Abstract: New Growth Theory helps us make sense of the
ongoing shift from a resource-based economy to a knowledge-based
economy. It underscores the point that the economic processes which
create and diffuse new knowledge are critical to shaping the growth
of nations, communities and individual firms. In all too many
contributions to New (Endogenous) Growth Theory – though not in
all – central reference is made to 'a stock of knowledge', a 'stock of
ideas', etc., this variable featuring centre-stage in the analysis. Yet it
is immediately apparent that this is far from being a crystal clear
concept. The difficulty and uncertainty of being able to capture the
value associated with knowledge is a real problem. The intent of this
paper is introducing new thinking and theorizing about the
knowledge and its measurability in new growth theory. Moreover the
study aims to synthesize various strain of the literature with a
practical bearing on knowledge concept. By contribution of
institution framework which is found within NGT, we can indirectly
measure the knowledge concept. Institutions matter because they
shape the environment for production and employment of new
knowledge
Abstract: Warranty is a powerful marketing tool for the
manufacturer and a good protection for both the manufacturer and the
customer. However, warranty always involves additional costs to the
manufacturer, which depend on product reliability characteristics and
warranty parameters. This paper presents an approach to optimisation
of warranty parameters for known product failure distribution to
reduce the warranty costs to the manufacturer while retaining the
promotional function of the warranty. Combination free replacement
and pro-rata warranty policy is chosen as a model and the length of
free replacement period and pro-rata policy period are varied, as well
as the coefficients that define the pro-rata cost function. Multiparametric
warranty optimisation is done by using genetic algorithm.
Obtained results are guideline for the manufacturer to choose the
warranty policy that minimises the costs and maximises the profit.
Abstract: This paper presents ageing experiments controlled by the evolution of junction parameters. The deterioration of the device is related to high injection effects which modified the transport mechanisms in the space charge region of the junction. Physical phenomena linked to the degradation of junction parameters that affect the devices reliability are reported and discussed. We have used the method based on numerical analysis of experimental current-voltage characteristic of the junction, in order to extract the electrical parameters. The simultaneous follow-up of the evolutions of the series resistance and of the transition voltage allow us to introduce a new parameter for reliability evaluation.
Abstract: This paper presents a Particle Swarm Optimization
(PSO) method for determining the optimal parameters of a first-order
controller for TCP/AQM system. The model TCP/AQM is described
by a second-order system with time delay. First, the analytical
approach, based on the D-decomposition method and Lemma of
Kharitonov, is used to determine the stabilizing regions of a firstorder
controller. Second, the optimal parameters of the controller are
obtained by the PSO algorithm. Finally, the proposed method is
implemented in the Network Simulator NS-2 and compared with the
PI controller.
Abstract: This paper is concerned with the delay-distributiondependent
stability criteria for bidirectional associative memory
(BAM) neural networks with time-varying delays. Based on the
Lyapunov-Krasovskii functional and stochastic analysis approach,
a delay-probability-distribution-dependent sufficient condition is derived
to achieve the globally asymptotically mean square stable of
the considered BAM neural networks. The criteria are formulated in
terms of a set of linear matrix inequalities (LMIs), which can be
checked efficiently by use of some standard numerical packages. Finally,
a numerical example and its simulation is given to demonstrate
the usefulness and effectiveness of the proposed results.
Abstract: In this paper, based on the estimation of the Cauchy matrix of linear impulsive differential equations, by using Banach fixed point theorem and Gronwall-Bellman-s inequality, some sufficient conditions are obtained for the existence and exponential stability of almost periodic solution for Cohen-Grossberg shunting inhibitory cellular neural networks (SICNNs) with continuously distributed delays and impulses. An example is given to illustrate the main results.
Abstract: Airport capacity has always been perceived in the
traditional sense as the number of aircraft operations during a
specified time corresponding to a tolerable level of average delay and
it mostly depends on the airside characteristics, on the fleet mix
variability and on the ATM. The adoption of the Directive
2002/30/EC in the EU countries drives the stakeholders to conceive
airport capacity in a different way though. Airport capacity in this
sense is fundamentally driven by environmental criteria, and since
acoustical externalities represent the most important factors, those are
the ones that could pose a serious threat to the growth of airports and
to aviation market itself in the short-medium term. The importance of
the regional airports in the deregulated market grew fast during the
last decade since they represent spokes for network carriers and a
preferential destination for low-fares carriers. Not only regional
airports have witnessed a fast and unexpected growth in traffic but
also a fast growth in the complaints for the nuisance by the people
living near those airports. In this paper the results of a study
conducted in cooperation with the airport of Bologna G. Marconi are
presented in order to investigate airport acoustical capacity as a defacto
constraint of airport growth.
Abstract: Antimicrobial resistant is becoming a major factor in
virtually all hospital acquired infection may soon untreatable is a
serious public health problem. These concerns have led to major
research effort to discover alternative strategies for the treatment of
bacterial infection. Nanobiotehnology is an upcoming and fast
developing field with potential application for human welfare. An
important area of nanotechnology for development of reliable and
environmental friendly process for synthesis of nanoscale particles
through biological systems In the present studies are reported on the
use of fungal strain Aspergillus species for the extracellular synthesis
of bionanoparticles from 1 mM silver nitrate (AgNO3) solution. The
report would be focused on the synthesis of metallic bionanoparticles
of silver using a reduction of aqueous Ag+ ion with the
culture supernatants of Microorganisms. The bio-reduction of the
Ag+ ions in the solution would be monitored in the aqueous
component and the spectrum of the solution would measure through
UV-visible spectrophotometer The bionanoscale particles were
further characterized by Atomic Force Microscopy (AFM), Fourier
Transform Infrared Spectroscopy (FTIR) and Thin layer
chromatography. The synthesized bionanoscale particle showed a
maximum absorption at 385 nm in the visible region. Atomic Force
Microscopy investigation of silver bionanoparticles identified that
they ranged in the size of 250 nm - 680 nm; the work analyzed the
antimicrobial efficacy of the silver bionanoparticles against various
multi drug resistant clinical isolates. The present Study would be
emphasizing on the applicability to synthesize the metallic
nanostructures and to understand the biochemical and molecular
mechanism of nanoparticles formation by the cell filtrate in order to
achieve better control over size and polydispersity of the
nanoparticles. This would help to develop nanomedicine against
various multi drug resistant human pathogens.
Abstract: Chua’s circuit is one of the most important electronic devices that are used for Chaos and Bifurcation studies. A central role of secure communication is devoted to it. Since the adaptive control is used vastly in the linear systems control, here we introduce a new trend of application of adaptive method in the chaos controlling field. In this paper, we try to derive a new adaptive control scheme for Chua’s circuit controlling because control of chaos is often very important in practical operations. The novelty of this approach is for sake of its robustness against the external perturbations which is simulated as an additive noise in all measured states and can be generalized to other chaotic systems. Our approach is based on Lyapunov analysis and the adaptation law is considered for the feedback gain. Because of this, we have named it NAFT (Nonlinear Adaptive Feedback Technique). At last, simulations show the capability of the presented technique for Chua’s circuit.
Abstract: Grid networks provide the ability to perform higher throughput computing by taking advantage of many networked computer-s resources to solve large-scale computation problems. As the popularity of the Grid networks has increased, there is a need to efficiently distribute the load among the resources accessible on the network. In this paper, we present a stochastic network system that gives a distributed load-balancing scheme by generating almost regular networks. This network system is self-organized and depends only on local information for load distribution and resource discovery. The in-degree of each node is refers to its free resources, and job assignment and resource discovery processes required for load balancing is accomplished by using fitted random sampling. Simulation results show that the generated network system provides an effective, scalable, and reliable load-balancing scheme for the distributed resources accessible on Grid networks.
Abstract: Importance of software quality is increasing leading to development of new sophisticated techniques, which can be used in constructing models for predicting quality attributes. One such technique is Artificial Neural Network (ANN). This paper examined the application of ANN for software quality prediction using Object- Oriented (OO) metrics. Quality estimation includes estimating maintainability of software. The dependent variable in our study was maintenance effort. The independent variables were principal components of eight OO metrics. The results showed that the Mean Absolute Relative Error (MARE) was 0.265 of ANN model. Thus we found that ANN method was useful in constructing software quality model.
Abstract: The purpose of this paper isunavailability of the two main types of conveSwedish traction power supply (TPS) system, i.e.static converter. The number of outages and the ouused to analyze and compare the unavailability oconverters. The mean cumulative function (MCF)analyze the number of outages and the unavailabthe forced outage rate (FOR) concept has been uoutage rates. The study shows that the outagesfailure occur at a constant rate by calendar timconverter stations, while very few stations havedecreasing rate. It has also been found that the stata higher number of outages and a higher outage ratcompared to the rotary converter types. The resultsthat combining the number of outages and the fgives a better view of the converters performasupport for the maintenance decision. In fact, usingdoes not reflect reality. Comparing these two indein identifying the areas where extra resources are maintenance planning and where improvementsoutage in the TPS system.KeywordsFrequency Converter, Forced OuCumulative Function, Traction Power Supply, ESystems.
Abstract: The paradigm of mobile agent provides a promising technology for the development of distributed and open applications. However, one of the main obstacles to widespread adoption of the mobile agent paradigm seems to be security. This paper treats the security of the mobile agent against malicious host attacks. It describes generic mobile agent protection architecture. The proposed approach is based on the dynamic adaptability and adopts the reflexivity as a model of conception and implantation. In order to protect it against behaviour analysis attempts, the suggested approach supplies the mobile agent with a flexibility faculty allowing it to present an unexpected behaviour. Furthermore, some classical protective mechanisms are used to reinforce the level of security.
Abstract: The last decade has shown that object-oriented
concept by itself is not that powerful to cope with the rapidly
changing requirements of ongoing applications. Component-based
systems achieve flexibility by clearly separating the stable parts of
systems (i.e. the components) from the specification of their
composition. In order to realize the reuse of components effectively
in CBSD, it is required to measure the reusability of components.
However, due to the black-box nature of components where the
source code of these components are not available, it is difficult to
use conventional metrics in Component-based Development as these
metrics require analysis of source codes. In this paper, we survey
few existing component-based reusability metrics. These metrics
give a border view of component-s understandability, adaptability,
and portability. It also describes the analysis, in terms of quality
factors related to reusability, contained in an approach that aids
significantly in assessing existing components for reusability.
Abstract: The problem of estimating time-varying regression is
inevitably concerned with the necessity to choose the appropriate
level of model volatility - ranging from the full stationarity of instant
regression models to their absolute independence of each other. In the
stationary case the number of regression coefficients to be estimated
equals that of regressors, whereas the absence of any smoothness
assumptions augments the dimension of the unknown vector by the
factor of the time-series length. The Akaike Information Criterion
is a commonly adopted means of adjusting a model to the given
data set within a succession of nested parametric model classes,
but its crucial restriction is that the classes are rigidly defined by
the growing integer-valued dimension of the unknown vector. To
make the Kullback information maximization principle underlying the
classical AIC applicable to the problem of time-varying regression
estimation, we extend it onto a wider class of data models in which
the dimension of the parameter is fixed, but the freedom of its values
is softly constrained by a family of continuously nested a priori
probability distributions.
Abstract: A human verification system is presented in this
paper. The system consists of several steps: background subtraction,
thresholding, line connection, region growing, morphlogy, star
skelatonization, feature extraction, feature matching, and decision
making. The proposed system combines an advantage of star
skeletonization and simple statistic features. A correlation matching
and probability voting have been used for verification, followed by a
logical operation in a decision making stage. The proposed system
uses small number of features and the system reliability is
convincing.
Abstract: Nigeria is considered as one of the many countries in
sub-Saharan Africa with a weak economy and gross deficiencies in technology and engineering. Available data from international monitoring and regulatory organizations show that technology is pivotal to determining the economic strengths of nations all over the
world. Education is critical to technology acquisition, development,
dissemination and adaptation. Thus, this paper seeks to critically
assess and discuss issues and challenges facing technological
advancement in Nigeria, particularly in the education sector, and also
proffers solutions to resuscitate the Nigerian education system
towards achieving national technological and economic sustainability
such that Nigeria can compete favourably with other technologicallydriven
economies of the world in the not-too-distant future.
Abstract: Multiprocessor task scheduling is a NP-hard problem and Genetic Algorithm (GA) has been revealed as an excellent technique for finding an optimal solution. In the past, several methods have been considered for the solution of this problem based on GAs. But, all these methods consider single criteria and in the present work, minimization of the bi-criteria multiprocessor task scheduling problem has been considered which includes weighted sum of makespan & total completion time. Efficiency and effectiveness of genetic algorithm can be achieved by optimization of its different parameters such as crossover, mutation, crossover probability, selection function etc. The effects of GA parameters on minimization of bi-criteria fitness function and subsequent setting of parameters have been accomplished by central composite design (CCD) approach of response surface methodology (RSM) of Design of Experiments. The experiments have been performed with different levels of GA parameters and analysis of variance has been performed for significant parameters for minimisation of makespan and total completion time simultaneously.
Abstract: The first generation of Mobile Agents based Intrusion
Detection System just had two components namely data collection
and single centralized analyzer. The disadvantage of this type of
intrusion detection is if connection to the analyzer fails, the entire
system will become useless. In this work, we propose novel hybrid
model for Mobile Agent based Distributed Intrusion Detection
System to overcome the current problem. The proposed model has
new features such as robustness, capability of detecting intrusion
against the IDS itself and capability of updating itself to detect new
pattern of intrusions. In addition, our proposed model is also capable
of tackling some of the weaknesses of centralized Intrusion Detection
System models.
Abstract: A reliability, availability and maintainability (RAM) model has been built for acid gas removal plant for system analysis that will play an important role in any process modifications, if required, for achieving its optimum performance. Due to the complexity of the plant, the model was based on a Reliability Block Diagram (RBD) with a Monte Carlo simulation engine. The model has been validated against actual plant data as well as local expert opinions, resulting in an acceptable simulation model. The results from the model showed that the operation and maintenance can be further improved, resulting in reduction of the annual production loss.