Abstract: Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.
Abstract: Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.
Abstract: Operators of vessel traffic service (VTS) center provides three different types of services; namely information service, navigational assistance and traffic organization to vessels. To provide these services, operators monitor vessel traffic through computer interface and provide navigational advice based on the information integrated from multiple sources, including automatic identification system (AIS), radar system, and closed circuit television (CCTV) system. Therefore, this information is crucial in VTS operation. However, what information the VTS operator actually need to efficiently and properly offer services is unclear. The aim of this study is to investigate into information requirements for VTS operation. To achieve this aim, field observation was carried out to elicit the information requirements for VTS operation. The study revealed that the most frequent and important tasks were handling arrival vessel report, potential conflict control and abeam vessel report. Current location and vessel name were used in all tasks. Hazard cargo information was particularly required when operators handle arrival vessel report. The speed, the course, and the distance of two or several vessels were only used in potential conflict control. The information requirements identified in this study can be utilized in designing a human-computer interface that takes into consideration what and when information should be displayed, and might be further used to build the foundation of a decision support system for VTS.
Abstract: This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.
Abstract: The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structures. Combined with qualitative measures the decision support system will contribute to a more efficient design of distribution logistics.
Abstract: In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.
Abstract: This study aims at being acquainted with the using the
body fat percentage (%BF) with body Mass Index (BMI) as input
parameters in fuzzy logic decision support system to predict properly
the lifted weight for students at weightlifting class lift according to
his abilities instead of traditional manner. The sample included 53
male students (age = 21.38 ± 0.71 yrs, height (Hgt) = 173.17 ± 5.28
cm, body weight (BW) = 70.34 ± 7.87.6 kg, Body mass index (BMI)
23.42 ± 2.06 kg.m-2, fat mass (FM) = 9.96 ± 3.15 kg and fat
percentage (% BF) = 13.98 ± 3.51 %.) experienced the weightlifting
class as a credit and has variance at BW, Hgt and BMI and FM. BMI
and % BF were taken as input parameters in FUZZY logic whereas
the output parameter was the lifted weight (LW). There were
statistical differences between LW values before and after using
fuzzy logic (Diff 3.55± 2.21, P > 0.001). The percentages of the LW
categories proposed by fuzzy logic were 3.77% of students to lift 1.0
fold of their bodies; 50.94% of students to lift 0.95 fold of their
bodies; 33.96% of students to lift 0.9 fold of their bodies; 3.77% of
students to lift 0.85 fold of their bodies and 7.55% of students to lift
0.8 fold of their bodies. The study concluded that the characteristic
changes in body composition experienced by students when
undergoing weightlifting could be utilized side by side with the
Fuzzy logic decision support system to determine the proper
workloads consistent with the abilities of students.
Abstract: This paper discusses the intake of combining multi-criteria
decision analysis (MCDA) with OLAP systems, to generate
an integrated analysis process dealing with complex multi-criteria
decision-making situations. In this context, a multi-agent modeling is
presented for decision support systems by combining multi-criteria
decision analysis (MCDA) with OLAP systems. The proposed
modeling which consists in performing the multi-agent system
(MAS) architecture, procedure and protocol of the negotiation model
is elaborated as a decision support tool for complex decision-making
environments. Our objective is to take advantage from the multi-agent
system which distributes resources and computational
capabilities across interconnected agents, and provide a problem
modeling in terms of autonomous interacting component-agents.
Thus, the identification and evaluation of criteria as well as the
evaluation and ranking of alternatives in a decision support situation
will be performed by organizing tasks and user preferences between
different agents in order to reach the right decision. At the end, an
illustrative example is conducted to demonstrate the function and
effectiveness of our MAS modeling.
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: 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: 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: 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: This paper presents an approach for the classification of
an unstructured format description for identification of file formats.
The main contribution of this work is the employment of data mining
techniques to support file format selection with just the unstructured
text description that comprises the most important format features for
a particular organisation. Subsequently, the file format indentification
method employs file format classifier and associated configurations to
support digital preservation experts with an estimation of required file
format. Our goal is to make use of a format specification knowledge
base aggregated from a different Web sources in order to select file
format for a particular institution. Using the naive Bayes method,
the decision support system recommends to an expert, the file format
for his institution. The proposed methods facilitate the selection of
file format and the quality of a digital preservation process. The
presented approach is meant to facilitate decision making for the
preservation of digital content in libraries and archives using domain
expert knowledge and specifications of file formats. To facilitate
decision-making, the aggregated information about the file formats is
presented as a file format vocabulary that comprises most common
terms that are characteristic for all researched formats. The goal is to
suggest a particular file format based on this vocabulary for analysis
by an expert. The sample file format calculation and the calculation
results including probabilities are presented in the evaluation section.
Abstract: Some plants of genus Schinus have been used in the
folk medicine as topical antiseptic, digestive, purgative, diuretic,
analgesic or antidepressant, and also for respiratory and urinary
infections. Chemical composition of essential oils of S. molle and S.
terebinthifolius had been evaluated and presented high variability
according with the part of the plant studied and with the geographic
and climatic regions. The pharmacological properties, namely
antimicrobial, anti-tumoural and anti-inflammatory activities are
conditioned by chemical composition of essential oils. Taking into
account the difficulty to infer the pharmacological properties of
Schinus essential oils without hard experimental approach, this work
will focus on the development of a decision support system, in terms
of its knowledge representation and reasoning procedures, under a
formal framework based on Logic Programming, complemented with
an approach to computing centered on Artificial Neural Networks
and the respective Degree-of-Confidence that one has on such an
occurrence.
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: Flash Floods, together with landslides, are a common
natural threat for people living in mountainous regions and foothills.
One way to deal with this constant menace is the use of Early
Warning Systems, which have become a very important mitigation
strategy for natural disasters.
In this work we present our proposal for a pilot Flash Flood Early
Warning System for Santiago, Chile, the first stage of a more
ambitious project that in a future stage shall also include early
warning of landslides.
To give a context for our approach, we first analyze three existing
Flash Flood Early Warning Systems, focusing on their general
architectures. We then present our proposed system, with main focus
on the decision support system, a system that integrates empirical
models and fuzzy expert systems to achieve reliable risk estimations.
Abstract: A Disaster Management System (DMS) is very important for countries with multiple disasters, such as Chile. In the world (also in Chile)different disasters (earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters) happen and have an effect on the population. It is also possible that two or more disasters occur at the same time. This meansthata multi-risk situation must be mastered. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs are concernedwith only a singledisaster (sometimes thecombination of earthquake and tsunami) and often with a particular disaster. Nevertheless, a DSS helps for a better real-time response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture and well defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.
Abstract: The aim of this study was to build ‘Ubi-Net’, a
decision-making support system for systematic establishment in
U-City planning. We have experienced various urban problems caused
by high-density development and population concentrations in
established urban areas. To address these problems, a U-Service
contributes to the alleviation of urban problems by providing real-time
information to citizens through network connections and related
information. However, technology, devices, and information for
consumers are required for systematic U-Service planning in towns
and cities where there are many difficulties in this regard, and a lack of
reference systems.
Thus, this study suggests methods to support the establishment of
sustainable planning by providing comprehensive information
including IT technology, devices, news, and social networking
services (SNS) to U-City planners through intelligent searches. In this
study, we targeted Smart U-Parking Planning to solve parking
problems in an ‘old’ city. Through this study, we sought to contribute
to supporting advances in U-Space and the alleviation of urban
problems.
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: The purposes of this study were to design and find
users’ satisfaction after using the decision support system for tourism
northern part of Thailand, which can provide tourists touristic
information and plan their personal voyage. Such information can be
retrieved systematically based on personal budget and provinces. The
samples of this study were five experts and users 30 persons white
collars in Bangkok. This decision support system was designed via
ASP.NET. Its database was developed by using MySQL, for
administrators are able to effectively manage the database. The
application outcome revealed that the innovation works properly as
sought in objectives. Specialists and white collars in Bangkok have
evaluated the decision support system; the result was satisfactorily
positive.