Abstract: A business case is a proposal for an investment
initiative to satisfy business and functional requirements. The
business case provides the foundation for tactical decision making
and technology risk management. It helps to clarify how the
organization will use its resources in the best way by providing
justification for investment of resources. This paper describes how
simulation was used for business case benefits and return on
investment for the procurement of 8 production machines. With
investment costs of about 4.7 million dollars and annual operating
costs of about 1.3 million, we needed to determine if the machines
would provide enough cost savings and cost avoidance. We
constructed a model of the existing factory environment consisting of
8 machines and subsequently, we conducted average day simulations
with light and heavy volumes to facilitate planning decisions
required to be documented and substantiated in the business case.
Abstract: Documents retrieval in Information Retrieval
Systems (IRS) is generally about understanding of
information in the documents concern. The more the system
able to understand the contents of documents the more
effective will be the retrieval outcomes. But understanding of the
contents is a very complex task. Conventional IRS apply algorithms
that can only approximate the meaning of document contents through
keywords approach using vector space model. Keywords may be
unstemmed or stemmed. When keywords are stemmed and conflated
in retrieving process, we are a step forwards in applying semantic
technology in IRS. Word stemming is a process in morphological
analysis under natural language processing, before syntactic and
semantic analysis. We have developed algorithms for Malay and
Arabic and incorporated stemming in our experimental systems in
order to measure retrieval effectiveness. The results have shown that
the retrieval effectiveness has increased when stemming is used in
the systems.
Abstract: The work presented in this paper focus on Knowledge Management services enabling CSCW (Computer Supported Cooperative Work) applications to provide an appropriate adaptation to the user and the situation in which the user is working. In this paper, we explain how a knowledge management system can be designed to support users in different situations exploiting contextual data, users' preferences, and profiles of involved artifacts (e.g., documents, multimedia files, mockups...). The presented work roots in the experience we had in the MILK project and early steps made in the MAIS project.
Abstract: Conflicts identification among non-functional requirements is often identified intuitively which impairs conflict analysis practices. This paper proposes a new model to identify conflicts among non-functional requirements. The proposed model uses the matrix mechanism to identify the quality based conflicts among non-functional requirements. The potential conflicts are identified through the mapping of low level conflicting quality attributes to low level functionalities using the matrices. The proposed model achieves the identification of conflicts among product and process requirements, identifies false conflicts, decreases the documentation overhead, and maintains transparency of identified conflicts. The attributes are not concomitantly taken into account by current models in practice.
Abstract: Recently, there has been a considerable increase in the
number of procedures carried out under regional anesthesia.
However, percutaneous nephrolithotomy (PCNL) procedures are
usually performed under general anesthesia. The aim of this study
was to assess the safety and efficacy of PCNL under spinal anesthesia
in patients with renal calculi. We describe our 9 years experience of
performing PCNL under spinal anesthesia for 387 patients with large
stones of the upper urinary tract, with regard to the effectiveness and
side effects. All patients received spinal anesthetics (Lidocain 5%, or
Bupivacaine 0.75%) and underwent PCNL in prone position. The
success rate was 94.1%. The incidence of complications was 11.6%.
PCNL under spinal anesthesia is feasible, safe, and well-tolerated in
management of patients with renal stones.
Abstract: The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.
Abstract: This paper describes a proposed support system which
enables applications designers to effectively create VR applications
using multiple haptic APIs. When the VR designers create
applications, it is often difficult to handle and understand many
parameters and functions that have to be set in the application program
using documentation manuals only. This complication may disrupt
creative imagination and result in inefficient coding. So, we proposed
the support application which improved the efficiency of VR
applications development and provided the interactive components of
confirmation of operations with haptic sense previously.
In this paper, we describe improvements of our former proposed
support application, which was applicable to multiple APIs and haptic
devices, and evaluate the new application by having participants
complete VR program. Results from a preliminary experiment suggest
that our application facilitates creation of VR applications.
Abstract: Restoration research has become important on principle recently in Czech Republic. The reason is simple. More than 70 % of mined brown coal comes from the North Bohemian Basin these days. Open cast brown coal mining has lead to large damage on the landscape. Reclamation of phytotoxic areas is one of the serious problems in the North Bohemian Basin. It mainly concerns the areas with the occurrence of overburden rocks from the coal bed enriched with coal. The presented paper includes the characteristics of the important phytotoxic areas and the methodology of their reclamation. The results are documented with the long term monitoring of physical, mineralogical, chemical and pedological parameters of rocks in the testing areas.
Abstract: Natural organic matter (NOM) is heterogeneous
mixture of organic compounds that enter the water media from
animal and plant remains, domestic and industrial wastes.
Researches showed that NOM is likely precursor material for
disinfection by products (DBPs). Chlorine very commenly used for
disinfection purposes and NOM and chlorine reacts then
Trihalomethane (THM) and Haloacetic acids (HAAs) which are
cancerogenics for human health are produced. The aim of the study is
to search NOM removal by enhanced coagulation from drinking
water source of Eskisehir which is supplied from Porsuk Dam.
Recently, Porsuk dam water is getting highly polluted and therefore
NOM concentration is increasing. Enhanced coagulation studies were
evaluated by measurement of Dissolved Organic Carbon (DOC), UV
absorbance at 254 nm (UV254), and different trihalomethane
formation potential (THMFP) tests. Results of jar test experiments
showed that NOM can be removed from water about 40-50 % of
efficiency by enhanced coagulation. Optimum coagulant type and
coagulant dosages were determined using FeCl3 and Alum.
Abstract: All Text processing systems allow their users to
search a pattern of string from a given text. String matching is
fundamental to database and text processing applications. Every text
editor must contain a mechanism to search the current document for
arbitrary strings. Spelling checkers scan an input text for words in the
dictionary and reject any strings that do not match. We store our
information in data bases so that later on we can retrieve the same
and this retrieval can be done by using various string matching
algorithms. This paper is describing a new string matching algorithm
for various applications. A new algorithm has been designed with the
help of Rabin Karp Matcher, to improve string matching process.
Abstract: The purpose of semantic web research is to transform
the Web from a linked document repository into a distributed knowledge base and application platform, thus allowing the vast range of available information and services to be more efficiently
exploited. As a first step in this transformation, languages such as
OWL have been developed. Although fully realizing the Semantic Web still seems some way off, OWL has already been very
successful and has rapidly become a defacto standard for ontology
development in fields as diverse as geography, geology, astronomy,
agriculture, defence and the life sciences. The aim of this paper is to classify key concepts of Semantic Web as well as introducing a new
practical approach which uses these concepts to outperform Word Wide Web.
Abstract: Digital news with a variety topics is abundant on the
internet. The problem is to classify news based on its appropriate
category to facilitate user to find relevant news rapidly. Classifier
engine is used to split any news automatically into the respective
category. This research employs Support Vector Machine (SVM) to
classify Indonesian news. SVM is a robust method to classify
binary classes. The core processing of SVM is in the formation of an
optimum separating plane to separate the different classes. For
multiclass problem, a mechanism called one against one is used to
combine the binary classification result. Documents were taken
from the Indonesian digital news site, www.kompas.com. The
experiment showed a promising result with the accuracy rate of 85%.
This system is feasible to be implemented on Indonesian news
classification.
Abstract: The objective of this research is to explore the role of actors at the local level in managing the Pre-hospital Emergency Medical Service (EMS) system in Thailand. The research method was done through documentary research, individual interviews, and one forum conducted in each province. This paper uses the case of three provinces located in three regions in Thailand including; Ubon Ratchathani (North-eastern region), Lampang (Northern Region), and Songkhla (Southern Region). The result shows that, recently, the role of the local government in being the service provider for their local people is increasingly concerned. In identifying the key success factors towards the EMS system, it includes; (i) the local executives- vision and influence that the decisions made by them, for both PAO (Provincial Administration Organisation (PAO) and TAO (Tambon Administration Organisation), is vital to address the overall challenges in EMS development, (ii) the administrative system through reforming their working style create the flexibility in running the EMS task, (iii) the network-based management among different agencies at the local level leads to the better EMS practices, and (iv) the development in human resource is very vital in delivering the effective services.
Abstract: Background: Blunt aortic trauma (BAT) includes
various morphological changes that occur during deceleration,
acceleration and/or body compression in traffic accidents. The
various forms of BAT, from limited laceration of the intima to
complete transection of the aorta, depends on the force acting on the
vessel wall and the tolerance of the aorta to injury. The force depends
on the change in velocity, the dynamics of the accident and of the
seating position in the car. Tolerance to aortic injury depends on the
anatomy, histological structure and pathomorphological alterations
due to aging or disease of the aortic wall.
An overview of the literature and medical documentation reveals
that different terms are used to describe certain forms of BAT, which
can lead to misinterpretation of findings or diagnoses. We therefore,
propose a classification that would enable uniform systematic
screening of all forms of BAT. We have classified BAT into three
morphologycal types: TYPE I (intramural), TYPE II (transmural) and
TYPE III (multiple) aortic ruptures with appropriate subtypes.
Methods: All car accident casualties examined at the Institute of
Forensic Medicine from 2001 to 2009 were included in this
retrospective study. Autopsy reports were used to determine the
occurrence of each morphological type of BAT in deceased drivers,
front seat passengers and other passengers in cars and to define the
morphology of BAT in relation to the accident dynamics and the age
of the fatalities.
Results: A total of 391 fatalities in car accidents were included in
the study. TYPE I, TYPE II and TYPE III BAT were observed in
10,9%, 55,6% and 33,5%, respectively. The incidence of BAT in
drivers, front seat and other passengers was 36,7%, 43,1% and
28,6%, respectively. In frontal collisions, the incidence of BAT was
32,7%, in lateral collisions 54,2%, and in other traffic accidents
29,3%. The average age of fatalities with BAT was 42,8 years and of
those without BAT 39,1 years.
Conclusion: Identification and early recognition of the risk factors
of BAT following a traffic accident is crucial for successful treatment
of patients with BAT. Front seat passengers over 50 years of age who
have been injured in a lateral collision are the most at risk of BAT.
Abstract: Graph has become increasingly important in modeling
complicated structures and schemaless data such as proteins, chemical
compounds, and XML documents. Given a graph query, it is desirable
to retrieve graphs quickly from a large database via graph-based
indices. Different from the existing methods, our approach, called
VFM (Vertex to Frequent Feature Mapping), makes use of vertices
and decision features as the basic indexing feature. VFM constructs
two mappings between vertices and frequent features to answer graph
queries. The VFM approach not only provides an elegant solution to
the graph indexing problem, but also demonstrates how database
indexing and query processing can benefit from data mining,
especially frequent pattern mining. The results show that the proposed
method not only avoids the enumeration method of getting subgraphs
of query graph, but also effectively reduces the subgraph isomorphism
tests between the query graph and graphs in candidate answer set in
verification stage.
Abstract: The analysis is mainly concentrating on the knowledge
management literatures productivity trend which subjects as
“knowledge management" in SSCI database. The purpose what the
analysis will propose is to summarize the trend information for
knowledge management researchers since core knowledge will be
concentrated in core categories. The result indicated that the literature
productivity which topic as “knowledge management" is still
increasing extremely and will demonstrate the trend by different
categories including author, country/territory, institution name,
document type, language, publication year, and subject area. Focus on
the right categories, you will catch the core research information. This
implies that the phenomenon "success breeds success" is more
common in higher quality publications.
Abstract: This research documents a qualitative study of
selected Native Americans who have successfully graduated from
mainstream higher education institutions. The research framework
explored the Bicultural Identity Formation Model as a means of
understanding the expressions of the students' adaptations to
mainstream education. This approach lead to an awareness of how
the participants in the study used specific cultural and social
strategies to enhance their educational success and also to an
awareness of how they coped with cultural dissonance to achieve a
new academic identity. Research implications impact a larger
audience of bicultural, foreign, or international students experiencing
cultural dissonance.
Abstract: Demand over web services is in growing with increases number of Web users. Web service is applied by Web application. Web application size is affected by its user-s requirements and interests. Differential in requirements and interests lead to growing of Web application size. The efficient way to save store spaces for more data and information is achieved by implementing algorithms to compress the contents of Web application documents. This paper introduces an algorithm to reduce Web application size based on reduction of the contents of HTML files. It removes unimportant contents regardless of the HTML file size. The removing is not ignored any character that is predicted in the HTML building process.
Abstract: Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.
Abstract: Processing the data by computers and performing
reasoning tasks is an important aim in Computer Science. Semantic
Web is one step towards it. The use of ontologies to enhance the
information by semantically is the current trend. Huge amount of
domain specific, unstructured on-line data needs to be expressed in
machine understandable and semantically searchable format.
Currently users are often forced to search manually in the results
returned by the keyword-based search services. They also want to use
their native languages to express what they search. In this paper, an
ontology-based automated question answering system on software
test documents domain is presented. The system allows users to enter
a question about the domain by means of natural language and
returns exact answer of the questions. Conversion of the natural
language question into the ontology based query is the challenging
part of the system. To be able to achieve this, a new algorithm
regarding free text to ontology based search engine query conversion
is proposed. The algorithm is based on investigation of suitable
question type and parsing the words of the question sentence.