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: 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: Authentication plays a vital role in many secure
systems. Most of these systems require user to log in with his or her
secret password or pass phrase before entering it. This is to ensure all
the valuables information is kept confidential guaranteeing also its
integrity and availability. However, to achieve this goal, users are
required to memorize high entropy passwords or pass phrases.
Unfortunately, this sometimes causes difficulty for user to remember
meaningless strings of data. This paper presents a new scheme which
assigns a weight to each personal question given to the user in
revealing the encrypted secrets or password. Concentration of this
scheme is to offer fault tolerance to users by allowing them to forget
the specific password to a subset of questions and still recover the
secret and achieve successful authentication. Comparison on level of
security for weight-based and weightless secret recovery scheme is
also discussed. The paper concludes with the few areas that requires
more investigation in this research.
Abstract: Internet access is a vital part of the modern world and an important tool in the education of our children. It is present in schools, homes and even shopping malls. Mastering the use of the internet is likely to be an important skill for those entering the job markets of the future. An internet user can be anyone he or she wants to be in an online chat room, or play thrilling and challenging games against other players from all corners of the globe. It seems at present time (or near future) for many people relationships in the real world may be neglected as those in the virtual world increase in importance. Internet is provided a fast mode of transportation caused freedom from family bonds and mixing with different cultures and new communities. This research is an attempt to study effect of Internet on Social capital. For this purpose a survey technique on the sample size amounted 168 students of Payame Noor University of Kermanshah city in country of Iran were considered. Degree of social capital is moderate. With the help of the Multi-variable Regression, variables of Iranian message attractive, Interest to internet with effect of positive and variable Creating a cordial atmosphere with negative effect be significant.
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: An optimal control of Reverse Osmosis (RO) plant is
studied in this paper utilizing the auto tuning concept in conjunction
with PID controller. A control scheme composing an auto tuning
stochastic technique based on an improved Genetic Algorithm (GA) is
proposed. For better evaluation of the process in GA, objective
function defined newly in sense of root mean square error has been
used. Also in order to achieve better performance of GA, more
pureness and longer period of random number generation in operation
are sought. The main improvement is made by replacing the uniform
distribution random number generator in conventional GA technique
to newly designed hybrid random generator composed of Cauchy
distribution and linear congruential generator, which provides
independent and different random numbers at each individual steps in
Genetic operation. The performance of newly proposed GA tuned
controller is compared with those of conventional ones via simulation.
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: A model based fault detection and diagnosis
technique for DC motor is proposed in this paper. Fault detection
using Kalman filter and its different variants are compared. Only
incipient faults are considered for the study. The Kalman Filter
iterations and all the related computations required for fault detection
and fault confirmation are presented. A second order linear state
space model of DC motor is used for this work. A comparative
assessment of the estimates computed from four different observers
and their relative performance is evaluated.
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: As the network based technologies become
omnipresent, demands to secure networks/systems against threat
increase. One of the effective ways to achieve higher security is
through the use of intrusion detection systems (IDS), which are a
software tool to detect anomalous in the computer or network. In this
paper, an IDS has been developed using an improved machine
learning based algorithm, Locally Linear Neuro Fuzzy Model
(LLNF) for classification whereas this model is originally used for
system identification. A key technical challenge in IDS and LLNF
learning is the curse of high dimensionality. Therefore a feature
selection phase is proposed which is applicable to any IDS. While
investigating the use of three feature selection algorithms, in this
model, it is shown that adding feature selection phase reduces
computational complexity of our model. Feature selection algorithms
require the use of a feature goodness measure. The use of both a
linear and a non-linear measure - linear correlation coefficient and
mutual information- is investigated respectively
Abstract: This paper presents a software quality support tool, a
Java source code evaluator and a code profiler based on
computational intelligence techniques. It is Java prototype software
developed by AI Group [1] from the Research Laboratories at
Universidad de Palermo: an Intelligent Java Analyzer (in Spanish:
Analizador Java Inteligente, AJI). It represents a new approach to
evaluate and identify inaccurate source code usage and transitively,
the software product itself.
The aim of this project is to provide the software development
industry with a new tool to increase software quality by extending
the value of source code metrics through computational intelligence.
Abstract: Extensive research has been devoted to economic
production quantity (EPQ) problem. However, no attention has been
paid to problems where production period length is constrained. In
this paper, we address the problem of deciding the optimal
production quantity and the number of minor setups within each
cycle, in which, production period length is constrained but a minor
setup is possible for pass the constraint. A mathematical model is
developed and Iterated Local Search (ILS) is proposed to solve this
problem. Finally, solution procedure illustrated with a numerical
example and results are analyzed.
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.
Abstract: The aim of this study was to develop a dynamic cardiac phantom for quality control in myocardial scintigraphy. The dynamic heart phantom constructed only contained the left ventricle, made of elastic material (latex), comprising two cavities: one internal and one external. The data showed a non-significant variation in the values of left ventricular ejection fraction (LVEF) obtained by varying the heart rate. It was also possible to evaluate the ejection fraction (LVEF) through different arrays of image acquisition and to perform an intercomparison of LVEF by two different scintillation cameras. The results of the quality control tests were satisfactory, showing that they can be used as parameters in future assessments. The new dynamic heart phantom was demonstrated to be effective for use in LVEF measurements. Therefore, the new heart simulator is useful for the quality control of scintigraphic cameras.
Abstract: This study examines knowledge management in the public organizations in Iran. The purpose of this article is to provide a conceptual framework for application of knowledge management in public organizations. The study indicates that an increasing tendency for implementation of knowledge management in organizations is emerging. Nonetheless knowledge management in public organizations is toddler and little has been done to bring the subject to use in the public sector. The globalization of change and popularization of some values like participation, citizen-orientation and knowledge-orientation in the new theories of public administration requires that the knowledge management is considered and attend to in the public sector. This study holds that a knowledge management framework for public organizations is different from this in the public sector, because public sector is stakeholder-dependent while the private is shareholder-dependent. Based on the research, we provide a conceptual model. The model proposed involves three factors: Organizational, knowledge citizens and contextual factors. The study results indicate these factors affect on knowledge management in public organizations in Iran.