Abstract: This paper is mainly concerned with the application of
a novel technique of data interpretation for classifying measurements
of plasma columns in Tokamak reactors for nuclear fusion
applications. The proposed method exploits several concepts derived
from soft computing theory. In particular, Artificial Neural Networks
and Multi-Class Support Vector Machines have been exploited to
classify magnetic variables useful to determine shape and position of
the plasma with a reduced computational complexity. The proposed
technique is used to analyze simulated databases of plasma equilibria
based on ITER geometry configuration. As well as demonstrating the
successful recovery of scalar equilibrium parameters, we show that
the technique can yield practical advantages compared with earlier
methods.
Abstract: In this paper we present the information life cycle and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here corresponds not just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise and in a manufacturing enterprise.
Abstract: Cryptographic algorithms play a crucial role in the
information society by providing protection from unauthorized
access to sensitive data. It is clear that information technology will
become increasingly pervasive, Hence we can expect the emergence
of ubiquitous or pervasive computing, ambient intelligence. These
new environments and applications will present new security
challenges, and there is no doubt that cryptographic algorithms and
protocols will form a part of the solution. The efficiency of a public
key cryptosystem is mainly measured in computational overheads,
key size and bandwidth. In particular the RSA algorithm is used in
many applications for providing the security. Although the security
of RSA is beyond doubt, the evolution in computing power has
caused a growth in the necessary key length. The fact that most chips
on smart cards can-t process key extending 1024 bit shows that there
is need for alternative. NTRU is such an alternative and it is a
collection of mathematical algorithm based on manipulating lists of
very small integers and polynomials. This allows NTRU to high
speeds with the use of minimal computing power. NTRU (Nth degree
Truncated Polynomial Ring Unit) is the first secure public key
cryptosystem not based on factorization or discrete logarithm
problem. This means that given sufficient computational resources
and time, an adversary, should not be able to break the key. The
multi-party communication and requirement of optimal resource
utilization necessitated the need for the present day demand of
applications that need security enforcement technique .and can be
enhanced with high-end computing. This has promoted us to develop
high-performance NTRU schemes using approaches such as the use
of high-end computing hardware. Peer-to-peer (P2P) or enterprise
grids are proven as one of the approaches for developing high-end
computing systems. By utilizing them one can improve the
performance of NTRU through parallel execution. In this paper we
propose and develop an application for NTRU using enterprise grid
middleware called Alchemi. An analysis and comparison of its
performance for various text files is presented.
Abstract: The article deals with the relation between rainfall in selected months and subsequent weed infestation of spring barley. The field experiment was performed at Mendel University agricultural enterprise in Žabčice, Czech Republic. Weed infestation was measured in spring barley vegetation in years 2004 to 2012. Barley was grown in three tillage variants: conventional tillage technology (CT), minimization tillage technology (MT), and no tillage (NT). Precipitation was recorded in one-day intervals. Monthly precipitation was calculated from the measured values in the months of October through to April. The technique of canonical correspondence analysis was applied for further statistical processing. 41 different species of weeds were found in the course of the 9-year monitoring period. The results clearly show that precipitation affects the incidence of most weed species in the selected months, but acts differently in the monitored variants of tillage technologies.
Abstract: This paper presents the development of analysis tools
for Home Agriculture project. The tools are required for monitoring
the condition of greenhouse which involves two components:
measurement hardware and data analysis engine. Measurement
hardware is functioned to measure environment parameters such as
temperature, humidity, air quality, dust and etc while analysis tool is
used to analyse and interpret the integrated data against the condition
of weather, quality of health, irradiance, quality of soil and etc. The
current development of the tools is completed for off-line data
recorded technique. The data is saved in MMC and transferred via
ZigBee to Environment Data Manager (EDM) for data analysis.
EDM converts the raw data and plot three combination graphs. It has
been applied in monitoring three months data measurement for
irradiance, temperature and humidity of the greenhouse..
Abstract: We presented results of research aimed on findings
influence of social - psychological training (realized with students of
Constantine the Philosopher University- future teachers within their
undergraduate preparation) on the choice of intrapersonal and
interpersonal features. After social- psychological training using
Interpersonal Check List (ICL) we found out shift of behavior to
more adaptive forms in categories, which are characterized by
extroversive friendly behavior, willingness to cooperation,
conformity regard to social situation, responsible and regardful
behavior.
Using State-Trait Anxiety Inventory (STAI) we found out the cut
down of state anxiety and of trait anxiety. The report was processed
within grants KEGA 3/5269/07 and VEGA 1/3675/06.
Abstract: This paper discusses a design of nonlinear observer by
a formal linearization method using an application of Chebyshev Interpolation
in order to facilitate processes for synthesizing a nonlinear
observer and to improve the precision of linearization.
A dynamic nonlinear system is linearized with respect to a linearization
function, and a measurement equation is transformed into
an augmented linear one by the formal linearization method which is
based on Chebyshev interpolation. To the linearized system, a linear
estimation theory is applied and a nonlinear observer is derived. To
show effectiveness of the observer design, numerical experiments
are illustrated and they indicate that the design shows remarkable
performances for nonlinear systems.
Abstract: What influences microsystems (MEMS) and nanosystems (NEMS) innovation teams apart from technology complexity? Based on in-depth interviews with innovators, this research explores the key influences on innovation teams in the early phases of MEMS/NEMS. Projects are rare and may last from 5 to 10 years or more from idea to concept. As fundamental technology development in MEMS/NEMS is highly complex and interdisciplinary by involving expertise from different basic and engineering disciplines, R&D is rather a 'testing of ideas' with many uncertainties than a clearly structured process. The purpose of this study is to explore the innovation teams- environment and give specific insights for future management practices. The findings are grouped into three major areas: people, know-how and experience, and market. The results highlight the importance and differences of innovation teams- composition, transdisciplinary knowledge, project evaluation and management compared to the counterparts from new product development teams.
Abstract: The governing two-dimensional equations of a heterogeneous material composed of a fluid (allowed to flow in the absence of acoustic excitations) and a crystalline piezoelectric cubic solid stacked one-dimensionally (along the z direction) are derived and special emphasis is given to the discussion of acoustic group velocity for the structure as a function of the wavenumber component perpendicular to the stacking direction (being the x axis). Variations in physical parameters with y are neglected assuming infinite material homogeneity along the y direction and the flow velocity is assumed to be directed along the x direction. In the first part of the paper, the governing set of differential equations are derived as well as the imposed boundary conditions. Solutions are provided using Hamilton-s equations for the wavenumber vs. frequency as a function of the number and thickness of solid layers and fluid layers in cases with and without flow (also the case of a position-dependent flow in the fluid layer is considered). In the first part of the paper, emphasis is given to the small-frequency case. Boundary conditions at the bottom and top parts of the full structure are left unspecified in the general solution but examples are provided for the case where these are subject to rigid-wall conditions (Neumann boundary conditions in the acoustic pressure). In the second part of the paper, emphasis is given to the general case of larger frequencies and wavenumber-frequency bandstructure formation. A wavenumber condition for an arbitrary set of consecutive solid and fluid layers, involving four propagating waves in each solid region, is obtained again using the monodromy matrix method. Case examples are finally discussed.
Abstract: Diabetes mellitus (DM) is frequently characterized by
autonomic nervous dysfunction. Analysis of heart rate variability
(HRV) has become a popular noninvasive tool for assessing the
activities of autonomic nervous system (ANS). In this paper, changes
in ANS activity are quantified by means of frequency and time
domain analysis of R-R interval variability. Electrocardiograms
(ECG) of 16 patients suffering from DM and of 16 healthy volunteers
were recorded. Frequency domain analysis of extracted normal to
normal interval (NN interval) data indicates significant difference in
very low frequency (VLF) power, low frequency (LF) power and
high frequency (HF) power, between the DM patients and control
group. Time domain measures, standard deviation of NN interval
(SDNN), root mean square of successive NN interval differences
(RMSSD), successive NN intervals differing more than 50 ms (NN50
Count), percentage value of NN50 count (pNN50), HRV triangular
index and triangular interpolation of NN intervals (TINN) also show
significant difference between the DM patients and control group.
Abstract: In this paper we investigate how wide-ranging
organizational support and the more specific form of support,
namely management support, may influence on tourism workers
satisfaction with a cash transaction system. The IS continuance
theory, proposed by Bhattacherjee in 2001, is utilized as a
theoretical framework. This implies that both perceived usefulness
and ease of use is included in the research model, in addition to
organizational and management support. The sample consists of
500 workers from 10 cruise and tourist ferries in Scandinavia that
use a cash transaction system to perform their work tasks. Using
structural equation modelling, results indicate that organizational
support and ease of use perceptions is critical for the users- level of
satisfaction with the cash transaction system.The findings have
implications for business managers and IS practitioners that want
to increase the quality of IT-based business processes within the
tourism industry.
Abstract: The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Abstract: Leo Breimans Random Forests (RF) is a recent
development in tree based classifiers and quickly proven to be one of
the most important algorithms in the machine learning literature. It
has shown robust and improved results of classifications on standard
data sets. Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques to the random forests. We
experiment the working of the ensembles of random forests on the
standard data sets available in UCI data sets. We compare the
original random forest algorithm with their ensemble counterparts
and discuss the results.
Abstract: In this paper, the local grid refinement is focused by
using a nested grid technique. The Cartesian grid numerical method is
developed for simulating unsteady, viscous, incompressible flows
with complex immersed boundaries. A finite volume method is used in
conjunction with a two-step fractional-step procedure. The key aspects
that need to be considered in developing such a nested grid solver are
imposition of interface conditions on the inter-block and accurate
discretization of the governing equation in cells that are with the
inter-block as a control surface. A new interpolation procedure is
presented which allows systematic development of a spatial
discretization scheme that preserves the spatial accuracy of the
underlying solver. The present nested grid method has been tested by
two numerical examples to examine its performance in the two
dimensional problems. The numerical examples include flow past a
circular cylinder symmetrically installed in a Channel and flow past
two circular cylinders with different diameters. From the numerical
experiments, the ability of the solver to simulate flows with
complicated immersed boundaries is demonstrated and the nested grid
approach can efficiently speed up the numerical solutions.
Abstract: This paper examines the depiction of Muslim militants in Thai newspapers in 2004. Stuart Hall-s “representation" and “public idioms" are used as theoretical frameworks. Critical Discourse Analysis is employed as a methodology to examine 240 news articles from two leading Thai language newspapers. The results show that the militants are usually labeled as “southern bandits." This suggests that they are just a culprit of the violence in the deep south of Thailand. They are usually described as people who cause turbulence. Consequently, the military have to get rid of them. However, other aspects of the groups such as their political agenda or the failures of the Thai state in dealing with the Malay Muslims were not mention in the news stories. In the time of violence, the researcher argues that this kind of newspaper coverage may help perpetuate the discourse of Malay Muslim, instead of providing fuller picture of the ongoing conflicts.
Abstract: According to the theory of capital structure, this paper uses principal component analysis and linear regression analysis to study the relationship between the debt characteristics of the private listed companies in Jiangsu Province and their business performance. The results show that the average debt ratio of the 29 private listed companies selected from the sample is lower. And it is found that for the sample whose debt ratio is lower than 80%, its debt ratio is negatively related to corporate performance, while for the sample whose debt ratio is beyond 80%, the relationship of debt financing and enterprise performance shows the different trends. The conclusions reflect the drawbacks may exist that the debt ratio is relatively low and having not take full advantage of debt governance effect of the private listed companies in Jiangsu Province.
Abstract: The company-s ability to draw on a range of external
sources to meet their needs for innovation, has been termed 'open
innovation' (OI). Very few empirical analyses have been conducted
on Small and Medium Enterprises (SMEs) to the extent that they
describe and understand the characteristics and implications of this
new paradigm.
The study's objective is to identify and characterize different
modes of OI, (considering innovation process phases and the variety
and breadth of the collaboration), determinants, barriers and
motivations in SMEs. Therefore a survey was carried out among
Italian manufacturing firms and a database of 105 companies was
obtained. With regard to data elaboration, a factorial and cluster
analysis has been conducted and three different OI modes have
emerged: selective low open, unselective open upstream, and mid-
partners integrated open. The different behaviours of the three
clusters in terms of determinants factors, performance, firm-s
technology intensity, barriers and motivations have been analyzed
and discussed.
Abstract: Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.
Abstract: The cyberspace is an instrument through which
internet users could get new experiences. It could contribute to foster
one-s own growth, widening cognitive, creative and communicative
abilities and promoting relationships. In the cyberspace, in fact, it is
possible to create virtual learning communities where internet users
improve their interpersonal sphere, knowledge and skills. The main
element of e-learning is the establishment of online relationships, that
are often collaborative.
Abstract: A research effort to find the reality of the business of Japan-s software globalization of enterprise-level business software systems has found that while the number of Japan-made enterpriselevel software systems is comparable with those of the other G7 countries, the business is limited to the East and Southeast Asian markets. This indicates that this business has a problem in the European and USA markets. Based on the knowledge that the research has established, the research concludes that the communication problems arise from the lack of individualists' communication styles and foreign language skills in Japan's software globalization is compensated by similarities in certain Japanese cultural factors and Japan's cultural power in the East and Southeast Asian markets and that this business does not have this compensation factor in the European and American markets due to dissimilarities and no cultural power.