied in this work, the low frequency noise can be modelled using the mobility fluctuation model; however for this device we can also see the effect of carrier fluctuations on the LFN characteristic. The noise characteristic at different gate bias and also the possible location of the traps is explained.
Abstract: Darcy’s Law is a well-known constitutive equation describing the flow of a fluid through a porous medium. The equation shows a relationship between the superficial or Darcy velocity and the pressure gradient which was first experimentally observed by Henry Darcy in 1855-1856. In this study, we apply homogenization method to Stokes equation in order to derive Darcy’s Law. The process of deriving the equation is complicated, especially in multidimensional domain. Thus, for the sake of simplicity, we use the indicial notation as well as the homogenization. This combination provides a smooth, simple and easy technique to derive Darcy’s Law.
Abstract: The problem of optimal planning of multiple sources
of distributed generation (DG) in distribution networks is treated in
this paper using an improved Ant Colony Optimization algorithm
(ACO). This objective of this problem is to determine the DG
optimal size and location that in order to minimize the network real
power losses. Considering the multiple sources of DG, both size and
location are simultaneously optimized in a single run of the proposed
ACO algorithm. The various practical constraints of the problem are
taken into consideration by the problem formulation and the
algorithm implementation. A radial power flow algorithm for
distribution networks is adopted and applied to satisfy these
constraints. To validate the proposed technique and demonstrate its
effectiveness, the well-know 69-bus feeder standard test system is
employed.cm.
Abstract: Learning the gradient of neuron's activity function
like the weight of links causes a new specification which is
flexibility. In flexible neural networks because of supervising and
controlling the operation of neurons, all the burden of the learning is
not dedicated to the weight of links, therefore in each period of
learning of each neuron, in fact the gradient of their activity function,
cooperate in order to achieve the goal of learning thus the number of
learning will be decreased considerably.
Furthermore, learning neurons parameters immunes them against
changing in their inputs and factors which cause such changing.
Likewise initial selecting of weights, type of activity function,
selecting the initial gradient of activity function and selecting a fixed
amount which is multiplied by gradient of error to calculate the
weight changes and gradient of activity function, has a direct affect
in convergence of network for learning.
Abstract: Building a service-centric business model requires
new knowledge and capabilities in companies. This paper enlightens
the challenges small and medium sized firms (SMEs) face when
developing their service-centric business models. This paper
examines the premise for knowledge transfer and capability
development required. The objective of this paper is to increase
knowledge about SME-s transformation to service-centric business
models.This paper reports an action research based case study. The
paper provides empirical evidence from three case companies. The
empirical data was collected through multiple methods. The findings
of the paper are: First, the developed model to analyze the current
state in companies. Second, the process of building the service –
centric business models. Third, the selection of suitable service
development methods. The lack of a holistic understanding on
service logic suggests that SMEs need practical and easy to use
methods to improve their business
Abstract: A reconfigurable manufacturing system (RMS) is an
advanced system designed at the outset for rapid changes in its hardware
and software components in order to quickly adjust its production
capacity and functionally. Among various operational decisions, this
study considers the scheduling problem that determines the input
sequence and schedule at the same time for a given set of parts. In
particular, we consider the practical constraints that the numbers of
pallets/fixtures are limited and hence a part can be released into the
system only when the fixture required for the part is available. To
solve the integrated input sequencing and scheduling problems, we
suggest a priority rule based approach in which the two sub-problems
are solved using a combination of priority rules. To show the effectiveness
of various rule combinations, a simulation experiment was
done on the data for a real RMS, and the test results are reported.
Abstract: In this paper, the existence, multiplicity and
noexistence of positive solutions for a class of semipositone
discrete boundary value problems with two parameters is
studied by applying nonsmooth critical point theory and
sub-super solutions method.
Abstract: Thousands of masters athletes participate
quadrennially in the World Masters Games (WMG), yet this cohort
of athletes remains proportionately under-investigated. Due to a
growing global obesity pandemic in context of benefits of physical
activity across the lifespan, the prevalence of obesity in this unique
population was of particular interest. Data gathered on a sub-sample
of 535 football code athletes, aged 31-72 yrs ( =47.4, s =±7.1),
competing at the Sydney World Masters Games (2009) demonstrated
a significantly (p
Abstract: A case study of the generation scheduling optimization
of the multi-hydroplants on the Yuan River Basin in China is reported
in this paper. Concerning the uncertainty of the inflows, the
long/mid-term generation scheduling (LMTGS) problem is solved by
a stochastic model in which the inflows are considered as stochastic
variables. For the short-term generation scheduling (STGS) problem, a
constraint violation priority is defined in case not all constraints are
satisfied. Provided the stage-wise separable condition and low
dimensions, the hydroplant-based operational region schedules
(HBORS) problem is solved by dynamic programming (DP). The
coordination of LMTGS and STGS is presented as well. The
feasibility and the effectiveness of the models and solution methods
are verified by the numerical results.
Abstract: This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.
Abstract: In this paper, an extreme learning machine with an automatic segmentation algorithm is applied to heart disorder classification by heart sound signals. From continuous heart sound signals, the starting points of the first (S1) and the second heart pulses (S2) are extracted and corrected by utilizing an inter-pulse histogram. From the corrected pulse positions, a single period of heart sound signals is extracted and converted to a feature vector including the mel-scaled filter bank energy coefficients and the envelope coefficients of uniform-sized sub-segments. An extreme learning machine is used to classify the feature vector. In our cardiac disorder classification and detection experiments with 9 cardiac disorder categories, the proposed method shows significantly better performance than multi-layer perceptron, support vector machine, and hidden Markov model; it achieves the classification accuracy of 81.6% and the detection accuracy of 96.9%.
Abstract: In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Abstract: Signature amortization schemes have been introduced
for authenticating multicast streams, in which, a single signature is
amortized over several packets. The hash value of each packet is
computed, some hash values are appended to other packets, forming
what is known as hash chain. These schemes divide the stream into
blocks, each block is a number of packets, the signature packet in
these schemes is either the first or the last packet of the block.
Amortization schemes are efficient solutions in terms of computation
and communication overhead, specially in real-time environment.
The main effictive factor of amortization schemes is it-s hash chain
construction. Some studies show that signing the first packet of each
block reduces the receiver-s delay and prevents DoS attacks, other
studies show that signing the last packet reduces the sender-s delay.
To our knowledge, there is no studies that show which is better, to
sign the first or the last packet in terms of authentication probability
and resistance to packet loss.
In th is paper we will introduce another scheme for authenticating
multicast streams that is robust against packet loss, reduces the
overhead, and prevents the DoS attacks experienced by the receiver
in the same time. Our scheme-The Multiple Connected Chain signing
the First packet (MCF) is to append the hash values of specific
packets to other packets,then append some hashes to the signature
packet which is sent as the first packet in the block. This scheme
is aspecially efficient in terms of receiver-s delay. We discuss and
evaluate the performance of our proposed scheme against those that
sign the last packet of the block.
Abstract: The performance of the Optical Code Division Multiplexing/ Wavelength Division Multiplexing (WDM/OCDM) technique for Optical Packet Switch is investigated. The impact on the performance of the impairment due to both Multiple Access Interference and Beat noise is studied. The Packet Loss Probability due to output packet contentions is evaluated as a function of the main switch and traffic parameters when Gold coherent optical codes are adopted. The Packet Loss Probability of the OCDM/WDM switch can reach 10-9 when M=16 wavelengths, Gold code of length L=511 and only 24 wavelength converters are used in the switch.
Abstract: In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.
Abstract: Heterogeneous repolarization causes dispersion of the T-wave and has been linked to arrhythmogenesis. Such heterogeneities appear due to differential expression of ionic currents in different regions of the heart, both in healthy and diseased animals and humans. Mice are important animals for the study of heart diseases because of the ability to create transgenic animals. We used our previously reported model of mouse ventricular myocytes to develop 2D mouse ventricular tissue model consisting of 14,000 cells (apical or septal ventricular myocytes) and to study the stability of action potential propagation and Ca2+ dynamics. The 2D tissue model was implemented as a FORTRAN program code for highperformance multiprocessor computers that runs on 36 processors. Our tissue model is able to simulate heterogeneities not only in action potential repolarization, but also heterogeneities in intracellular Ca2+ transients. The multicellular model reproduced experimentally observed velocities of action potential propagation and demonstrated the importance of incorporation of realistic Ca2+ dynamics for action potential propagation. The simulations show that relatively sharp gradients of repolarization are predicted to exist in 2D mouse tissue models, and they are primarily determined by the cellular properties of ventricular myocytes. Abrupt local gradients of channel expression can cause alternans at longer pacing basic cycle lengths than gradual changes, and development of alternans depends on the site of stimulation.
Abstract: The residue number system (RNS) is popular in high performance computation applications because of its carry-free nature. The challenges of RNS systems design lie in the moduli set selection and in the reverse conversion from residue representation to weighted representation. In this paper, we proposed a fully parallel reverse conversion algorithm for the moduli set {rn - 2, rn - 1, rn}, based on simple mathematical relationships. Also an efficient hardware realization of this algorithm is presented. Our proposed converter is very faster and results to hardware savings, compared to the other reverse converters.
Abstract: Robust stability and performance are the two most
basic features of feedback control systems. The harmonic balance
analysis technique enables to analyze the stability of limit cycles
arising from a neural network control based system operating over
nonlinear plants. In this work a robust stability analysis based on the
harmonic balance is presented and applied to a neural based control
of a non-linear binary distillation column with unstructured
uncertainty. We develop ways to describe uncertainty in the form of
neglected nonlinear dynamics and high harmonics for the plant and
controller respectively. Finally, conclusions about the performance of
the neural control system are discussed using the Nyquist stability
margin together with the structured singular values of the uncertainty
as a robustness measure.
Abstract: A numerical study on the effect of side-dump angle on
fuel droplets sizing and effective mass fraction have been
investigated in present paper. The mass of fuel vapor inside the
flammability limit is named as the effective mass fraction. In the first
step we have considered a side-dump combustor with dump angle of
0o (acrossthe cylinder) and by increasing the entrance airflow velocity
from 20 to 30, 40 and 50 (m/s) respectively, the mean diameter of
fuel droplets sizing and effective mass fraction have been studied.
After this step, we have changed the dump angle from 0o to 30o,45o
and finally 60o in direction of cylinderand also we have increased the
entrance airflow velocity from 20 up to 50 (m/s) with the amount of
growth of 10(m/s) in each step, to examine its effects on fuel droplets
sizing as well as effective mass fraction. With rise of entrance airflow
velocity, these calculations are repeated in each step too. The results
show, with growth of dump-angle the effective mass fraction has
been decreased and the mean diameter of droplets sizing has been
increased. To fulfill the calculations a modified version of KIVA-3V
code which is a transient, three-dimensional, multiphase,
multicomponent code for the analysis of chemically reacting flows
with sprays, is used.
Abstract: It has proved that nonlinear diffusion and bilateral
filtering (BF) have a closed connection. Early effort and contribution
are to find a generalized representation to link them by using adaptive
filtering. In this paper a new further relationship between nonlinear
diffusion and bilateral filtering is explored which pays more attention
to numerical calculus. We give a fresh idea that bilateral filtering can
be accelerated by multigrid (MG) scheme which likes the nonlinear
diffusion, and show that a bilateral filtering process with large kernel
size can be approximated by a nonlinear diffusion process based on
full multigrid (FMG) scheme.