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: This work aims to generalize the integer order Sallen-Key filters into the fractional-order domain. The analysis in the case of two different fractional-order elements introduced where the general transfer function becomes four terms which is unusual in the conventional case. In addition, the effect of the transfer function parameters on the filter poles and hence the stability is introduced and closed forms for the filter critical frequencies are driven. Finally, different examples for the fractional order Sallen-Key filter design are presented with circuit simulations using ADS where a great matching between the numerical and simulation results is obtained.
Abstract: Image registration is the process of establishing point
by point correspondence between images obtained from a same
scene. This process is very useful in remote sensing, medicine,
cartography, computer vision, etc. Then, the task of registration is to
place the data into a common reference frame by estimating the
transformations between the data sets. In this work, we develop a
rigid point registration method based on the application of genetic
algorithms and Hausdorff distance. First, we extract the feature points
from both images based on the algorithm of global and local
curvature corner. After refining the feature points, we use Hausdorff
distance as similarity measure between the two data sets and for
optimizing the search space we use genetic algorithms to achieve
high computation speed for its inertial parallel. The results show the
efficiency of this method for registration of satellite images.
Abstract: Taiwan was the first country in Asia to announce
“Nuclear-Free Homeland" in 2002. In 2008, the new government
released the Sustainable Energy Policy Guidelines to lower the
nationwide CO2 emissions some time between 2016 and 2020 back to
the level of year 2008, further abatement of CO2 emissions is planed in
year 2025 when CO2 emissions will decrease to the level of year 2000.
Besides, under consideration of the issues of energy, environment and
economics (3E), the new government declared that the nuclear power
is a carbon-less energy option. This study analyses the effects of
nuclear power generation for CO2 abatement scenarios in Taiwan. The
MARKAL-MACRO energy model was adopted to evaluate economic
impacts and energy deployment due to life extension of existing
nuclear power plants and build new nuclear power units in CO2
abatement scenarios. The results show that CO2 abatement effort is
expensive. On the other hand, nuclear power is a cost-effective choice.
The GDP loss rate in the case of building new nuclear power plants is
around two thirds of the Nuclear-Free Homeland case. Nuclear power
generation has the capacity to provide large-scale CO2 free electricity.
Therefore, the results show that nuclear power is not only an option for
Taiwan, but also a requisite for Taiwan-s CO2 reduction strategy.
Abstract: Absorption spectra of infra-red (IR) radiation of the
disperse water medium absorbing the most important greenhouse
gases: CO2 , N2O , CH4 , C2H2 , C2H6 have been calculated by
the molecular dynamics method. Loss of the absorbing ability at the
formation of clusters due to a reduction of the number of centers
interacting with IR radiation, results in an anti-greenhouse effect.
Absorption of O3 molecules by the (H2O)50 cluster is investigated
at its interaction with Cl- ions. The splitting of ozone molecule on
atoms near to cluster surface was observed. Interaction of water
cluster with Cl- ions causes the increase of integrated intensity of
emission spectra of IR radiation, and also essential reduction of the
similar characteristic of Raman spectrum. Relative integrated
intensity of absorption of IR radiation for small water clusters was
designed. Dependences of the quantity of weight on altitude for
vapor of monomers, clusters, droplets, crystals and mass of all
moisture were determined. The anti-greenhouse effect of clusters was
defined as the difference of increases of average global temperature
of the Earth, caused by absorption of IR radiation by free water
molecules forming clusters, and absorption of clusters themselves.
The greenhouse effect caused by clusters makes 0.53 K, and the antigreenhouse
one is equal to 1.14 K. The increase of concentration of
CO2 in the atmosphere does not always correlate with the
amplification of greenhouse effect.
Abstract: Themain goal of this article is to find efficient
methods for elemental and molecular analysis of living
microorganisms (algae) under defined environmental conditions and
cultivation processes. The overall knowledge of chemical
composition is obtained utilizing laser-based techniques, Laser-
Induced Breakdown Spectroscopy (LIBS) for acquiring information
about elemental composition and Raman Spectroscopy for gaining
molecular information, respectively. Algal cells were suspended in
liquid media and characterized using their spectra. Results obtained
employing LIBS and Raman Spectroscopy techniques will help to
elucidate algae biology (nutrition dynamics depending on cultivation
conditions) and to identify algal strains, which have the potential for
applications in metal-ion absorption (bioremediation) and biofuel
industry. Moreover, bioremediation can be readily combined with
production of 3rd generation biofuels. In order to use algae for
efficient fuel production, the optimal cultivation parameters have to
be determinedleading to high production of oil in selected
cellswithout significant inhibition of the photosynthetic activity and
the culture growth rate, e.g. it is necessary to distinguish conditions
for algal strain containing high amount of higher unsaturated fatty
acids. Measurements employing LIBS and Raman Spectroscopy were
utilized in order to give information about alga Trachydiscusminutus
with emphasis on the amount of the lipid content inside the algal cell
and the ability of algae to withdraw nutrients from its environment
and bioremediation (elemental composition), respectively. This
article can serve as the reference for further efforts in describing
complete chemical composition of algal samples employing laserablation
techniques.
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: 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: Nowadays, more engineering systems are using some
kind of Artificial Intelligence (AI) for the development of their
processes. Some well-known AI techniques include artificial neural
nets, fuzzy inference systems, and neuro-fuzzy inference systems
among others. Furthermore, many decision-making applications base
their intelligent processes on Fuzzy Logic; due to the Fuzzy
Inference Systems (FIS) capability to deal with problems that are
based on user knowledge and experience. Also, knowing that users
have a wide variety of distinctiveness, and generally, provide
uncertain data, this information can be used and properly processed
by a FIS. To properly consider uncertainty and inexact system input
values, FIS normally use Membership Functions (MF) that represent
a degree of user satisfaction on certain conditions and/or constraints.
In order to define the parameters of the MFs, the knowledge from
experts in the field is very important. This knowledge defines the MF
shape to process the user inputs and through fuzzy reasoning and
inference mechanisms, the FIS can provide an “appropriate" output.
However an important issue immediately arises: How can it be
assured that the obtained output is the optimum solution? How can it
be guaranteed that each MF has an optimum shape? A viable solution
to these questions is through the MFs parameter optimization. In this
Paper a novel parameter optimization process is presented. The
process for FIS parameter optimization consists of the five simple
steps that can be easily realized off-line. Here the proposed process
of FIS parameter optimization it is demonstrated by its
implementation on an Intelligent Interface section dealing with the
on-line customization / personalization of internet portals applied to
E-commerce.
Abstract: Fault detection determines faultexistence and detecting
time. This paper discusses two layered fault detection methods to
enhance the reliability and safety. Two layered fault detection methods
consist of fault detection methods of component level controllers and
system level controllers. Component level controllers detect faults by
using limit checking, model-based detection, and data-driven
detection and system level controllers execute detection by stability
analysis which can detect unknown changes. System level controllers
compare detection results via stability with fault signals from lower
level controllers. This paper addresses fault detection methods via
stability and suggests fault detection criteria in nonlinear systems. The
fault detection method applies tothe hybrid control unit of a military
hybrid electric vehicleso that the hybrid control unit can detect faults
of the traction motor.
Abstract: This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.
Abstract: Calcium oxide (CaO) as carbon dioxide (CO2)
adsorbent at the elevated temperature has been very well-received
thus far. The CaO can be synthesized from natural calcium carbonate
(CaCO3) sources through the reversible calcination-carbonation
process. In the study, cockle shell has been selected as CaO
precursors. The objectives of the study are to investigate the
performance of calcination and carbonation with respect to different
temperature, heating rate, particle size and the duration time. Overall,
better performance is shown at the calcination temperature of 850oC
for 40 minutes, heating rate of 20oC/min, particle size of < 0.125mm
and the carbonation temperature is at 650oC. The synthesized
materials have been characterized by nitrogen physisorption and
surface morphology analysis. The effectiveness of the synthesized
cockle shell in capturing CO2 (0.72 kg CO2/kg adsorbent) which is
comparable to the commercialized adsorbent (0.60 kg CO2/kg
adsorbent) makes them as the most promising materials for CO2
capture.
Abstract: This paper presents an algorithm for reconstructing phase and magnitude responses of the impulse response when only the output data are available. The system is driven by a zero-mean independent identically distributed (i.i.d) non-Gaussian sequence that is not observed. The additive noise is assumed to be Gaussian. This is an important and essential problem in many practical applications of various science and engineering areas such as biomedical, seismic, and speech processing signals. The method is based on evaluating the bicepstrum of the third-order statistics of the observed output data. Simulations results are presented that demonstrate the performance of this method.
Abstract: An electric utility-s main concern is to plan, design, operate and maintain its power supply to provide an acceptable level of reliability to its users. This clearly requires that standards of reliability be specified and used in all three sectors of the power system, i.e., generation, transmission and distribution. That is why reliability of a power system is always a major concern to power system planners. This paper presents the reliability analysis of Bangladesh Power System (BPS). Reliability index, loss of load probability (LOLP) of BPS is evaluated using recursive algorithm and considering no de-rated states of generators. BPS has sixty one generators and a total installed capacity of 5275 MW. The maximum demand of BPS is about 5000 MW. The relevant data of the generators and hourly load profiles are collected from the National Load Dispatch Center (NLDC) of Bangladesh and reliability index 'LOLP' is assessed for the period of last ten years.
Abstract: Synchronous cooperative systems (SCS) bring together users that are geographically distributed and connected through a network to carry out a task. Examples of SCS include Tele- Immersion and Tele-Conferences. In SCS, the coordination is the core of the system, and it has been defined as the act of managing interdependencies between activities performed to achieve a goal. Some of the main problems that SCS present deal with the management of constraints between simultaneous activities and the execution ordering of these activities. In order to resolve these problems, orderings based on Lamport-s happened-before relation have been used, namely, causal, Δ-causal, and causal-total orderings. They mainly differ in the degree of asynchronous execution allowed. One of the most important orderings is the causal order, which establishes that the events must be seen in the cause-effect order as they occur in the system. In this paper we show that for certain SCS (e.g. videoconferences, tele-immersion) where some degradation of the system is allowed, ensuring the causal order is still rigid, which can render negative affects to the system. In this paper, we illustrate how a more relaxed ordering, which we call Fuzzy Causal Order (FCO), is useful for such kind of systems by allowing a more asynchronous execution than the causal order. The benefit of the FCO is illustrated by applying it to a particular scenario of intermedia synchronization of an audio-conference system.
Abstract: IVE toolkit has been created for facilitating research,education and development in the ?eld of virtual storytelling andcomputer games. Primarily, the toolkit is intended for modellingaction selection mechanisms of virtual humans, investigating level-of-detail AI techniques for large virtual environments, and for exploringjoint behaviour and role-passing technique (Sec. V). Additionally, thetoolkit can be used as an AI middleware without any changes. Themain facility of IVE is that it serves for prototyping both the AI andvirtual worlds themselves. The purpose of this paper is to describeIVE?s features in general and to present our current work - includingan educational game - on this platform.Keywords? AI middleware, simulation, virtual world.
Abstract: IP networks are evolving from data communication
infrastructure into many real-time applications such as video
conferencing, IP telephony and require stringent Quality of Service
(QoS) requirements. A rudimentary issue in QoS routing is to find a
path between a source-destination pair that satisfies two or more endto-
end constraints and termed to be NP hard or complete. In this
context, we present an algorithm Multi Constraint Path Problem
Version 3 (MCPv3), where all constraints are approximated and
return a feasible path in much quicker time. We present another
algorithm namely Delay Coerced Multi Constrained Routing
(DCMCR) where coerce one constraint and approximate the
remaining constraints. Our algorithm returns a feasible path, if exists,
in polynomial time between a source-destination pair whose first
weight satisfied by the first constraint and every other weight is
bounded by remaining constraints by a predefined approximation
factor (a). We present our experimental results with different
topologies and network conditions.
Abstract: This paper investigates the encryption efficiency of RC6 block cipher application to digital images, providing a new mathematical measure for encryption efficiency, which we will call the encryption quality instead of visual inspection, The encryption quality of RC6 block cipher is investigated among its several design parameters such as word size, number of rounds, and secret key length and the optimal choices for the best values of such design parameters are given. Also, the security analysis of RC6 block cipher for digital images is investigated from strict cryptographic viewpoint. The security estimations of RC6 block cipher for digital images against brute-force, statistical, and differential attacks are explored. Experiments are made to test the security of RC6 block cipher for digital images against all aforementioned types of attacks. Experiments and results verify and prove that RC6 block cipher is highly secure for real-time image encryption from cryptographic viewpoint. Thorough experimental tests are carried out with detailed analysis, demonstrating the high security of RC6 block cipher algorithm. So, RC6 block cipher can be considered to be a real-time secure symmetric encryption for digital images.
Abstract: This paper presents the use of three-dimensional finite
elements coupled with infinite elements to investigate the ground
vibrations at the surface in terms of the peak particle velocity (PPV)
due to construction of the first bore of the Dublin Port Tunnel. This
situation is analysed using a commercially available general-purpose
finite element package ABAQUS. A series of parametric studies is
carried out to examine the sensitivity of the predicted vibrations to
variations in the various input parameters required by finite element
method, including the stiffness and the damping of ground. The
results of this study show that stiffness has a more significant effect
on the PPV rather than the damping of the ground.
Abstract: The use of neural networks for recognition application is generally constrained by their inherent parameters inflexibility after the training phase. This means no adaptation is accommodated for input variations that have any influence on the network parameters. Attempts were made in this work to design a neural network that includes an additional mechanism that adjusts the threshold values according to the input pattern variations. The new approach is based on splitting the whole network into two subnets; main traditional net and a supportive net. The first deals with the required output of trained patterns with predefined settings, while the second tolerates output generation dynamically with tuning capability for any newly applied input. This tuning comes in the form of an adjustment to the threshold values. Two levels of supportive net were studied; one implements an extended additional layer with adjustable neuronal threshold setting mechanism, while the second implements an auxiliary net with traditional architecture performs dynamic adjustment to the threshold value of the main net that is constructed in dual-layer architecture. Experiment results and analysis of the proposed designs have given quite satisfactory conducts. The supportive layer approach achieved over 90% recognition rate, while the multiple network technique shows more effective and acceptable level of recognition. However, this is achieved at the price of network complexity and computation time. Recognition generalization may be also improved by accommodating capabilities involving all the innate structures in conjugation with Intelligence abilities with the needs of further advanced learning phases.