Abstract: Background: To improve the delivery of paediatric
healthcare in low resource settings, Community Health Workers
(CHW) have been provided with a paper-based set of protocols
known as Community Case Management (CCM). Yet research has
shown that CHW adherence to CCM guidelines is poor, ultimately
impacting health service delivery. Digitising the CCM guidelines via
mobile technology is argued in extant literature to improve CHW
adherence. However, little research exist which outlines how (a) this
process can be digitised and (b) adherence could be improved as a
result. Aim: To explore how an electronic mobile version of CCM
(eCCM) can overcome issues associated with the paper-based CCM
protocol (inadequate adherence to guidelines) vis-à-vis service
blueprinting. This service blueprint will outline how (a) the CCM
process can be digitised using mobile Clinical Decision Support
Systems software to support clinical decision-making and (b)
adherence can be improved as a result. Method: Development of a
single service blueprint for a standalone application which visually
depicts the service processes (eCCM) when supporting the CHWs,
using an application known as Supporting LIFE (SL eCCM app) as
an exemplar. Results: A service blueprint is developed which
illustrates how the SL eCCM app can be utilised by CHWs to assist
with the delivery of healthcare services to children. Leveraging
smartphone technologies can (a) provide CHWs with just-in-time
data to assist with their decision making at the point-of-care and (b)
improve CHW adherence to CCM guidelines. Conclusions: The
development of the eCCM opens up opportunities for the CHWs to
leverage the inherent benefit of mobile devices to assist them with
health service delivery in rural settings. To ensure that benefits are
achieved, it is imperative to comprehend the functionality and form
of the eCCM service process. By creating such a service blueprint for
an eCCM approach, CHWs are provided with a clear picture
regarding the role of the eCCM solution, often resulting in buy-in
from the end-users.
Abstract: Evaluation of the excavation-induced ground
movements is an important design aspect of support systems in urban
areas. Geological and geotechnical conditions of an excavation area
have significant effects on excavation-induced ground movements and
the related damage. This paper is aimed at studying the performance of
excavation walls supported by nails in jointed rock medium. The
performance of nailed walls is investigated based on evaluating the
excavation-induced ground movements. For this purpose, a set of
calibrated 2D finite element models are developed by taking into
account the nail-rock-structure interactions, the anisotropic properties
of jointed rock, and the staged construction process. The results of this
paper highlight effects of different parameters such as joint
inclinations, anisotropy of rocks and nail inclinations on deformation
parameters of excavation wall supported by nails.
Abstract: Measuring the Electrocardiogram (ECG) signal is an
essential process for the diagnosis of the heart diseases. The ECG
signal has the information of the degree of how much the heart
performs its functions. In medical diagnosis and treatment systems,
Decision Support Systems processing the ECG signal are being
developed for the use of clinicians while medical examination. In this
study, a modular wireless ECG (WECG) measuring and recording
system using a single board computer and e-Health sensor platform
is developed. In this designed modular system, after the ECG signal
is taken from the body surface by the electrodes first, it is filtered and
converted to digital form. Then, it is recorded to the health database
using Wi-Fi communication technology. The real time access of the
ECG data is provided through the internet utilizing the developed
web interface.
Abstract: Sweden has succeeded to maintain a high level of
growth and development and has managed to sustain highly ranked
position among the world’s developed countries. In this regard,
Swedish universities are playing a vital role in supporting innovation
and entrepreneurship at all levels and developing Swedish knowledge
economy. This paper is aiming to draw on the experiences of two leading
Swedish universities, addressing their transformation approach to
create entrepreneurial universities and fulfilling their objectives in the
era of knowledge economy. The objectives of the paper include: 1) Introducing the Swedish
higher education and its characteristics. 2) Examining the
infrastructure elements for innovation and Entrepreneurship at two of
the Swedish entrepreneurial universities. 3) Addressing the key
aspects of support systems in the initiatives of both Chalmers and
Gothenburg universities to support innovation and advance
entrepreneurial practices. The paper will contribute to two discourses: 1) Examining the
relationship between support systems for innovation and
entrepreneurship and the Universities’ policies and practices. 2)
Lessons for University leaders to assist the development and
implementation of effective innovation and entrepreneurship policies
and practices.
Abstract: Land reallocation is one of the most important steps in
land consolidation projects. Many different models were proposed for
land reallocation in the literature such as Fuzzy Logic, block priority
based land reallocation and Spatial Decision Support Systems. A
model including four parts is considered for automatic block
reallocation with genetic algorithm method in land consolidation
projects. These stages are preparing data tables for a project land,
determining conditions and constraints of land reallocation, designing
command steps and logical flow chart of reallocation algorithm and
finally writing program codes of Genetic Algorithm respectively. In
this study, we designed the first three steps of the considered model
comprising four steps.
Abstract: This paper presents an approach of on-line control of
the state of technosphere and environment objects based on the
integration of Data Warehouse, OLAP and Expert systems
technologies. It looks at the structure and content of data warehouse
that provides consolidation and storage of monitoring data. There is a
description of OLAP-models that provide a multidimensional
analysis of monitoring data and dynamic analysis of principal
parameters of controlled objects. The authors suggest some criteria of
emergency risk assessment using expert knowledge about danger
levels. It is demonstrated now some of the proposed solutions could
be adopted in territorial decision making support systems.
Operational control allows authorities to detect threat, prevent natural
and anthropogenic emergencies and ensure a comprehensive safety of
territory.
Abstract: Waste Load Allocation (WLA) strategies usually
intend to find economic policies for water resource management.
Water quality trading (WQT) is an approach that uses discharge
permit market to reduce total environmental protection costs. This
primarily requires assigning discharge limits known as total
maximum daily loads (TMDLs). These are determined by monitoring
organizations with respect to the receiving water quality and
remediation capabilities. The purpose of this study is to compare two
approaches of TMDL assignment for WQT policy in small catchment
area of Haraz River, in north of Iran. At first, TMDLs are assigned
uniformly for the whole point sources to keep the concentrations of
BOD and dissolved oxygen (DO) at the standard level at checkpoint
(terminus point). This was simply simulated and controlled by
Qual2kw software. In the second scenario, TMDLs are assigned
using multi objective particle swarm optimization (MOPSO) method
in which the environmental violation at river basin and total treatment
costs are minimized simultaneously. In both scenarios, the equity
index and the WLA based on trading discharge permits (TDP) are
calculated. The comparative results showed that using economically
optimized TMDLs (2nd scenario) has slightly more cost savings rather
than uniform TMDL approach (1st scenario). The former annually
costs about 1 M$ while the latter is 1.15 M$. WQT can decrease
these annual costs to 0.9 and 1.1 M$, respectively. In other word,
these approaches may save 35 and 45% economically in comparison
with command and control policy. It means that using multi objective
decision support systems (DSS) may find more economical WLA,
however its outcome is not necessarily significant in comparison with
uniform TMDLs. This may be due to the similar impact factors of
dischargers in small catchments. Conversely, using uniform TMDLs
for WQT brings more equity that makes stakeholders not feel that
much envious of difference between TMDL and WQT allocation. In
addition, for this case, determination of TMDLs uniformly would be
much easier for monitoring. Consequently, uniform TMDL for TDP
market is recommended as a sustainable approach. However,
economical TMDLs can be used for larger watersheds.
Abstract: In this paper the problem of the application of
temporal reasoning and case-based reasoning in intelligent decision
support systems is considered. The method of case-based reasoning
with temporal dependences for the solution of problems of real-time
diagnostics and forecasting in intelligent decision support systems is
described. This paper demonstrates how the temporal case-based
reasoning system can be used in intelligent decision support systems
of the car access control. This work was supported by RFBR.
Abstract: Operations research science (OR) deals with good
success in developing and applying scientific methods for problem
solving and decision-making. However, by using OR techniques, we
can enhance the use of computer decision support systems to achieve
optimal management for institutions. OR applies comprehensive
analysis including all factors that effect on it and builds mathematical
modeling to solve business or organizational problems. In addition, it
improves decision-making and uses available resources efficiently.
The adoption of OR by universities would definitely contributes to
the development and enhancement of the performance of OR
techniques. This paper provides an understanding of the structures,
approaches and models of OR in problem solving and decisionmaking.
Abstract: In recent years, in addition to face the external threats such as energy shortages and climate change, traffic congestion and environmental pollution have become anxious problems for many cities. Considering private automobile-oriented urban development had produced many negative environmental and social impacts, the transit-oriented development (TOD) has been considered as a sustainable urban model. TOD encourages public transport combined with friendly walking and cycling environment designs, however, non-motorized modes help improving human health, energy saving, and reducing carbon emissions. Due to environmental changes often affect the planners’ decision-making; this research applies dynamic network process (DNP) which includes the time dependent concept to promoting friendly walking and cycling environmental designs as an advanced planning support system for environment improvements.
This research aims to discuss what kinds of design strategies can improve a friendly walking and cycling environment under TOD. First of all, we collate and analyze environment designing factors by reviewing the relevant literatures as well as divide into three aspects of “safety”, “convenience”, and “amenity” from fifteen environment designing factors. Furthermore, we utilize fuzzy Delphi Technique (FDT) expert questionnaire to filter out the more important designing criteria for the study case. Finally, we utilized DNP expert questionnaire to obtain the weights changes at different time points for each design criterion. Based on the changing trends of each criterion weight, we are able to develop appropriate designing strategies as the reference for planners to allocate resources in a dynamic environment. In order to illustrate the approach we propose in this research, Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.
Abstract: This review paper aims at understanding the importance of implementing sustainable green practices in the current hotel industry and the perception of the same from the point of view of the customers as well as the industry experts. Many hotels have benefited from green management such as enhanced reputation of the firm and more worth customers. For the business standing, it reduces business’s cost for posting advertisements and the clear hotel’s orientation shows hotels’ positive image which might increase employees’ recognition toward the business. Sustainability in business is the growth in lively processes which enable people to understand the potential to protect the Earth’s existent support systems. Well, looking to the future today’s green concerns will definitely become facet of more synchronized business environment, perhaps the concerns discussed in this study, may exchange a few words which hotels may consider in near future to widen awareness and improve business model.
Abstract: The design of temperature measuring approach for a re-configured milling machine to produce friction stir welds is reported in this paper. The product design specifications for the redesigning of a milling machine were first outlined and the ranking criteria were determined. Three different concepts were generated for the temperature measurement on the reconfigured system and the preferred or the best concept was selected based on the set design ranking criteria. Further simulation and performance analysis was then conducted on the concept. The Infrared Thermography (IRT) concept was selected for the temperature measurement among other concepts generated because it is an ideal and most effective system of measurement in this regard.
Abstract: Automated intelligent, clinical decision support systems generally promote to help or to assist physicians and patients regarding to prevention of diseases or treatment of illnesses using computer represented knowledge and information. In this paper, assessment factors affecting the proper design of clinical decision support system were investigated. The required procedure steps for gathering the data from clinical trial and extracting the information from large volume of healthcare repositories were listed, which are necessary for validation and verification of evidence-based implementation of clinical decision support system. The goal of this paper is to extract useful evaluation factors affecting the quality of the clinical decision support system in the design, development, and implementation of a computer-based decision support system.
Abstract: Data mining can be called as a technique to extract
information from data. It is the process of obtaining hidden
information and then turning it into qualified knowledge by statistical
and artificial intelligence technique. One of its application areas is
medical area to form decision support systems for diagnosis just by
inventing meaningful information from given medical data. In this
study a decision support system for diagnosis of illness that make use
of data mining and three different artificial intelligence classifier
algorithms namely Multilayer Perceptron, Naive Bayes Classifier and
J.48. Pima Indian dataset of UCI Machine Learning Repository was
used. This dataset includes urinary and blood test results of 768
patients. These test results consist of 8 different feature vectors.
Obtained classifying results were compared with the previous studies.
The suggestions for future studies were presented.
Abstract: Nowadays, driving support systems, such as car
navigation systems, are getting common, and they support drivers in
several aspects. It is important for driving support systems to detect
status of driver's consciousness. Particularly, detecting driver's
drowsiness could prevent drivers from collisions caused by drowsy
driving. In this paper, we discuss the various artificial detection
methods for detecting driver's drowsiness processing technique. This
system is based on facial images analysis for warning the driver of
drowsiness or in attention to prevent traffic accidents.
Abstract: Decision support systems are usually based on
multidimensional structures which use the concept of hypercube.
Dimensions are the axes on which facts are analyzed and form a
space where a fact is located by a set of coordinates at the
intersections of members of dimensions. Conventional
multidimensional structures deal with discrete facts linked to discrete
dimensions. However, when dealing with natural continuous
phenomena the discrete representation is not adequate. There is a
need to integrate spatiotemporal continuity within multidimensional
structures to enable analysis and exploration of continuous field data.
Research issues that lead to the integration of spatiotemporal
continuity in multidimensional structures are numerous. In this paper,
we discuss research issues related to the integration of continuity in
multidimensional structures, present briefly a multidimensional
model for continuous field data. We also define new aggregation
operations. The model and the associated operations and measures
are validated by a prototype.
Abstract: This paper presents an integrated case based and rule
based reasoning method for car faulty diagnosis. The reasoning
method is done through extracting the past cases from the Proton
Service Center while comparing with the preset rules to deduce a
diagnosis/solution to a car service case. New cases will be stored to
the knowledge base. The test cases examples illustrate the
effectiveness of the proposed integrated reasoning. It has proven
accuracy of similar reasoning if carried out by a service advisor from
the service center.
Abstract: The actual grow of the infrastructure in develop country require sophisticate ways manage the operation and control the quality served. This research wants to concentrate in the operation of this infrastructure beyond the construction. The infrastructure-s operation involves an uncertain environment, where unexpected variables are present every day and everywhere. Decision makers need to make right decisions with right information/data analyzed most in real time. To adequately support their decisions and decrease any negative impact and collateral effect, they need to use computational tools called decision support systems (DSS), but now the main source of information came from common users thought an extensive crowdsourcing
Abstract: A Decision Support System/Expert System for stock
portfolio selection presented where at first step, both technical and
fundamental data used to estimate technical and fundamental return
and risk (1st phase); Then, the estimated values are aggregated with
the investor preferences (2nd phase) to produce convenient stock
portfolio.
In the 1st phase, there are two expert systems, each of which is
responsible for technical or fundamental estimation. In the technical
expert system, for each stock, twenty seven candidates are identified
and with using rough sets-based clustering method (RC) the effective
variables have been selected. Next, for each stock two fuzzy rulebases
are developed with fuzzy C-Mean method and Takai-Sugeno-
Kang (TSK) approach; one for return estimation and the other for
risk. Thereafter, the parameters of the rule-bases are tuned with backpropagation
method. In parallel, for fundamental expert systems,
fuzzy rule-bases have been identified in the form of “IF-THEN" rules
through brainstorming with the stock market experts and the input
data have been derived from financial statements; as a result two
fuzzy rule-bases have been generated for all the stocks, one for return
and the other for risk.
In the 2nd phase, user preferences represented by four criteria and
are obtained by questionnaire. Using an expert system, four estimated
values of return and risk have been aggregated with the respective
values of user preference. At last, a fuzzy rule base having four rules,
treats these values and produce a ranking score for each stock which
will lead to a satisfactory portfolio for the user.
The stocks of six manufacturing companies and the period of
2003-2006 selected for data gathering.
Abstract: Multi criteria decision making (MCDM) methods like analytic hierarchy process, ELECTRE and multi-attribute utility theory are critically studied. They have irregularities in terms of the reliability of ranking of the best alternatives. The Routing Decision Support (RDS) algorithm is trying to improve some of their deficiencies. This paper gives a mathematical verification that the RDS algorithm conforms to the test criteria for an effective MCDM method when a linear preference function is considered.