Abstract: Transport infrastructures are high-cost, long-term investments that serve as vital foundations for the operation of a region or nation and are essential to a country’s or business’s economic development and prosperity, by improving well-being and generating jobs and income. The development of appropriate financing options is of key importance in the decision making process in order develop viable transport infrastructures. The development of transport infrastructure has increasingly been shifting toward alternative methods of project financing such as Public Private Partnership (PPPs) and hybrid forms. In this paper, a methodological decision-making framework based on the evaluation of the financial viability of transportation infrastructure for different financial schemes is presented. The framework leads to an assessment of the financial viability which can be achieved by performing various financing scenarios analyses. To illustrate the application of the proposed methodology, a case study of rail transport infrastructure financing scenario analysis in Greece is developed.
Abstract: In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.
Abstract: Traditionally in sensor networks and recently in the
Internet of Things, numerous heterogeneous sensors are deployed
in distributed manner to monitor a phenomenon that often can be
model by an underlying stochastic process. The big time-series
data collected by the sensors must be analyzed to detect change
in the stochastic process as quickly as possible with tolerable
false alarm rate. However, sensors may have different accuracy
and sensitivity range, and they decay along time. As a result,
the big time-series data collected by the sensors will contain
uncertainties and sometimes they are conflicting. In this study, we
present a framework to take advantage of Evidence Theory (a.k.a.
Dempster-Shafer and Dezert-Smarandache Theories) capabilities of
representing and managing uncertainty and conflict to fast change
detection and effectively deal with complementary hypotheses.
Specifically, Kullback-Leibler divergence is used as the similarity
metric to calculate the distances between the estimated current
distribution with the pre- and post-change distributions. Then mass
functions are calculated and related combination rules are applied to
combine the mass values among all sensors. Furthermore, we applied
the method to estimate the minimum number of sensors needed to
combine, so computational efficiency could be improved. Cumulative
sum test is then applied on the ratio of pignistic probability to detect
and declare the change for decision making purpose. Simulation
results using both synthetic data and real data from experimental
setup demonstrate the effectiveness of the presented schemes.
Abstract: Decision-makers tend to prefer the first alternative over subsequent alternatives which is called the primacy effect. To reliably measure this effect, we conducted an experiment with real consequences for preference statements. Therefore, we elicit preferences of subjects using a rating scale, i.e. hypothetical preferences, and willingness to pay, i.e. real preferences, for two sequences of pain. Within these sequences, both overall intensity and duration of pain are identical. Hence, a rational decision-maker should be indifferent, whereas the primacy effect predicts a stronger preference for the first sequence. What we see is a primacy effect only for hypothetical preferences. This effect vanishes for real preferences.
Abstract: NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.
Abstract: The dynamic and highly competitive nature of the consumer electronics retail industry means that businesses in this industry are experiencing different decision making challenges in relation to pricing, inventory control, consumer satisfaction and product offerings. To overcome the challenges facing retailers and create opportunities, we propose a generic data warehousing solution which can be applied to a wide range of consumer electronics retailers with a minimum configuration. The solution includes a dimensional data model, a template SQL script, a high level architectural descriptions, ETL tool developed using C#, a set of APIs, and data access tools. It has been successfully applied by ASK Outlets Ltd UK resulting in improved productivity and enhanced sales growth.
Abstract: There is drastic change in manufacturing era in last two decades. It has become mandatory for the industries to become aware of latest and advanced manufacturing technologies and strategies. Leagile manufacturing focuses on minimizing the wastes and meeting customers’ requirements in minimum time possible. However, it becomes difficult to implement all leagile tools simultaneously in industry. In this paper, 17 main criteria of leagile manufacturing have been found and DEMATEL (Decision Making Trial and Evaluation Laboratory) approach has been applied to analyze importance of criteria and casual relations among these criteria.
Abstract: Objectives: In recent years, the Faculty of Dentistry of the University of Hong Kong have extended the implementation of 3D electronic models (e-models) into problem-based learning (PBL) of the Bachelor of Dental Surgery (BDS) curriculum, aiming at mutual enhancement of PBL teaching quality and the students’ skills in using e-models. This study focuses on the effectiveness of e-models serving as a tool to enhance the students’ skills and competences in PBL. Methods: The questionnaire surveys are conducted to measure 50 fourth-year BDS students’ attitude change between beginning and end of blended PBL tutorials. The response rate of this survey is 100%. Results: The results of this study show the students’ agreement on enhancement of their learning experience after e-model implementation and their expectation to have more blended PBL courses in the future. The potential of e-models in cultivating students’ self-learning skills reduces their dependence on others, while improving their communication skills to argue about pros and cons of different treatment options. The students’ independent thinking ability and problem solving skills are promoted by e-model implementation, resulting in better decision making in treatment planning. Conclusion: It is important for future dental education curriculum planning to cope with the students’ needs, and offer support in the form of software, hardware and facilitators’ assistance for better e-model implementation.
Abstract: We present in this paper a web-based system called “HelpMeBreathe” for managing asthma. The proposed system provides analytical tools, which allow better understanding of environmental triggers of asthma, hence better support of data-driven decision making. The developed system provides warning messages to a specific asthma patient if the weather in his/her area might cause any difficulty in breathing or could trigger an asthma attack. HelpMeBreathe collects, stores, and analyzes individuals’ moving trajectories and health conditions as well as environmental data. It then processes and displays the patients’ data through an analytical tool that leads to an effective decision making by physicians and other decision makers.
Abstract: Advertising is commonly used to foster sales and reputation of an institution. It is at first the growth of print advertising that has increased the population and number of periodicals of newspaper and its circulation. The rise of Internet and online media has somehow blurred the role of media and advertising though the intention is still to reach out to audience and to increase sales. The relationship between advertising and audience on a product purchase through persuasion has been developing from print media to online media. From the changing media environment and audience, it is the concern of this research to study the impact of online advertising to such a relationship cycle. The content of online advertisements is much of text, multimedia, photo, audio and video. The messages of such content format may indeed bring impacts to its audience and its credibility. This study is therefore reflecting the effectiveness of online advertisement and its influences on generation Y in their purchasing behavior. This study uses Media Dependency Theory to analyze the relationship between the impact of online advertisement and media usage pattern of generation Y. Hierarchy of Effectiveness Model is used as a marketing communication model to study the effectiveness of advertising and further to determine the impact of online advertisement on generation Y in their purchasing decision making. This research uses online survey to reach out the sample of generation Y. The results have shown that online advertisements do not affect much on purchase decision making even though generation Y relies much on the media content including online advertisement for its information and believing in its credibility. There are few other external factors that may interrupt the effectiveness of online advertising. The very obvious influence of purchasing behavior is actually derived from the peers.
Abstract: Waste management decision making in developing countries has moved towards being more pragmatic, transparent, sustainable and comprehensive. Turkey is required to make its waste related legislation compatible with European Legislation as it is a candidate country of the European Union. Improper Turkish practices such as open burning and open dumping practices must be abandoned urgently, and robust waste management systems have to be structured. The determination of an optimum waste management system in any region requires a comprehensive analysis in which many criteria are taken into account by stakeholders. In conducting this sort of analysis, there are two main criteria which are evaluated by waste management analysts; economic viability and environmentally friendliness. From an analytical point of view, a central characteristic of sustainable development is an economic-ecological integration. It is predicted that building a robust waste management system will need significant effort and cooperation between the stakeholders in developing countries such as Turkey. In this regard, this study aims to provide data regarding the cost and environmental burdens of waste treatment technologies such as an incinerator, an autoclave (with different capacities), a hydroclave and a microwave coupled with updated information on calculation methods, and a framework for comparing any proposed scenario performances on a cost and environmental basis.
Abstract: The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1st, 2008 and December 31st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.
Abstract: Ultimatum game is an experimental paradigm to study human decision making. There are two players, a proposer and a responder, to split a fixed amount of money. According to the traditional economic theory on ultimatum game, proposer should propose the selfish offers to responder as much as possible to maximize proposer’s own outcomes. However, most evidences had showed that people chose more fair offers, hence two hypotheses – fairness favoring and strategic concern were proposed. In current study, we induced the motivation in participants to be either selfish or altruistic, and manipulated the task variables, the stake sizes (NT$100, 1000, 10000) and the share sizes (the 40%, 30%, 20%, 10% of the sum as selfish offers, and the 60%, 70%, 80%, 90% of the sum as altruistic offers), to examine the two hypotheses. The results showed that most proposers chose more fair offers with longer reaction times (RTs) no matter in choosing between the fair and selfish offers, or between the fair and altruistic offers. However, the proposers received explicit self-interest instruction chose more selfish offers accompanied with longer RTs in choosing between the fair and selfish offers. Therefore, the results supported the strategic concern hypothesis that previous proposers choosing the fair offers might be resulted from the fear of rejection by responders. Proposers would become more self-interest if the fear of being rejected is eliminated.
Abstract: The focus of the paper is to furnish the entropy measure
for a neutrosophic set and neutrosophic soft set which is a measure
of uncertainty and it permeates discourse and system. Various characterization
of entropy measures are derived. Further we exemplify
this concept by applying entropy in various real time decision making
problems.
Abstract: Considering a worldwide tendency, air transports are growing very fast and many changes have taken place in planning, management and decision making process. Given the complexity of airport operation, the best use of existing capacity is the key driver of efficiency and productivity. This paper deals with the evaluation framework for the ground access at airports, by using a set of mode choice indicators providing key messages towards airport’s ground access performance. The application presents results for a sample of 12 European airports, illustrating recommendations to define policy and improve service for the air transport access chain.
Abstract: Implementation of LARG (Lean, Agile, Resilient, Green) practices in the supply chain management is a complex task mainly because ecological, economical and operational goals are usually in conflict. To implement these LARG practices successfully, companies’ need relevant decision making tools allowing processes performance control and improvement strategies visibility. To contribute to this issue, this work tries to answer the following research question: How to master performance and anticipate problems in supply chain LARG practices implementation? To answer this question, a risk management approach (RMA) is adopted. Indeed, the proposed RMA aims basically to assess the ability of a supply chain, guided by “Lean, Green and Achievement” performance goals, to face “agility and resilience risk” factors. To proof its relevance, a logistics academic case study based on simulation is used to illustrate all its stages. It shows particularly how to build the “LARG risk map” which is the main output of this approach.
Abstract: Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.
Abstract: In this paper, our methodology to assess sustainability of wastewater treatment technologies in Egypt is presented. The preliminary list of factors to be considered, as well as their ranking listed. The factors include, but are not limited to pollutants removal efficiency and energy consumption under the environmental dimension, construction cost, operation and maintenance costs and required land area cost under the economic dimension and public acceptance, noise and generating job opportunities for local residents. This methodology is intended to be a user-friendly screening tool to support the decision making process when investigating different wastewater treatment technologies in Egypt. Based on the research work results presented in this paper, it can be generally concluded that the categorization of some of the social and environmental aspects of sustainability is subjective and highly dependent on the local conditions and researchers’ background.
Abstract: Understanding the help seeking decision making process and experiences of health disparity populations with posttraumatic stress disorder (PTSD) is central to development of trauma-informed, culturally centered, and patient focused services. Yet, little is known about the decision making process among adult Black women who are non-treatment seekers as they are, by definition, not engaged in services. Methods: Audiotaped interviews were conducted with 30 African American adult women with clinically significant PTSD symptoms who were engaged in primary care, but not in treatment for PTSD despite symptom burden. A qualitative interview guide was used to elucidate key themes. Independent coding of themes mapped to theory and identification of emergent themes were conducted using qualitative methods. An existing quantitative dataset was analyzed to contextualize responses and provide a descriptive summary of the sample. Results: Emergent themes revealed that active mental avoidance, the intermittent nature of distress, ambivalence, and self-identified resilience as undermining to help seeking decisions. Participants were stuck within the help-seeking phase of ‘recognition’ of illness and retained a sense of “it is my decision” despite endorsing significant social and environmental negative influencers. Participants distinguished ‘help acceptance’ from ‘help seeking’ with greater willingness to accept help and importance placed on being of help to others. Conclusions: Elucidation of the decision-making process from the perspective of non-treatment seekers has implications for outreach and treatment within models of integrated and specialty systems care. The salience of responses to trauma symptoms and stagnation in the help seeking recognition phase are findings relevant to integrated care service design and community engagement.
Abstract: The objective of this research work is to identify and analyze the significant corporate social responsibility (CSR) practices with an aim to improve the supply chain performance of automobile industry located at National Capital Region (NCR) of India. To achieve the objective, 6 CSR practices have been considered and analyzed using expert’s preference rating (EPR) approach. The considered CSR practices are namely, Top management and employee awareness about CSR (P1), Employee involvement in social and environmental problems (P2), Protection of human rights (P3), Waste reduction, energy saving and water conservation (P4), Proper visibility of CSR guidelines (P5) and Broad perception towards CSR initiatives (P6). The outcomes of this research may help mangers in decision making processes and framing polices for SCP implementation under CSR context.