Abstract: This paper proposes an efficient method to classify
inverse synthetic aperture (ISAR) images. Because ISAR images can
be translated and rotated in the 2-dimensional image place, invariance
to the two factors is indispensable for successful classification. The
proposed method achieves invariance to translation and rotation of
ISAR images using a combination of two-dimensional Fourier
transform, polar mapping and correlation-based alignment of the
image. Classification is conducted using a simple matching score
classifier. In simulations using the real ISAR images of five scaled
models measured in a compact range, the proposed method yields
classification ratios higher than 97 %.
Abstract: Case-Based Reasoning (CBR) is one of machine
learning algorithms for problem solving and learning that caught a lot
of attention over the last few years. In general, CBR is composed of
four main phases: retrieve the most similar case or cases, reuse the
case to solve the problem, revise or adapt the proposed solution, and
retain the learned cases before returning them to the case base for
learning purpose. Unfortunately, in many cases, this retain process
causes the uncontrolled case base growth. The problem affects
competence and performance of CBR systems. This paper proposes
competence-based maintenance method based on deletion policy
strategy for CBR. There are three main steps in this method. Step 1,
formulate problems. Step 2, determine coverage and reachability set
based on coverage value. Step 3, reduce case base size. The results
obtained show that this proposed method performs better than the
existing methods currently discussed in literature.
Abstract: In this paper a new concept of partial complement of a graph G is introduced and using the same a new graph parameter, called completion number of a graph G, denoted by c(G) is defined. Some basic properties of graph parameter, completion number, are studied and upperbounds for completion number of classes of graphs are obtained , the paper includes the characterization also.
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: This paper analyzes different techniques of the fine grained security of relational databases for the two variables-data accessibility and inference. Data accessibility measures the amount of data available to the users after applying a security technique on a table. Inference is the proportion of information leakage after suppressing a cell containing secret data. A row containing a secret cell which is suppressed can become a security threat if an intruder generates useful information from the related visible information of the same row. This paper measures data accessibility and inference associated with row, cell, and column level security techniques. Cell level security offers greatest data accessibility as it suppresses secret data only. But on the other hand, there is a high probability of inference in cell level security. Row and column level security techniques have least data accessibility and inference. This paper introduces cell plus innocent security technique that utilizes the cell level security method but suppresses some innocent data to dodge an intruder that a suppressed cell may not necessarily contain secret data. Four variations of the technique namely cell plus innocent 1/4, cell plus innocent 2/4, cell plus innocent 3/4, and cell plus innocent 4/4 respectively have been introduced to suppress innocent data equal to 1/4, 2/4, 3/4, and 4/4 percent of the true secret data inside the database. Results show that the new technique offers better control over data accessibility and inference as compared to the state-of-theart security techniques. This paper further discusses the combination of techniques together to be used. The paper shows that cell plus innocent 1/4, 2/4, and 3/4 techniques can be used as a replacement for the cell level security.
Abstract: Many water supply systems in Australia are currently
undergoing significant reconfiguration due to reductions in long term
average rainfall and resulting low inflows to water supply reservoirs
since the second half of the 20th century. When water supply systems
undergo change, it is necessary to develop new operating rules,
which should consider climate, because the climate change is likely
to further reduce inflows. In addition, water resource systems are
increasingly intended to be operated to meet complex and multiple
objectives representing social, economic, environmental and
sustainability criteria. This is further complicated by conflicting
preferences on these objectives from diverse stakeholders. This paper
describes a methodology to develop optimum operating rules for
complex multi-reservoir systems undergoing significant change,
considering all of the above issues. The methodology is demonstrated
using the Grampians water supply system in northwest Victoria,
Australia. Initial work conducted on the project is also presented in
this paper.
Abstract: Quantitative methods of economic decision-making as
the methodological base of the so called operational research
represent an important set of tools for managing complex economic
systems,both at the microeconomic level and on the macroeconomic
scale. Mathematical models of controlled and controlling processes
allow, by means of artificial experiments, obtaining information
foroptimalor optimum approaching managerial decision-making.The
quantitative methods of economic decision-making usually include a
methodology known as structural analysis -an analysisof
interdisciplinary production-consumption relations.
Abstract: This paper provides a flexible way of controlling
Variable-Bit-Rate (VBR) of compressed digital video, applicable to
the new H264 video compression standard. The entire video
sequence is assessed in advance and the quantisation level is then set
such that bit rate (and thus the frame rate) remains within
predetermined limits compatible with the bandwidth of the
transmission system and the capabilities of the remote end, while at
the same time providing constant quality similar to VBR encoding.
A process for avoiding buffer starvation by selectively eliminating
frames from the encoded output at times when the frame rate is slow
(large number of bits per frame) will be also described. Finally, the
problem of buffer overflow will be solved by selectively eliminating
frames from the received input to the decoder. The decoder detects
the omission of the frames and resynchronizes the transmission by
monitoring time stamps and repeating frames if necessary.
Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: Given a simple connected unweighted undirected graph G = (V (G), E(G)) with |V (G)| = n and |E(G)| = m, we present a new algorithm for the all-pairs shortest-path (APSP) problem. The running time of our algorithm is in O(n2 log n). This bound is an improvement over previous best known O(n2.376) time bound of Raimund Seidel (1995) for general graphs. The algorithm presented does not rely on fast matrix multiplication. Our algorithm with slight modifications, enables us to compute the APSP problem for unweighted directed graph in time O(n2 log n), improving a previous best known O(n2.575) time bound of Uri Zwick (2002).
Abstract: Among neural models the Support Vector Machine
(SVM) solutions are attracting increasing attention, mostly because
they eliminate certain crucial questions involved by neural network
construction. The main drawback of standard SVM is its high
computational complexity, therefore recently a new technique, the
Least Squares SVM (LS–SVM) has been introduced. In this paper we
present an extended view of the Least Squares Support Vector
Regression (LS–SVR), which enables us to develop new
formulations and algorithms to this regression technique. Based on
manipulating the linear equation set -which embodies all information
about the regression in the learning process- some new methods are
introduced to simplify the formulations, speed up the calculations
and/or provide better results.
Abstract: Turbine blade cooling is considered as the most
effective way of maintaining high operating temperature making use
of the available materials, and turbine systems with wet compression
have a potential for future power generation because of high efficiency
and high specific power with a relatively low cost. In this paper
performance analysis of wet-compression gas turbine cycle with
turbine blade cooling is carried out. The wet compression process is
analytically modeled based on non-equilibrium droplet evaporation.
Special attention is paid for the effects of pressure ratio and water
injection ratio on the important system variables such as ratio of
coolant fluid flow, fuel consumption, thermal efficiency and specific
power. Parametric studies show that wet compression leads to
insignificant improvement in thermal efficiency but significant
enhancement of specific power in gas turbine systems with turbine
blade cooling.
Abstract: At present time, competition, unpredictable fluctuations have made communication engineering education in the global sphere really difficult. Confront with new situation in the engineering education sector. Communication engineering education has to be reformed and ready to use more advanced technologies. We realized that one of the general problems of student`s education is that after graduating from their universities, they are not prepared to face the real life challenges and full skilled to work in industry. They are prepared only to think like engineers and professionals but they also need to possess some others non-technical skills. In today-s environment, technical competence alone is not sufficient for career success. Employers want employees (graduate engineers) who have good oral and written communication (soft) skills. It does require for team work, business awareness, organization, management skills, responsibility, initiative, problem solving and IT competency. This proposed curriculum brings interactive, creative, interesting, effective learning methods, which includes online education, virtual labs, practical work, problem-based learning (PBL), and lectures given by industry experts. Giving short assignments, presentations, reports, research papers and projects students can significantly improve their non-technical skills. Also, we noticed the importance of using ICT technologies in engineering education which used by students and teachers, and included that into proposed teaching and learning methods. We added collaborative learning between students through team work which builds theirs skills besides course materials. The prospective on this research that we intent to update communication engineering curriculum in order to get fully constructed engineer students to ready for real industry work.
Abstract: Recently, Northeast Asia has become one of the three
largest trade areas, covering approximately 30% of the total trade
volume of the world. However, the distribution facilities are saturated
due to the increase in the transportation volume within the area and
with the European countries. In order to accommodate the increase of
the transportation volume, the transportation networking with the
major countries in Northeast Asia and Europe is absolutely necessary.
The Eurasian Logistics Network will develop into an international
passenger transportation network covering the Northeast Asian region
and an international freight transportation network connecting across
Eurasia Continent. This paper surveys the changes and trend of the
distribution network in the Eurasian Region according to the political,
economic and environmental changes of the region, analyses the
distribution network according to the changes in the transportation
policies of the related countries, and provides the direction of the
development of composite transportation on the basis of the present
conditions of transportation means. The transportation means optimal
for the efficiency of transportation system are suggested to be train
ferries, sea & rail or sea & rail & sea. It is suggested to develop
diversified composite transportation means and routes within the
boundary of international cooperation system.
Abstract: In this paper two models using a functional network
were employed to solving classification problem. Functional networks
are generalized neural networks, which permit the specification of
their initial topology using knowledge about the problem at hand. In
this case, and after analyzing the available data and their relations, we
systematically discuss a numerical analysis method used for
functional network, and apply two functional network models to
solving XOR problem. The XOR problem that cannot be solved with
two-layered neural network can be solved by two-layered functional
network, which reveals a potent computational power of functional
networks, and the performance of the proposed model was validated
using classification problems.
Abstract: This paper proposes the analysis and design of robust
fuzzy control to Stochastic Parametrics Uncertaint Linear systems.
This system type to be controlled is partitioned into several linear
sub-models, in terms of transfer function, forming a convex polytope,
similar to LPV (Linear Parameters Varying) system. Once defined the
linear sub-models of the plant, these are organized into fuzzy Takagi-
Sugeno (TS) structure. From the Parallel Distributed Compensation
(PDC) strategy, a mathematical formulation is defined in the frequency
domain, based on the gain and phase margins specifications,
to obtain robust PI sub-controllers in accordance to the Takagi-
Sugeno fuzzy model of the plant. The main results of the paper are
based on the robust stability conditions with the proposal of one
Axiom and two Theorems.
Abstract: This paper proposes an architecture of dynamically
reconfigurable arithmetic circuit. Dynamic reconfiguration is a
technique to realize required functions by changing hardware
construction during operations. The proposed circuit is based on a
complex number multiply-accumulation circuit which is used
frequently in the field of digital signal processing. In addition, the
proposed circuit performs real number double precision arithmetic
operations. The data formats are single and double precision floating
point number based on IEEE754. The proposed circuit is designed
using VHDL, and verified the correct operation by simulations and
experiments.
Abstract: Westudy a dual-channel supply chain under
decentralized setting in which manufacturer sells to retailer and to
customers directly usingan online channel. A customer chooses the
purchase-channel based on price and service quality. Also, to buy
product from the retail store, the customer incurs a transportation cost
influenced by the fluctuating gasoline cost. Both companies are under
the revenue sharing contract. In this contract the retailer share a
portion of the revenue to the manufacturer while the manufacturer
will charge the lower wholesales price. The numerical result shows
that the effects of gasoline costs, the revenue sharing ratio and the
wholesale price play an important role in determining optimal prices.
The result shows that when the gasoline price fluctuatesthe optimal
on-line priceis relatively stable while the optimal retail price moves
in the opposite direction of the gasoline prices.
Abstract: Renewable energy resources are inexhaustible, clean as compared with conventional resources. Also, it is used to supply regions with no grid, no telephone lines, and often with difficult accessibility by common transport. Satellite earth stations which located in remote areas are the most important application of renewable energy. Neural control is a branch of the general field of intelligent control, which is based on the concept of artificial intelligence. This paper presents the mathematical modeling of satellite earth station power system which is required for simulating the system.Aswan is selected to be the site under consideration because it is a rich region with solar energy. The complete power system is simulated using MATLAB–SIMULINK.An artificial neural network (ANN) based model has been developed for the optimum operation of earth station power system. An ANN is trained using a back propagation with Levenberg–Marquardt algorithm. The best validation performance is obtained for minimum mean square error. The regression between the network output and the corresponding target is equal to 96% which means a high accuracy. Neural network controller architecture gives satisfactory results with small number of neurons, hence better in terms of memory and time are required for NNC implementation. The results indicate that the proposed control unit using ANN can be successfully used for controlling the satellite earth station power system.
Abstract: This paper reports a new and accurate method for load-flow solution of radial distribution networks with minimum data preparation. The node and branch numbering need not to be sequential like other available methods. The proposed method does not need sending-node, receiving-node and branch numbers if these are sequential. The proposed method uses the simple equation to compute the voltage magnitude and has the capability to handle composite load modelling. The proposed method uses the set of nodes of feeder, lateral(s) and sub lateral(s). The effectiveness of the proposed method is compared with other methods using two examples. The detailed load-flow results for different kind of load-modellings are also presented.