Abstract: Group key management is an important functional
building block for any secure multicast architecture.
Thereby, it has been extensively studied in the literature.
In this paper we present relevant group key management
protocols. Then, we compare them against some pertinent
performance criteria.
Abstract: Industrial design engineering is an information and
knowledge intensive job. Although Wikipedia offers a lot of this
information, design engineers are better served with a wiki tailored to
their job, offering information in a compact manner and functioning
as a design tool. For that reason WikID has been developed.
However for the viability of a wiki, an active user community is
essential. The main subject of this paper is a study to the influence of
the communication and the contents of WikID on the user-s
willingness to contribute.
At first the theory about a website-s first impression, general
usability guidelines and user motivation in an online community is
studied. Using this theory, the aspects of the current site are analyzed
on their suitability. These results have been verified with a
questionnaire amongst 66 industrial design engineers (or students
industrial design engineering).
The main conclusion is that design engineers are enchanted with
the existence of WikID and its knowledge structure (taxonomy) but
this structure has not become clear without any guidance. In other
words, the knowledge structure is very helpful for inspiring and
guiding design engineers through their tailored knowledge domain in
WikID but this taxonomy has to be better communicated on the main
page. Thereby the main page needs to be fitted more to the target
group preferences.
Abstract: Knowledge of an organization does not merely reside
in structured form of information and data; it is also embedded in
unstructured form. The discovery of such knowledge is particularly
difficult as the characteristic is dynamic, scattered, massive and
multiplying at high speed. Conventional methods of managing
unstructured information are considered too resource demanding and
time consuming to cope with the rapid information growth.
In this paper, a Multi-faceted and Automatic Knowledge
Elicitation System (MAKES) is introduced for the purpose of
discovery and capture of organizational knowledge. A trial
implementation has been conducted in a public organization to
achieve the objective of decision capture and navigation from a
number of meeting minutes which are autonomously organized,
classified and presented in a multi-faceted taxonomy map in both
document and content level. Key concepts such as critical decision
made, key knowledge workers, knowledge flow and the relationship
among them are elicited and displayed in predefined knowledge
model and maps. Hence, the structured knowledge can be retained,
shared and reused.
Conducting Knowledge Management with MAKES reduces work
in searching and retrieving the target decision, saves a great deal of
time and manpower, and also enables an organization to keep pace
with the knowledge life cycle. This is particularly important when
the amount of unstructured information and data grows extremely
quickly. This system approach of knowledge management can
accelerate value extraction and creation cycles of organizations.
Abstract: Decision Support System (DSS) are interactive
software systems that are built to assist the management of an
organization in the decision making process when faced with nonroutine
problems in a specific application domain. Non-functional
requirements (NFRs) for a DSS deal with the desirable qualities and
restrictions that the DSS functionalities must satisfy. Unlike the
functional requirements, which are tangible functionalities provided
by the DSS, NFRs are often hidden and transparent to DSS users but
affect the quality of the provided functionalities. NFRs are often
overlooked or added later to the system in an ad hoc manner, leading
to a poor overall quality of the system. In this paper, we discuss the
development of NFRs as part of the requirements engineering phase
of the system development life cycle of DSSs. To help eliciting
NFRs, we provide a comprehensive taxonomy of NFRs for DSSs.
Abstract: The survey and classification of the different security
attacks in structured peer-to-peer (P2P) overlay networks can be
useful to computer system designers, programmers, administrators,
and users. In this paper, we attempt to provide a taxonomy of
structured P2P overlay networks security attacks. We have specially
focused on the way these attacks can arise at each level of the
network. Moreover, we observed that most of the existing systems
such as Content Addressable Network (CAN), Chord, Pastry,
Tapestry, Kademlia, and Viceroy suffer from threats and vulnerability
which lead to disrupt and corrupt their functioning. We hope that our
survey constitutes a good help for who-s working on this area of
research.
Abstract: This paper focuses on a novel method for semantic
searching and retrieval of information about learning materials.
Metametadata encapsulate metadata instances by using the properties
and attributes provided by ontologies rather than describing learning
objects. A novel metametadata taxonomy has been developed which
provides the basis for a semantic search engine to extract, match and
map queries to retrieve relevant results. The use of ontological views
is a foundation for viewing the pedagogical content of metadata
extracted from learning objects by using the pedagogical attributes
from the metametadata taxonomy. Using the ontological approach
and metametadata (based on the metametadata taxonomy) we present
a novel semantic searching mechanism.These three strands – the
taxonomy, the ontological views, and the search algorithm – are
incorporated into a novel architecture (OMESCOD) which has been
implemented.
Abstract: Software Development Risks Identification (SDRI),
using Fault Tree Analysis (FTA), is a proposed technique to identify
not only the risk factors but also the causes of the appearance of the
risk factors in software development life cycle. The method is based
on analyzing the probable causes of software development failures
before they become problems and adversely affect a project. It uses
Fault tree analysis (FTA) to determine the probability of a particular
system level failures that are defined by A Taxonomy for Sources of
Software Development Risk to deduce failure analysis in which an
undesired state of a system by using Boolean logic to combine a
series of lower-level events. The major purpose of this paper is to use
the probabilistic calculations of Fault Tree Analysis approach to
determine all possible causes that lead to software development risk
occurrence
Abstract: This research paper presents a framework on how to
build up malware dataset.Many researchers took longer time to
clean the dataset from any noise or to transform the dataset into a
format that can be used straight away for testing. Therefore, this
research is proposing a framework to help researchers to speed up
the malware dataset cleaningprocesses which later can be used for
testing. It is believed, an efficient malware dataset cleaning
processes, can improved the quality of the data, thus help to improve
the accuracy and the efficiency of the subsequent analysis. Apart
from that, an in-depth understanding of the malware taxonomy is
also important prior and during the dataset cleaning processes. A
new Trojan classification has been proposed to complement this
framework.This experiment has been conducted in a controlled lab
environment and using the dataset from VxHeavens dataset. This
framework is built based on the integration of static and dynamic
analyses, incident response method and knowledge database
discovery (KDD) processes.This framework can be used as the basis
guideline for malware researchers in building malware dataset.
Abstract: Wikis are considered to be part of Web 2.0
technologies that potentially support collaborative learning and
writing. Wikis provide opportunities for multiple users to work on
the same document simultaneously. Most wikis have also a page for
written group discussion. Nevertheless, wikis may be used in
different ways depending on the pedagogy being used, and the
constraints imposed by the course design. This work explores
students- uses of wiki in teacher education. The analysis is based on a
taxonomy for classifying students- activities and actions carried out
on the wiki. The article also discusses the implications for using
wikis as collaborative writing tools in teacher education.
Abstract: In the context of business incubation (BI) as strategic
enablers, this paper critically reviews the literature relating to the
strategic benefits of BI in the Middle East. The taxonomy of BI
benefits in the strategic elements on 1) type, 2) financial model, 3)
services, 4) objectives, 5) number of clients, 6) number of graduates,
and 7) jobs creation. Understanding the importance of BI benefits can
be significant in the economic development although most incubators
lead to diversify the economy. Thus, taxonomies of the benefits of BI
are produced from both the academic literature and published case
studies. In this way, a classification of strategic benefits elements as
they relate to incubators has been developed to provide a greater
understanding of the benefits needed to obtain a specific element.
The result of this paper is Business incubators is aimed
entrepreneurship, jobs creation, research commercialization and
profitable enterprises in Middle Eastern countries.
Abstract: The present paper is oriented to classification and application of agent technique in simulation of anticipatory systems, namely those that use simulation models for the aid of anticipation. The main ideas root in the fact that the best way for description of computer simulation models is the technique of describing the simulated system itself (and the translation into the computer code is provided as automatic), and that the anticipation itself is often nested.
Abstract: The clustering ensembles combine multiple partitions
generated by different clustering algorithms into a single clustering
solution. Clustering ensembles have emerged as a prominent method
for improving robustness, stability and accuracy of unsupervised
classification solutions. So far, many contributions have been done to
find consensus clustering. One of the major problems in clustering
ensembles is the consensus function. In this paper, firstly, we
introduce clustering ensembles, representation of multiple partitions,
its challenges and present taxonomy of combination algorithms.
Secondly, we describe consensus functions in clustering ensembles
including Hypergraph partitioning, Voting approach, Mutual
information, Co-association based functions and Finite mixture
model, and next explain their advantages, disadvantages and
computational complexity. Finally, we compare the characteristics of
clustering ensembles algorithms such as computational complexity,
robustness, simplicity and accuracy on different datasets in previous
techniques.
Abstract: Managing knowledge of research is one way to ensure
just in time information and knowledge to support research strategist
and activities. Unfortunately researcher found the vital research
knowledge in IHL (Institutions of Higher Learning) are scattered,
unstructured and unorganized. Aiming on lay aside conceptual
foundations for understanding and developing OMS (Organizational
Memory System) to facilitate research in IHL, this research revealed
ten factors contributed to the needs of research in the IHL and seven
internal challenges of IHL in promoting research to their academic
members. This study then suggested a comprehensive support of
managing research knowledge using Organizational Memory System
(OMS). Eight OMS characteristics to support research were
identified. Finally the initial work in designing OMS was projected
using knowledge taxonomy. All analysis is derived from pertinent
research paper related to research in IHL and OMS. Further study can
be conducted to validate and verify results presented.
Abstract: In modern distributed software systems, the issue of communication among composing parts represents a critical point, but the idea of extending conventional programming languages with general purpose communication constructs seems difficult to realize. As a consequence, there is a (growing) gap between the abstraction level required by distributed applications and the concepts provided by platforms that enable communication. This work intends to discuss how the Model Driven Software Development approach can be considered as a mature technology to generate in automatic way the schematic part of applications related to communication, by providing at the same time high level specialized languages useful in all the phases of software production. To achieve the goal, a stack of languages (meta-meta¬models) has been introduced in order to describe – at different levels of abstraction – the collaborative behavior of generic entities in terms of communication actions related to a taxonomy of messages. Finally, the generation of platforms for communication is viewed as a form of specification of language semantics, that provides executable models of applications together with model-checking supports and effective runtime environments.