Abstract: In this paper a new approach to prioritize urban planning projects in an efficient and reliable way is presented. It is based on environmental pressure indices and multicriteria decision methods. The paper introduces a rigorous method with acceptable complexity of rank ordering urban development proposals according to their environmental pressure. The technique combines the use of Environmental Pressure Indicators, the aggregation of indicators in an Environmental Pressure Index by means of the Analytic Network Process method and interpreting the information obtained from the experts during the decision-making process. The ANP method allows the aggregation of the experts- judgments on each of the indicators into one Environmental Pressure Index. In addition, ANP is based on utility ratio functions which are the most appropriate for the analysis of uncertain data, like experts- estimations. Finally, unlike the other multicriteria techniques, ANP allows the decision problem to be modelled using the relationships among dependent criteria. The method has been applied to the proposal for urban development of La Carlota airport in Caracas (Venezuela). The Venezuelan Government would like to see a recreational project develop on the abandoned area and mean a significant improvement for the capital. There are currently three options on their table which are currently under evaluation. They include a Health Club, a Residential area and a Theme Park. The participating experts coincided in the appreciation that the method proposed in this paper is useful and an improvement from traditional techniques such as environmental impact studies, lifecycle analysis, etc. They find the results obtained coherent, the process seems sufficiently rigorous and precise, and the use of resources is significantly less than in other methods.
Abstract: Several recent studies have shown that the
transparency of financial reporting have a significant influence on investor-s decisions. Thus, regulation authorities and professional
organizations (IFAC) have emphasized the role of XBRL (eXtensible Business Reporting Language) and interactive data as a means of
promoting transparency and monitoring corporate reporting. In this
context, this paper has as objective the analysis of interactive reporting through XBRL and its use as a support in the process of
taking decisions in corporate governance, namely the potential of interactive reports in XBRL to increase the transparency and
monitoring process of corporate governance.
Abstract: This paper proposes a novel architecture for developing decision support systems. Unlike conventional decision support systems, the proposed architecture endeavors to reveal the decision-making process such that humans' subjectivity can be incorporated into a computerized system and, at the same time, to preserve the capability of the computerized system in processing information objectively. A number of techniques used in developing the decision support system are elaborated to make the decisionmarking process transparent. These include procedures for high dimensional data visualization, pattern classification, prediction, and evolutionary computational search. An artificial data set is first employed to compare the proposed approach with other methods. A simulated handwritten data set and a real data set on liver disease diagnosis are then employed to evaluate the efficacy of the proposed approach. The results are analyzed and discussed. The potentials of the proposed architecture as a useful decision support system are demonstrated.
Abstract: Land surface temperature (LST) is an important
parameter to study in urban climate. The understanding of the
influence of biophysical factors could improve the establishment of
modeling urban thermal landscape. It is well established that climate
hold a great influence on the urban landscape. However, it has been
recognize that climate has a low priority in urban planning process,
due to the complex nature of its influence. This study will focus on
the relatively cloud free Landsat Thematic Mapper image of the study
area, acquired on the 2nd March 2006. Correlation analyses were
conducted to identify the relationship of LST to the biophysical
factors; vegetation indices, impervious surface, and albedo to
investigate the variation of LST. We suggest that the results can be
considered by the stackholders during decision-making process to
create a cooler and comfortable environment in the urban landscape
for city dwellers.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.
Abstract: Supplier selection is a multi criteria decision-making process that comprises tangible and intangible factors. The majority of previous supplier selection techniques do not consider strategic perspective. Besides, uncertainty is one of the most important obstacles in supplier selection. For the first, time in this paper, the idea of the algorithm " Knapsack " is used to select suppliers Moreover, an attempt has to be made to take the advantage of a simple numerical method for solving model .This is an innovation to resolve any ambiguity in choosing suppliers. This model has been tried in the suppliers selected in a competitive environment and according to all desired standards of quality and quantity to show the efficiency of the model, an industry sample has been uses.
Abstract: To fight against the economic crisis, French
Government, like many others in Europe, has decided to give a boost
to high-speed line projects. This paper explores the implementation
and decision-making process in TGV projects, their evolutions,
especially since the Mediterranean TGV-line. This project was
probably the most controversial, but paradoxically represents today a
huge success for all the actors involved.
What kind of lessons we can learn from this experience? How to
evaluate the impact of this project on TGV-line planning? How can
we characterize this implementation and decision-making process
regards to the sustainability challenges?
The construction of Mediterranean TGV-line was the occasion to
make several innovations: to introduce more dialog into the decisionmaking
process, to take into account the environment, to introduce a
new project management and technological innovations. That-s why
this project appears today as an example in terms of integration of
sustainable development.
In this paper we examine the different kinds of innovations
developed in this project, by using concepts from sociology of
innovation to understand how these solutions emerged in a
controversial situation. Then we analyze the lessons which were
drawn from this decision-making process (in the immediacy and a
posteriori) and the way in which procedures evolved: creation of new
tools and devices (public consultation, project management...).
Finally we try to highlight the impact of this evolution on TGV
projects governance. In particular, new methods of implementation
and financing involve a reconfiguration of the system of actors. The
aim of this paper is to define the impact of this reconfiguration on
negotiations between stakeholders.
Abstract: Probabilistic characteristics of seismic responses of the
Partially Restrained connection rotation (PRCR) and panel zone
deformation (PZD) installed in older steel moment frames were
investigated in accordance with statistical inference in
decision-making process. The 4, 6 and 8 story older steel moment
frames with clip angle and T-stub connections were designed and
analyzed using 2%/50yrs ground motions in four cities of the
Mid-America earthquake region. The probability density function and
cumulative distribution function of PRCR and PZD were determined
by the goodness-of-fit tests based on probabilistic parameters
measured from the results of the nonlinear time-history analyses. The
obtained probabilistic parameters and distributions can be used to find
out what performance level mainly PR connections and panel zones
satisfy and how many PR connections and panel zones experience a
serious damage under the Mid-America ground motions.
Abstract: This study examines the issue of recommendation
sources from the perspectives of gender and consumers- perceived
risk, and validates a model for the antecedents of consumer online
purchases. The method of obtaining quantitative data was that of the
instrument of a survey questionnaire. Data were collected via
questionnaires from 396 undergraduate students aged 18-24, and a
multiple regression analysis was conducted to identify causal
relationships. Empirical findings established the link between
recommendation sources (word-of-mouth, advertising, and
recommendation systems) and the likelihood of making online
purchases and demonstrated the role of gender and perceived risk as
moderators in this context. The results showed that the effects of
word-of-mouth on online purchase intentions were stronger than those
of advertising and recommendation systems. In addition, female
consumers have less experience with online purchases, so they may be
more likely than males to refer to recommendations during the
decision-making process. The findings of the study will help
marketers to address the recommendation factor which influences
consumers- intention to purchase and to improve firm performances to
meet consumer needs.
Abstract: The new status generated by technological advancements and changes in the global economy raises important issues on how communities and organisations need to innovate upon their traditional processes in order to adapt to the challenges of the Knowledge Society. The DialogoS+ European project aims to study the role of and promote social dialogue in the banking sector, strengthen the link between old and new members and make social dialogue at the European level a force for innovation and change, also given the context of the international crisis emerging in 2008- 2009. Under the scope of DialogoS+, this paper describes how the community of Europe-s banking sector trade unions attempted to adapt to the challenges of the Knowledge Society by exploiting the benefits of new channels of communication, learning, knowledge generation and diffusion focusing on the concept of roadmapping. Important dimensions of social dialogue such as collective bargaining and working conditions are addressed.
Abstract: Heart failure is the most common reason of death
nowadays, but if the medical help is given directly, the patient-s life
may be saved in many cases. Numerous heart diseases can be
detected by means of analyzing electrocardiograms (ECG). Artificial
Neural Networks (ANN) are computer-based expert systems that
have proved to be useful in pattern recognition tasks. ANN can be
used in different phases of the decision-making process, from
classification to diagnostic procedures. This work concentrates on a
review followed by a novel method.
The purpose of the review is to assess the evidence of healthcare
benefits involving the application of artificial neural networks to the
clinical functions of diagnosis, prognosis and survival analysis, in
ECG signals. The developed method is based on a compound neural
network (CNN), to classify ECGs as normal or carrying an
AtrioVentricular heart Block (AVB). This method uses three
different feed forward multilayer neural networks. A single output
unit encodes the probability of AVB occurrences. A value between 0
and 0.1 is the desired output for a normal ECG; a value between 0.1
and 1 would infer an occurrence of an AVB. The results show that
this compound network has a good performance in detecting AVBs,
with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy
value is 87.9%.