Abstract: Clustering algorithms help to understand the hidden
information present in datasets. A dataset may contain intrinsic and
nested clusters, the detection of which is of utmost importance. This
paper presents a Distributed Grid-based Density Clustering algorithm
capable of identifying arbitrary shaped embedded clusters as well as
multi-density clusters over large spatial datasets. For handling
massive datasets, we implemented our method using a 'sharednothing'
architecture where multiple computers are interconnected
over a network. Experimental results are reported to establish the
superiority of the technique in terms of scale-up, speedup as well as
cluster quality.
Abstract: In this paper, by using the continuation theorem of coincidence degree theory, M-matrix theory and constructing some suitable Lyapunov functions, some sufficient conditions are obtained for the existence and global exponential stability of periodic solutions of recurrent neural networks with distributed delays and impulses on time scales. Without assuming the boundedness of the activation functions gj, hj , these results are less restrictive than those given in the earlier references.
Abstract: In this article, while it is attempted to describe the
problem and its importance, transformational leadership is studied by considering leadership theories. Issues such as the definition of
transformational leadership and its aspects are compared on the basis of the ideas of various connoisseurs and then it (transformational leadership) is examined in successful and
unsuccessful companies. According to the methodology, the
method of research, hypotheses, population and statistical sample
are investigated and research findings are analyzed by using descriptive and inferential statistical methods in the framework of
analytical tables. Finally, our conclusion is provided by considering the results of statistical tests. The final result shows that
transformational leadership is significantly higher in successful companies than unsuccessful ones P
Abstract: We report on a high-speed quantum cryptography
system that utilizes simultaneous entanglement in polarization and in
“time-bins". With multiple degrees of freedom contributing to the
secret key, we can achieve over ten bits of random entropy per detected coincidence. In addition, we collect from multiple spots o
the downconversion cone to further amplify the data rate, allowing usto achieve over 10 Mbits of secure key per second.
Abstract: Effective evaluation of software development effort is an important aspect of successful project management. Based on a large database with 4106 projects ever developed, this study statistically examines the factors that influence development effort. The factors found to be significant for effort are project size, average number of developers that worked on the project, type of development, development language, development platform, and the use of rapid application development. Among these factors, project size is the most critical cost driver. Unsurprisingly, this study found that the use of CASE tools does not necessarily reduce development effort, which adds support to the claim that the use of tools is subtle. As many of the current estimation models are rarely or unsuccessfully used, this study proposes a parsimonious parametric model for the prediction of effort which is both simple and more accurate than previous models.
Abstract: In this paper the concept of the cosets of an anti Lfuzzy
normal subgroup of a group is given. Furthermore, the group
G/A of cosets of an anti L-fuzzy normal subgroup A of a group
G is shown to be isomorphic to a factor group of G in a natural
way. Finally, we prove that if f : G1 -→ G2 is an epimorphism of
groups, then there is a one-to-one order-preserving correspondence
between the anti L-fuzzy normal subgroups of G2 and those of G1
which are constant on the kernel of f.
Abstract: Software reliability, defined as the probability of a
software system or application functioning without failure or errors
over a defined period of time, has been an important area of research
for over three decades. Several research efforts aimed at developing
models to improve reliability are currently underway. One of the
most popular approaches to software reliability adopted by some of
these research efforts involves the use of operational profiles to
predict how software applications will be used. Operational profiles
are a quantification of usage patterns for a software application. The
research presented in this paper investigates an innovative multiagent
framework for automatic creation and management of
operational profiles for generic distributed systems after their release
into the market. The architecture of the proposed Operational Profile
MAS (Multi-Agent System) is presented along with detailed
descriptions of the various models arrived at following the analysis
and design phases of the proposed system. The operational profile in
this paper is extended to comprise seven different profiles. Further,
the criticality of operations is defined using a new composed metrics
in order to organize the testing process as well as to decrease the time
and cost involved in this process. A prototype implementation of the
proposed MAS is included as proof-of-concept and the framework is
considered as a step towards making distributed systems intelligent
and self-managing.
Abstract: Optimization is often a critical issue for most system
design problems. Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, finding optimal solution to complex high
dimensional, multimodal problems often require highly
computationally expensive function evaluations and hence are
practically prohibitive. The Dynamic Approximate Fitness based
Hybrid EA (DAFHEA) model presented in our earlier work [14]
reduced computation time by controlled use of meta-models to
partially replace the actual function evaluation by approximate
function evaluation. However, the underlying assumption in
DAFHEA is that the training samples for the meta-model are
generated from a single uniform model. Situations like model
formation involving variable input dimensions and noisy data
certainly can not be covered by this assumption. In this paper we
present an enhanced version of DAFHEA that incorporates a
multiple-model based learning approach for the SVM approximator.
DAFHEA-II (the enhanced version of the DAFHEA framework) also
overcomes the high computational expense involved with additional
clustering requirements of the original DAFHEA framework. The
proposed framework has been tested on several benchmark functions
and the empirical results illustrate the advantages of the proposed
technique.
Abstract: The data measurement of mean velocity has been
taken for the wake of single circular cylinder with three different diameters for two different velocities. The effects of change in
diameter and in velocity are studied in self-similar coordinate system.
The spatial variations of velocity defect and that of the half-width
have been investigated. The results are compared with those
published by H.Schlichting. In the normalized coordinates, it is also observed that all cases except for the first station are self-similar. By attention to self-similarity profiles of mean velocity, it is observed for all the cases at the each station curves tend to zero at a same point.
Abstract: Shadow detection is still considered as one of the
potential challenges for intelligent automated video surveillance
systems. A pre requisite for reliable and accurate detection and
tracking is the correct shadow detection and classification. In such a
landscape of conditions, privacy issues add more and more
complexity and require reliable shadow detection.
In this work the intertwining between security, accuracy,
reliability and privacy is analyzed and, accordingly, a novel
architecture for Privacy Enhancing Video Surveillance (PEVS) is
introduced. Shadow detection and masking are dealt with through the
combination of two different approaches simultaneously. This results
in a unique privacy enhancement, without affecting security.
Subsequently, the methodology was employed successfully in a
large-scale wireless video surveillance system; privacy relevant
information was stored and encrypted on the unit, without
transferring it over an un-trusted network.
Abstract: Vertical ZnO nanowire array films were synthesized
based on aqueous method for sensing applications. ZnO nanowires
were investigated structurally using X-ray diffraction (XRD) and
scanning electron microscopy (SEM). The gas-sensing properties of
ZnO nanowires array films are studied. It is found that the ZnO
nanowires array film sensor exhibits excellent sensing properties
towards O2 and CO2 at 100 °C with the response time shorter than 5
s. High surface area / volume ratio of vertical ZnO nanowire and high
mobility accounts for the fast response and recovery. The sensor
response was measured in the range from 100 to 500 ppm O2 and CO2
in this study.
Abstract: The article is aimed at bringing information on the scope and the level of use of talent management by organizations in one of the Czech Republic regions, in the Moravian-Silesian Region. On the basis of data acquired by a questionnaire survey it has been found out that organizations in the above-mentioned region are implementing the system of talent management on a small scale: this approach is used by 3.8 % of organizations only that is 9 from 237 (100 %) of the approached respondents. The main reasons why this approach is not used is either that organizations have no knowledge of it or there is lack of financial and personnel resources. In the article recommendations suggested by the author can be found for a wider application of talent management in the Czech practice.
Abstract: The characterisation of agro-wastes fibres for composite applications from Nigeria using X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) has been done. Fibres extracted from groundnut shell, coconut husk, rice husk, palm fruit bunch and palm fruit stalk are processed using two novel cellulose fibre production methods developed by the authors. Cellulose apparent crystallinity calculated using the deconvolution of the diffractometer trace shows that the amorphous portion of cellulose was permeable to hydrolysis yielding high crystallinity after treatment. All diffratograms show typical cellulose structure with well-defined 110, 200 and 040 peaks. Palm fruit fibres had the highest 200 crystalline cellulose peaks compared to others and it is an indication of rich cellulose content. Surface examination of the resulting fibres using SEM indicates the presence of regular cellulose network structure with some agglomerated laminated layer of thin leaves of cellulose microfibrils. The surfaces were relatively smooth indicating the removal of hemicellulose, lignin and pectin.
Abstract: This paper develops a quality estimation method with
the application of fuzzy hierarchical clustering. Quality estimation is
essential to quality control and quality improvement as a precise
estimation can promote a right decision-making in order to help
better quality control. Normally the quality of finished products in
manufacturing system can be differentiated by quality standards. In
the real life situation, the collected data may be vague which is not
easy to be classified and they are usually represented in term of fuzzy
number. To estimate the quality of product presented by fuzzy
number is not easy. In this research, the trapezoidal fuzzy numbers
are collected in manufacturing process and classify the collected data
into different clusters so as to get the estimation. Since normal
hierarchical clustering methods can only be applied for real numbers,
fuzzy hierarchical clustering is selected to handle this problem based
on quality standards.
Abstract: The use of electronic sensors in the electronics
industry has become increasingly popular over the past few years,
and it has become a high competition product. The frequency
adjustment process is regarded as one of the most important process
in the electronic sensor manufacturing process. Due to inaccuracies
in the frequency adjustment process, up to 80% waste can be caused
due to rework processes; therefore, this study aims to provide a
preliminary understanding of the role of parameters used in the
frequency adjustment process, and also make suggestions in order to
further improve performance. Four parameters are considered in this
study: air pressure, dispensing time, vacuum force, and the distance
between the needle tip and the product. A full factorial design for
experiment 2k was considered to determine those parameters that
significantly affect the accuracy of the frequency adjustment process,
where a deviation in the frequency after adjustment and the target
frequency is expected to be 0 kHz. The experiment was conducted on
two levels, using two replications and with five center-points added.
In total, 37 experiments were carried out. The results reveal that air
pressure and dispensing time significantly affect the frequency
adjustment process. The mathematical relationship between these
two parameters was formulated, and the optimal parameters for air
pressure and dispensing time were found to be 0.45 MPa and 458 ms,
respectively. The optimal parameters were examined by carrying out
a confirmation experiment in which an average deviation of 0.082
kHz was achieved.
Abstract: This paper studies ruin probabilities in two discrete-time
risk models with premiums, claims and rates of interest modelled by
three autoregressive moving average processes. Generalized Lundberg
inequalities for ruin probabilities are derived by using recursive
technique. A numerical example is given to illustrate the applications
of these probability inequalities.
Abstract: The present work was conducted to find out the effect
of biofertilizer formulated with four species of bacteria (two species
of Azotobacter and two species of Lysobacter) and zinc sulphate.
Field experiments with mustard plant were conducted to study the
effectiveness of soil application of zinc sulphate and biofertilizer at
0, 10, 20, 30, 40, 50 days after sowing. Plant height and condition of
plant was found to be increased significantly using a mixture of
biofertilizer and zinc sulphate than other treatments after 40 days
sowing. Three treatments were also used in this field experiment such
as bacteria only, zinc sulphate only and mixture of biofertilizer and
zinc sulphate. The treatment using a mixture of zinc sulphate and
biofertilizer had the best yield (4688.008 kg/ha) within 50 days of
sowing and performed better than other treatments. Field experiment
using zinc sulphate only was second best yield (3380.75Kg/ha) and
biofertilizer only treatment gave (2639.04kg/ha).
Abstract: The Proton Exchange Membrane Fuel Cell (PEMFC)
control system has an important effect on operation of cell.
Traditional controllers couldn-t lead to acceptable responses because
of time- change, long- hysteresis, uncertainty, strong- coupling and
nonlinear characteristics of PEMFCs, so an intelligent or adaptive
controller is needed. In this paper a neural network predictive
controller have been designed to control the voltage of at the
presence of fluctuations of temperature. The results of
implementation of this designed NN Predictive controller on a
dynamic electrochemical model of a small size 5 KW, PEM fuel cell
have been simulated by MATLAB/SIMULINK.
Abstract: The research aims to study the quality of surface water
for consumer in Samut Songkram province. Water sample were
collected from 217 sampling sites conclude 72 sampling sites in
Amphawa, 67 sampling sites in Bangkhonthee and 65 sampling sites
in Muang. Water sample were collected in December 2011 for
winter, March 2012 for summer and August 2012 for rainy season.
From the investigation of surface water quality in Mae Klong
River, main and tributaries canals in Samut Songkram province, we
found that water quality meet the type III of surface water quality
standard issued by the National Environmental Quality Act B.E.
1992. Seasonal variations of pH, Temperature, nitrate, lead and
cadmium have statistical differences between 3 seasons.
Abstract: The number of electronic participation (eParticipation) projects introduced by different governments and international organisations is considerably high and increasing. In order to have an overview of the development of these projects, various evaluation frameworks have been proposed. In this paper, a five-level participation model, which takes into account the advantages of the Social Web or Web 2.0, together with a quantitative approach for the evaluation of eParticipation projects is presented. Each participation level is evaluated independently, taking into account three main components: Web evolution, media richness, and communication channels. This paper presents the evaluation of a number of existing Voting Advice Applications (VAAs). The results provide an overview of the main features implemented by each project, their strengths and weaknesses, and the participation levels reached.