Abstract: In this paper we propose an NLP-based method for
Ontology Population from texts and apply it to semi automatic
instantiate a Generic Knowledge Base (Generic Domain Ontology) in
the risk management domain. The approach is semi-automatic and
uses a domain expert intervention for validation. The proposed
approach relies on a set of Instances Recognition Rules based on
syntactic structures, and on the predicative power of verbs in the
instantiation process. It is not domain dependent since it heavily
relies on linguistic knowledge.
A description of an experiment performed on a part of the
ontology of the PRIMA1 project (supported by the European
community) is given. A first validation of the method is done by
populating this ontology with Chemical Fact Sheets from
Environmental Protection Agency2. The results of this experiment
complete the paper and support the hypothesis that relying on the
predicative power of verbs in the instantiation process improves the
performance.
Abstract: Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.
Abstract: In the current economy of increasing global
competition, many organizations are attempting to use knowledge as
one of the means to gain sustainable competitive advantage. Besides
large organizations, the success of SMEs can be linked to how well
they manage their knowledge. Despite the profusion of research
about knowledge management within large organizations, fewer
studies tried to analyze KM in SMEs.
This research proposes a new framework showing the determinant
role of organizational dimensions onto KM approaches. The paper
and its propositions are based on a literature review and analysis.
In this research, personalization versus codification,
individualization versus institutionalization and IT-based versus non
IT-based are highlighted as three distinct dimensions of knowledge
management approaches.
The study contributes to research by providing a more nuanced
classification of KM approaches and provides guidance to managers
about the types of KM approaches that should be adopted based on
the size, geographical dispersion and task nature of SMEs.
To the author-s knowledge, the paper is the first of its kind to
examine if there are suitable configurations of KM approaches for
SMEs with different dimensions. It gives valuable information, which
hopefully will help SME sector to accomplish KM.
Abstract: There are different kinds of online systems on the Internet for people who need support and develop new knowledge. Online communities and Ask the Expert systems are two such systems. In the health care area, the number of users of these systems has increased at a rapid pace. Interactions with medical trained experts take place online, and people with concerns about similar health problems come together to share experiences and advice. The systems are also used as storages and browsed for health information. Over the years, studies have been conducted of the usage of the different systems. However, in what ways the systems can be used together to enhance learning has not been explored. This paper presents results from a study of online health-communities and an Ask the Expert system for people who suffer from overweight. Differences and similarities in regards to posted issues and replies are discussed, and suggestions for a new holistic design of the two systems are presented.
Abstract: Extracting in-play scenes in sport videos is essential for
quantitative analysis and effective video browsing of the sport
activities. Game analysis of badminton as of the other racket sports
requires detecting the start and end of each rally period in an
automated manner. This paper describes an automatic serve scene
detection method employing cubic higher-order local auto-correlation
(CHLAC) and multiple regression analysis (MRA). CHLAC can
extract features of postures and motions of multiple persons without
segmenting and tracking each person by virtue of shift-invariance and
additivity, and necessitate no prior knowledge. Then, the specific
scenes, such as serve, are detected by linear regression (MRA) from
the CHLAC features. To demonstrate the effectiveness of our method,
the experiment was conducted on video sequences of five badminton
matches captured by a single ceiling camera. The averaged precision
and recall rates for the serve scene detection were 95.1% and 96.3%,
respectively.
Abstract: The primary purpose of this article is an attempt to
find the implication of globalization on education. Globalization has
an important role as a process in the economical, political, cultural
and technological dimensions in the life of the contemporary human
being and has been affected by it. Education has its effects in this
procedure and while influencing it through educating global citizens
having universal human features and characteristics, has been
influenced by this phenomenon too. Nowadays, the role of education
is not just to develop in the students the knowledge and skills
necessary for the new kinds of jobs. If education wants to help
students be prepared of the new global society, it has to make them
engaged productive and critical citizens for the global era, so that
they can reflect about their roles as key actors in a dynamic often
uneven, matrix of economic and cultural exchanges. If education
wants to reinforce and raise the national identity, the value system
and the children and teenagers, it should make them ready for living
in the global era of this century. The used method in this research is
documentary and analyzing the documents. Studies in this field show
globalization has influences on the processes of the production,
distribution and consuming of knowledge. The happening of this
event in the information era has not only provide the necessary
opportunities for the exchanges of education worldwide but also has
privileges for the developing countries which enables them to
strengthen educational bases of their society and have an important
step toward their future.
Abstract: Knowledge is attributed to human whose problemsolving
behavior is subjective and complex. In today-s knowledge
economy, the need to manage knowledge produced by a community
of actors cannot be overemphasized. This is due to the fact that
actors possess some level of tacit knowledge which is generally
difficult to articulate. Problem-solving requires searching and sharing
of knowledge among a group of actors in a particular context.
Knowledge expressed within the context of a problem resolution
must be capitalized for future reuse. In this paper, an approach that
permits dynamic capitalization of relevant and reliable actors-
knowledge in solving decision problem following Economic
Intelligence process is proposed. Knowledge annotation method and
temporal attributes are used for handling the complexity in the
communication among actors and in contextualizing expressed
knowledge. A prototype is built to demonstrate the functionalities of
a collaborative Knowledge Management system based on this
approach. It is tested with sample cases and the result showed that
dynamic capitalization leads to knowledge validation hence
increasing reliability of captured knowledge for reuse. The system
can be adapted to various domains.
Abstract: The pedagogy project has been proven as an active
learning method, which is used to develop learner-s skills and
knowledge.The use of technology in the learning world, has filed
several gaps in the implementation of teaching methods, and online
evaluation of learners. However, the project methodology presents
challenges in the assessment of learners online.
Indeed, interoperability between E-learning platforms (LMS) is
one of the major challenges of project-based learning assessment.
Firstly, we have reviewed the characteristics of online assessment
in the context of project-based teaching. We addressed the
constraints encountered during the peer evaluation process.
Our approach is to propose a meta-model, which will describe a
language dedicated to the conception of peer assessment scenario in
project-based learning. Then we illustrate our proposal by an
instantiation of the meta-model through a business process in a
scenario of collaborative assessment on line.
Abstract: This paper aims at identifying and analyzing the
knowledge transmission channels in textile and clothing clusters
located in Brazil and in Europe. Primary data was obtained through
interviews with key individuals. The collection of primary data was
carried out based on a questionnaire with ten categories of indicators
of knowledge transmission. Secondary data was also collected
through a literature review and through international organizations
sites. Similarities related to the use of the main transmission channels
of knowledge are observed in all cases. The main similarities are:
influence of suppliers of machinery, equipment and raw materials;
imitation of products and best practices; training promoted by
technical institutions and businesses; and cluster companies being
open to acquire new knowledge. The main differences lie in the
relationship between companies, where in Europe the intensity of this
relationship is bigger when compared to Brazil. The differences also
occur in importance and frequency of the relationship with the
government, with the cultural environment, and with the activities of
research and development. It is also found factors that reduce the
importance of geographical proximity in transmission of knowledge,
and in generating trust and the establishment of collaborative
behavior.
Abstract: In single trial analysis, when using Principal
Component Analysis (PCA) to extract Visual Evoked Potential
(VEP) signals, the selection of principal components (PCs) is an
important issue. We propose a new method here that selects only
the appropriate PCs. We denote the method as selective eigen-rate
(SER). In the method, the VEP is reconstructed based on the rate
of the eigen-values of the PCs. When this technique is applied on
emulated VEP signals added with background
electroencephalogram (EEG), with a focus on extracting the
evoked P3 parameter, it is found to be feasible. The improvement
in signal to noise ratio (SNR) is superior to two other existing
methods of PC selection: Kaiser (KSR) and Residual Power (RP).
Though another PC selection method, Spectral Power Ratio (SPR)
gives a comparable SNR with high noise factors (i.e. EEGs), SER
give more impressive results in such cases. Next, we applied SER
method to real VEP signals to analyse the P3 responses for
matched and non-matched stimuli. The P3 parameters extracted
through our proposed SER method showed higher P3 response for
matched stimulus, which confirms to the existing neuroscience
knowledge. Single trial PCA using KSR and RP methods failed to
indicate any difference for the stimuli.
Abstract: Knowledge sharing in general and the contextual
access to knowledge in particular, still represent a key challenge in
the knowledge management framework. Researchers on semantic
web and human machine interface study techniques to enhance this
access. For instance, in semantic web, the information retrieval is
based on domain ontology. In human machine interface, keeping
track of user's activity provides some elements of the context that can
guide the access to information. We suggest an approach based on
these two key guidelines, whilst avoiding some of their weaknesses.
The approach permits a representation of both the context and the
design rationale of a project for an efficient access to knowledge. In
fact, the method consists of an information retrieval environment
that, in the one hand, can infer knowledge, modeled as a semantic
network, and on the other hand, is based on the context and the
objectives of a specific activity (the design). The environment we
defined can also be used to gather similar project elements in order to
build classifications of tasks, problems, arguments, etc. produced in a
company. These classifications can show the evolution of design
strategies in the company.
Abstract: Knowledge development in companies relies on
knowledge-intensive business processes, which are characterized by
a high complexity in their execution, weak structuring,
communication-oriented tasks and high decision autonomy, and often the need for creativity and innovation. A foundation of knowledge development is provided, which is based on a new conception of
knowledge and knowledge dynamics. This conception consists of a three-dimensional model of knowledge with types, kinds and qualities. Built on this knowledge conception, knowledge dynamics is
modeled with the help of general knowledge conversions between
knowledge assets. Here knowledge dynamics is understood to cover
all of acquisition, conversion, transfer, development and usage of
knowledge. Through this conception we gain a sound basis for
knowledge management and development in an enterprise. Especially
the type dimension of knowledge, which categorizes it according to
its internality and externality with respect to the human being, is crucial for enterprise knowledge management and development,
because knowledge should be made available by converting it to
more external types.
Built on this conception, a modeling approach for knowledgeintensive
business processes is introduced, be it human-driven,e-driven or task-driven processes. As an example for this approach, a model of the creative activity for the renewal planning of
a product is given.
Abstract: Knowledge is renowned as a significant component
for sustaining competitive advantage and gives leading edge in
business. This study emphasizes towards proper and effectuate
utilization of internal and external (both either explicit or tacit)
knowledge comes from stakeholders, highly supportive to combat
with the challenges and enhance organizational productivity.
Furthermore, it proposed a model under context of IRSA framework
which facilitates the organization including flow of knowledge and
experience sharing among employees. In discussion section an
innovative model which indulges all functionality as mentioned in
analysis section.
Abstract: This paper presents a model of case based corporate
memory named ReCaRo (REsource, CAse, ROle). The approach
suggested in ReCaRo decomposes the domain to model through a set
of components. These components represent the objects developed by
the company during its activity. They are reused, and sometimes,
while bringing adaptations. These components are enriched by
knowledge after each reuse. ReCaRo builds the corporate memory on
the basis of these components. It models two types of knowledge: 1)
Business Knowledge, which constitutes the main knowledge capital
of the company, refers to its basic skill, thus, directly to the
components and 2) the Experience Knowledge which is a specialised
knowledge and represents the experience gained during the handling
of business knowledge. ReCaRo builds corporate memories which
are made up of five communicating ones.
Abstract: The tagging data of (users, tags and resources) constitutes a folksonomy that is the user-driven and bottom-up approach to organizing and classifying information on the Web. Tagging data stored in the folksonomy include a lot of very useful information and knowledge. However, appropriate approach for analyzing tagging data and discovering hidden knowledge from them still remains one of the main problems on the folksonomy mining researches. In this paper, we have proposed a folksonomy data mining approach based on FCA for discovering hidden knowledge easily from folksonomy. Also we have demonstrated how our proposed approach can be applied in the collaborative tagging system through our experiment. Our proposed approach can be applied to some interesting areas such as social network analysis, semantic web mining and so on.
Abstract: Foundation of tower crane serves to ensure stability
against vertical and horizontal forces. If foundation stress is not
sufficient, tower crane may be subject to overturning, shearing or
foundation settlement. Therefore, engineering review of stable support
is a highly critical part of foundation design. However, there are not
many professionals who can conduct engineering review of tower
crane foundation and, if any, they have information only on a small
number of cranes in which they have hands-on experience. It is also
customary to rely on empirical knowledge and tower crane renter-s
recommendations rather than designing foundation on the basis of
engineering knowledge. Therefore, a foundation design automation
system considering not only lifting conditions but also overturning
risk, shearing and vertical force may facilitate production of foolproof
foundation design for experts and enable even non-experts to utilize
professional knowledge that only experts can access now. This study
proposes Automatic Design Algorithm for the Tower Crane
Foundations considering load and horizontal force.
Abstract: Prior to 1975, women in Laos suffered from having
reduced levels of power over decision-making in their families and in
their communities. This has had a negative impact on their ability to
develop their own identities. Their roles were identified as being
responsible for household activities and making preparations for their
marriage. Many women lost opportunities to get educated and access
the outdoor work that might have empowered them to improve their
situations. So far, no accurate figures of either emigrants or return
migrants have been compiled but it appears that most of them were
women, and it was women who most and more frequently remitted
money home. However, very few recent studies have addressed the
relationship between remittances and the roles of women in Laos.
This study, therefore, aims at redressing to some extent the
deficiencies in knowledge. Qualitative techniques were used to gather
data, including individual in-depth interviews and direct observation
in combination with the content analysis method. Forty women in
Vientiane Municipality and Savannakhet province were individually
interviewed. It was found that the monetary remittance was typically
used for family security and well-being; on fungible activities; on
economic and business activities; and on community development,
especially concerning hospitality and providing daily household
necessities. Remittances played important roles in improving many
respondents- livelihoods and positively changed their identities in
families and communities. Women became empowered as they were
able to start commercial businesses, rather than taking care of (just)
housework, children and elders. Interviews indicated that 92.5% of
the respondents their quality of lives improved, 90% felt happier in
their families and 82.5% felt conflicts in their families were reduced.
Abstract: This study aims at investigating factors in research
and development (R&D) growth and exploring the role of R&D
management in enhancing social innovation and productivity
improvement in Iran-s industrial sector. It basically explores the
common types of R&D activities and the industries which benefited
the most from active R&D units in Iran. The researchers generated
qualitative analyses obtained from primary and secondary data.
The primary data have been retrieved through interviews with five
key players (Managing Director, Internal Manager, General Manager,
Executive Manager, and Project Manager) in the industrial sector.
The secondary data acquired from an investigation on Mazandaran, a
province of northern Iran. The findings highlight Iran-s focuses of R
& D on cost reduction and upgrading productivity. Industries that
have benefited the most from active R&D units are metallic,
machinery and equipment design, and automotive.
We rank order the primary effects of R&D on productivity
improvement as follows, industry improvement, economic growth,
using professional human resources, generating productivity and
creativity culture, creating a competitive and innovative environment,
and increasing people-s knowledge.
Generally, low budget dedication and insufficient supply of highly
skilled scientists and engineers are two important obstacles for R&D
in Iran. Whereas, R&D has resulted in improvement in Iranian
society, transfer of contemporary knowledge into the international
market is still lacking.
Abstract: An ontology is widely used in many kinds of applications as a knowledge representation tool for domain knowledge. However, even though an ontology schema is well prepared by domain experts, it is tedious and cost-intensive to add instances into the ontology. The most confident and trust-worthy way to add instances into the ontology is to gather instances from tables in the related Web pages. In automatic populating of instances, the primary task is to find the most proper concept among all possible concepts within the ontology for a given table. This paper proposes a novel method for this problem by defining the similarity between the table and the concept using the overlap of their properties. According to a series of experiments, the proposed method achieves 76.98% of accuracy. This implies that the proposed method is a plausible way for automatic ontology population from Web tables.
Abstract: In Thailand, the practice of pre-hospital Emergency
Medical Service (EMS) in each area reveals the different growth
rates and effectiveness of the practices. Those can be found as the
diverse quality and quantity. To shorten the learning curve prior to
speed-up the practices in other areas, story telling and lessons learnt
from the effective practices are valued as meaningful knowledge. To
this paper, it was to ascertain the factors, lessons learnt and best
practices that have impact as contributing to the success of prehospital
EMS system. Those were formulized as model prior to
speedup the practice in other areas. To develop the model, Malcolm
Baldrige National Quality Award (MBNQA), which is widely
recognized as a framework for organizational quality assessment and
improvement, was chosen as the discussion framework. Remarkably,
this study was based on the consideration of knowledge capture;
however it was not to complete the loop of knowledge activities.
Nevertheless, it was to highlight the recognition of knowledge
capture, which is the initiation of knowledge management.