Abstract: The optimization and control problem for 4D trajectories
is a subject rarely addressed in literature. In the 4D navigation
problem we define waypoints, for each mission, where the arrival
time is specified in each of them. One way to design trajectories for
achieving this kind of mission is to use the trajectory optimization
concepts. To solve a trajectory optimization problem we can use
the indirect or direct methods. The indirect methods are based on
maximum principle of Pontryagin, on the other hand, in the direct
methods it is necessary to transform into a nonlinear programming
problem. We propose an approach based on direct methods with a
pseudospectral integration scheme built on Chebyshev polynomials.
Abstract: In this paper, the sum of squares in linear regression is
reduced to sum of squares in semi-parametric regression. We
indicated that different sums of squares in the linear regression are
similar to various deviance statements in semi-parametric regression.
In addition to, coefficient of the determination derived in linear
regression model is easily generalized to coefficient of the
determination of the semi-parametric regression model. Then, it is
made an application in order to support the theory of the linear
regression and semi-parametric regression. In this way, study is
supported with a simulated data example.
Abstract: Laboratory experiments have been performed to investigate photocatalytic detoxification by using TiO2 photocatalyst for treating dairy effluent. Various operational parameters such as catalyst concentration, initial concentration, angle of tilt of solar flat plate reactor and flow rate were investigated. Results indicated that the photocatalytic detoxification process can efficiently treat dairy effluent. Experimental runs with dairy wastewater can be used to identify the optimum operational parameters to perform wastewater degradation on large scale for recycling purpose. Also effect of two different types of reactors on degradation process was analyzed.
Abstract: This paper aims to describe how student satisfaction is
measured for work-based learners as these are non-traditional
learners, conducting academic learning in the workplace, typically
their curricula have a high degree of negotiation, and whose
motivations are directly related to their employers- needs, as well as
their own career ambitions. We argue that while increasing WBL
participation, and use of SSD are both accepted as being of strategic
importance to the HE agenda, the use of WBL SSD is rarely
examined, and lessons can be learned from the comparison of SSD
from a range of WBL programmes, and increased visibility of this
type of data will provide insight into ways to improve and develop
this type of delivery. The key themes that emerged from the analysis
of the interview data were: learners profiles and needs, employers
drivers, academic staff drivers, organizational approach, tools for
collecting data and visibility of findings. The paper concludes with
observations on best practice in the collection, analysis and use of
WBL SSD, thus offering recommendations for both academic
managers and practitioners.
Abstract: To improve the efficiency of parametric studies or
tests planning the method is proposed, that takes into account all input parameters, but only a few simulation runs are performed to
assess the relative importance of each input parameter. For K input
parameters with N input values the total number of possible combinations of input values equals NK. To limit the number of runs,
only some (totally N) of possible combinations are taken into account. The sampling procedure Updated Latin Hypercube
Sampling is used to choose the optimal combinations. To measure the
relative importance of each input parameter, the Spearman rank
correlation coefficient is proposed. The sensitivity and the influence
of all parameters are analyzed within one procedure and the key
parameters with the largest influence are immediately identified.
Abstract: An approach of design of stable of control systems with ultimately wide ranges of uncertainly disturbed parameters is offered. The method relies on using of nonlinear structurally stable functions from catastrophe theory as controllers. Theoretical part presents an analysis of designed nonlinear second-order control systems. As more important the integrators in series, canonical controllable form and Jordan forms are considered. The analysis resumes that due to added controllers systems become stable and insensitive to any disturbance of parameters. Experimental part presents MATLAB simulation of design of control systems of epidemic spread, aircrafts angular motion and submarine depth. The results of simulation confirm the efficiency of offered method of design. KeywordsCatastrophes, robust control, simulation, uncertain parameters.
Abstract: A numerical simulation of vortex-induced vibration of
a 2-dimensional elastic circular cylinder with two degree of freedom
under the uniform flow is calculated when Reynolds is 200.
2-dimensional incompressible Navier-Stokes equations are solved
with the space-time finite element method, the equation of the cylinder
motion is solved with the new explicit integral method and the mesh
renew is achieved by the spring moving mesh technology. Considering
vortex-induced vibration with the low reduced damping parameter, the
variety trends of the lift coefficient, the drag coefficient, the
displacement of cylinder are analyzed under different oscillating
frequencies of cylinder. The phenomena of locked-in, beat and
phases-witch were captured successfully. The evolution of vortex
shedding from the cylinder with time is discussed. There are very
similar trends in characteristics between the results of the one degree
of freedom cylinder model and that of the two degree of freedom
cylinder model. The streamwise vibrations have a certain effect on the
lateral vibrations and their characteristics.
Abstract: Public housing is a vital factor in community
development. Successful city, housing and eco system regeneration
design is essential in providing positive community development.
This concerns work places, nice dwellings, providing premises for
child care, care of the elderly, providing qualitative premises for
different kinds of commercial service, providing a nice built
environment and housing areas and not the least activating tenants.
The public housing companies give value to society by stimulating
people, renovating socially and economically sustainable as well as
being partners to local business and authorities. By their activities the
housing companies contribute to sustainable local and regional
growth and the identity and reputation of cities. A Social, Economic
and Ecological Reputation Effect (SEERE) model for actions to
promote housing and community reputation is presented. The model
emphasizes regenerative actions to restore natural eco systems as part
of housing renewal strategies and to strengthen municipality
reputation.
Abstract: This paper explores the social and political imperatives in the sphere of public policy relating to social justice. In India, the colonial legacy and post-colonial social and political pressures sustained the appropriation of 'caste' category in allocating public resources to the backward class of citizens. For several reasons, 'economic' category could not be placed in allocating resources. This paper examines the reasons behind the deliberative exercises and formulating policies and seeks an alternative framework in realizing social justice in terms of a unified category. This attempt can be viewed as a reconciliation of traditional and modern values for a viable alternative in public policy making.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: The efficient use of available licensed spectrum is
becoming more and more critical with increasing demand and usage
of the radio spectrum. This paper shows how the use of spectrum as
well as dynamic spectrum management can be effectively managed
and spectrum allocation schemes in the wireless communication
systems be implemented and used, in future. This paper would be an
attempt towards better utilization of the spectrum. This research will
focus on the decision-making process mainly, with an
assumption that the radio environment has already been sensed and
the QoS requirements for the application have been specified either
by the sensed radio environment or by the secondary user itself. We
identify and study the characteristic parameters of Cognitive Radio
and use Genetic Algorithm for spectrum allocation. Performance
evaluation is done using MATLAB toolboxes.
Abstract: Small and Medium Sized Enterprises (SMEs) play an important role in many economies. In New Zealand, for example, 97% of all manufacturing companies employ less than 100 staff, and generate the predominant part of this industry sector-s economic output. Manufacturing SMEs as a group also have a significant impact on the environment. This situation is similar in many developed economies, including the European Union. Sustainable economic development therefore needs to strongly consider the role of manufacturing SMEs, who generally find it challenging to move towards more environmentally friendly business practices. This paper presents a systems thinking approach to modelling and understanding the factors which have an influence on the successful uptake of environmental practices in small and medium sized manufacturing companies. It presents a number of causal loop diagrams which have been developed based on primary action research, and a thorough understanding of the literature in this area. The systems thinking model provides the basis for further development of a strategic framework for the successful uptake of environmental innovation in manufacturing SMEs.
Abstract: TiO2 nanoparticles were synthesized by hydrothermal
method at 180°C from TiOSO4 aqueous solution with1m/l
concentration. The obtained products were coated with silica by
means of a seeded polymerization technique for a coating time of
1440 minutes to obtain well defined TiO2@SiO2 core-shell structure.
The uncoated and coated nanoparticles were characterized by using
X-Ray diffraction technique (XRD), Fourier Transform Infrared
Spectroscopy (FT-IR) to study their physico-chemical properties.
Evidence from XRD and FTIR results show that SiO2 is
homogenously coated on the surface of titania particles. FTIR spectra
show that there exists an interaction between TiO2 and SiO2 and
results in the formation of Ti-O-Si chemical bonds at the interface of
TiO2 particles and SiO2 coating layer. The non linear optical limiting
properties of TiO2 and TiO2@SiO2 nanoparticles dispersed in
ethylene glycol were studied at 532nm using 5ns Nd:YAG laser
pulses. Three-photon absorption is responsible for optical limiting
characteristics in these nanoparticles and it is seen that the optical
nonlinearity is enhanced in core-shell structures when compared with
single counterparts. This effective three-photon type absorption at
this wavelength, is of potential application in fabricating optical
limiting devices.
Abstract: Early Intervention Program (EIP) is required to
improve the overall development of children with Trisomy 21 (Down
syndrome). In order to help trainer and parent in the implementation
of EIP, a support system has been developed. The support system is
able to screen data automatically, store and analyze data, generate
individual EIP (curriculum) with optimal training duration and to
generate training automatically. The system consists of hardware and
software where the software has been implemented using Java
language and Linux Fedora. The software has been tested to ensure the
functionality and reliability. The prototype has been also tested in
Down syndrome centers. Test result shows that the system is reliable
to be used for generation of an individual curriculum which includes
the training program to improve the motor, cognitive, and combination
abilities of Down syndrome children under 6 years.
Abstract: The hydrologic time series data display periodic
structure and periodic autoregressive process receives considerable
attention in modeling of such series. In this communication long
term record of monthly waste flow of Lyari river is utilized to
quantify by using PAR modeling technique. The parameters of
model are estimated by using Frances & Paap methodology. This
study shows that periodic autoregressive model of order 2 is the most
parsimonious model for assessing periodicity in waste flow of the
river. A careful statistical analysis of residuals of PAR (2) model is
used for establishing goodness of fit. The forecast by using proposed
model confirms significance and effectiveness of the model.
Abstract: In this paper we propose a new approach to constructing the Delaunay Triangulation and the optimum algorithm for the case of multidimensional spaces (d ≥ 2). Analysing the modern state, it is possible to draw a conclusion, that the ideas for the existing effective algorithms developed for the case of d ≥ 2 are not simple to generalize on a multidimensional case, without the loss of efficiency. We offer for the solving this problem an effective algorithm that satisfies all the given requirements. But theoretical complexity of the problem it is impossible to improve as the Worst - Case Optimality for algorithms of solving such a problem is proved.
Abstract: In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.
Abstract: Laser engraving is a manufacturing method for those applications where previously Electrical Discharge Machining (EDM) was the only choice. Laser engraving technology removes material layer-by-layer and the thickness of layers is usually in the range of few microns. The aim of the present work is to investigate the influence of the process parameters on the surface quality when machined by laser engraving. The examined parameters were: the pulse frequency, the beam speed and the layer thickness. The surface quality was determined by the surface roughness for every set of parameters. Experimental results on Al7075 material showed that the surface roughness strictly depends on the process parameters used.
Abstract: Buildings with floating column are highly undesirable built in seismically active areas. Many urban multi-storey buildings today have floating column buildings which are adopted to accommodate parking at ground floor or reception lobbies in the first storey. The earthquake forces developed at different floor levels in a building need to be brought down along the height to the ground by the shortest path; any deviation or discontinuity in this load transfer path results in poor performance of the building. Floating column buildings are severely damaged during earthquake. Damage on this structure can be reduce by taking the effect of infill wall. This paper presents the effect of stiffness of infill wall to the damage occurred in floating column building when ground shakes. Modelling and analysis are carried out by non linear analysis programme IDARC-2D. Damage occurred in beams, columns, storey are studied by formulating modified Park & Ang model to evaluate damage indices. Overall structural damage indices in buildings due to shaking of ground are also obtained. Dynamic response parameters i.e. lateral floor displacement, storey drift, time period, base shear of buildings are obtained and results are compared with the ordinary moment resisting frame buildings. Formation of cracks, yield, plastic hinge, are also observed during analysis.
Abstract: In this paper, we propose an efficient hierarchical DNA
sequence search method to improve the search speed while the
accuracy is being kept constant. For a given query DNA sequence,
firstly, a fast local search method using histogram features is used as a
filtering mechanism before scanning the sequences in the database.
An overlapping processing is newly added to improve the robustness
of the algorithm. A large number of DNA sequences with low
similarity will be excluded for latter searching. The Smith-Waterman
algorithm is then applied to each remainder sequences. Experimental
results using GenBank sequence data show the proposed method
combining histogram information and Smith-Waterman algorithm is
more efficient for DNA sequence search.