Abstract: The use of e-business in small and medium-sized
enterprises (SMEs) has been recently received an enormous attention
in information systems research by both academic and practitioners.
With the adoption of new and efficient technologies to enhance
businesses, Thai SMEs should be able to compete worldwide.
Unfortunately, most of the owners are not used to new technologies.
It is clear that most Thai SMEs prefer to work manually rather than
electronically. This paper aims to provide a fundamental conceptual
framework for E-business adoption by Thai SMEs. Rooted in
Knowledge transfer model, several factors are identified, which drive
and enable e-business adoption. By overlooking the benefits
associated with implementing new technologies, it is difficult for
Thai SMEs to perform well enough to compete globally. The paper
also helps Thai SMEs to understand factors related to E-business
adoption.
Abstract: Text Mining is an important step of Knowledge
Discovery process. It is used to extract hidden information from notstructured
o semi-structured data. This aspect is fundamental because
much of the Web information is semi-structured due to the nested
structure of HTML code, much of the Web information is linked,
much of the Web information is redundant. Web Text Mining helps
whole knowledge mining process to mining, extraction and
integration of useful data, information and knowledge from Web
page contents.
In this paper, we present a Web Text Mining process able to
discover knowledge in a distributed and heterogeneous multiorganization
environment. The Web Text Mining process is based on
flexible architecture and is implemented by four steps able to
examine web content and to extract useful hidden information
through mining techniques. Our Web Text Mining prototype starts
from the recovery of Web job offers in which, through a Text Mining
process, useful information for fast classification of the same are
drawn out, these information are, essentially, job offer place and
skills.
Abstract: This paper invites to dialogue and reflections on
innovation and entrepreneurship by presenting concepts of innovation
leading to the introduction of a complex theoretical framework;
Cooperative Innovation (CO-IN). CO-IN is a didactic model
enhancing and scaffolding processes of cooperation creating
innovation drawing on a Scandinavian tradition.
CO-IN is based on a cross-sectorial and multidisciplinary
approach. We introduce the concept of complementarity to help
capture the validity of diversity and we suggest the concept of “the
space in between" to understand the creation of identity as a
collective mind. We see dialogue and the use of multi modal
techniques as essential tools for conceptualizations giving possibility
for clarification of the complexity and diversity leading to decision
making based on knowledge as commons.
We introduce the didactic design and present our empirical
findings from an innovation workshop in Argentina. In a final
paragraph we reflect on the design as a support of the development of
common ground, collective mind and collective action and the
creation of knowledge as commons to facilitate innovation and
entrepreneurship.
Abstract: This paper presents the application of Intelligent
Techniques to the various duties of Intelligent Condition Monitoring
Systems (ICMS) for Unmanned Aerial Vehicle (UAV) Robots. These
Systems are intended to support these Intelligent Robots in the event
of a Fault occurrence. Neural Networks are used for Diagnosis, whilst
Fuzzy Logic is intended for Prognosis and Remedy. The ultimate
goals of ICMS are to save large losses in financial cost, time and
data.
Abstract: Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.
Abstract: Narratives are invaluable assets of human lives. Due to
the distinct features of narratives, they are useful for supporting human
reasoning processes. However, many useful narratives become
residuals in organizations or human minds nowadays. Researchers
have contributed effort to investigate and improve narrative generation
processes. This paper attempts to contemplate essential components in
narratives and explore a computational approach to acquire and extract
knowledge to generate narratives. The methodology and significant
benefit for decision support are presented.
Abstract: In this paper a data miner based on the learning
automata is proposed and is called LA-miner. The LA-miner extracts
classification rules from data sets automatically. The proposed
algorithm is established based on the function optimization using
learning automata. The experimental results on three benchmarks
indicate that the performance of the proposed LA-miner is
comparable with (sometimes better than) the Ant-miner (a data miner
algorithm based on the Ant Colony optimization algorithm) and CNZ
(a well-known data mining algorithm for classification).
Abstract: Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.
Abstract: The advantage of solving the complex nonlinear
problems by utilizing fuzzy logic methodologies is that the
experience or expert-s knowledge described as a fuzzy rule base can
be directly embedded into the systems for dealing with the problems.
The current limitation of appropriate and automated designing of
fuzzy controllers are focused in this paper. The structure discovery
and parameter adjustment of the Branched T-S fuzzy model is
addressed by a hybrid technique of type constrained sparse tree
algorithms. The simulation result for different system model is
evaluated and the identification error is observed to be minimum.
Abstract: The Yazd-Ardakan basin in Central Iran has two separated aquifers. The shallow unconfined aquifer is supplies 40 Qanats. The deep saturated confined aquifer is the main water storage. Due to over-withdrawal, water table has been decreasing during last 25 years. Recent study shows that the shortage of the aquifer is about 16 meters and land subsidence is 0.5 - 1.2 meters. Long deep cracks are found just above the aquifer and devour the irrigation water and floods. Although the most cracks direction is NW-SE and could be compared to the main direction of YA basin, there is no direct evidence for relation between land subsidence and the huge cracks. Large-scale water pumping has been decreased the water pressure in aquifer. The pressure decline disturbed the balance and increased the pressure of overlying sediments. So porosity decreased and compaction started. Then, sediments compaction developed and made land subsidence and some huge cracks slowly.
Abstract: Emerging adulthood, the new period which is
especially prevalent in the developed or industrialized countries
during ages 18 to 29, is a new conceptualization proposed by Arnett.
Intimacy is a superordinate concept which includes intimate
interaction and intimate relationship. This study includes two
proceses which are scale development and conduction of gender
differences about markers of starting romantic intimacy among
Turkish emerging adults. In first process, Markers of Starting
Romantic Intimacy Scale, with 17 items and 5 factors, was developed
using by 220 participants. In the second step, the scale was
administered to 318 Turkish male and female emerging adults
between ages 22 and 25. Results show that there is no significant
difference between gender and total score of the scale. With respect
to gender, there are significant differences between gender and in
four subscales which are self perception, affective and cognitive
intimacy, self knowledge and romantic verbalizations. Moreover,
there is no significant relationship between gender and behavioral
intimacy subscale.
Abstract: Preparation and negotiation of innovative and future
projects can be characterized as a strategic-type decision situation,
involving many uncertainties and an unpredictable environment.
We will focus in this paper on the bidding process. It includes cooperative
and strategic decisions.
Our approach for bidding process knowledge capitalization is
aimed at information management in project-oriented organizations,
based on the MUSIC (Management and Use of Co-operative
Information Systems) model.
We will show how to capitalize the company strategic knowledge
and also how to organize the corporate memory. The result of the
adopted approach is improvement of corporate memory quality.
Abstract: For gamma radiation detection, assemblies having
scintillation crystals and a photomultiplier tube, also there is a
preamplifier connected to the detector because the signals from
photomultiplier tube are of small amplitude. After pre-amplification
the signals are sent to the amplifier and then to the multichannel
analyser. The multichannel analyser sorts all incoming electrical
signals according to their amplitudes and sorts the detected photons
in channels covering small energy intervals. The energy range of
each channel depends on the gain settings of the multichannel
analyser and the high voltage across the photomultiplier tube. The
exit spectrum data of the two main isotopes studied ,putting data in
biomass program ,process it by Matlab program to get the solid
holdup image (solid spherical nuclear fuel)
Abstract: This paper discusses the development of a qualitative
simulator (abbreviated QRiOM) for predicting the behaviour of
organic chemical reactions. The simulation technique is based on the
qualitative process theory (QPT) ontology. The modelling constructs
of QPT embody notions of causality which can be used to explain the
behaviour of a chemical system. The major theme of this work is
that, in a qualitative simulation environment, students are able to
articulate his/her knowledge through the inspection of explanations
generated by software. The implementation languages are Java and
Prolog. The software produces explanation in various forms that
stresses on the causal theories in the chemical system which can be
effectively used to support learning.
Abstract: In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.
Abstract: The purpose of the present study is the investigation
of the relationship between knowledge management and enabling
managers based on achieving proper function. This research is
descriptive and investigative. The sample includes all male and
female high school managers of first and second regions of Urmia
including 98 school and accordingly 98 managers. The instrument
applied was a questionnaire. To sum up, there is a statistically
significant relationship between knowledge management and
empowering managers. In the end, several suggestions are provided.
Abstract: This study explores how the mechanics of learning
paves the way to engineering innovation. Theories related to learning
in the new product/service innovation are reviewed from an
organizational perspective, behavioral perspective, and engineering
perspective. From this, an engineering team-s external interactions
for knowledge brokering and internal composition for skill balance
are examined from a learning and innovation viewpoints. As a result,
an integrated learning model is developed by reconciling the
theoretical perspectives as well as developing propositions that
emphasize the centrality of learning, and its drivers, in the
engineering product/service development. The paper also provides a
review and partial validation of the propositions using the results of a
previously published field study in the aerospace industry.
Abstract: This paper examines whether or not immigration has a positive influence on the duration of unemployment, in a macroeconomic perspective. We analyse also whether the degree of labor market integration can influence migration. The integration of immigrants into the labor market is a recurrence theme in the work on the economic consequences of immigration. However, to our knowledge, no researchers have studied the impact of immigration on unemployment duration, and vice versa. With two methodology of research (panel estimations (OLS and 2SLS) and panel cointegration techniques), we show that migration seems to influence positively the short-term unemployment and negatively long-term unemployment, for 14 OECD destination countries. In addition, immigration seems to be conditioned by the structural and institutional characteristics of the labour market.
Abstract: This paper provides some thoughts about the lack of
attentiveness of building commissioning in the construction industry
and the lack of handling in project commissioning as an integral part
of the project life-cycle. Many have perceived commissioning as the
problem solving process of a project, rather than the start up of the
equipment, or the handing over of the project to the client. Therefore,
there is a lack of proper attention in the planning of commissioning
as a vital part of the project life-cycle. This review paper aims to
highlight the benefits of building commissioning and to propose the
lacking of knowledge gap on building commissioning. Finally, this
paper hopes to propose the shift of focus on this matter in future
research.
Abstract: This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.