Abstract: This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.
Abstract: This paper describes identification of the two poles
unstable SOPDT process, especially with large time delay. A new
modified relay feedback identification method for two poles unstable
SOPDT process is proposed. Furthermore, for the two poles unstable
SOPDT process, an additional Derivative controller is incorporated
parallel with relay to relax the constraint on the ratio of delay to the
unstable time constant, so that the exact model parameters of
unstable processes can be identified. To cope with measurement
noise in practice, a low pass filter is suggested to get denoised output
signal toimprove the exactness of model parameter of unstable
process. PID Lead-lag tuning formulas are derived for two poles
unstable (SOPDT) processes based on IMC principle. Simulation
example illustrates the effectiveness and the simplicity of the
proposed identification and control method.
Abstract: This paper summarizes and compares approaches to
solving the knapsack problem and its known application in capital
budgeting. The first approach uses deterministic methods and can be
applied to small-size tasks with a single constraint. We can also
apply commercial software systems such as the GAMS modelling
system. However, because of NP-completeness of the problem, more
complex problem instances must be solved by means of heuristic
techniques to achieve an approximation of the exact solution in a
reasonable amount of time. We show the problem representation and
parameter settings for a genetic algorithm framework.
Abstract: The aim of this paper is to present a new
three-dimensional proportional-pursuit coupled (PP) guidance law to
track highly maneuverable aircraft. Utilizing a 3-D polar coordinate frame, the PP guidance law is formed by collecting proportional
navigation guidance in Z-R plane and pursuit guidance in X-Y plane.
Feedback linearization control method to solve the guidance
accelerations is used to implement PP guidance. In order to
compensate the actuator time delay, the time delay compensated
version of PP guidance law (CPP) was derived and proved the
effectiveness of modifying the problem of high acceleration in the final
phase of pursuit guidance and improving the weak robustness of
proportional navigation. The simulation results for intercepting Max G
turn situation show that the proposed proportional-pursuit coupled
guidance law guidance law with actuator delay compensation (CPP)
possesses satisfactory robustness and performance.
Abstract: In this paper we introduce some subspaces of fuzzy entire sequence space. Some general properties of these sequence spaces are discussed. Also some inclusion relation involving the spaces are obtained. Mathematics Subject Classification: 40A05, 40D25.
Abstract: Unmanned Aerial Vehicles (UAVs) have gained tremendous importance, in both Military and Civil, during first decade of this century. In a UAV, onboard computer (autopilot) autonomously controls the flight and navigation of the aircraft. Based on the aircraft role and flight envelope, basic to complex and sophisticated controllers are used to stabilize the aircraft flight parameters. These controllers constitute the autopilot system for UAVs. The autopilot systems, most commonly, provide lateral and longitudinal control through Proportional-Integral-Derivative (PID) controllers or Phase-lead or Lag Compensators. Various techniques are commonly used to ‘tune’ gains of these controllers. Some techniques used are, in-flight step-by-step tuning, software-in-loop or hardware-in-loop tuning methods. Subsequently, numerous in-flight tests are required to actually ‘fine-tune’ these gains. However, an optimization-based tuning of these PID controllers or compensators, as presented in this paper, can greatly minimize the requirement of in-flight ‘tuning’ and substantially reduce the risks and cost involved in flight-testing.
Abstract: This paper discusses a new heavy tailed distribution based data hiding into discrete cosine transform (DCT) coefficients of image, which provides statistical security as well as robustness against steganalysis attacks. Unlike other data hiding algorithms, the proposed technique does not introduce much effect in the stegoimage-s DCT coefficient probability plots, thus making the presence of hidden data statistically undetectable. In addition the proposed method does not compromise on hiding capacity. When compared to the generic block DCT based data-hiding scheme, our method found more robust against a variety of image manipulating attacks such as filtering, blurring, JPEG compression etc.
Abstract: This paper presents a comparative study on dry and wet grinding through experimental investigation in the grinding of CSM glass fibre reinforced polymer laminates using a pink aluminium oxide wheel. Different sets of experiments were performed to study the effects of the independent grinding parameters such as grinding wheel speed, feed and depth of cut on dependent performance criteria such as cutting forces and surface finish. Experimental conditions were laid out using design of experiment central composite design. An effective coolant was sought in this study to minimise cutting forces and surface roughness for GFRP laminates grinding. Test results showed that the use of coolants reduces surface roughness, although not necessarily the cutting forces. These research findings provide useful economic machining solution in terms of optimized grinding conditions for grinding CSM GFRP.
Abstract: The basic aim of our study is to give a possible model for handling uncertain information. This model is worked out in the framework of DATALOG. The concept of multivalued knowledgebase will be defined as a quadruple of any background knowledge; a deduction mechanism; a connecting algorithm, and a function set of the program, which help us to determine the uncertainty levels of the results. At first the concept of fuzzy Datalog will be summarized, then its extensions for intuitionistic- and interval-valued fuzzy logic is given and the concept of bipolar fuzzy Datalog is introduced. Based on these extensions the concept of multivalued knowledge-base will be defined. This knowledge-base can be a possible background of a future agent-model.
Abstract: In Egypt, the concept of Asset Management (AM) is
new; however, the need for applying it has become crucial because
deteriorating or losing an asset is unaffordable in a developing
country like Egypt. Therefore the current study focuses on
educational buildings as one of the most important assets regarding
planning, building, operating and maintenance expenditures. The
main objective of this study is to develop a SAMF for educational
buildings in Egypt. The General Authority for Educational Buildings
(GAEB) was chosen as a case study of the current research as it
represents the biggest governmental organization responsible for
planning, operating and maintaining schools in Egypt. To achieve the
research objective, structured interviews were conducted with senior
managers of GAEB using a pre designed questionnaire to explore the
current practice of AM. Gab analysis technique was applied against
best practices compounded from a vast literature review to identify
gaps between current practices and the desired one. The previous
steps mainly revealed; limited knowledge about strategic asset
management, no clear goals, no training, no real risk plan and lack of
data, technical and financial resources. Based on the findings, a
SAMF for GAEB was introduced and Framework implementation
steps and assessment techniques were explained in detail.
Abstract: Finding suitable non-supersingular elliptic curves for
pairing-based cryptosystems becomes an important issue for the
modern public-key cryptography after the proposition of id-based
encryption scheme and short signature scheme. In previous work
different algorithms have been proposed for finding such elliptic
curves when embedding degree k ∈ {3, 4, 6} and cofactor h ∈ {1, 2, 3,
4, 5}. In this paper a new method is presented to find more
non-supersingular elliptic curves for pairing-based cryptosystems with
general embedding degree k and large values of cofactor h. In
addition, some effective parameters of these non-supersingular elliptic
curves are provided in this paper.
Abstract: Turbulence of the incoming wind field is of paramount
importance to the dynamic response of civil engineering structures. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and
structural safety analysis. In the paper an empirical cross spectral
density function for the along-wind turbulence component over the wind field area is taken as the starting point. The spectrum is spatially
discretized in terms of a Hermitian cross-spectral density matrix for the turbulence state vector which turns out not to be positive
definite. Since the succeeding state space and ARMA modelling of
the turbulence rely on the positive definiteness of the cross-spectral
density matrix, the problem with the non-positive definiteness of such
matrices is at first addressed and suitable treatments regarding it are proposed. From the adjusted positive definite cross-spectral density
matrix a frequency response matrix is constructed which determines the turbulence vector as a linear filtration of Gaussian white noise.
Finally, an accurate state space modelling method is proposed which allows selection of an appropriate model order, and estimation of a state space model for the vector turbulence process incorporating its phase spectrum in one stage, and its results are compared with a conventional ARMA modelling method.
Abstract: This paper proposes a model of adding relations between
members of the same level in a pyramid organization structure
which is a complete K-ary tree such that the communication of
information between every member in the organization becomes the
most efficient. When edges between one node and every other node
with the same depth N in a complete K-ary tree of height H are
added, an optimal depth N* = H is obtained by minimizing the total
path length which is the sum of lengths of shortest paths between
every pair of all nodes.
Abstract: This work is devoted to the calculation of the
undulatory parameters and the study of the influence of te number
parallel path of a winding on overvoltage compared to the frame and
between turns (sections) in a multiturn random winding of an
asynchronous motors supplied with PWM- converters.
Abstract: This paper presents an algorithm based on the
wavelet decomposition, for feature extraction from the ECG signal
and recognition of three types of Ventricular Arrhythmias using
neural networks. A set of Discrete Wavelet Transform (DWT)
coefficients, which contain the maximum information about the
arrhythmias, is selected from the wavelet decomposition. After that a
novel clustering algorithm based on nature inspired algorithm (Ant
Colony Optimization) is developed for classifying arrhythmia types.
The algorithm is applied on the ECG registrations from the MIT-BIH
arrhythmia and malignant ventricular arrhythmia databases. We
applied Daubechies 4 wavelet in our algorithm. The wavelet
decomposition enabled us to perform the task efficiently and
produced reliable results.
Abstract: Behavior of dams against the seismic loads has been
studied by many researchers. Most of them proposed new numerical
methods to investigate the dam safety. In this paper, to study the
effect of nonlinear parameters of concrete in gravity dams, a twodimensional
approach was used including the finite element method,
staggered method and smeared crack approach. Effective parameters
in the models are physical properties of concrete such as modulus of
elasticity, tensile strength and specific fracture energy. Two different
models were used in foundation (mass-less and massed) in order to
determine the seismic response of concrete gravity dams. Results
show that when the nonlinear analysis includes the dam- foundation
interaction, the foundation-s mass, flexibility and radiation damping
are important in gravity dam-s response.
Abstract: This paper investigates the effects of lubrication on
the quantity of heat emission of two spur gear. System with and
without lubrication effected on the quantity of heat induced on the
gear box (oil - bearings – gears). Both of lubrication and speed of
motor are affected on the performance of gears. Research investigated
the lubrication on the system with and without loading as well as the
wear of gears and bearing's conditions. Gear box investigated
includes the motor, pump, two spur gears, two shafts; speed change
used pulleys and belts. Load used equal one weight ones of gear.
Lubrication mechanism used jet system (upper and lower jet). Gear
box we used system of jet lubrication is perpendicular direction of
the contact line between two teeth. Results appeared in this work that
the lubrication is the vital parameter which is affected on the
performance and durability of gears and bearings. In macroscopic
observation, we noted that damage of bearings happened during the
absence of lubrication as well as abrasive of wear of teeth. Higher
speed of motor without lubrication increased the noise, but in the
presence of lubrication was decreased.
Abstract: Inferring the network structure from time series data
is a hard problem, especially if the time series is short and noisy.
DNA microarray is a technology allowing to monitor the mRNA
concentration of thousands of genes simultaneously that produces
data of these characteristics. In this study we try to investigate the
influence of the experimental design on the quality of the result.
More precisely, we investigate the influence of two different types of
random single gene perturbations on the inference of genetic networks
from time series data. To obtain an objective quality measure for
this influence we simulate gene expression values with a biologically
plausible model of a known network structure. Within this framework
we study the influence of single gene knock-outs in opposite to
linearly controlled expression for single genes on the quality of the
infered network structure.
Abstract: This paper describes a rapid prototyping (RP)
technology for forming a hydroxyapatite (HA) bone scaffold model.
The HA powder and a silica sol are mixed into bioceramic slurry form
under a suitable viscosity. The HA particles are embedded in the
solidified silica matrix to form green parts via a wide range of process
parameters after processing by selective laser sintering (SLS). The
results indicate that the proposed process was possible to fabricate
multilayers and hollow shell structure with brittle property but
sufficient integrity for handling prior to post-processing. The
fabricated bone scaffold models had a surface finish of 25
Abstract: The medical data statistical analysis often requires the
using of some special techniques, because of the particularities of
these data. The principal components analysis and the data clustering
are two statistical methods for data mining very useful in the medical
field, the first one as a method to decrease the number of studied
parameters, and the second one as a method to analyze the
connections between diagnosis and the data about the patient-s
condition. In this paper we investigate the implications obtained from
a specific data analysis technique: the data clustering preceded by a
selection of the most relevant parameters, made using the principal
components analysis. Our assumption was that, using the principal
components analysis before data clustering - in order to select and to
classify only the most relevant parameters – the accuracy of
clustering is improved, but the practical results showed the opposite
fact: the clustering accuracy decreases, with a percentage
approximately equal with the percentage of information loss reported
by the principal components analysis.