Abstract: Through the course of this paper we define Business Case Management and its characteristics, and highlight its link to knowledge workers. Business Case Management combines knowledge and process effectively, supporting the ad hoc and unpredictable nature of cases, and coordinate a range of other technologies to appropriately support knowledge-intensive processes. We emphasize the growing importance of knowledge workers and the current poor support for knowledge work automation. We also discuss the challenges in supporting this kind of knowledge work and propose a novel approach to overcome these challenges.
Abstract: With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.
Abstract: The importance of low power consumption is widely
acknowledged due to the increasing use of portable devices, which
require minimizing the consumption of energy. Energy dissipation is
heavily dependent on the software used in the system. Applying
design patterns in object-oriented designs is a common practice
nowadays. In this paper we analyze six design patterns and explore
the effect of them on energy consumption and performance.
Abstract: MATCH project [1] entitle the development of an
automatic diagnosis system that aims to support treatment of colon
cancer diseases by discovering mutations that occurs to tumour
suppressor genes (TSGs) and contributes to the development of
cancerous tumours. The constitution of the system is based on a)
colon cancer clinical data and b) biological information that will be
derived by data mining techniques from genomic and proteomic
sources The core mining module will consist of the popular, well
tested hybrid feature extraction methods, and new combined
algorithms, designed especially for the project. Elements of rough
sets, evolutionary computing, cluster analysis, self-organization maps
and association rules will be used to discover the annotations
between genes, and their influence on tumours [2]-[11].
The methods used to process the data have to address their high
complexity, potential inconsistency and problems of dealing with the
missing values. They must integrate all the useful information
necessary to solve the expert's question. For this purpose, the system
has to learn from data, or be able to interactively specify by a domain
specialist, the part of the knowledge structure it needs to answer a
given query. The program should also take into account the
importance/rank of the particular parts of data it analyses, and adjusts
the used algorithms accordingly.
Abstract: In this paper, an improved edge detection algorithm
based on fuzzy combination of mathematical morphology and
wavelet transform is proposed. The combined method is proposed to
overcome the limitation of wavelet based edge detection and
mathematical morphology based edge detection in noisy images.
Experimental results show superiority of the proposed method, as
compared to the traditional Prewitt, wavelet based and morphology
based edge detection methods. The proposed method is an effective
edge detection method for noisy image and keeps clear and
continuous edges.
Abstract: Despite of many scholars and practitioners recognize
the knowledge management implementation in an organizations but
insufficient attention has been paid by researchers to select suitable
knowledge portal system (KPS) selection. This study develops a
Multi Criteria Decision making model based on the fuzzy VIKOR
approach to help organizations in selecting KPS. The suitable portal
is the critical influential factors on the success of knowledge
management (KM) implementation in an organization.
Abstract: In the recent past Learning Classifier Systems have
been successfully used for data mining. Learning Classifier System
(LCS) is basically a machine learning technique which combines
evolutionary computing, reinforcement learning, supervised or
unsupervised learning and heuristics to produce adaptive systems. A
LCS learns by interacting with an environment from which it
receives feedback in the form of numerical reward. Learning is
achieved by trying to maximize the amount of reward received. All
LCSs models more or less, comprise four main components; a finite
population of condition–action rules, called classifiers; the
performance component, which governs the interaction with the
environment; the credit assignment component, which distributes the
reward received from the environment to the classifiers accountable
for the rewards obtained; the discovery component, which is
responsible for discovering better rules and improving existing ones
through a genetic algorithm. The concatenate of the production rules
in the LCS form the genotype, and therefore the GA should operate
on a population of classifier systems. This approach is known as the
'Pittsburgh' Classifier Systems. Other LCS that perform their GA at
the rule level within a population are known as 'Mitchigan' Classifier
Systems. The most predominant representation of the discovered
knowledge is the standard production rules (PRs) in the form of IF P
THEN D. The PRs, however, are unable to handle exceptions and do
not exhibit variable precision. The Censored Production Rules
(CPRs), an extension of PRs, were proposed by Michalski and
Winston that exhibit variable precision and supports an efficient
mechanism for handling exceptions. A CPR is an augmented
production rule of the form: IF P THEN D UNLESS C, where
Censor C is an exception to the rule. Such rules are employed in
situations, in which conditional statement IF P THEN D holds
frequently and the assertion C holds rarely. By using a rule of this
type we are free to ignore the exception conditions, when the
resources needed to establish its presence are tight or there is simply
no information available as to whether it holds or not. Thus, the IF P
THEN D part of CPR expresses important information, while the
UNLESS C part acts only as a switch and changes the polarity of D
to ~D. In this paper Pittsburgh style LCSs approach is used for
automated discovery of CPRs. An appropriate encoding scheme is
suggested to represent a chromosome consisting of fixed size set of
CPRs. Suitable genetic operators are designed for the set of CPRs
and individual CPRs and also appropriate fitness function is proposed
that incorporates basic constraints on CPR. Experimental results are
presented to demonstrate the performance of the proposed learning
classifier system.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.
Abstract: This paper describes the Multilingual Virtual Simulated Patient framework. It has been created to train the social skills and testing the knowledge of primary health care medical students. The framework generates conversational agents which perform in serveral languages as virtual simulated patients that help to improve the communication and diagnosis skills of the students complementing their training process.
Abstract: This paper discusses the designing of knowledge
integration of clinical information extracted from distributed medical
ontologies in order to ameliorate a machine learning-based multilabel
coding assignment system. The proposed approach is
implemented using a decision tree technique of the machine learning
on the university hospital data for patients with Coronary Heart
Disease (CHD). The preliminary results obtained show a satisfactory
finding that the use of medical ontologies improves the overall
system performance.
Abstract: Fungal infections are becoming more common and the
range of susceptible individuals has expanded. While Candida
albicans remains the most common infective species, other Candida
spp. are becoming increasingly significant. In a range of large-scale
studies of candidaemia between 1999 and 2006, about 52% of 9717
cases involved C. albicans, about 30% involved either C. glabrata or
C. parapsilosis and less than 15% involved C. tropicalis, C. krusei or
C. guilliermondii. However, the probability of mortality within 30
days of infection with a particular species was at least 40% for C.
tropicalis, C. albicans, C. glabrata and C. krusei and only 22% for
C. parapsilopsis. Clinical isolates of Candida spp. grew at rates
ranging from 1.65 h-1 to 4.9 h-1. Three species (C. krusei, C. albicans
and C. glabrata) had relatively high growth rates (μm > 4 h-1), C.
tropicalis and C. dubliniensis grew moderately quickly (Ôëê 3 h-1) and
C. parapsilosis and C. guilliermondii grew slowly (< 2 h-1). Based
on these data, the log of the odds of mortality within 30 days of
diagnosis was linearly related to μm. From this the underlying
probability of mortality is 0.13 (95% CI: 0.10-0.17) and it increases
by about 0.09 ± 0.02 for each unit increase in μm. Given that the
overall crude mortality is about 0.36, the growth of Candida spp.
approximately doubles the rate, consistent with the results of larger
case-matched studies of candidaemia.
Abstract: High quality requirements analysis is one of the most
crucial activities to ensure the success of a software project, so that
requirements verification for software system becomes more and more
important in Requirements Engineering (RE) and it is one of the most
helpful strategies for improving the quality of software system.
Related works show that requirement elicitation and analysis can be
facilitated by ontological approaches and semantic web technologies.
In this paper, we proposed a hybrid method which aims to verify
requirements with structural and formal semantics to detect
interactions. The proposed method is twofold: one is for modeling
requirements with the semantic web language OWL, to construct a
semantic context; the other is a set of interaction detection rules which
are derived from scenario-based analysis and represented with
semantic web rule language (SWRL). SWRL based rules are working
with rule engines like Jess to reason in semantic context for
requirements thus to detect interactions. The benefits of the proposed
method lie in three aspects: the method (i) provides systematic steps
for modeling requirements with an ontological approach, (ii) offers
synergy of requirements elicitation and domain engineering for
knowledge sharing, and (3)the proposed rules can systematically assist
in requirements interaction detection.
Abstract: Work stress causes the organizational work-life
imbalance of employees. Because of this imbalance, workers perform
with lower effort to finish assignments and thus an organization will
experience reduced productivity. In order to investigate the problem
of an organizational work-life imbalance, this qualitative case study
focuses on an organizational work-life imbalance among Thai
software developers in a German-owned company in Chiang Mai,
Thailand. In terms of knowledge management, fishbone diagram is
useful analysis tool to investigate the root causes of an organizational
work-life imbalance systematically in focus-group discussions.
Furthermore, fishbone diagram shows the relationship between
causes and effects clearly. It was found that an organizational worklife
imbalance among Thai software developers is influenced by
management team, work environment, and information tools used in
the company over time.
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: It is important problems to increase the detection rates
and reduce false positive rates in Intrusion Detection System (IDS).
Although preventative techniques such as access control and
authentication attempt to prevent intruders, these can fail, and as a
second line of defence, intrusion detection has been introduced. Rare
events are events that occur very infrequently, detection of rare
events is a common problem in many domains. In this paper we
propose an intrusion detection method that combines Rough set and
Fuzzy Clustering. Rough set has to decrease the amount of data and
get rid of redundancy. Fuzzy c-means clustering allow objects to
belong to several clusters simultaneously, with different degrees of
membership. Our approach allows us to recognize not only known
attacks but also to detect suspicious activity that may be the result of
a new, unknown attack. The experimental results on Knowledge
Discovery and Data Mining-(KDDCup 1999) Dataset show that the
method is efficient and practical for intrusion detection systems.
Abstract: The utility of expert system generators has been
widely recognized in many applications. Several generators based on
concept of the paradigm object, have been recently proposed. The
generator of oriented object expert system (GSEOO) offers
languages that are often complex and difficult to use. We propose in
this paper an extension of the expert system generator, JESS, which
permits a friendly use of this expert system. The new tool, called
VISUAL JESS, bring two main improvements to JESS. The first
improvement concerns the easiness of its utilization while giving
back transparency to the syntax and semantic aspects of the JESS
programming language. The second improvement permits an easy
access and modification of the JESS knowledge basis. The
implementation of VISUAL JESS is made so that it is extensible and
portable.
Abstract: Heat source addition to the axisymmetric supersonic
inlet may improve the performance parameters, which will increase
the inlet efficiency. In this investigation the heat has been added to
the flow field at some distance ahead of an axisymmetric inlet by
adding an imaginary thermal source upstream of cowl lip. The effect
of heat addition on the drag coefficient, mass flow rate and the
overall efficiency of the inlet have been investigated. The results
show that heat addition causes flow separation, hence to prevent this
phenomena, roughness has been added on the spike surface.
However, heat addition reduces the drag coefficient and the inlet
mass flow rate considerably. Furthermore, the effects of position,
size, and shape on the inlet performance were studied. It is found that
the thermal source deflects the flow streamlines. By improper
location of the thermal source, the optimum condition has been
obtained. For the optimum condition, the drag coefficient is
considerably reduced and the inlet mass flow rate and its efficiency
have been increased slightly. The optimum shape of the heat source
is obtained too.
Abstract: Technology transfer by international trade and
foreign direct investment is the most important positive
outcome of open economy. It is widely accepted that new
technology and knowledge have an important role in
enhancing economic growth. Human capital is the other
important factor assisting economic growth. In this study, the
role of human capital in the growth process is examined in a
view of new endogenous growth theory emphasizing on the
technology transfer resulting from international trade. Using
the panel data of 10 developed and 10 developing countries,
impact of human capital and openness on the rate of economic
growth of different countries is analysed. Evidence suggests
the view that human capital and openness contribute to the
economic growth in both developing and developed countries,
but with different rates.
Abstract: In this paper a low cost knowledge base system (KBS)
framework is proposed for design of deep drawing die and procedure
for developing system modules. The task of building the system is
structured into different modules for major activities of design of
deep drawing die. A manufacturability assessment module of the
proposed framework is developed to check the manufacturability of
deep drawn parts. The technological knowledge is represented by
using IF- THEN rules and it is coded in AutoLISP language. The
module is designed to be loaded into the prompt area of AutoCAD.
The cost of implementation of proposed system makes it affordable
for small and medium scale sheet metal industries.
Abstract: e-mail has become an important means of electronic
communication but the viability of its usage is marred by Unsolicited
Bulk e-mail (UBE) messages. UBE consists of many types
like pornographic, virus infected and 'cry-for-help' messages as well
as fake and fraudulent offers for jobs, winnings and medicines. UBE
poses technical and socio-economic challenges to usage of e-mails.
To meet this challenge and combat this menace, we need to
understand UBE. Towards this end, the current paper presents a
content-based textual analysis of nearly 3000 winnings-announcing
UBE. Technically, this is an application of Text Parsing and
Tokenization for an un-structured textual document and we approach
it using Bag Of Words (BOW) and Vector Space Document Model
techniques. We have attempted to identify the most frequently
occurring lexis in the winnings-announcing UBE documents. The
analysis of such top 100 lexis is also presented. We exhibit the
relationship between occurrence of a word from the identified lexisset
in the given UBE and the probability that the given UBE will be
the one announcing fake winnings. To the best of our knowledge and
survey of related literature, this is the first formal attempt for
identification of most frequently occurring lexis in winningsannouncing
UBE by its textual analysis. Finally, this is a sincere
attempt to bring about alertness against and mitigate the threat of
such luring but fake UBE.