Abstract: Short-Term Load Forecasting (STLF) plays an important role for the economic and secure operation of power systems. In this paper, Continuous Genetic Algorithm (CGA) is employed to evolve the optimum large neural networks structure and connecting weights for one-day ahead electric load forecasting problem. This study describes the process of developing three layer feed-forward large neural networks for load forecasting and then presents a heuristic search algorithm for performing an important task of this process, i.e. optimal networks structure design. The proposed method is applied to STLF of the local utility. Data are clustered due to the differences in their characteristics. Special days are extracted from the normal training sets and handled separately. In this way, a solution is provided for all load types, including working days and weekends and special days. We find good performance for the large neural networks. The proposed methodology gives lower percent errors all the time. Thus, it can be applied to automatically design an optimal load forecaster based on historical data.
Abstract: According to the increasing utilization in power system, the transmission lines and power plants often operate in stability boundary and system probably lose its stable condition by over loading or occurring disturbance. According to the reasons that are mentioned, the prediction and recognition of voltage instability in power system has particular importance and it makes the network security stronger.This paper, by considering of power system contingencies based on the effects of them on Mega Watt Margin (MWM) and maximum loading point is focused in order to analyse the static voltage stability using continuation power flow method. The study has been carried out on IEEE 14-Bus Test System using Matlab and Psat softwares and results are presented.
Abstract: We explore entanglement in composite quantum systems
and how its peculiar properties are exploited in quantum
information and communication protocols by means of Diagrams
of States, a novel method to graphically represent and analyze how
quantum information is elaborated during computations performed
by quantum circuits.
We present quantum diagrams of states for Bell states generation,
measurements and projections, for dense coding and quantum teleportation,
for probabilistic quantum machines designed to perform
approximate quantum cloning and universal NOT and, finally, for
quantum privacy amplification based on entanglement purification.
Diagrams of states prove to be a useful approach to analyze quantum
computations, by offering an intuitive graphic representation of the
processing of quantum information. They also help in conceiving
novel quantum computations, from describing the desired information
processing to deriving the final implementation by quantum gate
arrays.
Abstract: Malaysia has successfully applied economic planning
to guide the development of the country from an economy of
agriculture and mining to a largely industrialised one. Now, with its
sights set on attaining the economic level of a fully developed nation
by 2020, the planning system must be made even more efficient and
focused.
It must ensure that every investment made in the country, contribute
towards creating the desirable objective of a strong, modern,
internationally competitive, technologically advanced, post-industrial
economy. Cities in Malaysia must also be fully aware of the enormous
competition it faces in a region with rapidly expanding and
modernising economies, all contending for the same pool of potential
international investments.
Efficiency of urban governance is also fundamental issue in
development characterized by sustainability, subsidiarity, equity,
transparency and accountability, civic engagement and citizenship, and
security. As described above, city competitiveness is harnessed
through 'city marketing and city management'.
High technology and high skilled industries, together with finance,
transportation, tourism, business, information and professional
services shopping and other commercial activities, are the principal
components of the nation-s economy, which must be developed to a
level well beyond where it is now. In this respect, Kuala Lumpur being
the premier city must play the leading role.
Abstract: In this article, we are dealing with a model consisting of a classical Van der Pol oscillator coupled gyroscopically to a linear oscillator. The major problem is analyzed. The regular dynamics of the system is considered using analytical methods. In this case, we provide an approximate solution for this system using parameter-expansion method. Also, we find approximate values for frequencies of the system. In parameter-expansion method the solution and unknown frequency of oscillation are expanded in a series by a bookkeeping parameter. By imposing the non-secularity condition at each order in the expansion the method provides different approximations to both the solution and the frequency of oscillation. One iteration step provides an approximate solution which is valid for the whole solution domain.
Abstract: Brushless DC motor with high torque density and slim
topology for easy loading for robot system is proposed and
manufactured. Electromagnetic design is executed by equivalent
magnetic circuit model and numerical analysis. Manufactured motor is
tested and verified characteristics comparing with conventional BLDC
motor.
Abstract: This paper presents a simple three phase power flow
method for solution of three-phase unbalanced radial distribution
system (RDN) with voltage dependent loads. It solves a simple
algebraic recursive expression of voltage magnitude, and all the data
are stored in vector form. The algorithm uses basic principles of
circuit theory and can be easily understood. Mutual coupling between
the phases has been included in the mathematical model. The
proposed algorithm has been tested with several unbalanced radial
distribution networks and the results are presented in the article. 8-
bus and IEEE 13 bus unbalanced radial distribution system results
are in agreements with the literature and show that the proposed
model is valid and reliable.
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: In this paper a new robust digital image watermarking
algorithm based on the Complex Wavelet Transform is proposed. This
technique embeds different parts of a watermark into different blocks
of an image under the complex wavelet domain. To increase security
of the method, two chaotic maps are employed, one map is used to
determine the blocks of the host image for watermark embedding,
and another map is used to encrypt the watermark image. Simulation
results are presented to demonstrate the effectiveness of the proposed
algorithm.
Abstract: An adaptive Chinese hand-talking system is presented
in this paper. By analyzing the 3 data collecting strategies for new
users, the adaptation framework including supervised and unsupervised
adaptation methods is proposed. For supervised adaptation,
affinity propagation (AP) is used to extract exemplar subsets, and enhanced
maximum a posteriori / vector field smoothing (eMAP/VFS)
is proposed to pool the adaptation data among different models. For
unsupervised adaptation, polynomial segment models (PSMs) are
used to help hidden Markov models (HMMs) to accurately label
the unlabeled data, then the "labeled" data together with signerindependent
models are inputted to MAP algorithm to generate
signer-adapted models. Experimental results show that the proposed
framework can execute both supervised adaptation with small amount
of labeled data and unsupervised adaptation with large amount
of unlabeled data to tailor the original models, and both achieve
improvements on the performance of recognition rate.
Abstract: A novel behavioral detection framework is proposed
to detect zero day buffer overflow vulnerabilities (based on network
behavioral signatures) using zero-day exploits, instead of the
signature-based or anomaly-based detection solutions currently
available for IDPS techniques. At first we present the detection
model that uses shadow honeypot. Our system is used for the online
processing of network attacks and generating a behavior detection
profile. The detection profile represents the dataset of 112 types of
metrics describing the exact behavior of malware in the network. In
this paper we present the examples of generating behavioral
signatures for two attacks – a buffer overflow exploit on FTP server
and well known Conficker worm. We demonstrated the visualization
of important aspects by showing the differences between valid
behavior and the attacks. Based on these metrics we can detect
attacks with a very high probability of success, the process of
detection is however very expensive.
Abstract: Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.
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: An adaptive dynamic cerebellar model articulation
controller (DCMAC) neural network used for solving the prediction
and identification problem is proposed in this paper. The proposed
DCMAC has superior capability to the conventional cerebellar model
articulation controller (CMAC) neural network in efficient learning
mechanism, guaranteed system stability and dynamic response. The
recurrent network is embedded in the DCMAC by adding feedback
connections in the association memory space so that the DCMAC
captures the dynamic response, where the feedback units act as
memory elements. The dynamic gradient descent method is adopted to
adjust DCMAC parameters on-line. Moreover, the analytical method
based on a Lyapunov function is proposed to determine the
learning-rates of DCMAC so that the variable optimal learning-rates
are derived to achieve most rapid convergence of identifying error.
Finally, the adaptive DCMAC is applied in two computer simulations.
Simulation results show that accurate identifying response and
superior dynamic performance can be obtained because of the
powerful on-line learning capability of the proposed DCMAC.
Abstract: The aim of this research was to calculate the
mechanical properties of Pd3Rh and PdRh3 ordered alloys. The
molecular dynamics (MD) simulation technique was used to obtain
temperature dependence of the energy, the Yong modulus, the shear
modulus, the bulk modulus, Poisson-s ratio and the elastic stiffness
constants at the isobaric-isothermal (NPT) ensemble in the range of
100-325 K. The interatomic potential energy and force on atoms were
calculated by Quantum Sutton-Chen (Q-SC) many body potential.
Our MD simulation results show the effect of temperature on the
cohesive energy and mechanical properties of Pd3Rh as well as
PdRh3 alloys. Our computed results show good agreement with the
experimental results where they have been available.
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: In this study, we propose the chaotic cipher combined with Mersenne Twister that is an extremely good pseudo-random number generator for the secure communications. We investigate the Lyapunov exponent of the proposed system, and evaluate the randomness performance by comparing RC4 and the chaotic cipher. In these results, our proposed system gets high chaotic property and more randomness than the conventional ciphers.
Abstract: Enzymatic hydrolysis is one of the major steps involved in the conversion from sugarcane bagasse to yield ethanol. This process offers potential for yields and selectivity higher, lower energy costs and milder operating conditions than chemical processes. However, the presence of some factors such as lignin content, crystallinity degree of the cellulose, and particle sizes, limits the digestibility of the cellulose present in the lignocellulosic biomasses. Pretreatment aims to improve the access of the enzyme to the substrate. In this study sugarcane bagasse was submitted chemical pretreatment that consisted of two consecutive steps, the first with dilute sulfuric acid (1 % (v/v) H2SO4), and the second with alkaline solutions with different concentrations of NaOH (1, 2, 3 and 4 % (w/v)). Thermal Analysis (TG/ DTG and DTA) was used to evaluate hemicellulose, cellulose and lignin contents in the samples. Scanning Electron Microscopy (SEM) was used to evaluate the morphological structures of the in natura and chemically treated samples. Results showed that pretreatments were effective in chemical degradation of lignocellulosic materials of the samples, and also was possible to observe the morphological changes occurring in the biomasses after pretreatments.
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.