Abstract: Knowledge is increasingly recognised in this, the
knowledge era, as a strategic resource, by public sector organisations,
in view of the public sector reform initiatives. People and knowledge
play a vital role in attaining improved organisational performance
and high service quality. Many government departments in the public
sector have started to realise the importance of knowledge
management in streamlining their operations and processes. This
study focused on knowledge management in the public healthcare
service organisations, where the concept of service provider
competitiveness pales to insignificance, considering the huge
challenges emanating from the healthcare and public sector reforms.
Many government departments are faced with challenges of
improving organisational performance and service delivery,
improving accountability, making informed decisions, capturing the
knowledge of the aging workforce, and enhancing partnerships with
stakeholders.
The purpose of this paper is to examine the knowledge
management practices of the Gauteng Department of Health in South
Africa, in order to understand how knowledge management practices
influence improvement in organisational performance and healthcare
service delivery. This issue is explored through a review of literature
on dominant views on knowledge management and healthcare service
delivery, as well as results of interviews with, and questionnaire
responses from, the general staff of the Gauteng Department of
Health. Web-based questionnaires, face-to-face interviews and
organisational documents were used to collect data. The data were
analysed using both the quantitative and qualitative methods. The
central question investigated was: To what extent can the conditions
required for successful knowledge management be observed, in order
to improve organisational performance and healthcare service
delivery in the Gauteng Department of Health.
The findings showed that the elements of knowledge management
capabilities investigated in this study, namely knowledge creation,
knowledge sharing and knowledge application, have a positive,
significant relationship with all measures of organisational
performance and healthcare service delivery. These findings thus
indicate that by employing knowledge management principles, the
Gauteng Department of Health could improve its ability to achieve its
operational goals and objectives, and solve organisational and
healthcare challenges, thereby improving organisational performance
and enhancing healthcare service delivery in Gauteng.
Abstract: A method is proposed to extract faithful representative patterns from data set of observations when they are suffering from non-negligible fluctuations. Supposing time interval between measurements to be extremely small compared to observation time, it consists in defining first a subset of intermediate time intervals characterizing coherent behavior. Data projection on these intervals gives a set of curves out of which an ideally “perfect” one is constructed by taking the sup limit of them. Then comparison with average real curve in corresponding interval gives an efficiency parameter expressing the degradation consecutive to fluctuation effect. The method is applied to sunlight data collected in a specific place, where ideal sunlight is the one resulting from direct exposure at location latitude over the year, and efficiency is resulting from action of meteorological parameters, mainly cloudiness, at different periods of the year. The extracted information already gives interesting element of decision, before being used for analysis of plant control.
Abstract: The planning in manufacturing system is becoming complicated day by day due to the expanding networks and shortage of skilled people to manage change. Consequently, faster lead time and rising demands for eco-efficient evaluation of manufacturing products and processes need exploitation of new and intelligent knowledge management concepts for manufacturing planning. This paper highlights motivation for incorporation of new features in the manufacturing planning system. Furthermore, it elaborates requirements for the development of intelligent knowledge management concept to support planning related decisions. Afterwards, the derived concept is presented in this paper considering two case studies. The first case study is concerned with the automotive ramp-up planning. The second case study specifies requirements for knowledge management system to support decisions in eco-efficient evaluation of manufacturing products and processes
Abstract: The research on ARCS for critical information retrieval development aimed to (1) investigate conditions of critical information retrieval skill of the Mathematics pre-service teachers before applying ARCS model in learning activities, (2) study and analyze the development of critical information retrieval skill of the Mathematics pre-service teachers after utilizing ARCS model in learning activities, and (3) evaluate the Mathematics pre-service teachers’ satisfaction on using ARCS model in learning activities as a tool to development critical information retrieval skill. Forty-one of 4th year Mathematics pre-service teachers who have enrolled in the subject of Research for Learning Development of semester 2 in 2012 were purposively selected as the research cohort. The research tools were self-report and interview questionnaire that was approved as content validity and reliability (IOC=.66-1.00, α =.834). The research found that critical information retrieval skill of the research samples before using ARCS model in learning activities was in the normal high level. According to the in-depth interview and focus group, the result however showed that the pre-service teachers still lack inadequate and effective knowledge in information retrieval. Additionally, critical information retrieval skill of the research cohort after applying ARCS model in learning activities appeared to be high level. The result revealed that the pre-service teachers are able to explain the method of searching, extraction, and selecting information as well as evaluating quality of information, and effectively making decision in accepting information. Moreover, the research discovered that the pre-service teachers showed normal high to highest level of satisfaction on using ARCS model in learning activities as a tool to development their critical information retrieval skill.
Abstract: Human society, there are many uncertainties, such as economic growth rate forecast of the financial crisis, many scholars have, since the the Song Chissom two scholars in 1993 the concept of the so-called fuzzy time series (Fuzzy Time Series)different mode to deal with these problems, a previous study, however, usually does not consider the relevant variables selected and fuzzy process based solely on subjective opinions the fuzzy semantic discrete, so can not objectively reflect the characteristics of the data set, in addition to carrying outforecasts are often fuzzy rules as equally important, failed to consider the importance of each fuzzy rule. For these reasons, the variable selection (Factor Selection) through self-organizing map (Self-Organizing Map, SOM) and proposed high-end weighted multivariate fuzzy time series model based on fuzzy neural network (Fuzzy-BPN), and using the the sequential weighted average operator (Ordered Weighted Averaging operator, OWA) weighted prediction. Therefore, in order to verify the proposed method, the Taiwan stock exchange (Taiwan Stock Exchange Corporation) Taiwan Weighted Stock Index (Taiwan Stock Exchange Capitalization Weighted Stock Index, TAIEX) as experimental forecast target, in order to filter the appropriate variables in the experiment Finally, included in other studies in recent years mode in conjunction with this study, the results showed that the predictive ability of this study further improve.
Abstract: A reconfigurable manufacturing system (RMS) is an
advanced system designed at the outset for rapid changes in its hardware
and software components in order to quickly adjust its production
capacity and functionally. Among various operational decisions, this
study considers the scheduling problem that determines the input
sequence and schedule at the same time for a given set of parts. In
particular, we consider the practical constraints that the numbers of
pallets/fixtures are limited and hence a part can be released into the
system only when the fixture required for the part is available. To
solve the integrated input sequencing and scheduling problems, we
suggest a priority rule based approach in which the two sub-problems
are solved using a combination of priority rules. To show the effectiveness
of various rule combinations, a simulation experiment was
done on the data for a real RMS, and the test results are reported.
Abstract: In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment.
Abstract: In this paper, an efficient method for personal identification based on the pattern of human iris is proposed. It is composed of image acquisition, image preprocessing to make a flat iris then it is converted into eigeniris and decision is carried out using only reduction of iris in one dimension. By comparing the eigenirises it is determined whether two irises are similar. The results show that proposed method is quite effective.
Abstract: In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.
Abstract: Nowadays, more engineering systems are using some
kind of Artificial Intelligence (AI) for the development of their
processes. Some well-known AI techniques include artificial neural
nets, fuzzy inference systems, and neuro-fuzzy inference systems
among others. Furthermore, many decision-making applications base
their intelligent processes on Fuzzy Logic; due to the Fuzzy
Inference Systems (FIS) capability to deal with problems that are
based on user knowledge and experience. Also, knowing that users
have a wide variety of distinctiveness, and generally, provide
uncertain data, this information can be used and properly processed
by a FIS. To properly consider uncertainty and inexact system input
values, FIS normally use Membership Functions (MF) that represent
a degree of user satisfaction on certain conditions and/or constraints.
In order to define the parameters of the MFs, the knowledge from
experts in the field is very important. This knowledge defines the MF
shape to process the user inputs and through fuzzy reasoning and
inference mechanisms, the FIS can provide an “appropriate" output.
However an important issue immediately arises: How can it be
assured that the obtained output is the optimum solution? How can it
be guaranteed that each MF has an optimum shape? A viable solution
to these questions is through the MFs parameter optimization. In this
Paper a novel parameter optimization process is presented. The
process for FIS parameter optimization consists of the five simple
steps that can be easily realized off-line. Here the proposed process
of FIS parameter optimization it is demonstrated by its
implementation on an Intelligent Interface section dealing with the
on-line customization / personalization of internet portals applied to
E-commerce.
Abstract: Value-based group decision is very complicated since many parties involved. There are different concern caused by differing preferences, experiences, and background. Therefore, a support system is required to enable each stakeholder to evaluate and rank the solution alternatives before engaging into negotiation with the other stakeholders. The support system is based on combination between value-based analysis, multi criteria group decision making based on satisfying options, and negotiation process based on coalition formation. This paper presents the group decision and negotiation on the selection of suitable material for a support bridge structure involving three decision makers, who are an estate manager, a project manager, and an engineer. There are three alternative solutions for the material of the support bridge structure, which are (a1) steel structure, (a2) reinforced concrete structure and (a3) wooden structure.
Abstract: There is widespread emphasis on reform in the teaching of introductory statistics at the college level. Underpinning this reform is a consensus among educators and practitioners that traditional curricular materials and pedagogical strategies have not been effective in promoting statistical literacy, a competency that is becoming increasingly necessary for effective decision-making and evidence-based practice. This paper explains the historical context of, and rationale for reform-oriented teaching of introductory statistics (at the college level) in the health, social and behavioral sciences (evidence-based disciplines). A firm understanding and appreciation of the basis for change in pedagogical approach is important, in order to facilitate commitment to reform, consensus building on appropriate strategies, and adoption and maintenance of best practices. In essence, reform-oriented pedagogy, in this context, is a function of the interaction among content, pedagogy, technology, and assessment. The challenge is to create an appropriate balance among these domains.
Abstract: This study uses a simulation to establish a realistic
environment for laboratory research on Accountable Care
Organizations. We study network attributes in order to gain insights
regarding healthcare providers- conduct and performance. Our
findings indicate how network structure creates significant
differences in organizational performance. We demonstrate how
healthcare providers positioning themselves at the central, pivotal
point of the network while maintaining their alliances with their
partners produce better outcomes.
Abstract: Decentralized Tuple Space (DTS) implements tuple
space model among a series of decentralized hosts and provides the
logical global shared tuple repository. Replication has been introduced
to promote performance problem incurred by remote tuple access. In
this paper, we propose a replication approach of DTS allowing
replication policies self-adapting. The accesses from users or other
nodes are monitored and collected to contribute the decision making.
The replication policy may be changed if the better performance is
expected. The experiments show that this approach suitably adjusts the
replication policies, which brings negligible overhead.
Abstract: This paper provides an overview of auction theory literature. We present a general review on literature of various auctions and focus ourselves specifically on an English auction. We are interested in modelling bidder's behavior in an English auction environment. And hence, we present an overview of the New Zealand wool auction followed by a model that would describe a bidder's decision making behavior from the New Zealand wool auction. The mathematical assumptions in an English auction environment are demonstrated from the perspective of the New Zealand wool auction.
Abstract: Post-disaster reconstruction projects offer
opportunities to facilitate physical, social and economic development
and to reduce future hazard vulnerability long after the disasters.
Sustainability of post-disaster reconstruction project conducted in the
villages of Dinar following the 1995 earthquake was investigated in
this paper. Officials of the Government who were involved in the
project were interviewed. Besides, two field surveys were done in 12
villages of Dinar in winter months of 2008. Beneficiaries were
interviewed and physical, socio-cultural and economic impacts of the
reconstruction were examined. The research revealed that the postdisaster
reconstruction project has negative aspects from the point
view of sustainability. The physical, socio-cultural and economic
factors were not considered during decision making process of the
project.
Abstract: The optimal control is one of the possible controllers
for a dynamic system, having a linear quadratic regulator and using
the Pontryagin-s principle or the dynamic programming method .
Stochastic disturbances may affect the coefficients (multiplicative
disturbances) or the equations (additive disturbances), provided that
the shocks are not too great . Nevertheless, this approach encounters
difficulties when uncertainties are very important or when the probability
calculus is of no help with very imprecise data. The fuzzy
logic contributes to a pragmatic solution of such a problem since it
operates on fuzzy numbers. A fuzzy controller acts as an artificial
decision maker that operates in a closed-loop system in real time.
This contribution seeks to explore the tracking problem and control
of dynamic macroeconomic models using a fuzzy learning algorithm.
A two inputs - single output (TISO) fuzzy model is applied to the
linear fluctuation model of Phillips and to the nonlinear growth model
of Goodwin.
Abstract: Creation and maintenance of knowledge management
systems has been recognized as an important research area.
Consecutively lack of accurate results from knowledge management
systems limits the organization to apply their knowledge
management processes. This leads to a failure in getting the right
information to the right people at the right time thus followed by a
deficiency in decision making processes. An Intranet offers a
powerful tool for communication and collaboration, presenting data
and information, and the means that creates and shares knowledge,
all in one easily accessible place. This paper proposes an archetype
describing how a knowledge management system, with the support
of intranet capabilities, could very much increase the accuracy of
capturing, storing and retrieving knowledge based processes thereby
increasing the efficiency of the system. This system will expect a
critical mass of usage, by the users, for intranet to function as
knowledge management systems. This prototype would lead to a
design of an application that would impose creation and maintenance
of an effective knowledge management system through intranet. The
aim of this paper is to introduce an effective system to handle
capture, store and distribute knowledge management in a form that
may not lead to any failure which exists in most of the systems. The
methodology used in the system would require all the employees, in
the organization, to contribute the maximum to deliver the system to
a successful arena. The system is still in its initial mode and thereby
the authors are under the process to practically implement the ideas,
as mentioned in the system, to produce satisfactory results.
Abstract: Collaborative planning, forecasting and
replenishment (CPFR) coordinates the various supply chain
management activities including production and purchase planning,
demand forecasting and inventory replenishment between supply
chain trading partners. This study proposes a systematic way of
analyzing CPFR supporting factors using fuzzy cognitive map
(FCM) approach. FCMs have proven particularly useful for solving
problems in which a number of decision variables and
uncontrollable variables are causally interrelated. Hence the FCMs
of CPFR are created to show the relationships between the factors
that influence on effective implementation of CPFR in the supply
chain.
Abstract: Building condition assessment is a critical activity in Malaysia-s Comprehensive Asset Management Model. It is closely related to building performance that impact user-s life and decision making. This study focuses on public primary school, one of the most valuable assets for the country. The assessment was carried out based on CSP1 Matrix in Kuching Division of Sarawak, Malaysia. Based on the matrix used, three main criteria of the buildings has successfully evaluate: the number of defects; schools rating; and total schools rating. The analysis carried out on 24 schools found that the overall 4, 725 defects has been identified. Meanwhile, the overall score obtained was 45, 868 and the overall rating is 9.71, which is at the fair condition. This result has been associated with building age to evaluate its impacts on school buildings condition. The findings proved that building condition is closely related to building age and its support the theory that 'the ageing building has more defect than the new one'.