Abstract: Modern civilization has come in recent decades into a new phase in its development, called the information society. The concept of "information society" has become one of the most common. Therefore, the attempt to understand what exactly the society we live in, what are its essential features, and possible future scenarios, is important to the social and philosophical analysis. At the heart of all these deep transformations is more increasing, almost defining role knowledge and information as play substrata of «information society». The mankind opened for itself and actively exploits a new resource – information. Information society puts forward on the arena new type of the power, at the heart of which activity – mastering by a new resource: information and knowledge. The password of the new power – intelligence as synthesis of knowledge, information and communications, the strength of mind, fundamental sociocultural values. In a postindustrial society, the power of knowledge and information is crucial in the management of the company, pushing into the background the influence of money and state coercion.
Abstract: The role of knowledge is a determinative factor in the
life of economy and society. To determine knowledge is not an easy
task yet the real task is to determine the right knowledge. From this
view knowledge is a sum of experience, ideas and cognitions which
can help companies to remain in markets and to realize a maximum
profit. At the same time changes of circumstances project in advance
that contents and demands of the right knowledge are changing. In
this paper we will analyse a special segment on the basis of an
empirical survey. We investigated the behaviour and strategies of
small and medium sized enterprises (SMEs) in the area of
knowledge-handling. This survey was realized by questionnaires and
wide range statistical methods were used during processing. As a
result we will show how these companies are prepared to operate in a
knowledge-based economy and in which areas they have prominent
deficiencies.
Abstract: Tacit knowledge has been one of the most discussed
and contradictory concepts in the field of knowledge management
since the mid 1990s. The concept is used relatively vaguely to refer
to any type of information that is difficult to articulate, which has led
to discussions about the original meaning of the concept (adopted
from Polanyi-s philosophy) and the nature of tacit knowing. It is
proposed that the subject should be approached from the perspective
of cognitive science in order to connect tacit knowledge to
empirically studied cognitive phenomena. Some of the most
important examples of tacit knowing presented by Polanyi are
analyzed in order to trace the cognitive mechanisms of tacit knowing
and to promote better understanding of the nature of tacit knowledge.
The cognitive approach to Polanyi-s theory reveals that the
tacit/explicit typology of knowledge often presented in the
knowledge management literature is not only artificial but totally
opposite approach compared to Polanyi-s thinking.
Abstract: In this contribution is presented a complex design of
individual objects identification in the workplace of intelligent
assembly cell. Intelligent assembly cell is situated at Institute of
Manufacturing Systems and Applied Mechanics and is used for
pneumatic actuator assembly. Pneumatic actuator components are
pneumatic roller, cover, piston and spring. Two identification objects
alternatives for assembly are designed in the workplace of industrial
robot. In the contribution is evaluated and selected suitable
alternative for identification – 2D codes reader. The complex design
of individual object identification is going out of intelligent
manufacturing systems knowledge.
Intelligent assembly and manufacturing systems as systems of
new generation are gradually loaded in to the mechanical production,
when they are removeing human operation out of production process
and they also short production times.
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: This research aims to study employment trends in
printing industry for prepress support by Suan Sunandha University
Fund. The objectives of this research are to explain the trends of the
employment in Thai Printing Industry for prepress in Bangkok and
the description of different personnel that prepress entrepreneur need
and also the problems of employment.
The population of prepress entrepreneurs is about 100
organizations in the area of Bangkok. The questionnaires has been
taken and analyzed with SPSS program by using the average
percentage and standard deviation.
This research is multiple case studies. The conceptual framework
is developed on the basis of the open systems theory.
The research result show that
1. The most of prepress entrepreneur have trend to choose the
employee by any sex, the age 25-29 years old, bachelor degree
and have 1-2 years experience.
2. The most problems are the understanding in job,
communication/relation and the understanding in new
technology.
3. The trends aims to employment in 1-3 years have 57.8% for
prepress industry in Bangkok.
This research suggests that:
1. Thai printing industry for prepress in Bangkok need quality
employee that expert in printing technology.
2. Prepress entrepreneur should have agreement to development
with university for practice the employee.
3. Prepress entrepreneur should support personal to fulfill the
knowledge.
Abstract: Knowledge Discovery in Databases (KDD) is the process of extracting previously unknown, hidden and interesting patterns from a huge amount of data stored in databases. Data mining is a stage of the KDD process that aims at selecting and applying a particular data mining algorithm to extract an interesting and useful knowledge. It is highly expected that data mining methods will find interesting patterns according to some measures, from databases. It is of vital importance to define good measures of interestingness that would allow the system to discover only the useful patterns. Measures of interestingness are divided into objective and subjective measures. Objective measures are those that depend only on the structure of a pattern and which can be quantified by using statistical methods. While, subjective measures depend only on the subjectivity and understandability of the user who examine the patterns. These subjective measures are further divided into actionable, unexpected and novel. The key issues that faces data mining community is how to make actions on the basis of discovered knowledge. For a pattern to be actionable, the user subjectivity is captured by providing his/her background knowledge about domain. Here, we consider the actionability of the discovered knowledge as a measure of interestingness and raise important issues which need to be addressed to discover actionable knowledge.
Abstract: Social media has led to paradigm shifts in ways
people work and do business, interact and socialize, learn and obtain
knowledge. So much so that social media has established itself as an
important spatial extension of this nation-s historicity and challenges.
Regardless of the enabling reputation and recommendation features
through social networks embedded in the social media system, the
overflow of broadcasted and publicized media contents turns the
table around from engendering trust to doubting the trust system.
When the trust is at doubt, the effects include deactivation of
accounts and creation of multiple profiles, which lead to the overflow
of 'ghost' contents (i.e. “the abundance of abandoned ships"). In
most literature, the study of trust can be related to culture; hence the
difference between Western-s “openness" and Eastern-s “blue-chip"
concepts in networking and relationships. From a survey on issues
and challenges among Malaysian social media users, 'authenticity'
emerges as one of the main factors that causes and is caused by other
factors. The other issue that has surfaced is credibility either in terms
of message/content and source. Another is the quality of the
knowledge that is shared. This paper explores the terrains of this
critical space which in recent years has been dominated increasingly
by, arguably, social networks embedded in the social media system,
the overflow of broadcasted and publicized media content.
Abstract: In the present paper, we-ll explore how social media tools provide an opportunity for new developments of the e-Learning in the context of managing personal knowledge. There will be a discussion how social media tools provide a possibility for helping knowledge workersand students to gather, organize and manage their personal information as a part of the e-learning process. At the centre of this social software driven approach to e-learning environments are the challenges of personalization and collaboration. We-ll share concepts of how organizations are using social media for e-Learning and believe that integration of these tools into traditional e-Learning is probably not a choice, but inevitability. Students- Survey of use of web technologies and social networking tools is presented. Newly developed framework for semantic blogging capable of organizing results relevant to user requirements is implemented at Varna Free University (VFU) to provide more effective navigation and search.
Abstract: It is not a secret that, IT management has become
more and more and integrated part of almost all organizations. IT
managers posses an enormous amount of knowledge within both
organizational knowledge and general IT knowledge. This article
investigates how IT managers keep themselves updated on IT
knowledge in general and looks into how much time IT managers
spend on weekly basis searching the net for new or problem solving
IT knowledge. The theory used in this paper is used to investigate the
current role of IT managers and what issues they are facing.
Furthermore a research is conducted where 7 IT managers in medium
sized and large Danish companies are interviewed to add further
focus on the role of the IT manager and to focus on how they keep
themselves updated. Beside finding substantial need for more
research, IT managers – generalists or specialists – only have limited
knowledge resources at hand in updating their own knowledge –
leaving much initiative to vendors.
Abstract: The Siemens Healthcare Sector is one of the world's
largest suppliers to the healthcare industry and a trendsetter in
medical imaging and therapy, laboratory diagnostics, medical
information technology, and hearing aids.
Siemens offers its customers products and solutions for the entire
range of patient care from a single source – from prevention and
early detection to diagnosis, and on to treatment and aftercare. By
optimizing clinical workflows for the most common diseases,
Siemens also makes healthcare faster, better, and more cost effective.
The optimization of clinical workflows requires a
multidisciplinary focus and a collaborative approach of e.g. medical
advisors, researchers and scientists as well as healthcare economists.
This new form of collaboration brings together experts with deep
technical experience, physicians with specialized medical knowledge
as well as people with comprehensive knowledge about health
economics.
As Charles Darwin is often quoted as saying, “It is neither the
strongest of the species that survive, nor the most intelligent, but the
one most responsive to change," We believe that those who can
successfully manage this change will emerge as winners, with
valuable competitive advantage.
Current medical information and knowledge are some of the core
assets in the healthcare industry. The main issue is to connect
knowledge holders and knowledge recipients from various
disciplines efficiently in order to spread and distribute knowledge.
Abstract: e-Government is already in its second decade. Prerequisite for further development and adaptation to new realities is the optimal management of administrative information and knowledge production by those involved, i.e. the public sector, citizens and businesses. Nowadays, the amount of information displayed or distributed on the Internet has reached enormous dimensions, resulting in serious difficulties when extracting and managing knowledge. The semantic web is expected to play an important role in solving this problem and the technologies that support it. In this article, we address some relevant issues.
Abstract: Gradual patterns have been studied for many years as
they contain precious information. They have been integrated in
many expert systems and rule-based systems, for instance to reason
on knowledge such as “the greater the number of turns, the greater
the number of car crashes”. In many cases, this knowledge has been
considered as a rule “the greater the number of turns → the greater
the number of car crashes” Historically, works have thus been
focused on the representation of such rules, studying how implication
could be defined, especially fuzzy implication. These rules were
defined by experts who were in charge to describe the systems they
were working on in order to turn them to operate automatically. More
recently, approaches have been proposed in order to mine databases
for automatically discovering such knowledge. Several approaches
have been studied, the main scientific topics being: how to determine
what is an relevant gradual pattern, and how to discover them as
efficiently as possible (in terms of both memory and CPU usage).
However, in some cases, end-users are not interested in raw level
knowledge, and are rather interested in trends. Moreover, it may be
the case that no relevant pattern can be discovered at a low level of
granularity (e.g. city), whereas some can be discovered at a higher
level (e.g. county). In this paper, we thus extend gradual pattern
approaches in order to consider multiple level gradual patterns. For
this purpose, we consider two aggregation policies, namely
horizontal and vertical.
Abstract: This article discusses the concept of student ownership of knowledge and seeks to determine how to move students from knowledge acquisition to knowledge application and ultimately to knowledge generation in a virtual setting. Instructional strategies for fostering student engagement in a virtual environment are critical to the learner-s strategic ownership of the knowledge. A number of relevant theories that focus on learning, affect, needs and adult concerns are presented to provide a basis for exploring the transfer of knowledge from teacher to learner. A model under development is presented that combines the dimensions of knowledge approach, the teacher-student relationship with regards to knowledge authority and teaching approach to demonstrate the recursive and scaffolded design for creation of virtual learning environments.
Abstract: This paper demonstrates an effort of a serviceoriented
engineering department in improving the sharing and
transfer of knowledge. Although the department consist of only six
employees, but it provides services in various chemical application in
an oil and gas business. The services provided span across Asia
Pacific region mainly Indonesia, Myanmar, Vietnam, Brunei,
Thailand and Singapore. Currently there are no effective tools or
integrated systems that support the sharing or transfer and
maintenance of knowledge so the department has considered
preserving this valuable knowledge by developing a Knowledge
Management System (KMS). This paper presents the development of
a KMS to support the sharing of knowledge in a service-oriented
engineering department of an oil and gas company. The embedded
features in the KMS like blog and forum will encourage iterative
process of knowledge sharing among the employees in the
department. The information and knowledge being shared, discussed
and communicated will be then achieved for future re-use. The re-use
of the knowledge allows the department to reduce redundant efforts
in providing consistent, up-to-date and cost effective of the best
solution to the its clients.
Abstract: Hybrid knowledge model is suggested as an underlying
framework for product development management. It can support such
hybrid features as ontologies and rules. Effective collaboration in
product development environment depends on sharing and reasoning
product information as well as engineering knowledge. Many studies
have considered product information and engineering knowledge.
However, most previous research has focused either on building the
ontology of product information or rule-based systems of engineering
knowledge. This paper shows that F-logic based knowledge model can
support such desirable features in a hybrid way.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: Knowledge management is a critical component of
competitive success in service organizations. Knowledge
management centers on creating new knowledge and utilizing
existing knowledge. While utilizing existing knowledge relates to
input and control and can lead to a reduction in costs; creating new
knowledge relates to output and growth and can lead to an increase in
revenue. Therefore managers must ensure that they can successfully
optimize the knowledge and talent in their organizations. To do this
they and must try to develop an environment that promotes the
generation, acquisition, transfer and use of valuable knowledge in
creative ways. However knowledge management is complex and
diverse. Research suggests that organizations in general and SMEs in
particular are finding it difficult to implement successful knowledge
management initiatives. Our research attempts to understand whether
organizations are adopting best practice initiatives in their
organizations. This paper presents findings from an exploratory study
of 139 SMEs operating in the tourism sector across Europe. The
goals of the survey is to assess the level of awareness of knowledge
and talent management strategies and methodologies and to
determine whether the responding companies implement best practice
knowledge management initiatives in their organizations Analysis of
the findings from the study are presented and discussed.
Abstract: Heuristics-based search methodologies normally
work on searching a problem space of possible solutions toward
finding a “satisfactory" solution based on “hints" estimated from the
problem-specific knowledge. Research communities use different
types of methodologies. Unfortunately, most of the times, these hints
are immature and can lead toward hindering these methodologies by
a premature convergence. This is due to a decrease of diversity in
search space that leads to a total implosion and ultimately fitness
stagnation of the population. In this paper, a novel Decision Maturity
framework (DMF) is introduced as a solution to this problem. The
framework simply improves the decision on the direction of the
search by materializing hints enough before using them. Ideas from
this framework are injected into the particle swarm optimization
methodology. Results were obtained under both static and dynamic
environment. The results show that decision maturity prevents
premature converges to a high degree.
Abstract: This paper aims to study at the use of local knowledge
to develop community self-protection in flood prone residential area,
Ayutthaya Island has been chosen as a case study. This study tries to
examine the strength of local knowledge which is able to develop
community self-protection and cope with flood disaster. In-depth, this
paper focuses on the influence of social network on knowledge
transfer. After conducted the research, authors reviewed the strength
of local knowledge and also mentioned the obstacles of community to
use and also transfer local knowledge. Moreover, the result of the
study revealed that local knowledge is not always transferred by the
strongest-tie social network (family or kinship) as we used to believe.
Surprisingly, local knowledge could be also transferred by the
weaker-tie social network (teacher/ monk) with the better
effectiveness in some knowledge.